1 ADHD incidence, treatment and associated comorbidity in children and adolescents: an epidemiological study using electronic healthcare records A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Biology, Medicine and Health 2016 Adrian James Hire Faculty of Biology, Medicine and Health
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1
ADHD incidence, treatment and associated comorbidity
in children and adolescents: an epidemiological study
using electronic healthcare records
A thesis submitted to the University of Manchester for the degree of
Doctor of Philosophy in the Faculty of Biology, Medicine and Health
2016
Adrian James Hire
Faculty of Biology, Medicine and Health
2
Contents List of Tables .................................................................................................................. 7
List of Figures ................................................................................................................. 8
Abstract ......................................................................................................................... 9
Declaration .................................................................................................................. 11
Copyright Statement .................................................................................................... 12
Preface ........................................................................................................................ 13
Acknowledgements ...................................................................................................... 13
Dissemination of results from this work ........................................................................ 15
List of Abbreviations .................................................................................................... 16
Chapter 1: Background ................................................................................................. 19
1.1 History of ADHD ........................................................................................................... 20
1.2 Diagnostic criteria ........................................................................................................ 20
1.3 Causes of ADHD ........................................................................................................... 23
1.4 Treatment of ADHD...................................................................................................... 26
1.4.1 Non-pharmaceutical interventions ....................................................................... 27
1.4.2 Pharmaceutical interventions ............................................................................... 27
1.5 Stimulant medications ................................................................................................. 28
1.5.1 Methylphenidate .................................................................................................. 29
1.5.2 Dexamfetamine and lisdexamfetamine ................................................................ 30
1.6 Non-stimulant medications ......................................................................................... 31
1.6.1 Atomoxetine ......................................................................................................... 31
1.6.2 Guanfacine ............................................................................................................ 32
1.7 Global epidemiology .................................................................................................... 34
1.7.1 Epidemiology of ADHD in the UK .......................................................................... 37
1.8 Personal and societal impacts of ADHD ....................................................................... 43
Chapter 2: Aims and Objectives .................................................................................... 45
2.1 Rationale and aims ....................................................................................................... 46
2.1.1 Diagnostic incidence ............................................................................................. 46
2.1.2 Patient demographics ........................................................................................... 46
2.1.3 Treatment ............................................................................................................. 47
2.1.4 Comorbidity .......................................................................................................... 47
2.2 Objectives..................................................................................................................... 48
Chapter 3: Methods ..................................................................................................... 50
3
3.1 Data Sources ................................................................................................................ 51
3.1.1 Clinical Practice Research Datalink (CPRD) ........................................................... 51
3.1.2 Index of Multiple Deprivation (IMD) data ............................................................. 53
3.1.3 Hospital Episode Statistics (HES) data ................................................................... 54
3.1.4 Independent Scientific Advisory Committee (ISAC) approval ............................... 54
3.2 Identifying cohorts of interest: Chapters 4 and 5 ........................................................ 55
3.2.1 Identifying the population ‘at risk’ of ADHD ......................................................... 55
3.2.2 Calculating person-time spent ‘at risk’ of developing ADHD ................................ 56
3.2.3 Identifying ADHD patients .................................................................................... 58
3.3 Identifying cohorts of interest: Chapters 6 and 7 ........................................................ 61
3.3.1 Linkage-eligible ADHD patients ............................................................................. 62
3.3.2 Linkage-eligible comparison cohort ...................................................................... 62
3.4 Identifying and comparing outcomes of interest ........................................................ 63
3.4.1 Identifying mental, behavioural and neurological comorbidities ......................... 63
3.4.2 Identifying exposure to psychotropic drugs ......................................................... 64
3.4.3 Identifying accidental fractures ............................................................................ 64
3.4.4 Determining the prevalence and relative risk of comorbidity, and psychotropic
treatment ....................................................................................................................... 65
3.4.5 Determining psychotropic exposure in the year before, and the year after index
date ................................................................................................................................ 67
3.4.6 Determining risk of fracture during the study period, and following index date . 68
3.5 Statistical Methods ...................................................................................................... 69
3.5.1 Poisson regression ................................................................................................ 69
3.5.2 Cox proportional hazards model ........................................................................... 69
Chapter 4: ADHD in the United Kingdom: Regional and socioeconomic variations in
incidence rates amongst children and adolescents (2004 – 2013) ................................... 71
4.1 Background .................................................................................................................. 72
4.1.1 Aims....................................................................................................................... 72
4.2 Methods ....................................................................................................................... 73
4.2.1 Data Source and Study Population ....................................................................... 73
4.2.2 Assessment of Geographical Location, and Socioeconomic Status ...................... 73
4.2.3 Incidence Calculation ............................................................................................ 74
4.3 Results .......................................................................................................................... 74
4.3.1 Overall and Annual Incidence Rates (United Kingdom) ........................................ 74
4.3.2 Incidence by Gender and Age Group .................................................................... 75
4
4.3.3 Incidence by Nation (England, Scotland, Wales, and Northern Ireland) .............. 76
4.3.4 Incidence by CPRD Region (England) .................................................................... 78
4.3.5 Incidence by Deprivation (IMD) Quintile .............................................................. 78
4.4 Discussion ..................................................................................................................... 80
4.5 Conclusion .................................................................................................................... 84
Chapter 5: ADHD in children and adolescents: Prevalence and predictors of medication
use in UK primary care ................................................................................................. 85
5.1 Background .................................................................................................................. 86
5.1.1 Aims....................................................................................................................... 87
5.2 Methods ....................................................................................................................... 88
5.2.1 Study Population and case definition ................................................................... 88
5.2.2 Statistical analysis ................................................................................................. 88
5.3 Results .......................................................................................................................... 89
5.3.1 Proportion of ADHD patients treated pharmaceutically in primary care ............. 89
5.3.2 Drug most commonly initiated first-line in primary care ..................................... 90
5.3.3 Age at which pharmaceutical treatment was commenced in primary care ......... 91
5.3.4 Interval between initial diagnosis and first primary care prescription ................. 91
5.3.5 Predictors of pharmaceutical treatment in primary care ..................................... 93
5.4 Discussion ..................................................................................................................... 94
5.4.1 Proportion of ADHD patients treated pharmaceutically in primary care ............. 94
5.4.2 Drug most commonly initiated first-line in primary care ..................................... 97
5.4.3 Age at commencement of pharmaceutical treatment in primary care ................ 98
5.4.4 Predictors of pharmaceutical treatment in primary care ..................................... 98
5.5 Conclusion .................................................................................................................. 100
Chapter 6: Mental, behavioural and neurological comorbidity and psychotropic treatment
in children and adolescents with ADHD: A cohort study using linked CPRD and HES data
.................................................................................................................................. 102
6.1 Background ................................................................................................................ 103
6.1.1 Aims..................................................................................................................... 105
6.2 Methods ..................................................................................................................... 106
6.2.1 Study Population ................................................................................................. 106
6.2.2 Determination of comorbidity, and psychotropic treatment ............................. 106
6.3 Results ........................................................................................................................ 108
6.3.1 Mental, behavioural and neurological comorbidity ........................................... 108
6.3.2 Psychotropic prescribing in primary care ........................................................... 112
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6.3.3 Timing of psychotropic prescribing ..................................................................... 114
6.4 Discussion ................................................................................................................... 117
6.4.1 Mental, behavioural and neurological comorbidity ........................................... 117
6.4.2 Psychotropic prescribing in primary care ........................................................... 119
6.4.3 Timing of psychotropic prescribing ..................................................................... 123
6.5 Conclusion .................................................................................................................. 125
Chapter 7: Fracture risk in children and adolescents with ADHD: A cohort study using
linked CPRD and HES data .......................................................................................... 126
7.1 Background ................................................................................................................ 127
7.1.1 Aims..................................................................................................................... 128
7.2 Methods ..................................................................................................................... 128
7.2.1 Study population ................................................................................................. 129
7.2.2 Identification of fractures ................................................................................... 129
7.2.3 Fracture risk amongst patients who developed ADHD during observation, and
matched comparators .................................................................................................. 130
7.2.4 Pre-existing ADHD and fracture risk ................................................................... 130
7.3 Results ........................................................................................................................ 131
7.3.1 Fracture risk amongst patients who developed ADHD during observation, and
matched comparators .................................................................................................. 131
7.3.2 Pre-existing ADHD and fracture risk ................................................................... 134
7.4 Discussion ................................................................................................................... 135
7.5 Conclusion .................................................................................................................. 138
Chapter 8: Discussion ................................................................................................. 139
8.1 Discussion ................................................................................................................... 140
8.1.1 Chapter 4: ADHD in the United Kingdom: Regional and Socioeconomic Variations
in Incidence Rates Amongst Children and Adolescents (2004-2013) .......................... 140
8.2.1 Chapter 5: ADHD in children and adolescents: Prevalence and predictors of
medication use in UK primary care .............................................................................. 146
8.3.1 Chapter 6: Mental, behavioural and neurological comorbidity and psychotropic
treatment in children and adolescents with ADHD: A cohort study using linked CPRD
and HES data ................................................................................................................ 154
8.4.1 Chapter 7: Fracture risk in children in adolescents with ADHD: a cohort study
using linked CPRD and HES data .................................................................................. 160
8.5 Future work ................................................................................................................ 161
Chapter 9: Conclusion ................................................................................................ 164
9.1 Conclusion .................................................................................................................. 165
6
References ................................................................................................................. 167
Appendix 1: ISAC Approval Notification and Protocol (15_036RAR) ............................. 187
Appendix 2: Read codes used to identify patients with ADHD ...................................... 199
Appendix 3: Product codes used to identify patients who were prescribed a medication
licensed for the treatment of ADHD (methylphenidate, atomoxetine, dexamfetamine,
lisdexamfetamine) ..................................................................................................... 200
Appendix 4: Read and ICD-10 codes used to identify comorbidities of interest ............. 202
Appendix 5: Product codes for psychotropic drugs of interest ..................................... 212
Appendix 6: Read and ICD-10 codes used in the identification of fracture .................... 234
Word count: 86,425 words
7
List of Tables
Table 1: Medications licensed for the treatment of ADHD in the UK p.33
Table 2: Selected studies addressing the epidemiology of ADHD in the UK (prior to
2016) p.42
Table 3: Description of files that comprise an individual patient’s CPRD record p.52
Table 4: UK ADHD incidence (2004 – 2013) p.77
Table 5: ADHD incidence by English region p.78
Table 6: Prevalence of pharmaceutical treatment in primary care p.89
Table 7: Predictors of pharmaceutical treatment following diagnosis in primary care
(Cox proportional hazards model) p.93
Table 8: Cohort characteristics (cases and comparators) p.109
Table 9: Prevalence and relative risk of comorbidity amongst ADHD patients and non-
ADHD comparators between 1/1/2004 and 31/12/2013 p.110
Table 10: Comorbidity ascertainment using Read codes and ICD-10 codes p.111
Table 11: Prevalence and relative risk of psychotropic exposure amongst ADHD
patients and non-ADHD comparators between 1/1/2004 and 31/12/2013 p.113
Table 12: Prevalence and relative risk of psychotropic exposure amongst ADHD
patients in the 365 days preceding, and the 365 days following, their index date p.115
Table 13: Prevalence and relative risk of psychotropic exposure amongst
comparators in the 365 days preceding, and the 365 days following, their index date
p.116
Table 14: Cohort characteristics (cases and comparators) p.132
Table 15: Prevalence and relative risk of fracture amongst ADHD patients and non-
ADHD comparators between 1/1/2004 and 31/12/2013 p.133
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Table 16: Fracture ascertainment using primary and secondary care data p.134
Table 17: Rate of fracture following index date in the ADHD and comparison cohorts
p.135
List of Figures
Figure 1: Diagnostic criteria for ADHD (adapted from the DSM-IV) p.21
Figure 2: UK ADHD incidence rate in under 19s (2004-2013) p.75
Figure 3: ADHD incidence by age of diagnosis p.76
Figure 4: Annual ADHD incidence (2004-2013) by deprivation quintile p.79
Figure 5: ADHD incidence by deprivation quintile (England, Scotland, Wales, Northern
Ireland) p.80
Figure 6: First-line drug choice by year (2004 – 2013) p.90
Figure 7: First-line methylphenidate use, and age of commencement in primary care
p.92
Figure 8: First-line drug use, and age of commencement in primary care p.92
9
Abstract
ADHD incidence, treatment and associated comorbidity in children and adolescents: an epidemiological study using electronic healthcare records
Adrian James Hire, University of Manchester Doctor of Philosophy/PhD candidate, 2016
Background ADHD is characterised by three core symptoms: hyperactivity, impulsivity and inattention. For those affected, ADHD can have a wide range of negative impacts. It has the potential to reduce academic performance, interfere with interpersonal relationships and is a purported risk factor for numerous mental and behavioural disorders, and accidental injury. However, questions remain regarding the epidemiology of ADHD in the UK.
Aims Phase 1: To describe the incidence and distribution of ADHD within the UK (2004-2013), and to examine if there was any association between ADHD incidence and socioeconomic deprivation. Phase 2: To assess what proportion of ADHD patients received a primary care prescription for a licensed ADHD medication, and to determine the average time between diagnosis and the start of treatment in primary care. Phase 3: To establish if selected comorbidities, and prescriptions for psychotropic drugs, are significantly more likely in patients with ADHD than matched comparators. Phase 4: To establish if accidental fractures are significantly more likely in patients with ADHD than matched comparators.
Methods The study used electronic healthcare records data. The study population comprised patients diagnosed with ADHD before the age of 19, between 1/1/2004 and 31/12/13. Patients with a diagnosis of ADHD, comorbidities of interest or who had received prescriptions for licensed ADHD medications/psychotropic drugs were identified by the presence of relevant codes in their medical records.
Results Phase 1: Between 2004 and 2013, the incidence of ADHD amongst under 19s in the UK was 11.67 (95% CI 11.45 – 11.90) cases per 10,000 person-years at risk. Most of those diagnosed with ADHD were male (n=8407; 82%). There appeared to be an association between increasing socioeconomic deprivation and ADHD incidence. Annual incidence rates remained relatively stable between 2004 and 2013, but were highest in the last two years studied. Phase 2: 57% of patients with a diagnosis of ADHD received a primary care prescription for a licensed ADHD medication during follow-up. In treated patients, the median interval between diagnosis and a first prescription for an ADHD medication was 84 days (IQR 21–258 days); methylphenidate was used first-line in 92% of treated patients. Phase 3: ADHD was associated with a significantly increased risk of comorbidity [RR 3.59 (95% CI 3.40 – 3.79)]. ADHD patients had significantly higher exposure to second generation antipsychotics [RR 29.48 (95% CI 23.25 – 37.40)], antidepressants and anxiolytics/hypnotics [RR 12.56 (95% CI 11.44 – 13.79)]. Phase 4: ADHD patients had a significantly higher risk of fracture relative to comparators [HR 1.17 (1.06 – 1.30)].
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Conclusion ADHD incidence appears stable, but demographic factors can significantly influence an individual’s risk of being diagnosed with the disorder. Pharmaceutical treatment is far from universal in primary care, suggesting that GPs remain cautious about prescribing drugs for ADHD. Comorbid diagnoses are more likely among children with ADHD, and the increased use of psychotropics in this population suggests that these comorbidities are clinically-significant. ADHD patients’ higher risk of fracture lends support to the theory that impaired impulse control increases these patients’ risk of accidental injury.
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Declaration
No portion of the work referred to in this thesis has been submitted in support of
an application for another degree or qualification of this or any other university or
other institute of learning.
12
Copyright Statement
i.
The author of this thesis (including any appendices and/or schedules to this thesis)
owns certain copyright or related rights in it (the “Copyright”) and s/he has given
The University of Manchester certain rights to use such Copyright, including for
administrative purposes.
ii.
Copies of this thesis, either in full or in extracts and whether in hard or electronic
copy, may be made only in accordance with the Copyright, Designs and Patents Act
1988 (as amended) and regulations issued under it or, where appropriate, in
accordance with licensing agreements which the University has from time to time.
This page must form part of any such copies made.
iii.
The ownership of certain Copyright, patents, designs, trade marks and other
intellectual property (the “Intellectual Property”) and any reproductions of
copyright works in the thesis, for example graphs and tables (“Reproductions”),
which may be described in this thesis, may not be owned by the author and may be
owned by third parties. Such Intellectual Property and Reproductions cannot and
must not be made available for use without the prior written permission of the
owner(s) of the relevant Intellectual Property and/or Reproductions.
iv.
Further information on the conditions under which disclosure, publication and
commercialisation of this thesis, the Copyright and any Intellectual Property
University IP Policy (see
http://documents.manchester.ac.uk/display.aspx?DocID=24420
), in any relevant Thesis restriction declarations deposited in the University Library,
The University Library’s regulations (see
http://www.library.manchester.ac.uk/about/regulations/) and in The University’s
policy on Presentation of Theses.
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Preface
Adrian James Hire graduated from Cardiff University in 2009 with a Masters degree
in Pharmacy (MPharm). Following pre-registration training, Adrian obtained his
professional registration as a pharmacist in 2010. After qualification, he initially
worked as a community locum pharmacist before joining Imperial College
Healthcare NHS Trust as a rotational pharmacist in March 2011. Having long held an
interest in research, Adrian joined the University of Manchester as a PhD research
student in July 2013. His original research proposal related to type 2 diabetes,
though his subsequent research focused exclusively on Attention Deficit
Hyperactivity Disorder (ADHD). Using primary care data, Adrian examined the
epidemiology of ADHD in UK children and adolescents.
Acknowledgements
Many people have supported and assisted me throughout the course of my PhD.
It’s been a long and sometimes arduous process; I would not have reached the end
without their contribution.
Firstly, I would like to acknowledge and sincerely thank my supervisors, Dr Douglas
Steinke and Professor Darren Ashcroft. Their input and support has been
invaluable, and I appreciate the time they have dedicated to reading all versions of
my abstracts, papers, results and thesis chapters.
I would also like to thank my friends and colleagues within the Drug Usage and
Pharmacy Practice (DUPP) division for their support, guidance and encouragement.
As a novice researcher and statistician, the help I received from them was
immeasurable. I particularly wish Salwa, Hayley, Alison, Rosa, Ireny, Nin, Mark and
Richard all the best in the future.
Dr David Springate, Dr Matthew Carr and Dr Jill Stocks all helped me at various
stages of my research, providing assistance and advice on the extraction and use of
CPRD data, the use of Stata, and the development of code lists. With regard to code
14
lists, I would particularly like to thank Hayley, Jane and Cathy for their help in
developing some of the code lists used in this study.
Finally, I would like to thank my parents, and my girlfriend Claire, for their
unwavering support and encouragement throughout.
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Dissemination of results from this work
Journal Publications:
Hire AJ, Ashcroft DM, Springate DA, Steinke DT. ADHD in the United Kingdom:
Regional and Socioeconomic Variations in Incidence Rates Amongst Children and
Adolescents (2004-2013). Journal of Attention Disorders 2015 Nov 23.
PMID:26604267
Work presented at conferences:
Hire AJ, Ashcroft DM, Springate DA, Steinke DT. Attention Deficit Hyperactivity
Disorder (ADHD) and socioeconomic deprivation in the United Kingdom. 5th World
Congress on ADHD in Glasgow (UK).
Hire AJ, Ashcroft DM, Springate DA, Steinke DT. Attention Deficit Hyperactivity
Disorder (ADHD) and socioeconomic status in children and adolescents in the UK.
31st International Conference on Pharmacoepidemiology & Therapeutic Risk
Management in Boston (USA).
Hire AJ, Ashcroft DM, Steinke DT. Attention Deficit Hyperactivity Disorder (ADHD) in
under 19s: prevalence and predictors of medication use in primary care. 32nd
International Conference on Pharmacoepidemiology & Therapeutic Risk
Management in Dublin (Ireland).
16
List of Abbreviations
ADHD: Attention Deficit Hyperactivity Disorder
ADORE: ADHD Observational Research in Europe
APA: American Psychiatric Association
BMJ: British Medical Journal
BNF: British National Formulary
BNFC: British National Formulary for Children
CBT: Cognitive Behavioural Therapy
CDC: Centers for Disease Control and Prevention
CQC: Care Quality Commission
CNS: Central Nervous System
CPRD: Clinical Practice Research Datalink
DAT1: Dopamine Transporter 1
DBH: Dopamine Beta-Hydroxylase
DRD4: Dopamine Receptor 4
DRD5: Dopamine Receptor 5
DSM: Diagnostic and Statistical Manual of Mental Disorders
DSM IV: Diagnostic and Statistical Manual of Mental Disorders Version 4
DZ: Datazone
GP: General Practitioner
GPRD: General Practice Research Database
HKD: Hyperkinetic Disorder
17
HES: Hospital Episode Statistics
HSCIC: The Health and Social Care Information Centre
HTR1B: Serotonin Receptor 1B
ICD-10: International Classification of Diseases 10th Revision
IMD: Index of Multiple Deprivation
IQR: Inter-Quartile Range
ISAC: Independent Scientific Advisory Committee
LHID: Longitudinal Health Insurance Database
LSOA: Lower Layer Super Output Areas
MeSH: Medical and Subject Heading
mg: Milligrams
MHRA: Medicines and Healthcare Products Regulatory Agency
NHS: National Health Service
NICE: National Institute for Health and Care Excellence (formerly National Institute
for Health and Clinical Excellence)
NIHR: National Institute for Health Research
ONS: Office for National Statistics
QOF: Quality and Outcomes Framework
SMD: Standard Mean Difference
SNAP25: Synaptosomal-Associated Protein 25
THIN: The Health Improvement Network
USD: United States Dollars
18
5HT-T: Serotonin Transporter Gene
19
Chapter 1
Background
20
1.1 History of ADHD
The first reference to attention deficit hyperactivity disorder (ADHD) in a
medical publication may have occurred as early as 1798 (Palmer & Finger 2001).
Scottish physician Sir Alexander Crichton described a state of “unnatural…mental
restlessness” arising early in life that resulted in “the incapacity of attending with a
necessary constancy to any one object” (Crichton 1798, p.270). In his book ‘An
inquiry into the nature and origin of mental derangement: comprehending a concise
system of the physiology and pathology of the human mind and a history of the
passions and their effects’, Crichton referred to the pathological attentive disorder
he described as “fidgets” (Crichton 1798, p.272). ‘Minimal brain dysfunction’,
‘Hyperkinetic Reaction of Childhood’ and ‘Attention Deficit Disorder with or without
hyperactivity’ are three further historical terms applied (by the American
Psychiatric Association’s Diagnostic and Statistical Manual of Mental
Disorders/DSM) to what is now referred to as attention deficit hyperactivity
disorder (Centers for Disease Control and Prevention 2013a). The changing names
have mirrored changing opinions regarding the nature and cause of the disorder’s
behavioural symptoms (Nefsky 2004). Despite the passage of time, the attentive
disorder observed by Crichton remains a controversial and evolving diagnosis, with
its definition, causes and epidemiology still to be fully characterised.
1.2 Diagnostic criteria
The National Institute for Health and Care Excellence (NICE) issued its first
guidance regarding the diagnosis and management of ADHD in 2008 (National
Institute for Health and Care Excellence 2008a). This guideline (last updated in
February 2016) states that any diagnosis of ADHD should be made in line with the
diagnostic criteria for the disorder set out in the DSM-IV. It also acknowledges the
overlap between ADHD and hyperkinetic disorder (HKD), a comparable diagnosis
listed by the World Health Organisation’s International Classification of Diseases
10th Revision (ICD-10) (National Institute for Health and Clinical Excellence, 2008).
Despite the differences in terminology, ADHD and HKD share three common
symptom domains: inattention, impulsivity and hyperactivity (Wong et al. 2009).
21
Figure 1: Diagnostic criteria for ADHD (adapted from the DSM-IV)
ADHD is characterised by a persistent pattern of inattention and/or hyperactivity-impulsivity that is more frequently displayed and more severe than is typically observed in individuals at a comparable level of development, and has a clinically-significant impact on functioning or development
Three subtypes (presentations) of ADHD can be diagnosed:
1. Combined Presentation: if ≥6 symptoms of inattention and ≥6 symptoms of hyperactivity-impulsivity have been present for the past six months or longer.
2. Predominantly Inattentive Presentation: if ≥6 symptoms of inattention, but <6 symptoms of hyperactivity-impulsivity have been present for the past six months or longer.
3. Predominantly Hyperactive-Impulsive Presentation: if ≥6 symptoms of hyperactivity-impulsivity, but <6 symptoms of inattention were present for the past six months or longer.
Symptoms of inattention:
o Often fails to give close attention to details or makes careless mistakes in schoolwork, at work, or with other activities.
o Often has trouble holding attention on tasks or play activities. o Often does not seem to listen when spoken to directly. o Often does not follow through on instructions and fails to finish schoolwork, chores, or
duties in the workplace (e.g., loses focus, side-tracked). o Often has trouble organizing tasks and activities. o Often avoids, dislikes, or is reluctant to do tasks that require mental effort over a long
period of time (such as schoolwork or homework). o Often loses things necessary for tasks and activities (e.g. school materials, pencils,
books, tools, wallets, keys, paperwork, eyeglasses, mobile telephones). o Is often easily distracted. o Is often forgetful in daily activities.
Symptoms of hyperactivity and impulsivity:
o Often fidgets with or taps hands or feet, or squirms in seat. o Often leaves seat in situations when remaining seated is expected. o Often runs about or climbs in situations where it is not appropriate (adolescents or
adults may be limited to feeling restless). o Often unable to play or take part in leisure activities quietly. o Is often "on the go" acting as if "driven by a motor". o Often talks excessively. o Often blurts out an answer before a question has been completed. o Often has trouble waiting his/her turn. o Often interrupts or intrudes on others (e.g., butts into conversations or games).
For a diagnosis to be made, the following conditions must also be met:
Several inattentive or hyperactive-impulsive symptoms present before the age of 7 years.
Several symptoms present in two or more settings, (e.g., at home, school or work; with friends or relatives; in other activities).
Clear evidence that the symptoms interfere with, or reduce the quality of, social, school, or work functioning.
Symptoms do not happen only during the course of schizophrenia or another psychotic disorder. The symptoms are not better explained by another mental disorder (e.g. Mood Disorder, Anxiety Disorder, Dissociative Disorder, or a Personality Disorder).
22
The core ‘symptoms’ of ADHD (elaborated upon in Figure 1) are present to
varying extents in many ‘normal’ individuals. For a diagnosis of ADHD to be made
however, these symptoms must be persistent, pervasive, and cause functional
impairment, significantly impacting on patients’ ability to function in social, familial,
educational and/or occupational settings (National Institute for Health and Care
Excellence 2008a). Furthermore, the DSM diagnostic criteria stipulate that the
symptoms must onset prior to the age of 7 for a diagnosis of ADHD to be made. This
does not mean that a diagnosis cannot be made in older children and adults,
provided that their symptoms can be traced back to this age. A further notable
aspect of the DSM guidance is recognition that ADHD has three distinct subtypes,
deemed ‘presentations’. A patient’s presentation is determined by which symptoms
predominate in their case. ‘Predominantly inattentive’ patients mainly exhibit
symptoms of inattention (for example, forgetfulness and disorganisation), whilst
‘predominantly hyperactive-impulsive’ patients exhibit hyperactive behaviours
(such as fidgeting) or problems with impulse control (blurting out or interrupting
others). Where both inattentive and hyperactive-impulsive symptoms are present
in sufficient numbers, a patient may be said to have a ‘combined presentation’.
ADHD with combined presentation is approximately equivalent to the ICD-10’s
hyperkinetic disorder, a diagnosis which requires all three core symptoms to be
present simultaneously.
In addition to its different presentations, ADHD can be further classified
according to severity. This is not addressed by the DSM, but is referred to by NICE’s
guidance on the disorder. Though poorly defined, ADHD severity is a function of its
presentation and the resultant level of impairment experienced by patients.
‘Moderate’ ADHD is characterised by symptoms of hyperactivity/impulsivity and/or
inattention in multiple settings, sufficient to cause at least moderate impairment;
severe ADHD (which corresponds approximately to ‘combined presentation’ ADHD
and hyperkinetic disorder) requires all three symptoms to be present
simultaneously, in multiple settings, causing severe impairment (National Institute
for Health and Clinical Excellence 2008). NICE’s guidance does not provide a
definition for ‘mild ADHD’, and determining the severity of impairment is left to the
23
clinical judgement of practitioners (Thomas et al., 2014). In the UK, general
practitioners (GPs) have an important role in identifying children who may have the
condition. As gatekeepers to the UK healthcare system (Herrett et al., 2015; Murray
et al., 2014), GPs will generally be the first port-of-call for individuals concerned
that they or their child may have ADHD. Where ADHD is suspected, NICE
recommends that patients are referred to secondary care for assessment; a formal
diagnosis of ADHD “should only be made by a specialist psychiatrist, paediatrician
or other appropriately qualified healthcare professional with training and expertise
in the diagnosis of ADHD” (National Institute for Health and Care Excellence 2008b,
p.9).
1.3 Causes of ADHD
Outstanding questions surrounding the cause of ADHD have been the
source of much controversy and debate. There is currently no physical, biological or
radiological test to confirm the presence or absence of ADHD, and the specific
impairments it causes are heterogeneous. This has led some to question both its
validity as a diagnosis and its very existence as a condition (Zwi & York, 2004). Prior
to drawing up its guidance for ADHD in 2008, NICE itself took the unusual step of
first considering whether or not ADHD actually constituted a valid medical disorder
(Taylor 2011). NICE’s conclusion (based on an extensive review of the literature
surrounding ADHD) was “unequivocal”; ADHD could indeed be considered a
medical disability with a strong neurobiological basis (Taylor 2011).
The ‘strong neurobiological basis’ of ADHD has yet to be fully characterised,
but its pathology appears to stem from an underlying disorder of brain maturation
(National Institute of Mental Health 2012). Brain imaging studies involving children
with ADHD have shown that their brains develop normally, but at a slower rate than
would normally be expected; one study found that the normal pattern of brain
growth and maturation is delayed by around three years on average (Shaw et al.
2007). The regions of the brain affected are wide-ranging, including the caudate
nucleus, corpus callosum and the cerebellar vermis (Tripp & Wickens 2009), with
the delays most pronounced in areas involved in response inhibition, planning,
24
working memory and attention (Shaw et al. 2007). Whilst specific areas of the brain
show particular delays in maturation, patients with ADHD have been observed to
have generally reduced white matter volume and cortical thickness when compared
with controls (Warikoo & Faraone 2013). As such, no regional developmental
abnormality or abnormalities can yet be described as the definitive cause of ADHD’s
symptoms. Indeed, ADHD may be a disorder arising from a global abnormality of
brain connectivity (Bolea-Alamañac et al. 2014).
At a cellular level, ADHD may also be linked with derangements in
neurotransmitter activity. Dopamine is involved in the pathophysiology of disorders
as diverse as Parkinson’s disease and schizophrenia; its potential role in ADHD has
been the subject of much research. The evidence for some degree of involvement is
multifaceted. ADHD has been treated for several decades with the central nervous
system (CNS) stimulants methylphenidate and dexamfetamine (discussed further in
section 1.5). These drugs act primarily at dopaminergic neurons, increasing synaptic
availability of the neurotransmitter and potentiating its activity. In ‘normal’
individuals, this promotes a stimulatory effect, increasing activity and energy levels.
However, in many patients with ADHD these stimulants have a ‘calming’ effect,
producing a significant improvement in symptoms. This discrepancy suggests that
some disorder of normal dopamine function is present in ADHD.
A large body of evidence suggests that ADHD has a strong genetic
component (Purper-Ouakil et al., 2011); twin studies suggest its heritability may be
as high as 80% (Turic et al., 2010). Mutations involving several dopamine receptor
and transporter genes have been consistently identified in ADHD patients. A meta-
analysis carried out by Li and colleagues (2006) found that specific mutations
involving the dopamine receptor 4 (DRD4) and dopamine receptor 5 (DRD5) genes
were associated with a significantly increased risk of developing ADHD. Other
studies have found evidence of association between ADHD and variants of the
dopamine transporter gene (DAT1), the serotonin receptor 1B gene (HTR1B), the
serotonin transporter gene (5HT-T) and the genes coding for synaptosomal-
associated protein 25 (SNAP25) and dopamine beta-hydroxylase (DBH) (Bolea-
Alamañac et al. 2014; Kooij et al. 2010). It is notable that whilst these genes (and
25
others) have all been linked with the development of ADHD, their individual (and
combined) effect sizes are small. Kuntsi et al. (2006) calculated that known
mutations involving DRD4, DRD5, DAT1, HTR1B, 5HT-T, SNAP25 and DBH only
explain 3.3% of phenotypic variance and 4% of the heritability of ADHD. This would
suggest that ADHD cannot be wholly ascribed to a derangement of a single
neurotransmitter system, or to variations of individual candidate genes. In
summarising our current knowledge regarding the genetics of ADHD, Turic and
colleagues likened ADHD to height. Like height, ADHD is a highly heritable polygenic
trait, but the majority of genes involved remain unidentified (Turic et al. 2010).
Whilst genetics has a large influence on the development of ADHD,
environmental influences may also increase an individual’s likelihood of developing
the disorder. The list of purported risk factors is long, and distinguishing between
correlation and causation is difficult in most instances. A systematic review carried
out by Coghill et al. (2014) identified prematurity as the only environmental factor
strongly associated with ADHD. For two other factors, maternal smoking in
pregnancy and low birth weight, evidence of a link was suggestive, but not
conclusive (Bolea-Alamañac et al. 2014). Numerous other risk factors for ADHD
have been suggested and scrutinised to varying extents, ranging from maternal
alcohol use in pregnancy, chemical exposure (to lead, nitrogen dioxide,
organophosphate pesticides) and nutritional deficiencies (zinc, magnesium,
polyunsaturated fatty acids); in many of these cases the evidence of any link is
insubstantial and/or conflicting (Bolea-Alamañac et al., 2014; Thapar et al., 2013).
Possibly the most publicised risk factors proposed for ADHD are artificial food
colourings and excessive sugar consumption. As with most of the other purported
risk factors, compelling evidence for a link is lacking. NICE does not currently
advocate dietary restrictions for the control of ADHD (National Institute for Health
and Clinical Excellence 2008), though one meta-analysis has suggested that such
measures may have a modest effect on symptoms in some children (Nigg et al.,
2012).
The potential role of psychosocial factors in the development of ADHD is
worthy of separate consideration. Epidemiological studies have suggested a link
26
between ADHD and several forms of psychosocial adversity, such as family conflict,
maternal psychopathology, low household income and low social class (Wong et al.
2009; Thapar et al. 2013). As with the physical, chemical and dietary risk factors,
establishing any definitive, causative link is problematic. As highlighted by Thapar
and colleagues (2013), further difficulties arise in establishing the direction of any
relationship between adversity and ADHD. For example, whilst family conflict may
be more common in families affected by ADHD, this conflict may be (at least in part)
a result of the disorder rather than its root cause (Thapar et al. 2013). There is
however compelling evidence that external risk factors can have a profound
influence on children’s psychological development (Wong et al. 2009). In the case
of ADHD specifically, one notable study has established that extreme psychosocial
deprivation in infancy can promote the development of persistent ADHD-type
symptoms (Rutter et al., 2007). It remains unclear whether less extreme adversity
can produce a similar effect, but this finding suggests that psychological and social
factors may play an important role in ADHD.
1.4 Treatment of ADHD
Numerous studies have shown that ADHD’s core symptoms can be
effectively treated in both children and adults (Kooij et al. 2010; Bolea-Alamañac et
al. 2014). Furthermore, treating these symptoms can improve related problems
such as low self-esteem, mood and anger problems, cognitive problems and social
and family functioning (Kooij et al. 2010). NICE’s 2008 guidance on the diagnosis
and management of ADHD sets out a detailed treatment pathway for children,
young people and adults with ADHD. As set out in the guidance, ADHD may not
necessarily require pharmacological intervention, and in some cases drugs may not
be appropriate. Drug treatment is not recommended in pre-school children, and is
not considered first-line treatment for school-aged children with moderate ADHD.
In these patients, parental education and training combined with cognitive
behavioural therapy (CBT) and/or social skills training for the affected child should
be employed first-line.
27
1.4.1 Non-pharmaceutical interventions
The range of non-pharmaceutical interventions that may be employed in the
treatment of ADHD is diverse, and establishing the comparative effectiveness of
such interventions is difficult from the available evidence. A systematic review of
non-pharmaceutical interventions conducted by the National Institute for Health
Research remarked that “the breadth of both interventions and outcomes in
reviewed studies presented a challenge for categorisation, analysis and
interpretation”, with many studies being of poor methodological quality
(Richardson et al. 2015). The studies reviewed featured self-management and skill-
based interventions (cognitive behavioural therapies, academic and study skills
training, emotional skills training), reward and punishment-based interventions
(contingency management) and creative and physical therapies. In general, these
interventions were associated with a beneficial effect on ADHD’s core symptoms, or
on scholastic behaviours and outcomes. However, varied trial designs, plus the
inclusion of trials where patients received both pharmaceutical and non-
pharmaceutical interventions, make this review’s findings hard to assess. Two
Cochrane reviews of parental training interventions and social skills training for
children with ADHD produced equally unclear results despite their narrower focus
(Zwi et al. 2011; Storebø et al. 2011). With regard to non-pharmaceutical
interventions for ADHD, NICE’s full guideline on the disorder gives a fair summary:
“the evidence indicates that psychological interventions for children with ADHD
have moderate beneficial effects on parent ratings of ADHD symptoms and conduct
problems, both for children not on medication and as an adjunct to continued
routine medication for ADHD” (National Institute for Health and Care Excellence
2008a).
1.4.2 Pharmaceutical interventions
Drug therapy is considered ‘superior’ to non-pharmacological interventions,
particularly in the treatment of severe ADHD (National Institute for Health and
Clinical Excellence 2008). If a child has severe ADHD, or if non-pharmaceutical
interventions are unavailable, refused or ineffective, medication may be
28
commenced. As with diagnosis, NICE stipulates that pharmacological treatment of
ADHD should be initiated by a healthcare professional with expertise in ADHD, and
should be reviewed at least annually. Once an appropriate regimen has been
decided upon, GPs typically continue treatment and undertake routine monitoring
measures as part of a shared care arrangement (Beau-Lejdstrom et al. 2016;
Rowlingson et al. 2013; National Institute for Health and Care Excellence 2008b).
Treatment of ADHD is based on symptom reduction. No cure for ADHD currently
exists, though sufferers may ‘grow out’ of the condition with age (Royal College of
Psychiatrists 2014). At present, five medications are licensed in the UK for the
treatment of ADHD; methylphenidate, dexamfetamine, lisdexamfetamine,
atomoxetine and guanfacine.
1.5 Stimulant medications
Methylphenidate, dexamfetamine and lisdexamfetamine are central
nervous system stimulants that increase the availability of dopamine and
noradrenaline in synaptic spaces between neurons. How this pharmacological
effect promotes a reduction in ADHD symptoms is not entirely clear (Kolar et al.
2008). However, there is much evidence for their efficacy in children (Brown et al.
2005) and adults with ADHD (Kooij et al. 2010). Improvements reported by patients
treated with stimulants are wide-ranging, including improved attentiveness,
improved impulse control and improved self-esteem (Wong et al. 2009). Response
rates to stimulant treatment are very high, in the region of 85-90% (Turic et al.
2010).
One problem associated with the central nervous system stimulants is their
potential for abuse. As a result, methylphenidate, dexamfetamine and
lisdexamfetamine are classed as Schedule 2 controlled drugs under the UK’s Misuse
of Drugs Regulations; they are subject to strict conditions for prescribing, storage
and supply (BMJ Group and Pharmaceutical Press & Joint Formulary Committee
2016). Whilst the potential for abuse, and diversion for the purposes of abuse, is a
valid concern addressed by NICE’s guidance on ADHD, there is evidence to suggest
that stimulant therapy may decrease, rather than increase, patients’ likelihood of
29
developing substance use disorders (Kooij et al. 2010). The side effects most
commonly associated with methylphenidate and the amfetamines are directly
related to their stimulant effects; insomnia, nervousness, reduced appetite,
tachycardia and increased blood pressure (BMJ Group and Pharmaceutical Press &
Joint Formulary Committee 2016). Many of these ‘stimulant’ side effects are
transient and can be negated by careful dose adjustment; rarer side effects include
weight loss and growth retardation (Wong et al. 2009). Prescribers are required to
monitor patients carefully whilst they are taking stimulants, and must undertake a
number of specific measures to detect and prevent side effects. Pulse, blood
pressure, psychiatric symptoms, appetite, weight and height should all be
monitored before initiating therapy, following dose adjustments, and at least every
6 months thereafter (BMJ Group and Pharmaceutical Press & Joint Formulary
Committee 2016). Though stimulants play an integral role in the treatment of ADHD
in the UK, two recent Cochrane reviews have reiterated their potential to cause
adverse effects (Storebø et al. 2015; Punja et al. 2016), and no stimulant is currently
approved for use in children below the age of six.
1.5.1 Methylphenidate
A 2010 meta-analysis of double-blind, placebo-controlled trials concluded
that methylphenidate consistently demonstrated efficacy in the treatment of ADHD
in children (Faraone & Buitelaar 2010). A growing number of trials have suggested
that it has comparable efficacy in adults (Kooij et al. 2010). Used for over 50 years
in the treatment of ADHD, methylphenidate received its initial UK product licence in
1988 (Wong et al. 2009). It remains by far the most commonly prescribed drug for
ADHD in the UK (McCarthy et al. 2012b). Methylphenidate is licensed for use
between the ages 6-18 and may be considered for patients with uncomplicated
ADHD, ADHD with comorbid conduct disorder and ADHD with concomitant tics,
Tourette’s syndrome or anxiety disorder (National Institute for Health and Clinical
Excellence 2008). It is generally considered the first-line treatment for both children
and adults, though its use above the age of 18 is unlicensed (BMJ Group and
Pharmaceutical Press & Joint Formulary Committee 2016). In its immediate-release
formulation (RitalinTM, Novartis Pharmaceuticals) methylphenidate is taken once,
30
twice or three times daily (BMJ Group and Pharmaceutical Press & Joint Formulary
Committee 2016). Newer modified-release formulations (Concerta XLTM, Equasym
XLTM and Medikinet XLTM) have the advantage of allowing once daily dosing and are
increasingly preferred (Bolea-Alamañac et al. 2014).
1.5.2 Dexamfetamine and lisdexamfetamine
Dexamfetamine and lisdexamfetamine offer an alternative in instances
where patients do not respond to methylphenidate (BMJ Group and
Pharmaceutical Press & Joint Formulary Committee 2016). After an initial period of
dose titration, dexamfetamine is generally taken twice to four times daily.
Lisdexamfetamine (ElvanseTM, Shire Pharmaceuticals) is an inactive prodrug of
dexamfetamine, and requires only once daily dosing. Being a prodrug,
lisdexamfetamine is thought to be less amenable to abuse than dexamfetamine
itself (Bolea-Alamañac et al. 2014). However, neither drug should be used first-line
if there is a significant likelihood of abuse, misuse or diversion. As with
methylphenidate, use of these amphetamines above the age of 18 is unlicensed;
both drugs are licensed for use between 6-18 years of age (BMJ Group and
Pharmaceutical Press & Joint Formulary Committee 2016). Though primarily
indicated for ADHD, dexamfetamine (though not its prodrug) is also licensed for the
treatment of narcolepsy in adults (BMJ Group and Pharmaceutical Press & Joint
Formulary Committee 2016).
Evidence for dexamfetmine’s effectiveness in ADHD is well-established
(Hodgkins et al., 2012). However, head-to-head studies comparing methylphenidate
and dexamfetamine in ADHD are relatively sparse (Faraone & Buitelaar 2010).
Faraone and Buitelaar’s meta-analysis of trial data indicated that mean effect sizes
produced by amphetamines were moderately, but significantly, greater than those
produced by methylphenidate. In the treatment of ADHD symptoms,
dexamfetamine had a standardised mean difference (SMD) of 1.03 compared to
placebo; the value for methylphenidate was 0.77 (p=0.02) (Faraone & Buitelaar
2010). A relatively new agent, lisdexamfetamine has been shown effective in a
31
number of randomised, double-blind, placebo-controlled trials involving children
and adults (Bolea-Alamañac et al. 2014).
1.6 Non-stimulant medications
In the United States and elsewhere, several non-stimulant medications are
used in the treatment of ADHD. These include atomoxetine, bupropion, modafinil,
clonidine, plus several antipsychotics and antidepressants (Bolea-Alamañac et al.
2014; Kooij et al. 2010; National Institute for Health and Care Excellence 2008a).
Evidence for the efficacy of these drugs varies widely; atomoxetine and bupropion
have evidence of efficacy in ADHD that is comparable to that of the stimulants
(Bolea-Alamañac et al. 2014). However, atomoxetine and guanfacine are the only
non-stimulant medications currently licensed for the treatment of ADHD in the UK.
1.6.1 Atomoxetine
Atomoxetine (StratteraTM, Eli Lilly & Co.) is licensed for the treatment of
ADHD in adults and children above the age of 6 years (BMJ Group and
Pharmaceutical Press & Joint Formulary Committee 2016). Atomoxetine is a highly
selective and potent inhibitor of pre-synaptic noradrenaline transporters, increasing
synaptic noradrenaline availability (Electronic Medicines Compendium 2013).
Unlike methylphenidate and the amphetamines, atomoxetine has no direct effect
on dopamine availability and is not classed as a CNS stimulant. Its lack of stimulant
effects gives the drug comparatively little potential for abuse (Bolea-Alamañac et al.
2014); it is resultantly classed as an ordinary prescription-only medicine rather than
a controlled substance (BMJ Group and Pharmaceutical Press & Joint Formulary
Committee 2016). Atomoxetine offers a useful treatment option in patients at risk
of stimulant abuse, misuse or diversion. It may also be used in patients who are
intolerant or unresponsive to methylphenidate (National Institute for Health and
Clinical Excellence 2008), or in whom stimulants are contraindicated.
Atomoxetine is generally given once daily (in the morning), though it may
also be given as two divided doses according to patient preference (BMJ Group and
Pharmaceutical Press & Joint Formulary Committee 2016). Its side effects include
32
abdominal pain, nausea and vomiting, decreased appetite and weight loss, and
changes in blood pressure (Electronic Medicines Compendium 2013). For this
reason, the monitoring requirements applied to CNS stimulants are also applicable
to atomoxetine. Following rare reports of hepatic toxicity, atomoxetine patients
should be warned of the risk and made aware of its potential symptoms (BMJ
Group and Pharmaceutical Press & Joint Formulary Committee 2016). Suicidal
ideation and behaviour has also been reported by some patients taking the drug
(Wong et al. 2009). Despite these notable issues, atomoxetine is an effective
treatment option for ADHD in patients of all ages; a recent meta-analysis has
suggested its efficacy may be comparable to that of the CNS stimulants (Bolea-
Alamañac et al. 2014).
1.6.2 Guanfacine
Prolonged-release guanfacine (IntunivTM, Shire Pharmaceuticals) received its
European marketing authorisation in 2015, and was launched in the UK in
September 2015 (National Institute for Health and Care Excellence 2016). A
selective alpha 2 adrenergic receptor agonist, guanfacine is licensed for the
treatment of ADHD in children and young people aged 6-17 years old for whom
stimulants are unsuitable, ineffective or not tolerated (Electronic Medicines
Compendium 2015). Much of the evidence for guanfacine's efficacy in reducing the
symptoms of ADHD is derived from placebo-controlled studies (National Institute
for Health and Care Excellence 2016), and the evidence for its efficacy is somewhat
less robust than for stimulants and atomoxetine (Chan et al. 2016; Mattes 2016).
Guanfacine does have a potential advantage over other licensed treatments for
ADHD in that it is unlikely to induce hypertension. However, it can induce a
potentially significant hypotensive effect in patients; other side effects include
syncope, somnolence and bradycardia (Electronic Medicines Compendium 2015;
National Institute for Health and Care Excellence 2016). In comparison to both
placebo, and atomoxetine, treatment-emergent side effects are more commonly
observed in patients commenced on guanfacine (National Institute for Health and
Care Excellence 2016). As shown in Table 1, dosage is initially determined based on
age and body-weight, and can then be tapered according to response.
33
Table 1: Medications licensed for the treatment of ADHD in the UK
Drug Licensed indications (UK)
Brand names
Formulations available in UK (mg = milligrams)
Maximum dose for ADHD (listed by the British National Formulary/British National Formulary for Children)
Methylphenidate
ADHD (6-18 years of age)
RitalinTM
Concerta XLTM
Equasym
XLTM
Medikinet
XLTM
Plain tablets: 5mg, 10mg, 20mg Modified release tablets: 18mg, 27mg, 36mg Modified release capsules: 10mg, 20mg, 30mg Modified release capsules: 5mg, 10mg, 20mg, 30mg, 40mg
4-6 years: 1.4mg/kg daily in 2-3 divided doses (unlicensed) 6-18 years: max. 60mg daily in 2-3 divided doses; up to 90mg daily may be used under
direction of a specialist (unlicensed) Adult: max. 100mg daily in 2-3 divided doses (unlicensed)
6-18 years: 54mg once daily; up to 108mg daily may be used under direction of a specialist
(unlicensed) Adult: max. 108mg daily (unlicensed)
6-18 years: max. 60mg once daily; up to 90mg daily may be used under direction of a
specialist (unlicensed) Adult: max. 100mg daily (unlicensed)
6-18 years: 60mg daily; up to 90mg daily may be used under direction of a specialist
(unlicensed) Adult: max. 100mg daily (unlicensed)
Dexamfetamine Refractory ADHD (6-18 years of age)
Narcolepsy
(adults)
(Generic only)
Plain tablets: 5mg 6-18 years: up to 20mg daily in 2-4 divided doses; 40mg daily has been required in some children (unlicensed)
Adult: max. 60mg daily (unlicensed)
Lisdexamfetamine ADHD refractory to methylphenidate
(6-18 years of age)
ElvanseTM Capsules: 30mg, 50mg, 70mg 6-18 years: max. 70mg daily Adult: max. 70mg daily (unlicensed)
Atomoxetine ADHD (6 years+) StratteraTM Capsules: 10mg, 18mg, 25mg, 40mg, 60mg, 80mg, 100mg
6 years and over: max. 120mg daily under direction of a specialist
Guanfacine ADHD in children and adolescents 6-17 years of age for
whom stimulants are not suitable, not
tolerated or ineffective
IntunivTM Modified release tablets: 1mg, 2mg, 3mg, 4mg
6–13 years, body-weight over 25 kg: initially 1 mg once daily, usual maintenance dose 0.05–0.12 mg/kg (max. 4 mg) daily
13–17 years, body-weight 34–41.5 kg: initially 1 mg once daily, usual maintenance dose 0.05–0.12 mg/kg (max. 4 mg) daily;
body-weight 41.5–49.5 kg: initially 1 mg once daily, usual maintenance dose 0.05–0.12 mg/kg (max. 5 mg) daily;
body-weight 49.5–58.5 kg: initially 1 mg once daily, usual maintenance dose 0.05–0.12 mg/kg (max. 6 mg) daily;
body-weight over 58.5 kg, initially 1 mg once daily, usual maintenance dose 0.05–0.12 mg/kg (max. 7 mg) daily;
doses should be increased by 1 mg increments at weekly intervals if necessary and tolerated
34
1.7 Global epidemiology
Discerning even basic epidemiological patterns from the body of research
carried out into ADHD is difficult. The definitions and diagnostic criteria used vary
between studies, as do the age groups scrutinised and the methods used for case
ascertainment. Furthermore, cultural and ethnic differences mean that some
populations do not recognise the existence of ADHD in accordance with its DSM
definition, or regard it as a variant of normal childhood behaviour rather than a
distinct medical disorder (Charach et al., 2011). As summarised by the Centers for
Disease Control and Prevention (2013b): “Although investigation of ADHD has been
quite extensive over the past 30 years, the scientific process has been significantly
slowed by the lack of a single, consistent, and standard research protocol for case
identification. Variable and disparate findings have been noted throughout the
literature even on basic issues such as prevalence”.
Though the range of prevalence values reported worldwide is broad (from
different regions, and even by different studies within the same region) it is
generally agreed that ADHD is a relatively common condition (Kooij et al. 2010;
Bolea-Alamañac et al. 2014; Adamou et al. 2013; Turic et al. 2010). ADHD may even
be the most prevalent neurodevelopmental disorder of childhood (Banerjee et al.,
2007; Shaw et al., 2007; Volkow et al., 2009). Furthermore, research from several
countries (including the United States, Australia and the Netherlands) suggests that
its prevalence is on the rise, though this is hotly debated (Thomas et al. 2014). The
United States has reported some of the highest estimates of ADHD prevalence. In
2011, the Centers for Disease Control and Prevention reported that approximately
6.4 million (around 11%) of American children aged 4-17 years had received a
medical diagnosis of ADHD (Centers for Disease Control and Prevention 2013b).
This (particularly high) estimate was based on parentally-reported diagnoses. This is
just one of the many and varied methods of case ascertainment used to estimate
the burden of ADHD, including parent/teacher/patient questionnaires, analysis of
prescription figures and scrutiny of medical records.
35
In 2007 Polanczyk et al. conducted a systematic review of the literature relating to
ADHD prevalence. One hundred and two studies from all regions of the world were
synthesised to derive a global pooled prevalence estimate for ADHD. ADHD/HKD in
combination were estimated to affect 5.29% (95% CI, 5.01 - 5.56) of persons aged
18 and under globally. The authors remarked on the high degree of variation
between studies, but determined that geographic location had comparatively little
impact on results. Multivariate regression modelling showed that the diagnostic
criteria and information sources used by different studies had a significant impact
on the estimates they produced. Based on these findings, the authors concluded
that much of the international variation in ADHD estimates could be ascribed to
methodological differences rather than any ‘true’ variations in prevalence
(Polanczyk et al., 2007). A more recent review by Thomas et al. (2015) involved 175
studies, and gave a somewhat higher pooled prevalence estimate (7.2%; 95% CI, 6.7
- 7.8). In marked contrast to the earlier review, the authors determined that the
region in which a study was conducted did have a significant impact on the results it
reported. Studies from the Middle East reported a higher prevalence of ADHD (on
average) compared to North American studies (Thomas et al. 2015).
Despite the aforementioned difficulties, a number of other inferences can
be drawn from the body of research into ADHD. As addressed previously, twin
studies have consistently indicated that ADHD is a highly heritable disorder (Kooij et
al. 2010). It has been estimated that first degree relatives of a child with ADHD are
4-5 times more likely to have the disorder themselves, compared to the general
population (Bolea-Alamañac et al. 2014). Siblings of children with severe/combined
presentation ADHD may have a 10-fold higher risk of having ADHD themselves
(Bolea-Alamañac et al. 2014). Studies have also found that ADHD is more common
in males than females, though the extent of the gender difference is not entirely
clear. Clinic-based studies suggest that ADHD is up to nine times more common in
boys, although this gender imbalance may be inflated to some extent by referral
bias; epidemiological studies suggest that prevalence is only two to four times
greater in males (National Institute for Health and Care Excellence 2008a). With
regard to age of onset, ADHD is most commonly diagnosed in younger children,
36
usually during their the primary school years (Thomas et al. 2014). The importance
of ethnicity in ADHD is unclear; available evidence suggests that it plays only a
peripheral role. Some North American studies have noted differences in ADHD
prevalence across ethnic groups, but these seem to be a function of cultural factors,
levels of access to healthcare services, and socioeconomic status (Knopf et al.,
2012; Lakhan & Kirchgessner, 2012). With regard to socioeconomic status, a
systematic review carried out by Reiss (2013) established that socioeconomically-
disadvantaged children and adolescents are two to three times more likely to
develop mental health problems in general, and several studies have suggested a
link between socioeconomic status and ADHD specifically (Hjern et al., 2010;
Nomura et al., 2012; Russell et al., 2013). A notable UK study into deprivation and
ADHD (Russell et al., 2013) will be discussed further in section 1.7.1.
There is comparatively little data concerning the epidemiology of ADHD in
adults specifically; until relatively recently ADHD was believed to be a disorder of
childhood and adolescence that resolved when patients reached adulthood.
However, it is increasingly recognised that ADHD may persist into adulthood in a
significant proportion of patients. A meta-analysis of follow-up studies established
that 15% of children with ADHD still met the requirements for a full diagnosis at 25
years of age (Faraone et al., 2006). A further 50% of patients were found to have
only ‘partial remission’, with the persistence of some symptoms sufficient to cause
continued clinical and psychosocial impairments (Kooij et al. 2010). Inattentive
symptoms of ADHD seem to predominate in adults, with hyperactive symptoms
tending to diminish with age (Wong et al. 2009).
Overall, ADHD is estimated to affect between 2-4% of adults worldwide
(McCarthy et al. 2013). This includes patients with ADHD that has persisted from
childhood, and patients whose ADHD was not recognised until later in life. The
gender gap between males and females is narrower in adults with ADHD than it is in
younger patients (Wong et al. 2009). It has been hypothesised that girls with ADHD
tend to exhibit inattentive symptoms rather than (more attention-grabbing)
hyperactive symptoms (Quinn & Madhoo 2014). As a result, they may less likely to
37
be referred and diagnosed as children, and (relatively) more likely to be diagnosed
later in life (Wong et al. 2009).
1.7.1 Epidemiology of ADHD in the UK
Much of the literature surrounding the epidemiology and treatment of
ADHD relates to North America, particularly the United States. There has been
comparatively little large-scale and in-depth epidemiological research carried out in
the UK. What research there has been has uncovered interesting trends in the
disorder and its treatment, but has often left relevant questions unanswered.
Possibly the most notable epidemiological study of ADHD in the UK was
published by McCarthy and colleagues (2012). The aim of the study was to
investigate the annual incidence and prevalence of pharmacologically-treated
ADHD in children, adolescents and adults in UK primary care. The researchers used
longitudinal prescribing data provided by The Health Improvement Network (THIN)
database. This database holds anonymised patient record data provided by a
representative sample of UK GPs. In 2009 it was estimated to hold primary care
records for 5.7% of the UK population (McCarthy et al. 2012a); at the time of the
study it held data for 3,529,615 patients.
Data from January 1st 2003 to December 31st 2008 was scrutinised. Patients
aged 6 and over with a recorded diagnosis of ADHD/hyperkinetic disorder and an
accompanying prescription for either methylphenidate, dexamfetamine or
atomoxetine were identified. In all, 4530 unique patients received 118,929
prescriptions for the drugs of interest during the six-year study. Excepting minor
fluctuations, the prevalence of pharmacologically-treated ADHD increased year-on-
year in all age groups studied. Between 2003 and 2008, the prevalence of
pharmaceutically-treated ADHD doubled in children, and increased fourfold in
adults. Methylphenidate was by far the most commonly-prescribed drug of the
three studied, accounting for at least 88% of prescribing during every year studied.
The number of methylphenidate prescriptions issued rose year-on-year between
2003 and 2008. Prescribing figures from the Care Quality Commission (CQC) show
that this upward trend in methylphenidate prescribing has continued since 2008.
38
Between 2007 and 2012 the number of methylphenidate prescriptions issued in
England rose by 56% (McClure 2013), and annual prescribing has continued to rise
since then (Care Quality Commission 2015). Returning to the McCarthy study, ADHD
was found to be most common in 6-12 year olds (0.91 treated individuals per 100
children in 2008) and least common in those aged 45+ (<0.01 treated individuals
per 100 adults aged 45+ in 2008). In all age groups, ADHD was more prevalent in
males than females, ranging from six times more prevalent in 13-17 year olds to
twice as prevalent in those aged 25-45.
The annual incidence of pharmacologically-treated ADHD provided an
insight into the number of patients being commenced on treatment annually.
Incidence rates were less consistent than prevalence rates across the sample as a
whole, but a number of trends were observed. In patients aged 6-17, overall
incidence rates peaked in 2006, before falling somewhat in 2007 and 2008.
However, in older patients (aged over 18) overall incidence rates peaked in 2008.
Incidence rates for adults were very low overall, and fluctuated across the six years
studied. However, the fact they peaked in 2008 might suggest that awareness of
adult ADHD was increasing at this point.
The study by McCarthy and colleagues has several undoubted strengths. It
was the first study that sought to estimate the incidence and prevalence of treated
ADHD in the UK population as a whole, rather than a particular age group. The
primary care database utilised was representative of the UK population (CSD
Medical Research 2012), has been widely used in epidemiological research
(McCarthy et al. 2012b) and provided a large cohort of ADHD patients for study. It
gave a valuable impression as to what was happening in everyday clinical practice,
rather than in a specific sample under trial conditions. However, the study does
have limitations. Though not in the study’s remit, its findings gave little detail
regarding individuals with ADHD barring their age group and sex. Similarly, the
study’s design meant that only pharmacologically-treated cases of ADHD were
detected, rather than ADHD cases as a whole. Finally, the period of study, the years
2003 to 2008, constituted a weakness. Though not an issue in itself, this period
largely preceded the publication of NICE’s first guidance on ADHD in September
39
2008. As this ‘novel’ guidance would have influenced subsequent practice,
McCarthy’s findings may have ‘dated’ somewhat.
Another analysis of ADHD prevalence in the UK was published by Holden et
al. in 2013. As with the McCarthy study, they utilised coded data provided by a large
primary care database (the Clinical Practice Research Datalink/CPRD) to perform a
retrospective analysis of trends between 1998 and 2010. Like McCarthy and
colleagues, they aimed to estimate changes in ADHD prevalence over the period
studied; there was also an attempt made to assess the resource use and the
financial cost of ADHD. However, their detection method for ADHD cases was
somewhat different.
As with the McCarthy study, ADHD patients were defined as patients aged 6
years plus, with a diagnosis code referring to ADHD and at least one prescription for
a licensed ADHD medication. However, they also included patients with two or
more diagnoses referring to ADHD in their records without any accompanying
prescriptions. The logic underlying this decision was as follows: “For cases where
there was no prescription for an ADHD medication, the requirement of two or more
diagnoses was used to avoid selecting patients with only a provisional diagnosis
recorded by the GP prior to assessment by a specialist. Under NICE guidelines,
diagnosis should be made by a mental health specialist; therefore the second
diagnosis (code) is used to confirm that the patient has ADHD” (Holden et al. 2013,
p.2). This approach gave an estimate of both treated and untreated ADHD in the
primary care sample, rather than just pharmacologically-treated ADHD. The
stipulation that two diagnosis codes should be present to indicate untreated ADHD
is logical, but may distort the study’s findings. In practice, GPs are not actively
encouraged to conform to this pattern of entering a code to indicate a suspected
diagnosis and entering the same code again when the diagnosis is confirmed. As
such, excluding patients with only one diagnostic code referring to ADHD may have
led the authors to exclude valid, diagnosed cases of ADHD, causing them to
underestimate the prevalence of the condition.
40
Between 1998 and 2009 the population prevalence of ADHD increased
markedly. The diagnosed prevalence was much higher in children aged 6-17 than in
adults. Prevalence among children increased 168% between 1998 and 2009, with
ADHD affecting 0.19% of children in 1998 and 0.51% of children in 2009. Whilst the
prevalence of ADHD amongst adults was far lower, it increased on a yearly basis.
Between 1998 and 2009, the prevalence of ADHD amongst adults increased 1029%
but remained negligible overall, affecting just 0.02% of adults in 2009. In common
with the McCarthy study, ADHD was more common in males than females.
Between the ages of 6 and 17 years, male ADHD was 7.9 times more common than
female ADHD, but in adults the gender gap was less pronounced (1.8 times more
common).
To assess the financial costs of ADHD, the authors utilised a case-control
method. Controls were randomly selected from the CPRD database, and were
matched to cases on the basis of year of birth, gender and GP practice. Costs were
compared on an annual basis; only patients with complete data for a particular year
were included in that year’s analysis. Individuals’ annual healthcare costs were
estimated according to prescriptions received, primary care contacts, outpatient
appointments attended and diagnostic investigations undertaken. This information
was derived from the information directly held by CPRD. Additionally, through the
linkage of CPRD records with Hospital Episode Statistics (HES) data, individuals’
hospital admissions could be added to the cost analysis. Based on the criteria
examined, the annual healthcare costs of ADHD patients were consistently and
substantially higher than those of controls. For the years studied, the mean annual
healthcare cost of individuals with ADHD was approximately £1182, compared to
£333 for controls. This £850 difference was not solely related to prescribing costs
for ADHD-related medications; across all the criteria scrutinised, patients with
ADHD incurred higher healthcare costs. For example, costs related to primary care
consultations, outpatient appointments and hospital admissions were all higher
amongst ADHD patients than controls, though it was unclear whether this extra
spending was totally attributable to ADHD.
41
Due to the different age groupings scrutinised, directly comparing the
prevalence figures reported by the McCarthy and Holden studies is problematic.
However, taken together they suggest that ADHD, and pharmacological treatment
for ADHD is increasingly prevalent amongst UK children and adolescents. This is
notable, given that individuals with ADHD incur significantly higher healthcare costs
than matched controls (Holden et al. 2013). In the UK, the healthcare costs of ADHD
may not even be its greatest economic impact. A longitudinal study carried out by
Telford and colleagues suggested that ADHD’s cost to the UK education system is
three times that borne by the NHS (Telford et al. 2013).
International research has suggested that there is an association between
ADHD and socioeconomic deprivation. In 2013, Russell and colleagues explored the
association between parentally-reported ADHD and indicators of socioeconomic
disadvantage in the UK. Using longitudinal data from a large UK birth cohort, the
researchers examined several indicators of social and economic disadvantage
(including poverty status, household income, housing tenure and maternal
education level). The number of ADHD cases in the cohort was relatively low
(n=187), but statistically significant differences between these children and children
without ADHD were observed. Mean weekly income was lower in households with
a child with ADHD (£324 v £391, p=0.001), and children living below the poverty
line were 1.65 times more likely to have ADHD than those living in wealthier
households (95% confidence interval/CI: 1.13 - 2.42, p=0.009). In all, 40% of
children with ADHD were classed as living in poverty according to the UK
government’s definition. Parents who owned their own homes were significantly
less likely to have a child with ADHD compared to those living in social housing
(odds ratio/OR 0.37, 95% CI: 0.26 - 0.53, p=<0.001); single parent households were
twice as likely to have a child with ADHD (OR 2.07, 95% CI: 1.42 - 3.03, p=<0.001).
The study’s authors sought to establish the direction of this apparent relationship;
did socioeconomic disadvantage promote childhood ADHD, or did childhood ADHD
promote socioeconomic disadvantage? They found no evidence that childhood
ADHD was a causal factor for socioeconomic disadvantage; having a child diagnosed
with ADHD had no subsequent effect on household income. Furthermore, the
42
authors dismissed the notion that clinician labelling bias was at work; children of
lower socioeconomic status were no more likely to be diagnosed with ADHD than
other children with the same level of symptoms. The overall conclusion that the
investigators drew was that a child’s socioeconomic status could significantly
influence their chances of developing ADHD.
The cohort of children included in Russell’s study were sampled from all
over the United Kingdom. If the links observed between socioeconomic deprivation
and ADHD applied at a national level, it would be reasonable to assume that
deprived geographic areas would have a higher concentration of ADHD patients
than less deprived areas. It has been established that primary care spending on
methylphenidate varies significantly across England (Rowlingson et al., 2013), but it
has not yet been established if these prescribing variations correspond to regional
variations in deprivation. A summary of previous studies addressing the
epidemiology of ADHD in the UK is provided in Table 2.
Table 2: Selected studies addressing the epidemiology of ADHD in the UK (prior to 2016)
Authors Year of
publication
Study design (number of ADHD patients)
[period studied]
Summary of key findings
McCarthy et al. 2012
Retrospective cohort study
(n=4530*)
[2003-2008]
Prevalence of pharmacologically-treated ADHD increased year-on-year between
2003-2008
Incidence of treated ADHD rose between 2003-2008, with incidence peaking in 2006
Prevalence of pharmaceutically-treated ADHD doubled in children and adolescents
and those aged 45+
Holden et al. 2013
Retrospective cohort study
(n=3229**)
[1998-2010]
Incidence of diagnosed ADHD rose markedly between 1998-2007, but
decreased somewhat between 2007-2010
Healthcare costs of patients with ADHD were approximately four times higher than
those of matched controls
Rowlingson et al.
2013
Analysis of national prescribing data
[September 2011]
Primary care spending on methylphenidate varied significantly across England; certain
regions exhibited substantially and significantly higher spending per child
Russell et al. 2013 Retrospective cohort study
(n=187)
ADHD significantly associated with several indicators of socioeconomic deprivation
*Total number of ADHD patients identified during period scrutinized (2003-2008) **Number of ADHD patients identified at the outset of the study (1998)
43
1.8 Personal and societal impacts of ADHD
The real-world impact of ADHD is significant, both on its sufferers and society as a
whole. Impairments stemming from the symptoms of ADHD can have a chaotic
impact on all aspects of patients’ lives (Matheson et al. 2013). Possibly the most
discussed societal impact is on the education system. There is a wealth of research
showing that ADHD in childhood can be incredibly disruptive to childrens’
education. Patients are likely to underachieve academically, completing fewer years
in education, attaining poorer exam results and being subject to more frequent
disciplinary action (Wong et al. 2009; Birchwood & Daley 2012). This early academic
impact in itself may limit individuals’ future prospects; if ADHD persists into
adulthood its impact on employability is compounded. Adults with ADHD have a
lower rate of employment than controls, and have less job stability; unsurprisingly
persons with ADHD are more likely to have a lower socioeconomic status (Wong et
al. 2009). Whilst education and employment have been the focus of much research
surrounding ADHD, its impact on patients’ domestic lives should not be
underestimated. ADHD’s symptoms can impede the formation and maintenance of
normal family relationships; it is often the source of familial and marital discord
(National Institute for Health and Care Excellence 2008a; McCarthy et al. 2012a).
The nature of the link between ADHD and antisocial behaviour is both
complex and controversial. However, the evidence for the existence of a link is
substantial. Schilling et al. (2011) summarised: “there is an abundance of research
that identifies a strong and robust relationship between ADHD and delinquent and
criminal behaviour” (Schilling et al. 2011, p.1). A review of the literature carried out
by Ellis and Walsh (2000) found that 99 out of 100 papers identified reported a
positive correlation between ADHD and antisocial behaviour, ranging from violent
and property crime to juvenile delinquency and drug offences. Studies from several
countries around the world have found that patients with ADHD are consistently
over-represented in young offenders institutions, jails and prisons (Young et al.
2011). Adolescents and adults with ADHD have an increased risk of developing
alcohol and drug problems; this comprises a further and distinct risk factor for
involvement in crime and the criminal justice system (McCarthy et al. 2012a).
44
Disorders relating to alcohol and drugs (collectively termed ‘substance use
disorders’) are just one of a vast number of comorbidities that have been linked
with ADHD. It has been estimated that up to 65% of children with ADHD have one
or more significant comorbidities (Kooij et al. 2010); the figure in adults is even
higher (Sobanski 2006; Kooij et al. 2010). The most prevalent comorbidities appear
to be neurodevelopmental disorders such as autism, tic disorder, Tourette’s
syndrome (Kooij et al. 2010); mood disorders such as anxiety and depression
(McCarthy et al. 2012b); and personality disorders such as oppositional defiant
disorder, conduct disorder, antisocial personality disorder (Lakhan & Kirchgessner
2012). ADHD may even be a significant risk factor for accidental injury (Hodgkins et
al., 2011). These comorbidities may complicate the diagnosis and treatment of the
disorder, and can only serve to compound its harmful effects.
ADHD’s negative impact is clearly not limited to its sufferers; parents,
siblings, classmates, colleagues and society in general may all experience problems
stemming from a single patient’s disorder. Quantifying its many and varied impacts
is almost impossible, but some studies have attempted to do so. A systematic
review carried out by Doshi et al. (2012) surmised that the total cost of ADHD, to
the economy of the United States alone, was between $143 and $266 billion (USD)
per annum. Most of the cost incurred was indirectly linked to ADHD (such as
reduced productivity and income); a relatively small proportion was directly
incurred through its treatment (Doshi et al. 2012). In the UK, ADHD is estimated to
cost the education, health and social care system around £670 million per annum
(Telford et al. 2013). However, this estimate did not factor in indirect costs such as
reduced productivity and income.
45
Chapter 2
Aims and Objectives
46
2.1 Rationale and aims
ADHD can have a massive and multi-faceted impact on both its sufferers and
society as a whole. In spite of this, the epidemiology of ADHD in the UK has yet to
be fully characterised, and several questions remain unanswered. This study will
seek to update the findings of earlier epidemiological studies, and provide new
insights into the epidemiology of ADHD in the UK.
2.1.1 Diagnostic incidence
Earlier population studies have demonstrated that ADHD is increasingly
prevalent in UK children (McCarthy et al. 2013; Holden et al. 2013). It is unclear
whether diagnostic incidence has reached a plateau; prescribing for ADHD appears
to have increased notably in recent years (National Institute for Health and Care
Excellence 2013a). This has led to concerns that ADHD is being over-diagnosed,
over-treated, or both (Thomas et al. 2014; Lloyd 2015).
By establishing if increases in prescribing directly corresponded to increases in the
number of children and adolescents being diagnosed with ADHD, it could be
established whether ADHD constitutes a growing problem among UK children.
2.1.2 Patient demographics
Relatively little is known about the demographic characteristics of UK
children with ADHD. Prescribing data suggests that the burden of ADHD is not
evenly distributed across the UK (Rowlingson et al. 2013), and there is some
evidence that ADHD is more common in patients from a socioeconomically-
deprived background (Russell et al. 2013). However, no large-scale study has
systematically examined if patients’ location within the UK, and socioeconomic
status, affects their risk of being diagnosed with ADHD.
Identifying who is being diagnosed with ADHD had the potential to highlight ‘at risk’
groups, and inform the targeting of diagnostic and management resources for
ADHD. Ascertaining if different regions of the UK have different rates of ADHD
47
diagnosis, and if ADHD is more prevalent in socioeconomically-deprived areas, could
give some insights into the disorder’s aetiology.
2.1.3 Treatment
Pharmaceutical treatment has an important role in the management of
ADHD. However, NICE recommends that drugs are reserved for children with
symptomatically-severe ADHD (National Institute for Health and Care Excellence
2008), and no medication for ADHD is currently approved for use in children below
the age of six. In spite of this, cuts to services offering non-pharmaceutical
interventions for ADHD have affected many areas (Lloyd 2015). Primary care
prescribing for ADHD has increased (National Institute for Health and Care
Excellence 2013a), and there is evidence that medications are increasingly being
used outside their licensed indications (Hill & Turner 2015). This has raised concerns
that medication has become the ‘go to’ treatment for all patients with ADHD (Lloyd
2015).
By establishing what proportion of ADHD patients were treated with medication in
primary care, the extent of medication use for ADHD can be gauged. That is to say,
is a diagnosis of ADHD invariably followed by pharmaceutical treatment? By
examining the age at which patients commenced medication, the extent of
unlicensed prescribing in children with ADHD can be established. By establishing the
typical interval between diagnosis and first treatment in primary care, it may be
possible to determine if drugs are being commenced at the point of diagnosis, or
very soon after.
2.1.4 Comorbidity
There is evidence to suggest that ADHD is associated with significant mental,
behavioural and neurological comorbidity (Kraut et al. 2013). However, the burden
of such disorders amongst UK children and adolescents with ADHD has not been
extensively explored. With regard to physical comorbidity, it seems intuitive that
ADHD’s core symptoms (hyperactivity, impulsivity and inattention) would increase
48
an individuals’ likelihood of sustaining accidental injuries. However, evidence for
this is lacking.
Examining the prevalence of specific mental, behavioural and neurological
comorbidities amongst UK children with ADHD will establish how common these
disorders are in these patients. By examining psychotropic use in these patients, the
burden of such disorders more generally can be estimated amongst UK children with
ADHD. Examining the prevalence of accidental fractures amongst UK children with
ADHD will establish if accidental injury is a significant source of comorbidity in these
patients.
2.2 Objectives
Chapter 4: ADHD in the United Kingdom: Regional and socioeconomic variations in
incidence rates amongst children and adolescents (2004-2013)
Describe the annual incidence of ADHD amongst UK under 19s between 2004
and 2013.
Examine differences in ADHD incidence by age band, gender, geographic
location and socioeconomic status.
Chapter 5: ADHD in children and adolescents: Prevalence and predictors of
medication use in UK primary care
Establish what proportion of patients diagnosed with ADHD received a primary
care prescription for a licensed ADHD medication.
Determine (in pharmaceutically-treated patients) the average time between
diagnosis and the start of treatment in primary care, and the age at which
treatment was commenced.
Determine which of the four medications licensed to treat ADHD are most
commonly initiated first-line in primary care.
Examine if patients’ likelihood of receiving medication in primary care varies
according to age, gender, geographic location and socioeconomic status.
49
Chapter 6: Mental, behavioural and neurological comorbidity and psychotropic
treatment in children and adolescents with ADHD: A cohort study using linked CPRD
and HES data
Describe the prevalence of selected mental, behavioural and neurological
comorbidities amongst a cohort of ADHD patients registered with English
general practices, and a cohort of age, gender and practice-matched
comparators.
Establish if selected mental, behavioural and neurological comorbidities are
significantly more likely in children with ADHD than a cohort of matched
comparators.
Establish if children with ADHD have greater exposure to psychotropic drugs
than those without ADHD.
Chapter 7: Fracture risk in children and adolescents with ADHD: a cohort study using
linked CPRD and HES data
Describe the prevalence of accidental fracture amongst a cohort of ADHD
patients registered with English general practices, and a cohort of age, gender
and practice-matched comparators.
Establish if certain types of fracure are more likely to occur in children with
ADHD than a cohort of matched comparators.
Establish if accidental fractures are significantly more likely to occur in patients
with ADHD than matched comparators.
50
Chapter 3
Methods
51
3.1 Data Sources
3.1.1 Clinical Practice Research Datalink (CPRD)
The study used diagnostic and prescribing data held by the Clinical Practice
Research Datalink (CPRD). CPRD has been collecting longitudinal medical records
data from UK general practices since 1987 (Mansell 2013). At the time of its
inception (as the ‘General Practice Research Database’/GPRD), UK general practices
were beginning to widely adopt computer systems and clinical management
software; from the outset it was realised that the data these held would be useful
for research purposes (Rodríguez & Gutthann, 1998). Almost the entire UK
population is registered with a general practice; they play a key role in the
diagnosis, treatment and management of both acute and chronic conditions, and
act as a gatekeeper to specialist secondary care services (Roland et al. 2012). The
number of general practices sharing data with the CPRD has expanded steadily over
time; it now holds research-quality data for around 680 UK general practices
(Clinical Practice Research Datalink 2014c). This equates to around 9% of the UK’s
general practices (Mansell 2013) and records for around 13 million individuals
(Clinical Practice Research Datalink 2014c), a very large sample that is broadly
representative of the UK population in terms of age, sex and geographic
distribution (Thomas et al. 2013; Holden et al. 2013; Herrett et al. 2015). Electronic
healthcare records databases have become a mainstay of epidemiological research
(Ehrenstein et al., 2010); of these databases, CPRD is the largest (Frampton 2014).
As of January 2016, over 1500 clinical research papers and other publications have
been produced based on its data (Clinical Practice Research Datalink 2014a).
The range of data CPRD holds for patients is diverse (see Table 3), and made
it well-suited to use in the current study. Given the important role GPs play in the
diagnosis and routine management of ADHD, CPRD could be used to identify a large
and representative sample of ADHD patients with a medically-affirmed diagnosis of
ADHD. Patients’ age, gender and region of residence could be determined, along with a
proxy measure for their socioeconomic status (discussed further in section 3.1.2) and
details of their pharmaceutical treatment in primary care. The longitudinal data
52
provided by CPRD allowed diagnostic and prescribing trends to be tracked over a
long period; its nationwide scope allowed regional variations in these trends to be
identified.
Table 3: Description of files that comprise an individual patient’s CPRD record
File Description Overview of data provided
Patient File
Contains demographic information about
patient, and details regarding their general
practice registration.
Encrypted patient identifier (‘patid’),
gender, birth year, birth month, date of
registration with general practice,
registration status (temporary or
permanent), transfer out of practice date
(if applicable), date of death (if
applicable)
Practice File
Contains information on the patient’s general
practice, its geographic location and its data
contributions to CPRD.
Patid, encrypted practice identifier
(‘pracid’), UK region in which practice is
based*, ‘up to standard’ date, last date
of data collection by CPRD
Staff File
Contains information relating to general
practice staff who have entered data into
patient’s record.
Patid, encrypted staff identifier (‘staffid’),
staff member’s role within practice
Consultation File Contains information relating to the type of
consultations undertaken.
Patid, staffid, date of consultation,
consultation type, unique consultation
identifier
Clinical File
Contains patient’s medical history. Every
medical event (eg a clinical sign, symptom or
diagnosis) is recorded using a unique
medical code (‘medcode’). Each medcode in
CPRD is associated with a specific Read
code; each Read code denotes a specified
clinical term.
Patid, medcode associated with medical
event, date of medical event (as entered
by GP), staffid, consultation type,
additional details identifier (‘adid’)
Additional
Clinical Details
File
Contains additional data associated with
events recorded in the Clinical File (not
applicable in all cases). Clinical Files and
their associated Additional Clinical Details
Files may be linked by their adid.
Patid, adid, data field 1-7, entity type
(denotes what type of data type is
documented in data fields 1-7)
Referral File
Contains details of referrals made to
secondary care and other external care
centres, along with the reasons for these
referrals.
Patid, medcode associated with referral,
date of referral event (as entered by
GP), referral speciality, type of referral,
urgency of referral
Immunisation
File
Contains information on immunisations
received.
Patid, medcode associated with
immunisation, date of referral event (as
entered by GP), immunisation
components, reason for immunisation,
route of administration, immunisation
batch number
Test File Contains details of medical tests performed. Patid, medcode associated with test,
date of test (as entered by GP)
Therapy File
Contains details of all items prescribed to an
individual by their GP. Every drug or product
issued is recorded using a unique product
code (‘prodcode’). Each prodcode in CPRD
is associated with a specific drug or medical
product; a full list of prodcodes and their
associated items are accessible through
CPRD.
Patid, prodcode associated with
prescribed item, date item was issued
(as entered by GP), British National
Formulary (BNF) code for item (denoting
the chapter and section of the BNF in
which item is listed), quantity prescribed,
number of packs prescribed, daily dose
specified
*By looking at the practice identifier associated with a particular patient, their location within the United Kingdom
can be discerned. CPRD subdivides the UK (a nation itself comprised of four ‘nations’—England, Scotland,
Wales, and Northern Ireland) into 13 geographical regions. Scotland, Wales, and Northern Ireland comprise
three of these regions; the remainder are regions situated within England (North West, North East, Yorkshire
and the Humber, East Midlands, West Midlands, East of England, South West, South Central, London, and the
South East Coast; West et al., 2014).
53
3.1.1.1 CPRD data linkage
CPRD’s data linkage scheme allows CPRD’s primary care data to be cross-
referenced against other patient-level datasets, such as Hospital Episode Statistics
(HES), Office of National Statistics (ONS) mortality data and UK cancer registries
(Lee 2014). Data linkage adds to the depth of information available to researchers,
but cannot be carried out for all patients within CPRD. Linked data is only accessible
for patients registered with English general practices that have specifically
consented to participate in the linkage scheme. This equates to around 70% of
English general practices, and just over 50% of all patients in CPRD (CPRD
Knowledge Centre, personal communication, 2014). The study made use of linked
data in two ways: in the assessment of patients’ socioeconomic status, and the
identification of comorbid diagnoses/accidental fractures.
3.1.2 Index of Multiple Deprivation (IMD) data
England and Wales are divided up into approximately 35,000 defined
geographical areas known as Lower Layer Super Output Areas (LSOA; Office of
National Statistics, 2011). Generated for the purposes of statistical research, these
areas each contain populations of between 1000 and 3000 people (Office of
National Statistics, 2011). Similar geographic divisions are applied to Northern
Ireland and Scotland, which are divided into smaller areas termed datazones (DZ;
U.K. Data Service, 2014). Measurements relating to seven key indicators of
socioeconomic deprivation are routinely compiled for each LSOA/DZ. These
indicators examine household income, employment, health and disability,
education and training, barriers to housing and services, crime, and the living
environment (U.K. Data Service, 2014). An amalgamation of this information is used
to calculate an Index of Multiple Deprivation (IMD) score for each LSOA/DZ,
allowing each to be ranked in order of relative deprivation.
Every general practice contributing data to CPRD has an IMD score based on
the LSOA/DZ in which it is situated. These scores are available to CPRD researchers,
rounded to the nearest quintile. For the purposes of this study, these ‘practice-
level’ IMD scores were used as a surrogate measure of patients’ deprivation status.
54
This measure was deemed appropriate as patients would be expected to reside in
the locality of their general practice, within a geographically defined catchment
area (NHS Choices, 2014). For patients registered with English practices that
participated in CPRD’s data linkage scheme, an additional measure of IMD could be
obtained. Through data linkage, these patients’ home post code was used (by
CPRD) to confirm the specific LSOA in which they were resident. By comparing
these individuals’ ‘practice-level’ IMD score with their ‘postcode-level’ IMD score, it
could be established whether practice-level deprivation scores provided an
accurate reflection of postcode-level deprivation scores.
3.1.3 Hospital Episode Statistics (HES) data
Hospital Episode Statistics (HES) inpatient data was accessed for patients
registered with general practices in England that had consented to data linkage.
This data contained details of all admissions and day case management involving
National Health Service (NHS) hospitals in England (Medicines and Healthcare
Products Regulatory Agency 2016). All new or pre-existing diagnoses documented
during patients’ hospital spells were accessible, along with the date of patients’
discharge and more general patient information (such as ethnicity and gender). As
such, HES data had the potential to identify hospital admissions related to
comorbidities of interest, to verify diagnoses that were present in patients’ primary
care records, or to identify diagnoses not otherwise recorded in patients’ primary
care records.
3.1.4 Independent Scientific Advisory Committee (ISAC) approval
Data held by CPRD is subject to stringent governance and security measures.
All patient data is anonymised and encrypted before it is sent to CPRD (Robinson
2013); individual patients remain recognisable as such through the assignment of
unique identifying numbers (Medicines and Healthcare Products Regulatory Agency
2012). Patients have the option to opt-out of data sharing at any time; just over one
thousand individuals have taken up this option (Mansell 2013). Only approved
researchers and organisations are given access to CPRD data, and steps are taken to
prevent its misuse (Robinson 2013). All data linkage is performed by a trusted third
55
party (The Health and Social Care Information Centre/HSCIC), and no direct
identifying data is released to researchers (Clinical Practice Research Datalink
2014b). To utilise CPRD data for the purposes of research, approval was obtained
from CPRD’s Independent Scientific Advisory Committee (ISAC). The study protocol
approved by ISAC (reference 15_036RAR) and approval notification are available in
Appendix 1.
3.2 Identifying cohorts of interest: Chapters 4 and 5
Chapters 4 and 5 involved the identification of UK children and adolescents
newly diagnosed with ADHD between 1/1/2004 and 31/12/2013. Within this
incident cohort, patients who received pharmaceutical treatment for their ADHD
were identified.
3.2.1 Identifying the population ‘at risk’ of ADHD
The study aimed to identify new diagnoses of ADHD amongst previously
undiagnosed children and adolescents. Previously undiagnosed children and
adolescents were defined as being at risk of developing ADHD at a given point in
time if:
1. It was during the ten-year study period (1/1/2004 – 31/12/2013)
2. They were alive, and under nineteen years of age.
3. They had no prior diagnosis of ADHD, and had not previously received a
prescription for one of its licensed treatments. The identification of ADHD
and drugs used in its treatment is detailed in sections 3.2.3 and 3.2.3.1.
4. They were registered with a CPRD general practice classified as ‘up to
standard’ for research purposes, and had been registered with that practice
for the preceding 365 days or longer.
3.2.1.1 Exclusion criteria
1. Individuals temporarily registered with GP practices were excluded from the
‘at risk’ population. Temporary registrations potentially represented
individuals visiting a particular GP on a single, isolated occasion (when on
56
holiday, for example). These patients would be expected to have a
permanent GP registration elsewhere, holding a more complete record of
their medical and prescribing history.
2. Individuals were only eligible for involvement in the study if they were
registered with ‘up to standard’ general practices. Rigorous quality control
procedures ensure that research data provided by CPRD is complete and of
high quality (Khan et al., 2010), and all data shared by GP practices is
assessed for completeness and continuity upon its submission. Only when a
practice meets specified quality criteria for data recording is it deemed ‘up
to standard’ for research purposes. At the time the study was conducted,
CPRD held data for 680 ‘up to standard’ practices and contained research
standard data for over 13 million patients (Clinical Practice Research
Datalink 2014c).
3. The study did not consider undiagnosed individuals at risk of developing
ADHD after the age of nineteen. It is true that ADHD can persist into
adulthood, and may only be recognised and diagnosed in adulthood in some
cases (McCarthy et al. 2013). However, previous research had demonstrated
that these patients (at present) comprise a very small proportion of UK
ADHD patients (McCarthy et al. 2012; Holden et al. 2013). Prior to the study,
an exploratory analysis was conducted to identify adults diagnosed with
ADHD between 2004 and 2013. The number of individuals identified was
small, and in some cases the data held on these patients was of
questionable accuracy. For example, several patients appeared to have been
diagnosed with ADHD in their seventies and eighties, which would seem
highly unusual for a disorder that first manifests in childhood. For these
reasons, the decision was taken to focus the research purely on children and
adolescents.
3.2.2 Calculating person-time spent ‘at risk’ of developing ADHD
Between 1/1/2004 and 31/12/2013, 1,982,021 children and adolescents
were at risk of developing ADHD. However, the exact length of time each child
spent at risk varied. Individuals joined and left general practices at different times,
57
some individuals died, and some reached adulthood. Some may have been at risk of
developing ADHD for just one year; others may have been at risk for the entire ten-
year study period. The exact time each individual spent at risk of developing ADHD
could be calculated.
Individuals were at risk of developing ADHD from the latest point of the following
dates:
1. The date on which they had been registered with their general practice for
365 consecutive days.
2. The date on which their practice became ‘up to standard’ for research
purposes.
3. The study start date (1/1/2004).
Individuals ceased to be at risk of developing ADHD on the earliest of the following
dates/censoring points:
1. The earliest date on which a diagnosis of ADHD was made, or a prescription
for a licensed ADHD treatment was issued.
2. The date they transferred out of their CPRD-registered general practice (if
applicable).
3. Their date of death (if applicable).
4. January 1st on the year they turned nineteen. The study had access to
patients’ year of birth, but the data held on month of birth was incomplete.
For this reason, patients were assumed to have turned nineteen on January
1st during the year they turned nineteen.
5. The last date on which their practice shared data with CPRD.
6. The study end date (31/12/2013).
By establishing how long each individual spent at risk of developing ADHD
(their follow-up time), the total ‘person-time at risk’ for the ten-year study period
was established. By counting the number of new ADHD diagnoses that occurred
during the study period, and dividing it by the number of person-years at risk during
the study period, the incidence of ADHD during the ten-year study period could be
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determined. This was presented as the number of cases per 10,000 person-years at
risk.
The person-time at risk during each year of the study period was also
derived. By establishing the number of new ADHD diagnoses made in a particular
year, and dividing that number by the person-time at risk during that year, that
year’s incidence of ADHD could be determined, and compared to other years.
Person-time at risk could additionally be stratified by gender, general practice
region, age and socioeconomic status.
3.2.3 Identifying ADHD patients
Individuals developing ADHD were identified amongst the ‘at risk’
population through the presence of codes indicating the disorder. As discussed
previously, clinical and prescribing information within CPRD is coded. Each code
corresponds to a clinical term (such as a diagnosis, clinical sign or symptom), or a
medical item (such as a drug or medical device). By identifying relevant codes in a
patient’s CPRD record, relevant diagnoses and prescriptions could be identified.
Assembling a list of Read codes for ADHD involved several steps. It was important
to establish if a standardised and/or validated list of Read codes for ADHD already
existed, and had been widely used in epidemiological studies involving CPRD (and
its predecessor, GPRD). Using such a list would save time, and increase the external
validity of the study’s findings. Whilst several studies had examined ADHD using
CPRD/GPRD data, the code lists used by these studies were often unpublished. One
notable exception was identified. Wong and colleagues (2009) examined
medication cessation in teenagers with ADHD. The code list they used in the
identification of patients with ADHD was included among their supplementary
research materials. This code list, though informative, was not felt to be
appropriate for use in the current study. There was no indication that the list had
been validated, and some of the clinical terms and codes listed appeared relatively
unspecific for ADHD. For example, Read codes for terms such as “poor
concentration” and “behaviour problem” were included on their code list for the
identification of ADHD patients. Given the importance of identifying valid cases of
59
ADHD, the decision was taken to prepare a bespoke code list for use in the current
study.
CPRD provides a dictionary of Read codes and their associated clinical terms.
By identifying clinical terms related to ADHD, a list of Read codes was compiled. To
ensure that the list compiled was comprehensive, the Medical and Subject Heading
(MeSH) facility provided by the U.S. National Library of Medicines (available at
https://www.nlm.nih.gov/mesh/2016/mesh_browser/MBrowser.html) was used
beforehand to identify synonyms, keywords and word stems associated with ADHD.
Once compiled, the code list prepared was reviewed by a panel containing
psychiatrists and general practice specialists. The final list of Read codes (n=30)
used in the identification of ADHD patients is listed in Appendix 2.
A diagnosis of ADHD was ascertained by the presence of a Read code
denoting the disorder in a patient’s CPRD record (Clinical File). All ADHD patients
identified were required to have at least one Read code for the disorder
documented in their CPRD record; most ADHD patients had more than one Read
code relating to the disorder in their records. The earliest date on which a Read
code for ADHD was documented was taken as the patient’s date of diagnosis (with
some exceptions, see section 3.2.3.1).
In all, 10,284 individuals amongst the population ‘at risk’ developed ADHD
during the study period. To be at risk of developing incident ADHD, undiagnosed
individuals had to have been registered with their general practice for at least 365
consecutive days. This measure was taken to reduce the likelihood of non-incident
ADHD patients being mistaken for newly-diagnosed patients. A Read code for ADHD
documented within days or weeks of a patient joining a general practice could
indicate a patient diagnosed with ADHD elsewhere who has transferred general
practices. In contrast, the occurrence of a diagnostic code for ADHD, after a year
without any recorded reference to ADHD, would be more likely to denote a new,
incident case of ADHD.
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3.2.3.1 Treated and untreated ADHD patients
Diagnosed ADHD does not always require treatment with medication
(Holden et al. 2013; National Institute for Health and Care Excellence 2008). It was
therefore assumed that the 10,284 ADHD patients identified would consist of both
pharmaceutically-treated and pharmaceutically-untreated individuals. In order to
obtain information on how ADHD was treated in primary care, the cohort was
subdivided into two groups: ADHD patients who received pharmaceutical treatment
in primary care (termed ‘treated’ patients), and patients who did not receive
pharmaceutical treatment in primary care (hereafter referred to as ‘untreated’
patients).
Untreated patients (n=5813)
These were patients with at least one Read code indicating a diagnosis of ADHD in
their CPRD record during the study period, but no recorded prescription for a
licensed ADHD medication. The date on which this diagnostic event occurred was
referred to as patients’ ‘index date’.
Treated patients (n=4471)
Treated patients had at least one Read code indicating a diagnosis of ADHD in their
CPRD record during the study period, along with at least one documented
prescription for an ADHD medication.
The study examined the use of four drugs in the treatment of ADHD. These
drugs were methylphenidate, dexamfetamine, lisdexamfetamine and atomoxetine.
All four drugs are licensed for use in the treatment of children and adolescents with
ADHD, and all four drugs were available to UK prescribers for at least some part of
the ten-year study period. Methylphenidate and dexamfetamine have been
available to prescribers in the UK for decades; atomoxetine was introduced to the
UK market in 2004, and lisdexamfetamine was introduced in 2013. Pemoline was
formerly licensed for the treatment of ADHD in the UK but was withdrawn from the
market several years before the study began (Committee on Safety of
Medicines/Medicines Control Agency 1997). Conversely, guanfacine entered the UK
61
market in 2016, after the end of the study period (National Institute for Health and
Care Excellence 2016). Exposure to these drugs was not examined.
Items prescribed by GPs (such as medications and medical devices) are
recorded in CPRD using prodcodes/product codes. A dictionary of product codes
and the items they represent are provided by CPRD. All medications containing
methylphenidate, dexamfetamine, lisdexamfetamine and atomoxetine were
identified and their product codes were noted. Both branded and generic versions
of the medications were captured, along with all strengths and oral dosage forms
available. These codes would be used to identify patients who received a licensed
ADHD medication in primary care; a full list of product codes and their associated
items is provided in Appendix 3.
The earliest occurrence of a product code for a licensed ADHD medication
was taken as the point at which patients commenced pharmaceutical treatment in
primary care. The time between an individual’s first recorded Read code for ADHD
and their first recorded product code for an ADHD medication could be calculated.
This represented the time between their first diagnosis and first treatment in
primary care. In most treated patients, the earliest occurrence of a diagnostic Read
code for ADHD preceded a product code for one of its licensed treatments.
However, in cases where a patient’s earliest prescription for a licensed ADHD
medication preceded their earliest recorded diagnosis, the date of that prescription
was taken as their index date.
3.3 Identifying cohorts of interest: Chapters 6 and 7
In chapters 6 and 7, ADHD patients and matched comparators without
ADHD were screened to establish what proportion of individuals:
1. Had a diagnosis of autism/autistic spectrum disorder, anxiety disorder,
depression, tic disorder/Tourette’s syndrome, epilepsy, conduct
disorder/oppositional defiant disorder or a severe mental illness (SMI)
documented between 1/1/2004 and 31/12/2013. These were collectively
termed mental, behavioural and neurological comorbidities.
62
2. Received a primary care prescription for an antipsychotic, an antidepressant or
an anxiolytic/hypnotic drug between 1/1/2004 and 31/12/2013.
3. Sustained a fracture between 1/1/2004 and 31/12/2013.
It was important that the detection of these outcomes was robust. CPRD’s
primary care data provided extensive clinical information on patients (including
information communicated from secondary care). However, linkage with secondary
care data held the potential to detect cases of comorbidity/fracture that may not
have been recorded in individuals' primary care records. As such, chapters 6 and 7
required the identification of a cohort of ADHD patients that were eligible for CPRD
data linkage. A matched cohort of patients without ADHD was similarly identified.
3.3.1 Linkage-eligible ADHD patients
From the incident cohort of ADHD patients (n=10,284), all ADHD patients
eligible for data linkage were identified (n=5111). This cohort contained both
treated and untreated ADHD patients, as described in section 3.2.3.1. For these
patients, hospital episode statistics could be accessed, along with home postcode-
level deprivation data. The use of a linkage-eligible cohort in this study's
comorbidity/fracture research did involve a trade-off. The use of HES data
enhanced the detection of comorbidity/fracture. However, HES data could only be
obtained for patients registered with linkage-eligible general practices in England.
As such, the findings of this study in relation to comorbidity, fracture and
psychotropic treatment only relate to ADHD patients registered with general
practices in England (rather than the UK as a whole).
3.3.2 Linkage-eligible comparison cohort
In order to compare the prevalence of comorbidity amongst individuals with
ADHD to individuals without the disorder, a comparison cohort was identified.
These individuals were members of the ‘at risk’ population who did not develop
ADHD or receive a licensed ADHD treatment during the study period. Comparators
had to belong to linkage-eligible general practices; each linkage-eligible ADHD
patient was matched with up to 10 comparators on the basis of general practice,
63
gender and year of birth. This matching was designed to eliminate any influence
these factors could have on patients' likelihood of being diagnosed with a
comorbidity/being prescribed a psychotropic/sustaining a fracture. Comparators
were required to have a GP encounter in the same year their matched case was
diagnosed with ADHD to establish that they were active GP users during that
particular year. This consultation date was termed their ‘index date’. The final
comparison cohort identified comprised 49,489 individuals (9.68 comparators per
ADHD patient).
3.4 Identifying and comparing outcomes of interest
3.4.1 Identifying mental, behavioural and neurological comorbidities
Linkage-eligible ADHD patients and linkage-eligible comparators were
screened for mental, behavioural and neurological comorbidities. A review of the
literature identified numerous comorbidities that have been associated, to varying
extents, with ADHD. The range of comorbidities examined by this study
encompassed all comorbid conditions specifically mentioned in NICE's guidance on
the diagnosis and management of ADHD (conduct disorder, epilepsy, anxiety
disorders, tic disorder and Tourette’s syndrome; National Institute for Health and
Care Excellence 2008). Also examined were autistic spectrum disorders, depression,
bipolar disorder and schizophrenia. There is some evidence that these conditions
share a common genetic basis with ADHD (Cross-Disorder Group of the Psychiatric
Genomics Consortium 2013), suggesting that they may be more likely to occur in
patients with ADHD. Read codes for these conditions were identified and reviewed
according to the method described in section 3.2.3.
HES records data was also screened for the presence of comorbidity. This
data was coded differently to CPRD data. ICD-10 codes denoted the presence of
relevant diagnoses, with each code equating to a diagnostic/clinical term listed in
the ICD-10. Due to the difference in coding systems and diagnostic terms, the
comorbidities examined by the study were screened to ensure that they could be
clearly defined using both Read codes and ICD-10 codes. ICD-10 codes for
comorbidities of interest were identified using an online dictionary provided by the
64
World Health Organisation (available at
http://apps.who.int/classifications/icd10/browse/2016/en). The final list of Read
codes and ICD-10 codes used in the detection of each mental, behavioural and
neurological comorbidity are listed in Appendix 4.
3.4.2 Identifying exposure to psychotropic drugs
Psychotropics are defined as drugs that affect individuals’ mental processes,
such as cognition or affect (World Health Organisation 2016). As they are generally
employed in the treatment of mental and behavioural disorders, treatment with
these drugs was used as more general indicator of mental and behavioural disorder.
Psychotropic drugs and their associated product codes were identified using CPRD’s
product dictionary (as described in section 3.2.3.1). The code list prepared
contained drugs belonging to several drug classes primarily utilised in the treatment
of mental and behavioural disorder (a full list of product codes is listed in Appendix
5). These were antipsychotic drugs, antidepressants, and anxiolytics/hypnotics. It
was recognised that some of the specific drugs examined had uses outside of
mental and behavioural disorders; these drugs were highlighted and discussed in
Chapter 6.
3.4.3 Identifying accidental fractures
Due to differences in how accidents are coded in CPRD and HES, identifying
specific types of accident, or a more general list of accidental injuries, would have
been problematic. Instead, the decision was taken to use fractures as a surrogate
measure of accidental injury. Fractures were chosen as they are most commonly
the result of accidents in children (Kemp et al. 2008; Rennie et al. 2007; Mathison &
Agrawal 2010), and fractures alone may account for up to a quarter of significant
accidental injuries in children (Cooper et al. 2004). Focusing on fractures permitted
robust and unambiguous code lists to be prepared; the clinical terms associated
with fractures are comparable under the Read and ICD-10 coding systems.
A list of fracture Read codes was prepared. It was adapted from a list used in
previous fracture research using CPRD (Curtis et al. 2016; Moon et al. 2016). This
65
list was kindly shared by one of the study authors currently based at the University
of Manchester (Prof. Tjeerd van Staa). The existing list included codes for fractures
stemming from underlying pathology (such as osteoporosis or neoplastic disease),
or a specified, non-accidental cause (such as surgical fractures, cough fractures and
birth injuries). Such Read codes were excluded from analysis, along with codes
denoting spontaneous fractures and stress fractures (which would generally not be
the result of acute, accidental trauma). Additional Read codes denoting fracture,
and follow-up care relating to fracture, were identified using CPRD’s Read code
dictionary. ICD-10 codes for fractures were identified using the online dictionary
provided by the World Health Organisation. The final list of Read codes and ICD-10
codes used in the detection of fracture are listed in Appendix 6.
3.4.4 Determining the prevalence and relative risk of comorbidity, and psychotropic
treatment
All linkage-eligible ADHD patients received their incident diagnosis of ADHD
between 1/1/2004 and 31/12/2013. Conversely, all matched comparators remained
free of ADHD, and were not exposed to any licensed medication for ADHD between
1/1/2004 and 31/12/2013. ADHD patients’ date of diagnosis was referred to as
their index date. Comparators were required to have at least one documented
consultation with their GP in the year that their matched case was diagnosed with
ADHD; this was referred to as their index date.
The study aimed to describe, quantify and compare the presence of
comorbid conditions amongst ADHD patients and matched comparators without
ADHD. It was important that the detection of these outcomes was robust. If
instances of comorbidity went undetected, this had the potential to affect the
study's internal validity, and any conclusions drawn. Such mental, behavioural and
neurological comorbidities could in practice be diagnosed either before or after a
patient’s formal diagnosis with ADHD (or index date in matched comparators). For
example, an ADHD patient with comorbid tic disorder might have had their tic
disorder recognised and diagnosed either before or after their diagnosis with
ADHD. By focusing on diagnoses made after a patient was diagnosed with ADHD (or
66
index date in matched comparators), comorbid diagnoses made before this point
might have been missed.
Similarly, the study aimed to describe, quantify and compare psychotropic
drug exposure amongst ADHD patients and matched comparators without ADHD.
Concerns have been raised regarding the use of psychotropic drugs in children; the
long-term effects of such drugs on the developing body and brain are not yet fully
understood (Birnbaum et al. 2013; Bottelier et al. 2014). As such it was felt
important to capture children exposed to such drugs both before and after their
diagnosis of ADHD (or index date in matched comparators).
To avoid missing comorbidities diagnosed/psychotropic exposure occurring
before patients’ index dates, comorbidity/psychotropic exposure amongst ADHD
patients and comparators was determined in the following way.
Individuals were screened for the presence of comorbidity/psychotropic prescribing
from the latest point of the following:
1. Their registration date with their CPRD general practice.
2. The date at which their general practice attained CPRD’s data quality
standards (the practice ‘up to standard’ date).
3. The study start date (1/1/2004).
Individuals were then observed until the earliest point of the following:
1. The date at which they left their CPRD general practice (if applicable).
2. The date of their death (if applicable).
3. January 1st of the year they turned 19 years of age.
4. The last date on which data was transferred from their practice to CPRD.
5. The study end date (31/12/2013).
Effectively the study determined if individuals diagnosed with ADHD
between 1/1/2004 and 31/12/2013 were more likely to be diagnosed with
comorbidities during observation than matched comparators who remained free of
ADHD. Any individual with a comorbidity of interest recorded in their CPRD/HES
record during their period of observation was counted as having a comorbidity,
67
whether the diagnosis occurred before or after their index date. The number of
ADHD patients and comparator patients with each comorbidity was calculated. The
prevalence of comorbidity was also presented as the number of cases per 10,000
person-year [pyar] of observation time in the ADHD and comparator cohort. The
relative risk of comorbidity amongst ADHD patients and non-ADHD comparators
was determined using risk ratios (RR) with 95% confidence intervals.
The study also determined if individuals diagnosed with ADHD between
1/1/2004 and 31/12/2013 were more likely to be exposed to psychotropic
medications during observation than matched comparators who remained free of
ADHD. Any individual who received a prescription for a psychotropic during their
period of observation was counted as having been exposed to that psychotropic,
whether that prescription was issued before or after their index date. The number
of ADHD patients and comparator patients who were exposed to each class of
psychotropic was calculated. The prevalence of psychotropic treatment was also
presented as the number of cases per 10,000 person-years [pyar] of observation
time in the ADHD and comparator cohort. The relative risk of psychotropic
exposure amongst ADHD patients and non-ADHD comparators was determined
using risk ratios (RR) with 95% confidence intervals.
3.4.5 Determining psychotropic exposure in the year before, and the year after index
date
ADHD and its associated symptoms may be treated with psychotropic
medications other than those specifically licensed for the condition (National
Institute for Health and Care Excellence 2013b; Birnbaum et al. 2013). By comparing
psychotropic prescribing rates in the year before, and the year after, individuals’
initial diagnosis with ADHD, it could be determined if individuals’ risk of receiving
psychotropic medication was significantly higher following their diagnosis with
ADHD. Prescribing in the year before, and the year after index date was also
determined in the comparison cohort to serve as a reference.
The number of ADHD patients and comparator patients who received a
particular psychotropic in the year before, and the year after their index date was
68
calculated. The prevalence of psychotropic treatment in the year before, and the
year after index date was also presented as the number of cases per 10,000 person-
years [pyar] of observation time in the ADHD and comparator cohort. Some
individuals did not have a full 365 days observation before, or after, their index date
(for example, if their index date occurred less than 365 days after they registered
with their general practice, or less than 365 days before they transferred out of
their GP). However, the number of days between these events and their index date
could still be determined, and counted towards the person-time at risk for
whichever cohort an individual belonged to. In both cohorts, rate ratios and 95% CI
were calculated to establish if psychotropic prescribing rates were significantly
higher in the year following individuals’ index dates than they were in the year
before this date.
3.4.6 Determining risk of fracture during the study period, and following index date
It has been observed that certain types of injury are more prevalent in
individuals with ADHD, or who go on to be diagnosed with ADHD (Maxson et al.
2009; Keenan et al. 2008; DiScala et al. 1998). The study aimed to determine if
individuals diagnosed with ADHD between 1/1/2004 and 31/12/2013 were more
likely to be sustain fractures during observation than matched comparators who
remained free of ADHD. The most prevalent fractures in each cohort were
determined and compared; this had the potential to reveal if certain types of
fracture were particularly likely to occur in the ADHD cohort compared to the
comparator cohort.
Any individual with a fracture recorded in their CPRD/HES record during
their period of observation (described in section 3.4.4) was counted as having
sustained a fracture, whether this occurred before or after their index date. The
number of ADHD patients and comparators who sustained fracture was calculated.
The prevalence of fracture was also presented as the number of cases per 10,000
person-years [pyar] of observation time in the ADHD and comparator cohort. The
relative risk of fracture (both in general, and for specific types of fracture) amongst
69
ADHD patients and non-ADHD comparators was determined using risk ratios (RR)
with 95% confidence intervals.
A further analysis focused on the likelihood of fracture following index date
in ADHD patients and comparators. The number of patients who sustained a
fracture after their index date, and before the end of observation, was calculated in
both cohorts. The prevalence of fracture was also presented as the number of cases
per 10,000 person-years [pyar] of observation time in the ADHD and comparator
cohort. A Cox proportional hazards model was used to determine the impact of pre-
existing ADHD on fracture risk; this is discussed further in section 3.5.2.
3.5 Statistical Methods
Advice was sought from statisticians on how to analyse the data generated
by the study, in light of the study’s objectives. All statistical analysis was conducted
using Stata version 13 (StataCorp, College Station, Texas, United States); statistical
significance was set at p 0.05.
3.5.1 Poisson regression
Poisson regression allowed the impact of several covariates on ADHD
incidence to be determined. For example, it could be estimated whether males had
a higher or lower risk of ADHD compared to females, whether any gender effect
was statistically significant, and whether any effect remained after adjustment for
other patient factors and individual variations in observation time. The
multivariable Poisson model generated was used to determine incidence rate ratios
(IRR) and accompanying 95% confidence intervals (CI) and p-values, adjusted for
gender, general practice nation, age group, and deprivation quintile. A regression
was similarly conducted using only patients registered with English general
practices; this was adjusted for gender, CPRD region, age group, and deprivation
quintile. All models used robust standard errors, and accounted for variations in
follow-up time between individuals; model diagnostics were performed to ensure
goodness-of-fit.
3.5.2 Cox proportional hazards model
70
Cox proportional hazards regression investigates the relationship between a
patient’s risk of sustaining an outcome at a given time and possible explanatory
variables. Cox proportional hazards models were used to estimate 1) the impact of
gender, general practice nation, age at diagnosis, and deprivation level on patients’ risk
of receiving a licensed treatment for ADHD in primary care following diagnosis, and 2)
the impact of ADHD diagnosis on patients’ risk of sustaining a fracture. Hazard ratios
(HRs) with accompanying 95% CI were presented. Robust standard errors were
used, and models accounted for variations in follow-up time between individuals.
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Chapter 4
ADHD in the United Kingdom:
Regional and socioeconomic
variations in incidence rates
amongst children and adolescents
(2004 – 2013)
72
4.1 Background
ADHD is a neurodevelopmental disorder characterised by three core
symptoms: hyperactivity, impulsivity, and inattention (Bolea-Alamañac et al. 2014).
In the United Kingdom, general practitioners play a key role in the diagnosis,
management, and treatment of the disorder. As gatekeepers to the UK healthcare
system (Herrett et al. 2015; Murray et al. 2014), GPs will generally be the first port-
of-call for individuals concerned that they or their child may have ADHD. After
referring suspected cases to secondary care (such as paediatric or psychiatry
services) for a confirmation of the diagnosis, GPs generally prescribe medications
and undertake monitoring measures as part of a shared care arrangement (National
Institute for Health and Care Excellence 2008b; Rowlingson et al. 2013; Holden et
al. 2013; Beau-Lejdstrom et al. 2016). Though several medications are licensed for
use in the treatment of ADHD in children, pharmacological intervention is not
required in all cases (McCarthy et al. 2012).
McCarthy et al. (2012) and Holden et al. (2013) both detected increases in
the incidence and prevalence of ADHD in the United Kingdom during the first
decade of the 21st century. However, there is some evidence to suggest that the
burden of the disorder is unevenly distributed. Rowlingson and colleagues (2013)
observed that primary care spending on methylphenidate varied significantly across
England; in some areas, spending on methylphenidate was over four times the
national average. In addition, a UK cohort study by Russell & Ford (2014) found that
ADHD was particularly prevalent among children living in circumstances of social
and economic disadvantage.
The findings of Rowlingson et al. (2013) were based on national prescribing
data from a single month in 2011. Similarly, the link between parentally-reported
ADHD and socioeconomic deprivation was based on a sample containing a relatively
small number (n = 187) of affected children (Russell & Ford 2014).
4.1.1 Aims
The aim of this study was to establish whether the regional prescribing
variations observed in the United Kingdom reflected regional variations in ADHD
73
incidence, and to determine whether ADHD incidence showed any association with
socioeconomic deprivation on a national scale. The study also sought to update the
findings of earlier epidemiological studies, describing ADHD incidence rates among
children and adolescents in the United Kingdom between the years 2004 and 2013.
4.2 Methods
4.2.1 Data Source and Study Population
A retrospective cohort study was performed using primary care consultation
data from the Clinical Practice Research Datalink. The study population comprised
patients diagnosed with ADHD before the age of 19, between January 1, 2004 and
December 31, 2013. Individuals with a diagnosis of ADHD were identified by the
presence of Read codes relating to the disorder in their CPRD record. To be eligible for
inclusion as an incident case of ADHD, the earliest occurrence of a relevant code had to
occur within the study window, and following at least 365 days continuous registration
with their general practice.
4.2.2 Assessment of Geographical Location, and Socioeconomic Status
Every general practice contributing data to CPRD has a unique identifying
number. Associated with this number is information about that practice’s geographical
location within the United Kingdom. By looking at the practice identifier associated
with a particular patient, their location within the United Kingdom was discerned.
Patients were referred to as English, Scottish, Welsh or Northern Irish. This designation
reflected where their general practice was based (and, by extension, their likely nation
of residence), and did not necessarily reflect their country of birth/nationality.
England and Wales are divided up into approximately 35,000 defined
geographical areas known as Lower Layer Super Output Areas (LSOA; Office of
National Statistics, 2011). Similar geographic divisions are applied to Northern
Ireland and Scotland, which are divided into smaller areas termed datazones (DZ;
UK Data Service, 2014). Measurements relating to seven key indicators of
socioeconomic deprivation are routinely compiled for each LSOA/DZ. This
information is used to calculate an Index of Multiple Deprivation (IMD) score for
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each LSOA/DZ, allowing each to be ranked in order of relative deprivation. Every
general practice contributing data to CPRD has an IMD score based on the LSOA/DZ
in which it is situated. These scores are available to CPRD researchers, rounded to
the nearest quintile. For the purposes of this study, these ‘practice-level’ IMD
scores were used as a surrogate measure of patients’ deprivation status.
4.2.3 Incidence Calculation
The earliest occurrence of an ADHD-related Read code in each patient’s records
was identified, and the calendar year in which this occurred was noted. The patient
was then counted as a newly-diagnosed incident case in that calendar year. The
incidence denominator for each year comprised of person-time contributed by
individuals who were considered ‘at risk’ of developing ADHD in that year. Incidence
rates were expressed as cases per 10,000 person-years at risk (pyar) and presented
with 95% confidence intervals (CI). Annual incidence rates were calculated and
stratified by patient gender, nation (England/Scotland/Wales/Northern Ireland),
and practice-level deprivation (IMD) quintile. An incidence rate was calculated for
the study period overall; this was stratified by gender, nation, CPRD region (in the
case of patients registered with English general practices), age band, and
deprivation quintile. Multivariable Poisson modelling was used to determine
incidence rate ratios (IRR) and accompanying 95% CIs and p-values, adjusted for
gender, nation, age group, and deprivation quintile. A regression was similarly
conducted using patients registered with English general practices; this was
adjusted for gender, CPRD region, age band, and deprivation quintile. Statistical
significance was set at p 0.05, and all statistical analyses were performed using
Stata version 13 (StataCorp, College Station, Texas, United States).
4.3 Results
4.3.1 Overall and Annual Incidence Rates (United Kingdom)
Over the 10-year study period, 10,284 new diagnoses of ADHD were
recorded in under 19s in CPRD. The overall ADHD incidence rate for the study
period was 11.67 cases per 10,000 pyar (95% CI 11.45 - 11.90). Incidence rates were
at their lowest in 2008 [11.04 cases per 10,000 pyar (95% CI 10.38, 11.75)] and
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highest in 2012 [12.56 cases per 10,000 pyar (95% CI 11.84 - 13.33)], as shown in
Figure 2.
4.3.2 Incidence by Gender and Age Group
After adjustment for nation, deprivation quintile, and age group, a large and
statistically significant difference (p < 0.01) in incidence rates was observed
between males and females. Between 2004 and 2013, the overall incidence of
ADHD among the male population at risk was 18.63 cases per 10,000 pyar (95% CI
18.24 - 19.03). The overall incidence rate in females was much lower [4.37 cases per
Figure 2: UK ADHD incidence rate in under 19s (2004-2013)
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10,000 pyar (95% CI 4.18 - 4.57)]. As shown in Figure 2, female incidence rates were
relatively static from 2004 to 2010 but were notably higher in the last 3 years of the
study period [peaking at 5.45 cases per 10,000 pyar (95% CI 4.80 – 6.21) in 2012].
Figure 3 shows the incidence of ADHD in males and females according to age at
diagnosis. In both males and females, ADHD was most commonly diagnosed at age 7
(1057 new diagnoses in males, 238 new diagnoses in females). Thirty-five percent of all
ADHD patients identified (n = 3606) were diagnosed between the ages of 7 and 9.
Figure 3: ADHD incidence by age of diagnosis
4.3.3 Incidence by Nation (England, Scotland, Wales, and Northern Ireland)
As shown in Table 4, Northern Ireland’s overall incidence rate was the
highest of the four UK nations [with 13.32 cases per 10,000 pyar (95% CI 12.11 –
14.66)]. This was significantly higher than that of Scotland (p < 0.01), England (p
< 0.01), and Wales (p = 0.02). Wales had the second highest incidence rate
across the study period, significantly higher than that of England (p = 0.01) and
Scotland (p = 0.01). Scotland’s overall incidence rate was the lowest of the four
nations, although the difference between Scottish and English rates was not
statistically significant (p = 0.36).
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In England, annual fluctuations in incidence rates broadly corresponded to
those of the United Kingdom overall. Incidence rates were at their lowest in 2008
and highest in 2012 [peaking at 12.73 cases per 10,000 pyar (95% CI 11.90 – 13.62)].
However, a decrease in incidence rates between 2007 [11.87 cases per 10,000 pyar
(95% CI 11.10 – 12.70)] and 2008 [10.27 cases per 10,000 pyar (95% CI 9.55 –
11.05)] was observed in England but not the UK data as a whole.
In Scotland, ADHD incidence was lowest in 2005 [7.60 cases per 10,000 pyar
(95% CI 6.00 – 9.62)] and highest in 2013 [14.80 cases per 10,000 pyar (95% CI
12.52 – 17.48)]. In contrast to England, 2008 saw a relatively high incidence of
newly diagnosed ADHD in Scotland and peak annual incidence in Northern Ireland
[15.46 cases per 10,000 pyar (95% CI 11.62 – 20.58)]. In Wales, peak ADHD
incidence was observed in 2007 [15.63 cases per 10,000 pyar (95% CI 12.98 –
18.83)].
Table 4: UK ADHD incidence (2004 – 2013)
ADHD cases
Person-years at risk
(nearest whole year)
Incidence rate 2004-2013 per 10,000 person-years
(95% CI)
Adjusted incidence rate
ratio* (95% CI)
UK (total) 10284 8,808,590 11.67 (11.45 – 11.90) N/A
Gender
Male 8407 4,512,611 18.63 (18.24 – 19.03) 1.00 (ref)
Female 1877 4,295,979 4.37 (4.18 – 4.57) 0.23 (0.22 – 0.25)
Nation
England 7984 6,851,691 11.65 (11.40 – 11.91) 1.00 (ref)
Scotland 976 917,860 10.63 (9.99 – 11.32) 0.97 (0.91 – 1.04)
Wales 903 723,038 12.49 (11.70 – 13.33) 1.09 (1.02 – 1.17)
Northern Ireland 421 316,002 13.32 (12.11 – 14.66) 1.26 (1.14 – 1.39)
Deprivation quintile
(practice-level)
(least deprived) 1 1539
1,646,181
9.35 (8.89 – 9.82)
1.00 (ref)
2 1864 1,706,407 10.92 (10.45 – 11.43) 1.16 (1.08 – 1.24)
3 2029 1,786,384 11.36 (10.87 – 11.86) 1.19 (1.12 – 1.27)
4 2359 1,904,857 12.38 (11.89 – 12.89) 1.30 (1.22 – 1.39)
5 (most deprived)
2493 1,764,762 14.13 (13.58 – 14.69) 1.49 (1.39 – 1.58)
Age group
1-3 years old 420 305,937 13.73 (12.48 – 15.11) 1.00 (ref)
4-6 years old 1984 847,226 23.42 (22.41 – 24.47) 1.71 (1.54 – 1.89)
7-9 years old 3606 1,191,796 30.26 (29.29 – 31.26) 2.20 (1.99 – 2.44)
10-12 years old 2222 1,390,343 15.98 (15.33 – 16.66) 1.17 (1.06 – 1.30)
13-15 years old 1592 1,494,459 10.65 (10.14 – 11.19) 0.78 (0.70 – 0.87)
16-18 years old 460 3,578,831 1.29 (1.17 – 1.41) 0.09 (0.08 – 0.11) *Adjusted for gender, nation, practice-level deprivation quintile, age group
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4.3.4 Incidence by CPRD Region (England)
Within each English region, annual incidence rates fluctuated between the
years 2004 and 2013 without any consistent pattern. However, the South East
Coast region had both the highest number of ADHD diagnoses during the study
period (n = 1461, 18.3% of England’s total cases) and the highest overall incidence
rate of ADHD in under 19s (see Table 5). This was significantly higher (p < 0.01) than
that of the Yorkshire and the Humber region, which had the lowest incidence rate
of England’s 10 CPRD regions.
Table 5: ADHD incidence by English region
ADHD cases
Person-years at risk
(nearest whole year)
Incidence rate 2004-2013 per 10,000 person-
years (95% CI)
Adjusted incidence rate
ratio* (95% CI)
England (total) 7984 6,851,691 11.65 (11.40 – 11.91) N/A
English region
North West 1078 1,043,531 10.33 (9.73 – 10.97) 1.00 (ref)
North East 168 155,931 10.77 (9.26 – 12.53) 0.98 (0.83 – 1.15)
Yorkshire and the Humber
209 258,378 8.09 (7.06 – 9.26) 0.73 (0.63 – 0.85)
East Midlands 335 281,963 11.88 (10.67 – 13.22) 1.14 (1.00 – 1.28)
West Midlands 791 769,010 10.29 (9.59 – 11.02) 0.96 (0.87 – 1.05)
East of England 1174 795,373 14.76 (13.94 – 15.63) 1.53 (1.40 – 1.66)
South West 673 683,147 9.85 (9.13 – 10.62) 0.99 (0.90 – 1.09)
South Central 1175 1,001,399 11.73 (11.08 – 12.42) 1.30 (1.19 – 1.42)
London 920 942,061 9.77 (9.15 – 10.42) 0.92 (0.84 – 1.01)
South East Coast 1461 920,899 15.86 (15.07 – 16.70) 1.67 (1.54 – 1.81) *Adjusted for gender, practice-level deprivation quintile, age group
4.3.5 Incidence by Deprivation (IMD) Quintile
When stratified by deprivation quintile, the UK’s diagnostic data suggested a
significant link between deprivation and ADHD incidence. In almost every year
studied, incidence rates were highest in the most deprived patients and lowest in
the least deprived patients (see Figure 4). Underlying this UK trend were England’s
diagnostic data. Patients belonging to practices in the most deprived areas of
England (IMD quintile 5) had the highest incidence of ADHD overall [13.84 cases per
10,000 pyar (95% CI 13.23 – 14.47)]. This was significantly higher (p < 0.01) than the
incidence rates for quintiles 1, 2, 3, and 4. At the opposite end of the deprivation
scale, patients belonging to the least deprived quintile (1) had a significantly lower
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incidence (p < 0.01) of diagnosed ADHD than patients in any other quintile [9.24
cases per 10,000 pyar (95% CI 8.72 – 9.80)].
Figure 4: Annual ADHD incidence (2004-2013) by deprivation quintile
In the other three nations of the United Kingdom, evidence for an
association between deprivation and ADHD was somewhat weaker (see Figure 5).
In Scotland (as in England), patients belonging to practices in the most deprived
areas (IMD quintile 5) had the highest incidence of diagnosed ADHD; rates were
significantly higher (p < 0.01) than those in the less deprived quintiles (quintiles 1, 2,
3, and 4). In Wales, patients in the most deprived quintile had the highest incidence
of ADHD, significantly higher (p < 0.01) than that observed in the least deprived
quintile. In Northern Ireland, there was no clear association between ADHD and
deprivation.
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Figure 5: ADHD incidence by deprivation quintile (England, Scotland, Wales, Northern Ireland)
4.4 Discussion
This study found that there were statistically significant differences in ADHD
incidence rates between the United Kingdom’s constituent nations, and between
individual regions within England. The finding of significant geographical differences
within the United Kingdom is probably unsurprising. In the United States, significant
differences in diagnostic and treatment rates for ADHD have been observed between
states, and between different communities within the same state (Fulton et al. 2009;
McDonald & Jalbert 2013). Furthermore, Rowlingson et al. (2013) had observed
regional variations in methylphenidate spending in England that had suggested such
variations might be present. That study identified a notable area in the South East of
England where medical practices’ methylphenidate spending was 4 times the national
average; this study found that the CPRD’s South East Coast region had the highest
ADHD incidence rate of all CPRD regions.
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It may be the case that these differences in diagnostic rates are explicable by
regional and national differences in diagnostic and management procedures. All areas
of the United Kingdom would be expected to take the 2008 NICE guidance on the
diagnosis and management of ADHD as a primary resource (National Institute for
Health and Care Excellence 2008b). However, it is possible that a child diagnosed with
ADHD in one part of the United Kingdom may not have had the disorder recognised
and diagnosed had they lived in another part of the country. All four constituent
nations of the United Kingdom have distinct budgets for healthcare and must prioritise
spending according to national needs and priorities (National Audit Office 2012).
Similarly, different regions within each nation have their own allocated budgets which
must be used to provide a well-rounded health service to the local populace. It has
been acknowledged that different areas of the United Kingdom provide inconsistent
levels of service provision for ADHD (National Institute for Health and Care Excellence
2013), potentially resulting in different levels of case recognition.
Alternatively, the regional and national differences in diagnostic rates may
reflect genuine differences in ADHD incidence across the United Kingdom. That is to
say, populations in some parts of the United Kingdom may have a higher proportion
of individuals with some genetic susceptibility to ADHD and/or higher exposure to
environmental risk factors that promote its onset. One environmental factor
suggested to play a role in the aetiology of ADHD is sunlight. In 2013, Arns et al.
reported an inverse association between regional solar intensity and ADHD
prevalence across 49 U.S. states, and across several countries. That finding has
been contested elsewhere (Hoffmann et al. 2014), and this study’s findings did not
appear to suggest an association between ADHD and solar intensity in the United
Kingdom. The South East Coast of England had the highest incidence of ADHD of all
English regions, despite its southerly latitude and its relatively high solar intensity
(Met Office 2014). In addition, Scotland had the lowest ADHD incidence of all four
UK nations despite being the most northerly and having the lowest solar intensity
overall (Met Office 2014). This does not rule out a relationship between ADHD and
sunlight, but does suggest that in a country the size of the United Kingdom, in the
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United Kingdom’s position geographically, regional differences in ADHD incidence
do not appear to be influenced by regional differences in solar irradiation.
Exposure to socioeconomic deprivation is another purported risk factor for
ADHD, and this study did observe a clear association between ADHD and
socioeconomic deprivation. In England, Scotland, and Wales, ADHD incidence rates
were highest among patients belonging to practices in the most deprived areas
(IMD quintile 5). In all three nations, and in half of England’s 10 CPRD regions,
incidence rates among individuals in quintile 5 (the most deprived quintile) were
significantly higher (p < 0.05) than those of individuals in quintile 1 (the least
deprived quintile). These findings lend support to the theory that an individual’s
likelihood of being diagnosed with ADHD may be increased by exposure to
socioeconomic deprivation. This observation is in line with the findings of several
studies from around the world (Döpfner et al. 2008; Froehlich et al. 2007; Hjern et
al. 2010; Nomura et al. 2012) and from the United Kingdom specifically (Green et al.
2005; Russell & Ford 2014).
It was beyond the capabilities of this study to identify an underlying reason
for the apparent link between deprivation and the development of ADHD. The
measure of deprivation used by this study (the Index of Multiple Deprivation 2010)
assesses several distinct aspects of socioeconomic deprivation, rather than one
specific characteristic or risk factor that could then be investigated further.
Furthermore, estimating patients’ deprivation status using the IMD details of their
general practice made use of readily available data, but posed the risk of ecological
fallacy in some instances (a point discussed further in Chapter 8). However, by
identifying that local deprivation and ADHD often coexist, this study highlights the
need for adequate service provision in deprived areas of the United Kingdom.
In line with current consensus, this study found that ADHD incidence rates
were significantly higher in males than in females in every year studied, and across
the study period as a whole. The overall incidence rate observed among males was
approximately 4.3 times that of females. This gender imbalance is not exceptional
when compared with other studies in the literature. Epidemiological studies have
typically found ADHD to be 2 to 4 times more common in males than in females
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(National Institute for Health and Care Excellence 2008a). Although the association
between ADHD and gender is long-standing, in recent years its underlying reasons
have come under increased scrutiny. Boys are more likely to have ADHD
characterised by impulsivity and hyperactivity, whereas inattentive symptoms tend
to predominate in girls (Kooij et al. 2010). It has therefore been hypothesised that
ADHD in males is simply more visible and attention-grabbing than it is in females,
leading to higher rates of recognition and diagnosis (Bedrossian 2015).
In both males and females, ADHD diagnosis was most commonly observed
during patients’ primary school years (especially between the ages 7 and 9). This is
broadly in line with the findings of earlier UK studies. One study observed peak
incidence rates in 6-17 year olds; the mean age of diagnosis among this group was
9.8 years (standard deviation/SD = 2.8; Holden et al., 2013). Another reported peak
incidence rates in 6-12 year olds (McCarthy et al. 2012). Given that the underlying
causes of ADHD are yet to be fully understood, it is possible that the disorder
commonly develops or first manifests itself around this time in patients’ lives.
However, it may be the case that existing ADHD is particularly likely to be
recognised as a problem during a child’s early years of formal schooling. Although a
child may have exhibited tendencies toward hyperactivity, impulsivity, and
inattention at an earlier stage, its disruptive impacts on early schooling could be the
catalyst for seeking a medical assessment and subsequent diagnosis.
Across the United Kingdom as a whole, ADHD incidence peaked in 2012 and
was higher in the last 2 years of the study than it had been in any of the preceding 8
years. This study’s results showed some agreement with those presented by Holden
et al. (2013), which examined the period 1998 to 2010. Both studies found that
incidence fell between 2004 and 2005, before rising in 2006 and 2007 and then
falling in 2008. However, the continued decline in incidence rates observed by the
earlier study in 2009 and 2010 was not observed by this study. Concordance with
the findings of McCarthy et al. (2012) was somewhat mixed. That study (covering
the years 2003-2008) observed peak incidence rates in 2006 and a slight decline in
the following year; this study observed an increase in incidence rates between 2006
and 2007. Although comparing incidence rates across the three UK studies is an
84
interesting exercise, drawing firm conclusions from these comparisons is not
possible. Each study used slightly different case definitions, focused on different
study populations (treated and untreated vs. treated only, all ages vs. under 19s)
and used somewhat different sampling populations. What is clear is that ADHD
diagnostic rates among children and adolescents in the United Kingdom have not
been on a continual upward trend over the last decade, or even during the last 5
years. It is unclear whether the increases observed in the last 2 years of this study
are outliers, or will be sustained in the coming years.
4.5 Conclusion
Statistically significant differences in ADHD incidence were observed
between the United Kingdom’s four constituent nations, and between England’s 10
CPRD regions. In addition, ADHD incidence showed a positive association with
socioeconomic deprivation. Annual ADHD incidence rates in the United Kingdom
remained relatively stable between 2004 and 2013, but were highest in the last 2
years studied.
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Chapter 5
ADHD in children and adolescents:
Prevalence and predictors of
medication use in UK primary care
86
5.1 Background
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental
disorder characterised by three core symptoms: hyperactivity, impulsivity and
inattention (Bolea-Alamañac et al. 2014). Untreated ADHD can have diverse and
often profound impacts on its sufferers, ranging from impaired academic
achievement to an increased susceptibility to psychiatric disorders (Birchwood &
Daley 2012; Wong et al. 2009; Pliszka 2003). However, numerous studies have
shown that ADHD’s core symptoms can be effectively treated in both children and
adolescents (Bolea-Alamañac et al. 2014); treating these symptoms can significantly
improve patient outcomes (Kooij et al. 2010; Shaw et al. 2012).
NICE’s guidance on the management of ADHD in children and adolescents
sets out the different treatment options available to medical practitioners in the UK
(National Institute for Health and Care Excellence 2008b). These can be broadly
divided into pharmaceutical and non-pharmaceutical interventions. In patients with
severe impairments stemming from ADHD, pharmaceutical treatment is
recommended first-line. Between 2004 and 2013, four drugs were licensed for the
treatment of children and adolescents with ADHD in the UK. Methylphenidate is
licensed for use between 6 and 17 years of age; atomoxetine may be used from the
age of six upwards. Where these drugs are ineffective or not tolerated,
dexamfetamine or lisdexamfetamine may be used (both are licensed for use
between 6 and 17 years; Joint Formulary Committee 2015). In pre-school age
children, and in children and adolescents with only moderate impairments
stemming from the disorder, NICE recommends that drug treatment is not used as
a first-line option (National Institute for Health and Care Excellence 2008b).
Parental training and education, combined with psychological treatments for
affected children (such as cognitive behavioural therapy [CBT] and/or social skills
training) are preferred in these patients. Prior to initiating any intervention(s) for
ADHD, general practitioners are advised to refer suspected cases of ADHD to
secondary care for assessment (that is, a child psychiatrist, paediatrician, or
specialist ADHD child and adolescent mental health services [CAMHS]; National
Institute for Health and Care Excellence 2008b). After this, GPs typically undertake
87
routine prescribing and monitoring measures as part of a shared care arrangement
(Beau-Lejdstrom et al. 2016; Rowlingson et al. 2013; National Institute for Health
and Care Excellence 2008b).
It has been acknowledged that access to non-pharmaceutical services for
the management of ADHD is highly variable across the UK (National Institute for
Health and Care Excellence 2013b). Coupled with this, methylphenidate prescribing
has increased markedly in primary care in recent years (National Institute for Health
and Care Excellence 2013a; McClure 2013). This has led to concerns that ADHD is
being treated pharmaceutically as a matter of course in UK primary care, even
amongst pre-schoolers (Hill & Turner 2015). Recent Cochrane reviews have
reiterated the need for caution in the prescribing of stimulant medications on
account of their potential side effects (Storebø et al. 2015; Punja et al. 2016),
though the extent to which prescribing in ADHD has become routine is somewhat
unclear.
5.1.1 Aims
This study examined patients diagnosed with ADHD before the age of 19,
between 1/1/2004 and 31/12/2013. It established what proportion of these
patients received a prescription for an ADHD medication during that time. This gave
an indication of how often a diagnosis of ADHD was accompanied by
pharmaceutical treatment in primary care. The study also determined which of the
four medications licensed to treat ADHD were most commonly initiated first-line,
and at what age patients started medication in the community. This established if
medications for ADHD were being utilised outside their licensed indications (ie in
children below the age of six), and identified which drugs were most commonly
used in the first-line treatment of ADHD. In treated patients, the median time
between diagnosis (denoted by a Read code for ADHD) and first treatment
(denoted by a product code for a licensed ADHD medication) was calculated. This
established how quickly a diagnosis of ADHD was followed by pharmaceutical
treatment in primary care, and if the two events (diagnosis and prescribing) often
occurred concurrently. Finally, it was established if specific patient characteristics
88
were associated with an increased likelihood of pharmaceutical treatment in
primary care.
5.2 Methods
5.2.1 Study Population and case definition
All patients with ADHD had a Read code denoting an incident diagnosis of
ADHD documented in their CPRD record between 1/1/2004 and 31/12/2013. In
addition, pharmaceutically-treated patients had at least one product code denoting a
prescription for a licensed ADHD medication (methylphenidate, atomoxetine,
dexamfetamine and lisdexamfetamine) documented during the study period, and
before the age of 19. Patients’ date of diagnosis was taken as the first date on which an
ADHD-related code was documented in their CPRD record. In treated patients, it was
anticipated that a Read code denoting a formal diagnosis of ADHD would precede a
product code for a licensed ADHD medication. However, in instances where a product
code was observed before a diagnostic Read code, the date of the earliest prescription
was taken as the patient’s diagnostic event. The age at which pharmaceutical
treatment was commenced was ascertained by subtracting patients’ year of birth from
the year in which their first product code for an ADHD drug was documented. The
interval between patients’ first diagnosis and first prescription was calculated by
counting the number of days between patients’ first Read code for ADHD and their first
prescription for a licensed ADHD medication. By examining the product code of the first
ADHD medication prescribed, it could be determined which licensed ADHD medication
was utilised first-line in each treated patient.
5.2.2 Statistical analysis
The study examined the time between ADHD diagnosis (denoted by a Read
code) and the earliest prescription for a licensed ADHD medication in primary care (the
outcome of interest). A Cox proportional hazards model was used to assess if ADHD
patients’ probability of receiving medication following diagnosis was significantly
influenced by their gender, the nation in which their general practice was based, their
level of deprivation (derived from their general practice’s Index of Multiple Deprivation
89
quintile), and their age at first diagnosis. Individuals who received a prescription for an
ADHD medication (the outcome of interest) before a diagnostic Read code for ADHD
were excluded from this time-to-event analysis. Hazard ratios (HRs) with
accompanying 95% CI and p-values were presented. Statistical significance was set
at p 0.05, and all statistical analyses were performed using Stata version 13
(StataCorp, College Station, Texas, United States).
5.3 Results
Table 6: Prevalence of pharmaceutical treatment in primary care
5.3.1 Proportion of ADHD patients treated pharmaceutically in primary care
In all, 10,284 patients were defined as incident cases of ADHD between 2004
and 2013. All these patients had at least one ADHD-related Read code documented in
Incident cases of
ADHD 2004-2013
(n)
Total number pharmaceutically
treated during study period
(% of incident cases)
^Number pharmaceutically treated following
diagnosis (% of
pharmaceutically treated patients)
Total 10,284 5813 (56.52%) 5116 (88.01%)
Gender
Male 8407 4803 (57.13%) 4223 (87.92%)
Female 1877 1010 (53.81%) 893 (88.41%)
Nation
England 7984 4424 (55.41%) 3883 (87.78%)
Scotland 976 633 (64.86%) 565 (89.26%)
Wales 903 519 (57.48%) 466 (89.79%)
Northern Ireland 421 237 (56.29%) 202 (85.23%)
Deprivation quintile
(practice-level)
(least deprived) 1 1539
914 (59.39%)
812 (88.84%)
2 1864 984 (52.79%) 867 (88.11%)
3 2029 1211 (59.68%) 1043 (86.13%)
4 2359 1329 (56.34%) 1166 (87.74%)
5 (most deprived)
2493 1375 (55.15%) 1228 (89.31%)
Age at diagnosis*
1-3 years old 420 36 (8.57%) 36 (100%)
4-6 years old 1984 843 (42.49%) 763 (90.51%)
7-9 years old 3606 2230 (61.84%) 1970 (88.34%)
10-12 years old 2222 1448 (65.17%) 1235 (85.29%)
13-15 years old 1592 1026 (64.45%) 902 (87.91%)
16-18 years old 460 230 (50.00%) 210 (91.30%) ^Number of treated patients with a Read code for ADHD documented before (or on the same date as) their first prescription for a licenced ADHD medication *Age at the point of earliest documented ADHD event (ie diagnostic Read code or prescription for a licensed ADHD medication)
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their CPRD record. Of these, 5813 (56.5%) received at least one documented
prescription for a licensed ADHD medication during the study period, before the age of
19 (see Table 6). In 88% of treated patients, a Read code denoting a diagnosis of ADHD
preceded (or occurred on the same date as) their first primary care prescription for a
licensed ADHD medication. This is discussed further in section 5.3.4.
5.3.2 Drug most commonly initiated first-line in primary care
Methylphenidate was the first ADHD medication prescribed to 92% of all
pharmaceutically-treated ADHD patients (n = 5346). In every year between 2004 and
2013, methylphenidate accounted for at least 87% of first-line prescribing in primary
care (see Figure 6). Atomoxetine was initiated first-line in 413 patients (7.1% of all
treated patients), and dexamfetamine was the first drug used in the treatment of 49
patients with ADHD (0.8% of all treated patients). Lisdexamfetamine was the first
documented treatment in five patients with ADHD (less than 0.1% of treated patients).
Figure 6: First-line drug choice by year (2004 – 2013)
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5.3.3 Age at which pharmaceutical treatment was commenced in primary care
Pharmaceutical treatment between the ages of one and three years was rare in
primary care; 0.05% of treated patients commenced medication before the age of four.
The most common age at which pharmaceutical treatment was started was eight years
of age (809 patients; 13.9% of treated patients commenced treatment at this age). As
shown by figures 7 and 8, methylphenidate accounted for the highest proportion of
first-line prescribing in all age categories examined.
5.3.4 Interval between initial diagnosis and first primary care prescription
In the 5813 treated patients, the median interval between patients’ first Read
code for ADHD and their first primary care prescription for an ADHD medication was 92
days (interquartile range [IQR] = 23-290 days). However, in 12% of pharmaceutically-
treated ADHD patients (n = 697), their earliest ADHD-related event was a prescription
for an ADHD drug rather than a Read code indicating a diagnosis of ADHD. When these
patients were excluded, the median interval between diagnosis and the start of
pharmaceutical treatment decreased to 84 days (IQR = 21-258 days), with 81% of
treated patients receiving their first prescription within 365 days of diagnosis. In 659
treated patients (11.3% of all treated patients), their first Read code for ADHD and their
first prescription for an ADHD medication were recorded on the same day. In 310
treated patients (5.3% of those treated) the interval between their first Read code for
ADHD and their first prescription for an ADHD medication was greater than three
years; the largest gap observed between an ADHD Read code and an initial prescription
for an ADHD medication was 2978 days.
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Figure 7: First-line methylphenidate use, and age of commencement in primary care
Figure 8: First-line drug use, and age of commencement in primary care
93
5.3.5 Predictors of pharmaceutical treatment in primary care
5.3.5.1 Gender
Compared to females, a higher proportion of males received pharmaceutical
treatment following their diagnosis with ADHD (50% v 47%). However, after adjusting
for other variables, gender did not have a statistically significant impact on an
individual’s likelihood of receiving medication in primary care (see Table 7).
Table 7: Predictors of pharmaceutical treatment following diagnosis in primary care (Cox proportional hazards model)
Incident cases of
ADHD 2004-2013
Number pharmaceutically treated following
diagnosis^ (% of incident
cases)
Crude hazard ratio
[95% CI]
Adjusted hazard ratio*
[95% CI]
Total 10284 5116 (49.75%) N/A N/A
Gender
Male 8407 4223 (50.23%) 1.00 1.00 (Ref)
Female 1877 893 (47.58%) 0.94 [0.87 – 1.02] 0.99 [0.91 – 1.07]
Nation
England 7984 3883 (48.63%) 1.00 1.00 (Ref)
Scotland 976 565 (57.89%) 1.33 [1.21 – 1.46] 1.35 [1.23 –1.48]
Wales 903 466 (51.61%) 1.12 [1.01 – 1.25] 1.13 [1.01 – 1.25]
Northern Ireland 421 202 (47.98%) 0.72 [0.59 – 0.88] 0.79 [0.64 – 0.97]
Deprivation quintile (practice-level)
(least deprived) 1 1539
812 (52.76%)
1.00
1.00 (Ref)
2 1864 867 (46.51%) 0.82 [0.74 – 0.91] 0.84 [0.76 – 0.94]
3 2029 1043 (51.40%) 1.02 [0.93 – 1.13] 1.03 [0.93 – 1.14]
4 2359 1166 (49.43%) 0.96 [0.87 – 1.06] 0.98 [0.89 – 1.08]
5 (most deprived)
2493 1228 (49.26%) 0.93 [0.85 – 1.03] 0.96 [0.87 – 1.06]
Age at diagnosis
1-3 years old 420 36 (8.57%) 0.10 [0.07 – 0.13] 0.10 [0.07 – 0.13]
4-6 years old 1984 763 (38.46%) 0.54 [0.49 – 0.59] 0.54 [0.49 – 0.59]
7-9 years old 3606 1970 (54.63%) 0.95 [0.87 – 1.02] 0.94 [0.86 – 1.01]
10-12 years old 2222 1235 (55.58%) 1.00 (Ref) 1.00 (Ref)
13-15 years old 1592 902 (56.66%) 1.05 [0.94 – 1.14] 1.04 [0.95 – 1.15]
16-18 years old 460 210 (45.65%) 0.78 [0.66 – 0.93] 0.78 [0.66 – 0.93] ^Time-to-event analysis examined time between first Read code denoting a diagnosis of ADHD, and first prescription for a licensed ADHD medication in primary care. Individuals who received a medication before their formal diagnosis of ADHD were excluded from analysis * Adjusted for gender, nation, deprivation quintile, age at diagnosis
5.3.5.2 Nation
ADHD patients in Scotland were the most likely to be treated in primary care
following diagnosis. After adjustment for gender, deprivation quintile and age, patients
registered with Scottish general practices were significantly more likely to receive
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medication in primary care than patients in Wales (p = 0.01), England (p < 0.01) and
Northern Ireland (p < 0.01). Conversely, children and adolescents in Northern Ireland
were significantly less likely to receive pharmaceutical treatment following diagnosis
than children in England (p = 0.02), Wales (p < 0.01) and Scotland (p < 0.01), after
adjusting for other variables.
5.3.5.3 Index of Multiple Deprivation (IMD) quintile
In the least deprived quintile (quintile 1), 53% of patients received a
pharmaceutical treatment for ADHD following diagnosis. This compared to 49% of
patients in the most deprived quintile (quintile 5). However, after adjusting for the
other variables of interest, the likelihood of receiving pharmaceutical treatment in
quintile one and quintile five was not significantly different (see Table 7).
5.3.5.4 Age at diagnosis
Patients diagnosed with ADHD between the ages of ten and twelve went on
to receive medication in primary care in 55.6% of cases. Relative to this group,
patients diagnosed between the ages of seven and nine years of age [adjusted HR
0.94 (95% CI 0.86 – 1.01)] and thirteen and fifteen years of age [adjusted HR 1.04
(95% CI 0.95 – 1.15)] were equally likely to receive pharmaceutical treatment
following diagnosis. Children diagnosed with ADHD between one and three years of
age (n=420) went on to receive pharmaceutical treatment in primary care in 8.6% of
cases; patients diagnosed within any other age category were significantly more likely
to receive medication following diagnosis (p < 0.01).
5.4 Discussion
5.4.1 Proportion of ADHD patients treated pharmaceutically in primary care
The study found that a documented diagnosis of ADHD was not always
accompanied by a primary care prescription for a licensed ADHD medication. 56.5% of
patients diagnosed with ADHD between 1/1/2004 and 31/12/2013 were issued a
pharmaceutical treatment during that time by their GP. In those who did receive
pharmaceutical treatment from their GP, there was often an appreciable interval
95
between their first diagnosis of ADHD (denoted by a Read code) and their first ADHD-
related prescription. Taken together, these observations would suggest that a diagnosis
of ADHD does not invariably lead to pharmaceutical treatment in primary care, and
that pharmaceutical treatment is not commenced at the point of diagnosis in most
cases.
The observed delay between diagnosis and drug initiation may reflect the time
taken for secondary care input to be sought, as stipulated by NICE’s guidance on ADHD
(National Institute for Health and Care Excellence 2008a). However, this cannot be
definitively confirmed from the available data. Whilst CPRD captures referrals made
to secondary care specialities, the information held regarding the reason for
specific referrals is often inconclusive (a limitation discussed further in section
8.2.1.4). Furthermore, it is important to emphasise that this study’s findings regarding
treatment rates only have relevance to UK primary care. Whilst 43% of diagnosed
ADHD patients were found to be untreated in primary care, these patients may have
been prescribed pharmaceutical treatment elsewhere (for example privately, or via
secondary care).
No previous study had examined the average time between diagnosis and the
start of pharmaceutical treatment in UK children and adolescents with ADHD.
However, several studies have examined the proportions of children with ADHD who
also receive pharmaceutical treatment for the disorder. The methods and cohorts used
in these studies varied, as did their findings. In the United Kingdom, Sayal et al. (2010)
used data from the nationally-representative 2004 British Child and Adolescent Mental
Health Survey to identify a small cohort of five to sixteen year olds with ADHD (n =
176). Of these patients, 30% (n = 53) were taking either methylphenidate (n = 52) or
dexamfetamine (n = 1) for the condition. Comparing the findings of this ‘point
prevalence’ survey to the results of the current longitudinal study is difficult, as in a
longitudinal study individuals have more opportunity to ‘develop’ pharmaceutically-
treated ADHD over time. Furthermore, the earlier UK study was conducted at a time
when fewer licensed agents were available for the treatment of ADHD (namely
methylphenidate and dexamfetamine; atomoxetine received its UK product licence in
May 2004).
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At the time of writing, a newly-published paper by Renoux et al (2016)
examined what proportion of ADHD patients in the UK received treatment within one
year of their diagnosis. Using CPRD data, they observed that 55.6% of patients
diagnosed with ADHD in 2014 received a prescription from ADHD within one year of
their diagnosis. Whilst it is tempting to make a comparison between two CPRD studies,
achieving an accurate comparison is problematic. From the figures presented by the
Renoux study, it was not entirely clear if ‘prescribing within one year of diagnosis’
referred to prescribing occurring in the same calendar year as diagnosis, or within 365
days of diagnosis (the approach taken by the current study). In addition, whilst the
current study focused on children and adolescents, the other study examined patients
diagnosed between 6 and 45 years of age. What can be said of the current study is that
the percentage of treated patients observed is not exceptionally high by international
standards. A 2007 study using data from the National Survey of Children’s Health in the
United States found that 56.3% of 4-17 year olds with a diagnosis of ADHD were
receiving medication to treat the disorder at the point they were surveyed (Visser et al.
2007). A study using Sweden’s National Patient Register and Prescribed Drug
Register found that 65% of under 19s diagnosed with ADHD received a prescribed
treatment within one year of diagnosis; by the end of follow-up 82% had received
some sort of pharmaceutical treatment (Bahmanyar et al. 2013).
Returning to the current study, it must be acknowledged that the relationship
observed between diagnosis and pharmaceutical treatment was complex, and varied
significantly within the cohort examined. Furthermore, some of the findings made can
be interpreted in multiple ways using the information available within CPRD. For
example, in some treated patients (n=659) their first documented Read code for ADHD
occurred on the same day as their first documented prescription for an ADHD
treatment. At first glance, this would suggest that these patients’ first visit to a GP with
symptoms suggestive of ADHD resulted in a diagnosis being made and pharmaceutical
treatment being started that very day. This would conflict with NICE’s 2008 guidance
on ADHD, which recommends that a diagnosis of ADHD, and the initiation of treatment
in primary care, should only occur following referral to a specialist (which is unlikely to
occur on the same day) (National Institute for Health and Care Excellence 2008b). It
97
may be the case that some GPs have a paediatric or psychiatric specialism that permits
them to diagnose ADHD themselves, negating the need for specialist referral. An
alternative interpretation of events is however possible. It may be that when these
patients first consulted their general practitioner regarding their ADHD symptoms, a
referral to psychiatry, paediatric services or CAMHS was made, but no Read code
specific to ADHD was documented. Following specialist assessment and diagnosis,
general practitioners would then be informed of the diagnosis and, where appropriate,
asked to ‘pick up’ prescribing and monitoring. This could potentially result in GPs
documenting the confirmed diagnosis of ADHD at the same point they authorised an
initial prescription for methylphenidate, atomoxetine, dexamfetamine or
lisdexamfetamine.
In a comparable number of treated ADHD patients (n = 697), the earliest ADHD-
related event documented in their CPRD record was a prescription for an ADHD
medication, rather than a Read code denoting a diagnosis of ADHD. This runs counter
to the logic that a condition would be diagnosed and documented before (or at least
the same time as) pharmaceutical treatment was commenced. Definitively explaining
this finding is difficult, and it may again be the result of documentary rather than
clinical practices. For example, if a suspected diagnosis of ADHD was initially
documented using a “free text” entry in a patient’s medical records (rather than a
formal, coded diagnosis), this would not have been detectable by the study. Access to
free text information is not routinely provided by CPRD, as it may contain information
that could compromise patient anonymity (Herrett et al. 2015). However, a study of
rheumatoid arthritis patients in CPRD found that free text information suggestive of
rheumatoid arthritis preceded a formal coded diagnosis of the disorder in a sizeable
minority of patients (Ford et al. 2013).
5.4.2 Drug most commonly initiated first-line in primary care
In the cohort of treated patients identified, methylphenidate was found to be
the first-choice drug in the vast majority of cases. This is in-line with the findings of a
previous UK database study (McCarthy et al. 2012), and corresponds to NICE’s
guidelines on the treatment of ADHD in children and adolescents (National Institute for
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Health and Care Excellence 2008b). Atomoxetine was found to be the second most
common drug commenced in the treatment of ADHD. This is again in-line with previous
UK findings (McCarthy et al. 2012), and NICE’s guidance (which names atomoxetine as
an alternative first-line agent to methylphenidate in patients with certain
comorbidities, or where stimulant treatment would be inappropriate; National
Institute for Health and Care Excellence 2008b). Lisdexamfetamine, which only
received its UK marketing authorisation in 2013, was predictably used first-line in only a
very small number of all treated patients.
5.4.3 Age at commencement of pharmaceutical treatment in primary care
All the medications examined by this study are licensed for use from the age of
six upwards; unlicensed prescribing in patients below the age of six was rare. Only 146
treated patients received their first primary care prescription before the age of six. Of
these, 126 (86.3%) were treated with methylphenidate in the first instance. As
discussed, methylphenidate is the initial drug of choice in most older children with
ADHD; it has been extensively utilised in the treatment of childhood ADHD for decades
(De Sousa & Kalra 2012). Furthermore, the BNF for Children gives dosage instructions
for prescribing methylphenidate in four and five year olds (Paediatric Formulary
Committee 2015). All these factors may make general practitioners somewhat more
comfortable prescribing the drug as part of a shared care arrangement, even on an
unlicensed basis. The use of the other drugs in children below the age of six is perhaps
harder to explain with the data available. It may simply be the case that, in these
individuals, general practitioners were acting on expert secondary care advice and
were happy to prescribe the drugs as directed.
5.4.4 Predictors of pharmaceutical treatment in primary care
Cox regression identified several factors that significantly increased individuals’
likelihood of being prescribed medication in primary care following diagnosis. One such
factor was general practice location. Geography appears to have a complex role in
ADHD in the UK. As discussed in Chapter 4, Scotland’s overall diagnostic rate was the
lowest of the four UK nations. However, patients registered with Scottish general
practices were significantly more likely to receive a primary care prescription for ADHD
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compared to patients at English, Welsh and Northern Irish practices. Explaining this
finding definitively is beyond the scope of this study. However, there are potential
differences between Scotland and the other UK nations that may contribute to this
observation. Prescribing in ADHD may be administered using shared care protocols,
both in Scotland and the rest of the UK. Under the terms of such protocols, prescribing
is generally carried out by GPs once a patient’s diagnosis and initial drug regimen has
been determined in secondary care (Beau-Lejdstrom et al. 2016; Holden et al. 2013;
Rowlingson et al. 2013). A report by Healthcare Improvement Scotland (published in
2012) found that all Scotland’s Health Boards had shared care arrangements in place
for ADHD (Healthcare Improvement Scotland 2012). No comparable report was carried
out in the other three nations. However, this universal provision of shared care
arrangements may contribute to GPs in Scotland managing a greater share of routine
prescribing for ADHD than their English, Welsh and Northern Irish counterparts.
The role of gender in ADHD appears equally nuanced. Whilst males are
significantly more likely to be diagnosed with ADHD than females (Hire et al. 2015), in
the cohort studied gender did not appear to affect patients’ likelihood of receiving
pharmaceutical treatment. Once diagnosed, females were equally likely to go on to
receive a prescription from their GP as their male counterparts. This finding is in line
with those presented by the ADHD Observational Research in Europe (ADORE) study
group (Nøvik et al. 2006), and would appear logical; there is no evidence that drugs are
any less effective in girls than boys with ADHD (Rucklidge 2010).
In chapter 4, an analysis of this cohort revealed a relatively clear relationship
between practice-level deprivation quintile and ADHD incidence. The most deprived
patients (IMD quintile 5) had the highest incidence of diagnosed ADHD, significantly
higher than the incidence observed in the least deprived patients (IMD quintile 1).
Following diagnosis however, the most deprived patients were just as likely to receive a
medication from their GP as the least deprived patients [adjusted HR 0.96 (95% CI
0.87 – 1.06)]. Pharmaceutical treatment was most likely amongst patients in
deprivation quintile three (the ‘middle’ deprivation quintile), and least likely amongst
patients in quintile two. As with gender, it appears that deprivation greatly influences
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an individual’s likelihood of being diagnosed with ADHD, more so than their likelihood
of subsequently receiving medication.
Patients’ age at diagnosis appeared to be a significant predictor of
pharmaceutical treatment in primary care. Patients diagnosed with ADHD between the
ages of ten and twelve, and between thirteen and fifteen, were significantly more likely
to receive medication during observation than those diagnosed at an earlier or later
age. A combination of factors probably contributes to this finding. Between ten and
fifteen, all four ADHD medications may be utilised within their licensed indications.
Additionally, this period would encompass particularly important periods in childrens’
schooling, such as the transition from primary to secondary education, and the run up
to examinations at the end of secondary schooling. Perhaps the most interesting
observation relates to those diagnosed between one and three years of age. Just 8.6%
of patients diagnosed at this age were subsequently prescribed an ADHD medication in
primary care. This was irrespective of how long they were registered with their general
practice. As such, this observation is not entirely explicable by reluctance amongst GPs
to prescribe drugs (on an unlicensed basis) to the youngest patients with ADHD. It may
be that ADHD diagnoses recorded earlier in life tended to be more ’provisional’ in
nature. ADHD may be difficult to distinguish from normal developmental behaviour in
younger children (Smith 2011); patients with behavioural symptoms very early on in life
may have grown out of them by the time pharmaceutical treatment became an option
(Royal College of Psychiatrists 2014). Alternatively, it could be that patients who
developed ADHD at a very young age represented more complex cases to manage. This
would perhaps lead to the prescribing of ADHD medications being both commenced
and maintained in specialist care, even as they grew older. This is discussed further in
section 8.2.1.2.
5.5 Conclusion
A documented diagnosis of ADHD in patients’ CPRD record was not always
accompanied by a primary care prescription for a licensed ADHD medication. In most
treated patients, a formal coded diagnosis of ADHD preceded the earliest prescription
for an ADHD medication. In these patients, the median interval between an initial
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diagnosis of ADHD and their first primary care prescription for an ADHD medication
was 84 days (IQR = 21-258 days). Methylphenidate was employed first-line in 92% of
treated patients; pharmaceutical treatment below the age of six was rare. Gender did
not significantly influence patients’ likelihood of receiving pharmaceutical treatment
from their GP following diagnosis. However, patients age at diagnosis, deprivation
level, and nation of residence all had the potential to affect their likelihood of receiving
a primary care prescription for a licensed ADHD medication.
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Chapter 6
Mental, behavioural and
neurological comorbidity and
psychotropic treatment in children
and adolescents with ADHD: A
cohort study using linked CPRD
and HES data
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6.1 Background
Comorbidity may be defined as the presence of one or more medical
disorders alongside a primary disorder (Valderas et al. 2009). Previous research has
suggested that comorbidity is common in patients with ADHD; it has been
estimated that up to 65% of children and adolescents with ADHD have some form
of clinically significant comorbidity (Kooij et al. 2010). The presence of comorbidity
in ADHD can have a major impact on patients; it potentially complicates the
treatment of the disorder and has the potential to worsen academic, social,
emotional and psychological outcomes for those affected (Spencer 2006). Many of
the specific comorbidities most commonly associated with ADHD can be broadly
classed as mental, behavioural and neurological disorders. Among those most
frequently linked with ADHD are conduct disorder, autistic spectrum disorders,
epilepsy, tic disorder and Tourette’s syndrome, depression, anxiety disorders,
bipolar disorder and schizophrenia (Steinhausen et al. 2006; Williams et al. 2016;
Kraut et al. 2013; Jensen & Steinhausen 2015).
Conduct disorder (CD) and the closely related diagnosis of oppositional
defiant disorder (ODD) are behavioural disorders characterised by a repetitive and
persistent pattern of dissocial, aggressive, or defiant conduct that is more severe
than ordinary childhood misbehaviour, and disrupts a child’s ability to lead a normal
life (World Health Organisation 2015). These disorders have been cited as the most
common comorbidities observed alongside ADHD (Steinhausen et al. 2006; Jensen
& Steinhausen 2015). The ICD-10 recognises the high degree of overlap between
conduct disorder and ADHD. It lists “hyperkinetic conduct disorder” as a distinct
variant of hyperkinetic disorder (a diagnosis analogous to severe ADHD; World
Health Organisation 2015). Autistic spectrum disorders (ASD) are complex and
pervasive developmental disorders that have also been observed alongside ADHD.
Estimates vary, but it has been reported that 20-50% of children with ADHD meet
the diagnostic criteria for an autistic spectrum disorder; there is ongoing research
into whether ASD and ADHD have a shared genetic basis (Rommelse et al. 2010).
Reported rates of ADHD amongst individuals with epilepsy are comparable to those
reported for autism. A recent review of ADHD prevalence in epilepsy determined
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that symptoms suggestive of ADHD are present in 20-50% of children with epilepsy
(Williams et al. 2016). The notion that seizures may play a causative role in the
onset of ADHD has also been explored (Kaufmann et al. 2009). However, Williams
and colleagues noted that “ADHD symptoms are frequently present at the time of,
or before, first seizure onset, suggesting that ADHD is a comorbid condition and not
a condition caused solely by the seizure disorder or (its) treatments” (Williams et al.
2016, p.288).
Tic disorders (TD) are a comorbidity of ADHD specifically mentioned in the
National Institute for Health and Care Excellence guidelines on the diagnosis and
management of the disorder (National Institute for Health and Care Excellence
2008). Characterised by involuntary vocalisations or motor movements (or both in
the case of Tourette’s syndrome), the relationship between tic disorders and ADHD
appears to be complex. Reported rates of association between the two disorders
vary widely (Bloch et al. 2009; Scharf et al. 2012) but are much higher than would
be expected due to chance alone; treatment of ADHD with its licensed agents may
exacerbate tic severity (though this is disputed) (Pringsheim & Steeves 2011).
Mood disorders such as depression and anxiety disorders are frequently
reported in children and adolescents with ADHD (Banaschewski 2016). It is unclear
whether this reflects a common genetic basis linking depression, anxiety disorders
and ADHD, or if the detrimental effects of ADHD (on interpersonal relationships,
educational achievement and other aspects of patients’ lives) may precipitate the
onset of these disorders (Banaschewski 2016; Meinzer et al. 2014). Depressive and
anxiety disorders can vary in severity, from mild to very severe. However, mental
disorders characterised by psychosis (such as bipolar disorder, schizophrenia and
related delusional disorders) are specifically classed as severe mental illnesses (SMI)
under the National Health Service Quality and Outcomes Framework (QOF)
(Gutacker et al. 2015). Severe mental illnesses have been observed in patients with
ADHD, though the extent of any comorbid association is unclear. Though brain
imaging studies have suggested that comorbid ADHD-bipolar disorder has a distinct
phenotypic signature (Hegarty et al. 2012), the very existence of comorbid bipolar
disorder alongside ADHD is questioned by some, and estimates of co-occurrence
105
vary widely (Youngstrom et al. 2010). Likewise, the co-existence of ADHD and
schizophrenia has not been extensively researched in children. However, one small
study of 4-15 year olds with schizophrenia and schizoaffective disorder found that
84% met the diagnostic criteria for ADHD (Ross et al. 2006).
Though numerous studies have examined ADHD and its links with mental,
behavioural and neurological comorbidities, the focus, design, and results of these
studies have been heterogeneous. Many prior studies have been prospective in
nature. These identified comorbidities amongst cohorts of ADHD patients though
the application of rigorous screening measures and procedures. This is effective at
identifying potential cases of comorbidity, but whether these diagnoses would have
been made in ‘real-world’ circumstances outside of the study is open to question.
Other notable issues include the use of relatively low sample sizes, and samples in
which females were absent or under-represented. To my knowledge, no large-scale
examination of mental, behavioural and neurological comorbidities in ADHD had
previously been conducted in the UK.
Diagnosis with such comorbidities may result in treatment with psychotropic
medications. Psychotropics are defined as drugs that affect individuals’ mental
processes, such as cognition or affect (World Health Organisation 2016). Paediatric
psychotropic prescribing has become increasingly prevalent in the UK in recent
years (Rani et al. 2008; Bachmann et al. 2016). This is despite concerns regarding
their potential long term effects on the developing body and brain (Birnbaum et al.
2013; Bottelier et al. 2014). To my knowledge, no previous study had assessed if
exposure to such psychotropics (aside from those specifically indicated for ADHD) is
higher amongst children with the ADHD than children without the disorder.
6.1.1 Aims
The aim of this study was to establish if patients diagnosed with ADHD
between 1/1/2004 and 31/12/2013 were more likely to be diagnosed with selected
mental, behavioural and neurological comorbidities during that period than
matched comparators who remained free of ADHD. Given that mental and
behavioural problems may be treated pharmaceutically, the study also established
106
if psychotropic exposure was significantly more likely amongst children diagnosed
with ADHD between 1/1/2004 and 31/12/2013, compared to children without the
disorder. By comparing prescribing rates in the year before, and the year after, their
initial diagnosis with ADHD, it could be determined if individuals’ risk of receiving
psychotropic medication was significantly higher following their diagnosis with
ADHD. Using a large cohort of several thousand ADHD patients, and both primary
care and hospital admissions data, the ‘real-world’ burden of mental, behavioural
and neurological comorbidity amongst children and adolescents with ADHD was
established.
6.2 Methods
6.2.1 Study Population
The study made use of electronic healthcare records data: CPRD primary
care data and integrated Hospital Episode Statistics (HES). From the larger cohort of
10,284 ADHD patients diagnosed with the disorder between 1/1/2004 and
31/12/2013, 5111 who were eligible for HES linkage (from 381 English general
practices) were selected as the ADHD cohort for this study. This cohort included
both pharmaceutically-treated and untreated ADHD patients. A cohort of 49,489
matched comparison patients was identified using CPRD. All comparators were
eligible for HES linkage, and were matched on gender, year of birth and general
practice; each member of the ADHD cohort was matched with up to 10
comparators. All comparators were screened to ensure that they had no Read code
denoting a diagnosis of ADHD, or any product code for a licensed ADHD medication,
documented in their CPRD record prior to 31/12/2013. Comparators were required
to have at least one documented consultation with their GP in the year that their
matched case was diagnosed with ADHD. This was referred to as their index date. In
ADHD patients, their date of diagnosis served as their index date.
6.2.2 Determination of comorbidity, and psychotropic treatment
Patient’s electronic healthcare records were screened for comorbid
diagnoses and psychotropic prescriptions recorded between 1/1/2004 and
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31/12/2013 (the ‘study period’). The exact observation period for each individual
varied, and this observation time could be determined for all individuals. Patients
were observed from the latest point of the following: their registration date with
their CPRD general practice, the date on which their general practice attained
CPRD’s data quality standards (the practice ‘up to standard’ date), the study start
date (1/1/2004). Patients were then observed until the earliest point of the
following: the date at which they left their CPRD general practice (if applicable), the
date of their death (if applicable), January 1st of the year they turned 19 years of
age, the last date on which data was transferred from their practice to CPRD, the
study end date (31/12/2013).
Comorbidities of interest were identified by the presence of Read codes (in
patients’ CPRD records), and ICD-10 codes (in patients’ HES records, where
present). A full list of relevant Read codes and ICD-10 codes is presented in
Appendix 4. Primary care psychotropic prescribing was identified by the presence of
product codes for drugs of interest in patients’ CPRD records. Drugs of interest
were broadly classed as antipsychotics, antidepressants or anxiolytics/hypnotics.
Product codes for the psychotropic medications examined are presented in
Appendix 5. To assess if comorbidities were more likely to be detected using
primary or secondary care data, the number and proportion of individuals with a
Read code and/or an ICD-10 code for each comorbidity was presented.
The study assessed sequential comorbidity, the co-occurrence of disorders
in a time-independent manner (Jensen & Steinhausen 2015). Any individual with a
comorbidity of interest recorded in their CPRD/HES record during their period of
observation was counted as having a comorbidity, whether the diagnosis occurred
before or after their index date. The number of ADHD patients and comparator
patients with each comorbidity was calculated. The relative risk of comorbidity
amongst ADHD patients and non-ADHD comparators was illustrated using risk ratios
(RR) with 95% confidence intervals. The prevalence of comorbidity was also
presented as the number of cases per person-year [pyar] of observation time in the
ADHD and comparator cohort.
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The prevalence of psychotropic prescribing in primary care was described in
a similar manner to comorbidity. The number of ADHD patients and comparators
who received a primary care prescription for a psychotropic was calculated. The
relative risk of psychotropic exposure amongst ADHD patients and non-ADHD
comparators was illustrated using risk ratios with 95% CI. The number of patients
who received a prescription for a psychotropic was also presented as the number of
cases per 10,000 person-years [pyar] of observation time in cases and comparators.
Details of psychotropic medications issued to individuals between 1/1/2004 and
31/12/2013 were provided (specific drugs prescribed, numbers of prescriptions
issued).
The number of ADHD patients/comparators who received a psychotropic
prescription in the 365 days preceding their index date was compared to the
number that received a prescription in the 365 days following their index date. The
number of patients who received a prescription for a psychotropic in the year
before, and the year after, their index date was also presented as the number of
cases per 10,000 person-years [pyar] of observation time in cases and comparators.
In both cohorts, rate ratios and 95% CI were calculated to establish if psychotropic
prescribing rates were significantly higher in the year following individuals’ index
dates than they were in the year before this date.
Statistical significance was set at p 0.05, and all statistical analyses were
performed using Stata version 13 (StataCorp, College Station, Texas, United States).
6.3 Results
6.3.1 Mental, behavioural and neurological comorbidity
The characteristics of the two cohorts studied are shown in Table 8.
Between 1/1/2004 and 31/12/2013, 27% of ADHD patients (n = 1379) had at least one
Read code or ICD-10 code indicating a comorbidity of interest recorded in their
electronic healthcare record. This compared to just 6.2% of comparators (n = 3718).
Every mental, behavioural and neurological comorbidity examined was significantly
more common amongst the ADHD cohort (see Table 9). The greatest difference in risk
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Table 8: Cohort characteristics (cases and comparators)
Cohort ADHD cohort Comparator cohort
Description Individuals diagnosed with incident ADHD between 1/1/2004 and 31/12/2013
Individuals with no diagnosis of ADHD, or exposure to a
licensed treatment for the disorder, prior to 31/12/2013
Number of subjects 5111 49,489
Gender
Male 4174 (81.67%) 40,315 (81.46%)
Female 937 (18.33%) 9174 (18.54%)
Observation time
Median observation time per subject, days [IQR]
2922 days [IQR 2093 - 3650] 2821 days [IQR 1847 – 3650]
Total observation time between 1/1/2004-31/12/2013
(person-years)
38,304 353,888
Observation time covering 365 days prior to index date
(person-years)
5111 38,780
Observation time covering 365 days following index date
(person-years)
4676 43,201
Year of birth
1986 & 1987 6 (0.12%) 60 (0.12%)
1988 11 (0.22%) 107 (0.22%)
1989 20 (0.39%) 200 (0.40%)
1990 44 (0.86%) 429 (0.87%)
1991 86 (1.68%) 835 (1.69%)
1992 123 (2.41%) 1196 (2.42%)
1993 186 (3.64%) 1784 (3.60%)
1994 214 (4.19%) 2074 (4.19%)
1995 234 (4.58%) 2276 (4.60%)
1996 261 (5.11%) 2526 (5.10%)
1997 368 (7.20%) 3513 (7.10%)
1998 431 (8.43%) 4199 (8.48%)
1999 394 (7.71%) 3747 (7.57%)
2000 411 (8.04%) 3942 (7.97%)
2001 392 (7.67%) 3740 (7.56%)
2002 365 (7.14%) 3490 (7.05%)
2003 412 (8.06%) 4024 (8.13%)
2004 368 (7.20%) 3577 (7.23%)
2005 294 (5.75%) 2884 (5.83%)
2006 221 (4.32%) 2188 (4.42%)
2007 146 (2.86%) 1459 (2.95%)
2008 73 (1.43%) 729 (1.47%)
2009 31 (0.61%) 310 (0.63%)
2010 12 (0.23%) 120 (0.24%)
2011 & 2012 8 (0.16%) 80 (0.16%)
Region of general practice
North East 128 (2.50%) 1256 (2.54%)
North West 789 (15.44%) 7522 (15.20%)
Yorkshire & The Humber 120 (2.35%) 1196 (2.42%)
East Midlands 169 (3.31%) 1664 (3.36%)
West Midlands 496 (9.70%) 4820 (9.74%)
East of England 751 (14.69%) 7293 (14.74%)
South West 508 (9.94%) 4998 (10.10%)
South Central 687 (13.44%) 6707 (13.55%)
London 533 (10.43%) 5120 (10.35%)
South East Coast 930 (18.20%) 8913 (18.01%) Cell counts less than 5 not specified in line with CPRD reporting requirements; 1986/1987 & 2011/2012 figures were combined for this reason
110
was observed in relation to conduct disorder and oppositional defiant disorder. The
risk of CD/ODD amongst ADHD patients was 15.72 (95% CI 12.02 – 20.57) times the
risk amongst the non-ADHD comparators. At the opposite end of the scale, the risk of
depression amongst ADHD patients was 1.90 (95% CI 1.62 – 2.23) times that of
comparators. The most prevalent comorbidity amongst ADHD patients was autism and
autistic spectrum disorders; 16% (n= 817) of ADHD patients had a documented
Read/ICD-10 code relating to these conditions. The most prevalent comorbidity
amongst comparators was anxiety disorders, affecting 1017 individuals (1.9% of the
cohort).
Table 9: Prevalence and relative risk of comorbidity amongst ADHD patients and non-ADHD comparators between 1/1/2004 and 31/12/2013
Individuals with at least one Read or
ICD-10 code indicating:
ADHD cohort (% of
cohort)
Prevalence (cases per
10,000 pyar)
Comparator cohort
(% of cohort)
Prevalence (cases per
10,000 pyar)
Risk ratio (cases v
comparators) [95% CI]
Any comorbidity of interest
1379 (26.98%)
360.01 3718 (7.51%)
105.06 3.59 [3.40 – 3.79]
Autism/autistic spectrum disorder
817 (15.99%)
213.29 936 (1.89%)
26.45 8.45 [7.73 – 9.24]
Anxiety disorders 210 (4.11%)
54.82 1017 (2.06%)
28.74 2.00 [1.73 – 2.31]
Epilepsy 191 (3.74%)
49.86 885 (1.79%)
25.01 2.09 [1.79 – 2.44]
Depression 174 (3.40%)
45.43 886 (1.79%)
25.04 1.90 [1.62 – 2.23]
Conduct disorder/ Oppositional defiant
disorder
138 (2.70%)
36.03 85 (0.17%)
2.40 15.72 [12.02 – 20.57]
Tic disorder/Tourette’s
disorder
119 (2.33%)
31.07 278 (0.56%)
7.86 4.14 [3.35 – 5.13]
Severe mental illness 42 (0.82%)
10.96 104 (0.21%)
2.94 3.91 [2.74 – 5.59]
Combining CPRD’s primary care data with secondary care HES data did
detect individuals with mental, behavioural and neurological comorbidities who
would not have been identified using primary care data alone. These individuals had
an ICD-10 code indicating a comorbidity of interest in their HES records, but no
accompanying Read code in their primary care records (see Table 10). Though more
cases of comorbidity were identified, the addition of secondary care data did not
fundamentally change the observations made using primary care data alone. Without
the use of secondary care data, autism remained the most prevalent comorbidity
among ADHD patients, and anxiety disorders remained the most prevalent comorbidity
111
among comparators. Of all the comorbidities examined, ADHD patients still had the
had the greatest risk of conduct disorder and oppositional defiant disorder, relative to
non-ADHD comparators.
Table 10: Comorbidity ascertainment using Read codes and ICD-10 codes
Comorbidity ADHD cohort Comparator cohort
Individuals with an autism/autistic spectrum disorder:
Read code and/or ICD-10 code
Both Read code only
ICD-10 code only
817 (100%)
153 (18.73%) 574 (70.26%) 90 (11.02%)
936 (100%)
166 (17.74%) 626 (66.88%) 144 (15.38%)
Individuals with an anxiety disorders: Read code and/or ICD-10 code
Both Read code only
ICD-10 code only
210 (100%)
10 (4.76%) 180 (85.71%)
20 (9.52%)
1017 (100%)
30 (2.95%) 902 (88.69%)
85 (8.36%)
Individuals with an epilepsy: Read code and/or ICD-10 code
Both Read code only
ICD-10 code only
191 (100%)
68 (35.60%) 38 (19.90%) 85 (44.50%)
885 (100%)
311 (35.14%) 153 (17.29%) 421 (47.57%)
Individuals with a depression: Read code and/or ICD-10 code
Both Read code only
ICD-10 code only
174 (100%)
15 (8.62%) 133 (76.44%) 26 (14.94%)
886 (100%)
61 (6.88%) 751 (84.76%)
74 (8.35%)
Individuals with a conduct disorder/oppositional defiant disorder:
Read code and/or ICD-10 code
Both Read code only
ICD-10 code only
138 (100%)
6 (4.35%) 87 (63.04%) 45 (32.61%)
85 (100%)
0 (0%) 34 (40.00%) 51 (60.00%)
Individuals with a tic disorder/Tourette’s disorder:
Read code and/or ICD-10 code
Both* Read code only
ICD-10 code only*
119 (100%)
omitted 105 (88.24%)
omitted
278 (100%)
omitted 268 (96.40%)
omitted
Individuals with a severe mental illness: Read code and/or ICD-10 code
Both Read code only
ICD-10 code only
42 (100%)
6 (14.29%) 25 (59.52%) 11 (26.19%)
104 (100%)
11 (10.58%) 55 (52.88%) 38 (36.54%)
*Cell counts less than 5 not specified in line with CPRD reporting requirements
Most cases of comorbidity (in general) were identifiable using patients’ primary
care records. Epilepsy was notable in that more cases were identified using secondary
care data than primary care data. This was the case in both the ADHD cohort and the
comparator cohort. Altogether 80.1% of ADHD patients with epilepsy had a secondary
112
care record associated with the disorder. The proportion amongst comparators was
slightly higher, with 82.7% of individuals having a secondary care record relating to the
disorder.
6.3.2 Psychotropic prescribing in primary care
The risk of being prescribed a psychotropic drug of interest during the study
period was higher amongst ADHD patients than comparators (see Table 11). The
most pronounced difference in risk was observed in relation to anxiolytics and
hypnotics. In all, 18.1% of ADHD patients had received a prescription for an
anxiolytic/hypnotic between 1/1/2004 and 31/12/2013; the risk of receiving an
anxiolytic/hypnotic prescription as an ADHD patient was over twelve times the risk
amongst comparators. In ADHD patients, melatonin prescribing accounted for a
high proportion of anxiolytic/hypnotic prescribing; 89.1% of all ADHD patients
prescribed an anxiolytic/hypnotic had received a prescription for melatonin
specifically. In contrast, 36.9% of comparators in receipt of a prescription for an
anxiolytic/hypnotic had received a melatonin prescription. During the study period,
rectal diazepam and buccal midazolam combined accounted for 40.4% of
benzodiazepine prescriptions in the ADHD cohort, and 51.3% of prescriptions in
comparators. When clonazepam prescriptions were considered alongside rectal
diazepam and buccal midazolam, these preparations accounted for 73.2% of
benzodiazepine prescriptions in ADHD patients and 59.1% of benzodiazepine
prescriptions in comparators.
ADHD patients had 29.5 (95% CI 23.25 – 37.40) times the risk of receiving a
prescription for a second generation antipsychotic relative to comparators.
Risperidone was the most common second generation antipsychotic prescribed in
ADHD patients; it was prescribed to 246 individuals and accounted for 87.6% of
second generation prescriptions observed (n=3646). Risperidone additionally
accounted for 66.9% of all second generation prescriptions observed in the
comparator group (n=189). In contrast to the findings for second generation
antipsychotics, the risk of being prescribed a first generation antipsychotic was not
significantly higher amongst the ADHD patients (see Table 11). Haloperidol was the
113
Table 11: Prevalence and relative risk of psychotropic exposure amongst ADHD patients and non-ADHD comparators between 1/1/2004 and 31/12/2013
Individuals with at least one primary care prescription for:
ADHD cohort
(% of cohort)
Prevalence (per 10,000
pyar)
Comparator cohort
(% of cohort)
Prevalence (per 10,000
pyar)
Risk ratio (cases v comparators)
[95%CI]
Any psychotropic of interest 1196 (23.40%)
312.24 1622 (3.28%)
45.83 7.14 [6.66 – 7.65]
Any Antipsychotic 309 (6.05%) 80.67 440 (0.89%) 12.43 6.80 [5.90 – 7.84]
1st generation 48 (0.94%) 12.53 357 (0.72%) 10.09 1.30 [0.96 – 1.76] 2nd generation 271 (5.30%) 70.75 89 (0.03%) 2.51 29.48 [23.25 – 37.40]
Any Antidepressant 213 (4.17%) 55.61 683 (1.38%) 18.03 3.02 [2.60 – 3.51]
Selective serotonin reuptake inhibitor 166 (3.25%) 43.34 426 (0.86%) 12.04 3.77 [3.16 – 4.50] Tricyclic antidepressant Other antidepressant^
49 (0.96%) 7 (0.14%)
12.79 1.83
282 (0.57%) 27 (0.05%)
7.97 0.76
1.68 [1.24 – 2.28] 2.51 [1.09 – 5.76]
Monoamine oxidase inhibitor 0 (0%) 0 0 (0%) 0 N/A
Any Anxiolytic or Hypnotic 925 (18.10%) 241.49 713 (1.44%) 20.15 12.56 [11.44 – 13.79]
Benzodiazepine Chloral hydrate/cloral betaine
101 (1.98%) 24 (0.47%)
26.37 6.27
373 (0.75%) 32 (0.06%)
10.54 0.90
2.62 [2.10 – 3.26] 7.26 [4.28 – 12.32]
Melatonin 824 (16.12%) 215.12 263 (0.53%) 7.43 30.34 [26.49 – 34.75] Z drug+ 19 (0.37%) 4.96 84 (0.17%) 2.37 2.19 [1.33 – 3.60]
Other anxiolytic/hypnotic* 12 (0.23%) 3.13 22 (0.04%) 0.62 5.28 [2.62 – 10.67] ^Other antidepressant = Duloxetine, mirtazepine, trazodone, venlafaxine +Z drug = Zopiclone, zolpidem, zaleplon *Other anxiolytic/hypnotics = Phenobarbital, buspirone or triclofos sodium
114
most commonly prescribed first generation antipsychotic in ADHD patients
between 2004 and 2013 (87 prescriptions; 49.7% of all first generation
prescriptions). In contrast, prochlorperazine accounted for 79.5% of all first
generation prescribing amongst comparators (434 prescriptions).
Patients with ADHD had approximately three times the risk of being
prescribed an antidepressant relative to comparators. In both cohorts, selective
serotonin reuptake inhibitors (SSRIs) were the most commonly prescribed class of
antidepressant. The SSRIs fluoxetine (1057 prescriptions issued to 97 individuals)
and sertraline (781 prescriptions issued to 53 individuals) accounted for 72.3% of all
antidepressant prescriptions in ADHD patients. These were the most commonly
prescribed antidepressants amongst comparators also, though they accounted for a
lower proportion of prescribing (52.9% of all antidepressant prescriptions). There
was a notable difference in tricyclic antidepressant prescribing between cases and
comparators. In ADHD patients, imipramine was the most commonly prescribed
tricyclic antidepressant. It accounted for 64.6% of all tricyclic prescriptions in this
cohort, ahead of amitriptyline which accounted for 33.9% of prescribing. In
contrast, amitriptyline prescribing was most prevalent among comparators (67.4%
of prescriptions), ahead of imipramine (25.1% of prescriptions).
6.3.3 Timing of psychotropic prescribing
As shown in Table 12, patients with ADHD were significantly more likely to receive a
psychotropic drug in the year following their diagnosis with ADHD than the year
prior to diagnosis (rate ratio 3.13 [95% CI 2.67 – 3.68]). With regard to
antipsychotics specifically, ADHD patients had a significantly higher risk of receiving
a second generation antipsychotic in the year after their ADHD diagnosis date,
compared to the year before. In relation to first generation antipsychotics, no
statistically significant difference was observed. For antidepressants, the findings
were equally nuanced. The risk of receiving an SSRI was significantly higher in ADHD
patients in the year following their diagnosis date, compared to the year before.
However, there was no statistically significant difference in prescribing rates for
tricyclic antidepressants. In ADHD patients, the relative risk of receiving an
115
Table 12: Prevalence and relative risk of psychotropic exposure amongst ADHD patients in the 365 days preceding, and the 365 days following, their index date
ADHD cohort
Individuals with a primary care
prescription for:
Within 365 days (pre
diagnosis) [% of total]~
Prescribing prevalence
(pre diagnosis) [cases per
10,000 pyar]
Within 365 days (post
diagnosis) [% of total]~
Prescribing prevalence
(post diagnosis) [cases per
10,000 pyar]
Rate ratio (before v
after) [95%CI]
Any psychotropic of interest
202 (16.89%)
395.23 578 (48.33%)
1236.10 3.13 [2.67 – 3.68]
Any Antipsychotic
36 (11.65%)
70.44 117 (37.86%)
250.21 3.55 [2.46 – 5.22]
1st generation <5 (<10.42%)
5.87 9 (18.75%)
19.25 3.28 [0.93 – 15.02]
2nd generation 33 (12.18%)
64.57 111 (40.96%)
237.38 3.67 [2.51 – 5.49]
Any Antidepressant
44 (20.66%)
86.09 75 (35.21%)
160.39 1.86 [1.29 – 2.72]
Selective serotonin reuptake inhibitor
35 (21.08%)
68.48 65 (39.16%)
139.01 2.03 [1.35 – 3.09]
Tricyclic antidepressant
10 (20.41%)
19.57 10 (20.41%)
21.39 1.09 [0.44 – 2.69]
Other antidepressant^
0 (0%)
0 0 (0%)
0 N/A
Monoamine oxidase inhibitor
0 (0%)
0 0 (0%)
0 N/A
Any Anxiolytic or Hypnotic
140 (15.13%)
273.92 449 (48.54%)
960.22 3.51 [2.91 – 4.25]
Benzodiazepine 22 (21.78%)
43.04 28 (27.72%)
59.88 1.39 [0.79 – 2.46]
Chloral hydrate/cloral
betaine
6 (25.00%)
11.74 8 (33.33%)
17.11 1.46 [0.49 – 4.50]
Melatonin 116 (14.08%)
226.96 416 (50.48%)
889.65 3.92 [3.20 – 4.83]
Z drug+ <5 (<26.32%)
<9.78 6 (31.58%)
12.83 6.56 [0.79 – 54.47]
Other anxiolytic/hypnotic*
<5 (<41.67%)
<9.78 <5 (<41.67%)
<10.69 0.55 [0.07 – 3.08]
~% of all ADHD patients treated with this medication between 1/1/2004 – 31/12/2013 ^Other antidepressant = Duloxetine, mirtazepine, trazodone, venlafaxine +Z drug = Zopiclone, zolpidem, zaleplon *Other anxiolytic/hypnotics = Phenobarbital, buspirone or triclofos sodium Cell counts less than 5 not specified in line with CPRD reporting requirements
anxiolytic/hypnotic was 3.51 times higher in the year post-diagnosis than in the
year preceding diagnosis. This finding was heavily influenced by melatonin
prescribing. Over 50% of ADHD patients who received a prescription for melatonin
during the study period had one in the year following their ADHD diagnosis; just
14% had a prescription in the year before their diagnosis. In terms of relative risk,
ADHD patients were 3.9 times as likely to receive a melatonin prescription in the
116
year following their ADHD diagnosis than they were in the year before their
diagnosis (95% CI 3.20 – 4.83).
As shown in Table 13, comparators were no more likely to receive a
psychotropic prescription in the year following their index date than they were in
the year before their index date. This was true for psychotropics in general, and for
every individual class of psychotropic examined.
Table 13: Prevalence and relative risk of psychotropic exposure amongst comparators in the 365 days preceding, and the 365 days following, their index date
Comparator cohort
Individuals with a primary care
prescription for:
Within 365 days
(pre index date)
[% of total] ~
Prescribing prevalence (pre index
date) [cases per
10,000 pyar]
Within 365 days
(post index date)
[% of total] ~
Prescribing prevalence (post index
date) [cases per
10,000 pyar]
Rate ratio (before v after)
[95%CI]
Any psychotropic of interest
266 (16.40%)
68.59 327 (20.16%)
75.69 1.10 [0.94 – 1.30]
Any Antipsychotic 51 (11.59%)
13.15 70 (15.91%)
16.20 1.23 [0.86 – 1.78]
1st generation 31 (8.68%)
7.99 43 (12.04%)
9.95 1.25 [0.79 – 2.00]
2nd generation 21 (23.60%)
5.42 27 (30.34%)
6.25 1.15 [0.65 – 2.07]
Any Antidepressant
80 (11.71%)
20.63 100 (14.64%)
23.15 1.12 [0.84 – 1.51]
Selective serotonin reuptake inhibitor
41 (9.62%)
10.57 66 (15.49%)
15.28 1.45 [0.98 – 2.15]
Tricyclic antidepressant
40 (14.18%)
10.31 37 (13.12%)
8.56 0.83 [0.53 – 1.30]
Other antidepressant^
0 (0%)
0 <5 (<18.52%)
<1.16 N/A
Monoamine oxidase inhibitor
0 (0%)
0 0 (0%)
0 N/A
Any Anxiolytic or Hypnotic
149 (20.90%)
38.42 182 (25.53%)
42.13 1.10 [0.88 – 1.36]
Benzodiazepine 75 (20.11%)
19.34 90 (24.12%)
20.83 1.08 [0.79 – 1.47]
Chloral hydrate/cloral
betaine
6 (18.75%)
1.55 <5 (<15.63%)
<1.16 0.60 [0.15 – 2.19]
Melatonin 67 (25.48%)
17.28 85 (32.32%)
19.68 1.14 [0.83 – 1.57]
Z drug+ 6 (7.14%)
1.55 9 (10.71%)
2.08 1.35 [0.47 – 4.07]
Other anxiolytic/hypnotic*
<5 (<22.73%)
<1.29 <5 (<22.73%)
<1.16 0.45 [0.06 – 2.53]
~% of all comparators treated with this medication between 1/1/2004 – 31/12/2013 ^Other antidepressant = Duloxetine, mirtazepine, trazodone, venlafaxine +Z drug = Zopiclone, zolpidem, zaleplon *Other anxiolytic/hypnotics = Phenobarbital, buspirone or triclofos sodium Cell counts less than 5 not specified in line with CPRD reporting requirements
117
6.4 Discussion
6.4.1 Mental, behavioural and neurological comorbidity
This study found that, for every comorbidity examined, the risk of diagnosis
was significantly higher in ADHD patients than non-ADHD comparators. This
strongly supports the hypothesis that mental, behavioural and neurological
disorders are more likely to be present in patients with ADHD than those
unaffected by the disorder. Of all the comorbidities examined by this study, ADHD
patients had the highest relative risk of conduct disorder and oppositional defiant
disorder compared to matched comparators [RR 15.72 (95% CI 12.02 – 20.57)]. This
is in line with the findings of earlier studies examining multiple comorbidities in
ADHD (Jensen & Steinhausen 2015; Steinhausen et al. 2006). Providing definitive
reasons as to why ADHD so often occurs in tandem with CD/ODD (or any other
disorder) is beyond the capabilities of this study. However, some potential reasons
for this finding can be put forward. Firstly, ADHD and CD/ODD have overlapping
behavioural symptoms. As such, screening for one may promote consideration and
diagnosis of the other. Secondly, both the Read and ICD-10 coding systems allow
the easy documentation of ADHD in concurrence with conduct disorder.
‘Hyperkinetic conduct disorder’ has its own ICD-10 code, and similar ‘combined’
codes exist in the Read coding system. Therefore, a patient with both disorders can
be simultaneously captured using a single Read/ICD-10 code. Whilst the relative risk
of CD/ODD was high in ADHD patients compared to comparators, the actual
numbers of patients affected were comparatively small (n=138, 2.7% of the ADHD
cohort). This was much lower than reported by some other studies in the literature.
For example, Jensen & Steinhausen (2015) examined a cohort of ADHD patients
diagnosed in Danish psychiatric hospitals, finding that 16.5% had a comorbid
diagnosis of CD/ODD. Steinhausen and colleagues (2006) found that 67% of patients
with ADHD had symptoms suggestive of ODD, and 46% had symptoms
corresponding to CD. It is likely that differences in setting and methodology
contribute at least in part to these different estimates.
118
The most prevalent comorbidity amongst the ADHD cohort in this study was
autism and autistic spectrum disorders. Just under 16% of all ADHD patients had
either a Read code or ICD-10 code denoting these disorders, compared to 1.9% of
comparators. When compared to other studies in the literature, this rate of co-
occurrence between ADHD and autism is not exceptionally high. As with CD/ODD,
ADHD and autism have overlapping symptoms. NICE guidance on the diagnosis of
autism in under 19s lists ADHD as a differential diagnosis and a potential
comorbidity of autism (National Institute for Health and Care Excellence 2011). As
such, screening for autism may increase individuals’ likelihood of being diagnosed
with ADHD. This ‘procedural’ reason may contribute to the relatively high
proportion of ADHD patients with autism compared to comparators, though other
neurobiological reasons could of course be at work (Rommelse et al. 2010).
Whilst it appears that all the comorbidities examined were significantly
more likely to arise alongside ADHD, it may be the case that they were simply more
likely to be detected and diagnosed in patients with ADHD. As per NICE guidance,
diagnosis and management of ADHD would generally involve contact with a
psychiatrist, child and adolescent mental health services (CAMHS) or paediatric
services (National Institute for Health and Care Excellence 2008). Such specialists
may be ideally placed to recognise and formally diagnose mental, behavioural and
neurological conditions in children, given their specialist expertise. Without ADHD,
comparators may have no reason to have contact with these specialist services, and
a higher proportion of comorbidities may go undiagnosed.
HES data, with its information relating to diagnoses noted in secondary care,
detected additional cases of comorbidity. However, with the possible exception of
epilepsy (in particular), CD/ODD and severe mental illness, the use of HES data did
not markedly increase the number of ‘comorbid’ patients identified. The fact this
study examined a paediatric population may have reduced the chances of
comorbidities being picked up in secondary care. Children and adolescents are
probably less likely to be admitted to a hospital than the average member of the
population, as they are less likely to have chronic illnesses associated with aging.
With this being the case, it is understandable that many patients with comorbidities
119
had no documented secondary care episode. In addition, the nature of the
comorbidities examined may have contributed to the modest detection of
comorbidities in secondary care. For example, depression, anxiety disorders and tic
disorder/Tourette’s are not in themselves disorders that would require a hospital
admission and inpatient care. The patients with ICD-10 codes for these disorders
likely had them noted at some point during a hospital stay related to some other
primary cause. If these comorbidities were present but irrelevant to the patient’s
management, it is questionable whether they would have been documented 100%
of the time.
It is perhaps understandable that epilepsy was the clear exception to the
general rule, with more patients detected using secondary care data. Epilepsy may
onset in childhood, and the seizures that characterise the disorder may necessitate
supportive treatment, observation or further investigation in a hospital setting
(National Institute for Health and Care Excellence 2013b). This would be especially
likely in the case of an initial seizure in a child/adolescent who had never exhibited
symptoms before. In addition, a proportion of patients who experience a suspected
epileptic seizure never go on to have another seizure in their lives (Epilepsy Society
2015). Such patients would not necessarily require any management of the disorder
to be carried out in primary care, and the disorder may not be formally
documented in their primary care records. These factors in combination may
contribute to 82% of the epilepsy patients identified having at least one secondary
care episode associated with an epilepsy ICD-10 code, and only 53% having a Read
code for the disorder.
6.4.2 Psychotropic prescribing in primary care
When psychotropic exposure in cases and comparators was compared, the
results suggested that a diagnosis of ADHD is linked with a generally increased risk
of receiving psychotropic treatment. The risk of receiving a prescription for any
psychotropic of interest between 1/1/2004 and 31/12/2013 was approximately
seven times higher amongst ADHD patients when compared to comparators [RR
120
7.14 (95% CI 6.66 – 7.65)]. For almost every drug class examined, the risk of
treatment was significantly higher in ADHD patients than comparators.
6.4.2.1 Anxiolytics and Hypnotics
The most marked difference between cases and comparators was observed
in relation to anxiolytic and hypnotic prescribing, in particular the prescribing of
melatonin. The risk of receiving a prescription for melatonin (a hypnotic) was 30
times higher as an ADHD patient. In all, 16% of all individuals in the ADHD cohort
received a prescription for melatonin during the study period. This compared to just
0.5% of the comparison cohort. Prescriptions within CPRD are not documented
along with their exact indications. As such, it cannot be definitively determined why
melatonin was being prescribed to such differing extents in children with ADHD and
comparators. However, likely reasons can be put forward for the relatively high
melatonin use amongst ADHD patients. Firstly sleep disorders are more common in
children with ADHD, owing to the symptoms of the disorder itself and/or its
treatments (methylphenidate, dexamfetamine, lisdexamfetamine and atomoxetine
all have the potential to cause insomnia as a side effect; Stein et al. 2012). In
addition, NICE has produced specific advice relating to the use of melatonin in
children and young people with ADHD (National Institute for Health and Care
Excellence 2013a). This provides information on the use of melatonin in children
with ADHD, despite the fact that melatonin is not licensed for use in children
(Paediatric Formulary Committee 2015). These factors probably contribute to the
extensive use of melatonin in ADHD patients relative to non-ADHD comparators.
The risk of receiving a benzodiazepine prescription was significantly higher
amongst ADHD patients compared to comparators, but to a much lower extent
than melatonin [RR 2.62 (95% CI 2.01 – 3.26)]. As benzodiazepines are generally
classed as anxiolytics and hypnotics, it may be that a higher prevalence of
anxiety/sleep disorders amongst patients with ADHD underlies this finding.
However, there is some evidence to suggest that benzodiazepines were not
primarily being used in the treatment of anxiety and sleeping problems in either the
ADHD or comparison cohort. As highlighted previously, clonazepam preparations,
121
rectal diazepam and buccal midazolam accounted for 73% of benzodiazepine
prescriptions in ADHD patients and 59% of benzodiazepine prescriptions in
comparators during the study period. Rectal diazepam and buccal midazolam are
licensed for use in the treatment of status epilepticus, and clonazepam is licensed
for use in paediatric epilepsy and seizures (Paediatric Formulary Committee 2015).
Furthermore, 73% of ADHD patients and 89% of comparators with a prescription for
these drugs had a documented Read/HES code indicating epilepsy during their
period of observation. With this being the case, it suggests that benzodiazepine use
in both cohorts was primarily related to the treatment of epilepsy rather than
anxiety or sleep disorders.
6.4.2.2 Antipsychotics
The comparison of antipsychotic prescribing in cases and comparators
produced an interesting discrepancy. The risk of receiving a first generation
antipsychotic was only slightly higher in ADHD patients compared to comparators,
and the difference in risk was not statistically significant [RR 1.30 (0.96 – 1.76)].
Though referred to as ‘antipsychotics’, many first generation agents have other
applications outside the treatment of psychotic conditions (particularly in the
treatment of nausea and vomiting). For example, prochlorperazine is a first
generation antipsychotic but is solely licensed for use as an anti-emetic in children
and adolescents (Paediatric Formulary Committee 2015). As such, 79% of all first
generation prescriptions in the comparison cohort and 29% of those in the ADHD
cohort may have been issued for the treatment of nausea and vomiting rather than
for the control of psychotic symptoms. The comparable risk of receiving a first
generation antipsychotic both cohorts may (at least in part) reflect that nausea and
vomiting is no more common amongst ADHD patients than children without the
disorder.
In marked contrast, the risk of receiving a second generation antipsychotic
was over 29 times higher in ADHD patients compared to comparators [RR 29.48
(95% CI 23.25 – 37.40)], a statistically significant difference in risk. Unlike first
generation antipsychotics, second generation agents such as risperidone,
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aripiprazole, quetiapine and olanzapine are exclusively used for the treatment of
mental and behavioural disorders in children and adolescents (Paediatric Formulary
Committee 2015). This observation arguably strengthens the hypothesis that ADHD
increases the risk of receiving psychotropic drugs in the treatment of mental and
behavioural disorders specifically, as a prescription for a second generation agent is
unlikely to be for anything else.
6.4.2.3 Antidepressants
The risk of receiving an antidepressant of any class was significantly higher
amongst ADHD patients. Selective serotonin reuptake inhibitors were the most
commonly prescribed class of antidepressants in both cohorts. SSRIs are almost
exclusively used for depression and related mental disorders in children (including
obsessive compulsive disorder and anxiety disorders; Paediatric Formulary
Committee, 2015). As such, treatment with an SSRI is likely to indicate treatment
for a mental or behavioural disorder. The proportion of cases and controls treated
with SSRIs was relatively modest (3.3% and 0.9% respectively), but the risk of
treatment was significantly higher in ADHD patients [RR 3.77 (95% CI 3.16 – 4.50)].
The use of SSRIs in paediatric patients with depression is controversial; they have
been linked with an increased risk of suicidal ideation in under 18s (Lu et al. 2014).
Despite this they remain the first-line agents for children who require
pharmaceutical intervention for depression, though only fluoxetine is specifically
licensed for use in under 18s (Paediatric Formulary Committee 2015). Given this, it
is perhaps unsurprising that fluoxetine was the most commonly prescribed SSRI in
both cases and comparators.
Tricyclic antidepressants were less commonly prescribed than SSRIs in both
cohorts, though the risk of receiving a tricyclic remained significantly higher as an
ADHD patient [RR 1.68 (95% CI 1.24 – 2.28)]. Unlike SSRIs, tricyclic antidepressants
have a heterogeneous range of uses in children, including the treatment of
neuropathic pain and nocturnal enuresis. Coupled with this, the British National
Formulary for Children (BNFC) specifically states that tricyclics are ‘not effective’
and ‘should be avoided for the treatment of depression in children’ (Paediatric
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Formulary Committee 2015). Taken together, it is fair to say that a prescription for a
tricyclic antidepressant in a paediatric patient cannot be assumed to be for a
mental or behavioural disorder, let alone depression specifically. However, their
prescribing patterns potentially give some insight into psychotropic use in ADHD.
The most commonly prescribed tricyclic in the comparison cohort was amitriptyline,
prescribed to 71% of those treated with a tricyclic antidepressant. In contrast,
imipramine was the most commonly prescribed tricyclic amongst ADHD patients,
prescribed to 51% of individuals who received a tricyclic. Though not licensed for
the indication, there is some evidence to support the use of imipramine in the
treatment of ADHD (Scottish Intercollegiate Guidelines Network 2009). It is briefly
mentioned in NICE’s guideline on the treatment of ADHD in children and
adolescents (National Institute for Health and Care Excellence 2008), and the BNFC
gives dosing information relating to the use of imipramine in the treatment of
ADHD (Paediatric Formulary Committee 2015). The fact that imipramine was used
more extensively in the ADHD cohort may suggest that it is be being used to some
appreciable extent in the treatment of ADHD in UK children. However, the low
number of patients involved (25 ADHD patients received imipramine) and the
possibility of imipramine being prescribed for another indication (such as nocturnal
enuresis) would make this a questionable assertion.
6.4.3 Timing of psychotropic prescribing
ADHD patients were significantly more likely to receive a psychotropic
prescription in the year after their ADHD diagnosis than the year preceding that
date [rate ratio 3.13 (95% CI 2.67 – 3.68)]. This applied to psychotropics in general,
and to several specific categories of psychotropic drug (second generation
antipsychotics, SSRIs and melatonin). This finding was not replicated in the
comparison cohort. This suggested that a diagnosis of ADHD did in some way
increase the likelihood of subsequent treatment with these agents. In the case of
melatonin, evidence can be readily offered to support this hypothesis. As addressed
previously, melatonin is not licensed for use in children. However, NICE has
produced advice specifically relating to its use in ADHD patients with sleep
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problems. As such, a formal diagnosis of ADHD may reasonably increase a child’s
chances of being prescribed the drug.
In the case of antipsychotics, the picture is less clear. In the UK, no
antipsychotic is licensed for use in the treatment of ADHD, and NICE has specifically
recommended that they are not used in the treatment of the disorder (National
Institute for Health and Care Excellence 2008). However, Marston et al. (2014)
found that a sizeable minority of patients prescribed antipsychotics in UK primary
care had no documented diagnosis of psychotic illness but did have a diagnosis of
ADHD. In the United States Birnbaum et al. (2013) concluded that that “despite the
lack of empirical support and FDA approval, adjunctive antipsychotic use in youth
with ADHD appears to be the fastest growing indication (for antipsychotic use)”
(Birnbaum et al. 2013, p.2). It could therefore be speculated that some
antipsychotic use in the ADHD cohort was for the treatment of ADHD symptoms
directly. This in turn could explain why antipsychotic prescribing was more common
in ADHD patients in the year following their diagnosis than the year before. Relating
SSRI use to a diagnosis of ADHD is more difficult. As with antipsychotics, no SSRI is
licensed for the treatment of ADHD. Unlike antipsychotics, there is little evidence
that SSRIs are being used on an unlicensed basis in the treatment of ADHD. As such
it seems unlikely that the increase in SSRI prescribing following ADHD diagnosis
related to the treatment of ADHD directly. So whilst patients were significantly
more likely to receive SSRI treatment in the year following ADHD diagnosis, it is not
clear what role (if any) a diagnosis of ADHD had in the higher SSRI prescribing.
Though a diagnosis of ADHD appeared to significantly increase patients’
likelihood of subsequent psychotropic treatment, this statement must be made
with caution. From the data available it was impossible to conclusively establish if
the increased risk of psychotropic treatment was related to the ADHD diagnosis, or
to some other unrelated event. In addition, it is possible that some confounding
factor played a role in the increased prescribing observed following ADHD
diagnosis. For example, the simple fact patients would be older in the year
following a particular date than they were in the year before it may have increased
their chances of being prescribed a particular drug. Some drugs are only licensed
125
for use above a certain age, and such licensing restrictions would be expected to
influence prescribing decisions made by GPs. Therefore simply reaching the
relevant ‘licensed’ age would potentially increase an individual’s chance of receiving
that drug. However, the impact of this potential confounding factor would seem to
be minimal. In contrast to ADHD patients, comparators were no more likely to
receive any form of psychotropic in the year after their index date than they were
in the year before this date.
6.5 Conclusion
ADHD was associated with a significantly increased risk of mental,
behavioural and neurological comorbidity. Individuals who received a diagnosis of
ADHD between 1/1/2004 and 31/12/2013 were significantly more likely to receive a
comorbid diagnosis during this period than age, gender and general practice-
matched comparators who remained free of ADHD [RR 3.59 (95% CI 3.40 – 3.79)];
every comorbidity examined was significantly more likely to occur in ADHD
patients. The most prevalent comorbidity amongst ADHD patients was autism,
though ADHD patients had the highest relative risk of conduct
disorder/oppositional defiant disorder compared to age, gender and general
practice-matched comparator patients [RR 15.72 (95% CI 12.02 – 20.57)]. With
regard to psychotropic exposure, ADHD patients had significantly higher exposure
to second generation antipsychotics, antidepressants and anxiolytics/hypnotics. Of
all the drug groups examined, ADHD patients had the highest relative risk of being
prescribed melatonin compared to non-ADHD comparators [RR 30.34 (95% CI 26.49
– 34.75)]. In the ADHD cohort, psychotropic exposure was significantly more likely
to occur in the year following ADHD diagnosis than in the year preceding diagnosis
[RR 3.13 (95% CI 2.67 – 3.68)]; whether this prescribing was related to the disorder
was unclear from the available data. However, non-ADHD comparators were
equally likely to receive a psychotropic in the year before, and the year after, their
index date [RR 1.10 (95% CI 0.94 – 1.30)].
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Chapter 7
Fracture risk in children and
adolescents with ADHD: A cohort
study using linked CPRD and HES
data
127
7.1 Background
Accidental injuries are a significant cause of morbidity in children and
adolescents (Dalsgaard et al. 2015); fractures alone account for up to 25% of all
accidental injuries in this population (Cooper et al. 2004). Aside from the medical
impacts for those affected, fractures are associated with significant disruption to
schooling and parental time off work (Morris et al. 2006). Fractures as a whole cost
the National Health Service over £1.7 billion pounds per annum (National Institute
for Health Research 2015), and the treatment of paediatric fractures is associated
with significant financial costs (Gulati et al. 2012). In the UK, the epidemiology of
fracture in children has been explored using CPRD data (Moon et al. 2016).
Between 1988 and 2012 the rate of fracture amongst under 18s was calculated to
be 137 events per 10,000 person years at risk (pyar). The incidence of fracture was
found to be higher in males than females, and regional variations in fracture
incidence were observed. Fractures involving the forearm were found to constitute
29% of all childhood fractures; the most common fracture site was the radius/ulna,
followed by the carpal bones and humerus respectively.
It has been observed that certain types of injury are more prevalent in
individuals with ADHD, or who go on to be diagnosed with ADHD (Maxson et al.
2009; Keenan et al. 2008; DiScala et al. 1998), and there is increasing evidence to
suggest that ADHD is a significant risk factor for accidental injury. Pre-school
children with ADHD exhibit behaviours likely to increase their likelihood of
sustaining injury (Byrne et al. 2003). At the opposite end of the age scale, young
adults with ADHD have a higher risk of being involved in road traffic accidents
compared to non-ADHD comparators (McCarthy et al. 2012). A recent Danish study
involving 4557 patients with ADHD found that they were twice as likely to sustain
an accidental injury than comparable individuals without the disorder (Dalsgaard et
al. 2015). However, few descriptive details were provided regarding the nature of
the accidental injuries sustained. It would seem logical that the inattentive,
impulsive and hyperactive behaviours that characterise ADHD could all increase the
likelihood of sustaining an accidental fracture. However, relatively few papers have
examined the link between ADHD and fracture risk specifically. In the United States
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Merrill et al. (2009) examined insurance claims made by employees of the Church
of Jesus Christ of Latter-day Saints, their spouses and dependent children. The
study focused on claims resulting from accidental injuries, and the sample
contained 2186 individuals with ADHD. Though the number of ADHD patients who
sustained a fracture during the study’s observation period was relatively low
(n=117), their likelihood of sustaining a fracture was significantly higher than
individuals unaffected by ADHD. A study from Taiwan used the Longitudinal Health
Insurance Database (LHID) to compare fracture incidence amongst children with
ADHD and a cohort of matched comparators. The incidence of fracture among the
ADHD cohort was 198 instances per 10,000 person years at risk; fracture was 1.32
(hazard ratio/HR; 95% CI 1.17 – 1.49) times as likely in the ADHD cohort, relative to
the comparison cohort (Chou et al. 2014). A separate study using the LHID reported
similar findings (Guo et al. 2015). Outside Taiwan, studies comparing fracture rates
amongst ADHD patients and matched comparators appear to be sparse. To my
knowledge, no such study has yet been conducted in the UK.
7.1.1 Aims
The aim of this study was to establish if patients diagnosed with ADHD
between 1/1/2004 and 31/12/2013 were more likely to sustain accidental fractures
during that period than matched comparators who remained free of ADHD. This
established if patients who developed ADHD had a relatively higher risk of
sustaining accidental fractures than individuals who did not develop the disorder.
The fractures sustained by individuals in each cohort were described, and the
relative risk of fracture in each cohort was determined. By comparing the types of
fractures sustained by both cohorts, it could be established if certain types of
fracture were particularly likely amongst patients who developed ADHD, relative to
matched comparators who remained free of the disorder. The study also
determined rates of fracture in patients following diagnosis with ADHD, and
established if a prior diagnosis of ADHD was associated with an increased risk of
subsequent fracture in children and adolescents.
7.2 Methods
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7.2.1 Study population
The study cohorts consisted of 5111 children and adolescents diagnosed
with ADHD between 1/1/2004 and 31/12/2013, and 49,489 comparator patients.
All ADHD patients had their incident diagnosis of ADHD documented between
1/1/2004 and 31/12/2013, but not all these patients received a licensed ADHD
medication from their GP during this period. Comparators were not diagnosed with
ADHD, and did not receive a medication licensed for ADHD prior to 31/12/2013.
Comparator patients were matched on gender, year of birth and general practice;
each member of the ADHD cohort was matched with up to 10 comparators.
Matching according to these characteristics was relevant as gender, age and the UK
region in which a person resides may all have some role in determining their risk of
fracture (Curtis et al. 2016). Comparators were required to have at least one
documented consultation with their GP in the year that their matched case was
diagnosed with ADHD. This was referred to as their index date. In ADHD patients,
their date of diagnosis served as their index date. CPRD primary care data was
obtained for all individuals, and integrated HES data was obtained for all patients
who had been admitted to an NHS hospital in England during the study period
(1/1/2004 – 31/12/2013).
7.2.2 Identification of fractures
Patient’s electronic healthcare records were screened for fractures, or
follow-up care relating to fractures, that occurred during the study period. The
exact observation period for each individual varied, and this observation time could
be determined for all individuals. Patients were observed from the latest point of
the following: their registration date with their CPRD general practice, the date on
which their general practice attained CPRD’s data quality standards (the practice
‘up to standard’ date), the study start date (1/1/2004). Patients were then observed
until the earliest point of the following: the date at which they left their CPRD
general practice (if applicable), the date of their death (if applicable), January 1st of
the year they turned 19 years of age, the last date on which data was transferred
from their practice to CPRD, the study end date (31/12/2013).
130
Bone fracture and related follow-up care was identified by the presence of
Read codes (in patients’ CPRD records), and ICD-10 codes (in patients’ HES records,
where present). Most children who sustain fractures do so as a result of accidents;
falls, motor vehicle crashes, or other non-abusive trauma (Kemp et al. 2008; Rennie
et al. 2007; Mathison & Agrawal 2010). However certain Read codes and ICD-10
codes specifically denote fractures stemming from underlying pathology (such as
osteoporosis or neoplastic disease), or a specified, non-accidental cause (such as
surgical fractures, cough fractures and birth injuries). Such Read codes were
excluded from analysis, along with codes denoting spontaneous fractures and stress
fractures (which would generally not be the result of acute, accidental trauma). A
full list of codes used in the identification of fracture are presented in Appendix 6.
7.2.3 Fracture risk amongst patients who developed ADHD during observation, and
matched comparators
An initial analysis established if children and adolescents diagnosed with
ADHD between 1/1/2004 and 31/12/2013 were more likely to sustain fractures
during this period than individuals who remained free of ADHD. Any individual with
a fracture (or follow-up care for fracture) recorded during their period of
observation (either before or after their index date) was counted as having
sustained a fracture. The number of ADHD patients and comparators who sustained
a fracture/received follow-up care for fracture was calculated. The relative risk of
fracture amongst ADHD patients and non-ADHD comparators was illustrated using
risk ratios (RR) with 95% confidence intervals. The prevalence of fracture/follow-up
care for fracture was also presented as the number of cases per 10,000 person-
years [pyar] of observation time in both cohorts. The most common fractures
amongst each cohort were determined. To assess if fractures were more likely to be
detected using primary or secondary care data, the number and proportion of
individuals with a Read code and/or an ICD-10 code for fracture was presented.
7.2.4 Pre-existing ADHD and fracture risk
The number of ADHD patients/comparators who sustained a fracture
following their index date, and before the end of their observation period, was also
131
determined. The rate of fracture in both cohorts was presented as the number of
cases per 10,000 person-years [pyar] of observation time. Each member of the
ADHD cohort was matched with up to ten comparators on the basis of gender, year
of birth and general practice. Each group of matched individuals was referred to as
a ‘set’. To account for this matching, a stratified Cox regression (stratified by set)
was performed to estimate the impact of pre-existing ADHD on individuals’ risk of
sustaining a fracture during observation. Hazard ratios (HR) with 95% CI were
calculated. Statistical significance was set at p < 0.05, and all statistical analyses
were performed using Stata version 13 (StataCorp, College Station, Texas, United
States).
7.3 Results
7.3.1 Fracture risk amongst patients who developed ADHD during observation, and
matched comparators
The characteristics of the two cohorts studied are shown in Table 14. As
shown in table 15, 20.1% of patients in the ADHD cohort (n = 1029) had a code
relating to fracture documented in their electronic healthcare record between
1/1/2004 and 31/12/2013. This compared to 17.1% of comparators (n = 8461), and
constituted a significantly higher risk of fracture amongst the ADHD cohort [RR 1.18
(95% CI 1.11 – 1.25)]. In both cohorts there was extensive use of codes denoting
fractures of unspecified body regions, or follow-up care relating to fractures.
However, in both the ADHD and comparison cohort, fractures involving the upper
limbs were found to be the most common type of fracture sustained during the
study period. The risk of sustaining an upper limb fracture in general was
significantly higher amongst ADHD patients [RR 1.17 (95% CI 1.09 – 1.27)], and the
difference in fracture risk between cases and comparators was highest in relation to
fractures of the wrist and hand [RR 1.30 (95% CI 1.15 – 1.47)]. Lower limb fractures
were somewhat less common than upper limb fractures, affecting 3.8% of patients
in the ADHD cohort (n = 196) and 2.9% of comparators (n = 1431) between
1/1/2004 and 31/12/2013; the risk of sustaining a lower limb fracture was
significantly higher as an ADHD patient [RR 1.33 (95% CI 1.15 – 1.54)].
132
During the study period, no fractures involving the neck were documented
amongst the ADHD cohort, and only five comparators had a Read or ICD-10 code
denoting a neck fracture. Fractures involving the skull or facial bones were also
relatively rare in both cohorts. However, ADHD patients had a significantly higher
risk of sustaining these fractures [RR 1.39 (95% CI 1.08 – 1.80)]. Fractures involving
the trunk region accounted for the lowest proportion of fractures in both cohorts.
ADHD patients had a significantly higher risk of fractures involving the ribs, sternum
and thoracic spine than non-ADHD comparators [RR 3.23 (95% CI 1.17 – 8.88)].
However, the actual number of individuals sustaining such fractures was low and
the confidence intervals associated with this finding were relatively wide.
Table 14: Cohort characteristics (cases and comparators)
Cohort ADHD cohort (n = 5111) Comparator cohort (n = 49,489)
Description Individuals diagnosed with incident ADHD between 1/1/2004 and
31/12/2013
Individuals with no diagnosis of ADHD, or exposure to a licensed treatment for
the disorder, prior to 31/12/2013
Gender
Male 4174 (81.67%) 40,315 (81.46%)
Female 937 (18.33%) 9174 (18.54%)
Observation time
Median observation time per subject, days [IQR]
2922 days [IQR 2093 - 3650] 2821 days [IQR 1847 – 3650]
Total observation time between 1/1/2004-31/12/2013
(person-years)
38,304 353,888
Year of birth
1986 & 1987 6 (0.12%) 60 (0.12%)
1988 11 (0.22%) 107 (0.22%)
1989 20 (0.39%) 200 (0.40%)
1990 44 (0.86%) 429 (0.87%)
1991 86 (1.68%) 835 (1.69%)
1992 123 (2.41%) 1196 (2.42%)
1993 186 (3.64%) 1784 (3.60%)
1994 214 (4.19%) 2074 (4.19%)
1995 234 (4.58%) 2276 (4.60%)
1996 261 (5.11%) 2526 (5.10%)
1997 368 (7.20%) 3513 (7.10%)
1998 431 (8.43%) 4199 (8.48%)
1999 394 (7.71%) 3747 (7.57%)
2000 411 (8.04%) 3942 (7.97%)
2001 392 (7.67%) 3740 (7.56%)
2002 365 (7.14%) 3490 (7.05%)
2003 412 (8.06%) 4024 (8.13%)
2004 368 (7.20%) 3577 (7.23%)
2005 294 (5.75%) 2884 (5.83%)
2006 221 (4.32%) 2188 (4.42%)
2007 146 (2.86%) 1459 (2.95%)
2008 73 (1.43%) 729 (1.47%)
2009 31 (0.61%) 310 (0.63%)
2010 12 (0.23%) 120 (0.24%)
2011 & 2012 8 (0.16%) 80 (0.16%)
Region of general practice
North East 128 (2.50%) 1256 (2.54%)
North West 789 (15.44%) 7522 (15.20%)
Yorkshire & The Humber 120 (2.35%) 1196 (2.42%)
East Midlands 169 (3.31%) 1664 (3.36%)
West Midlands 496 (9.70%) 4820 (9.74%)
East of England 751 (14.69%) 7293 (14.74%)
South West 508 (9.94%) 4998 (10.10%)
South Central 687 (13.44%) 6707 (13.55%)
London 533 (10.43%) 5120 (10.35%)
South East Coast 930 (18.20%) 8913 (18.01%)
Cell counts less than 5 not specified in line with CPRD reporting requirements; 1986/1987 & 2011/2012 figures were combined for this reason
133
Table 15: Prevalence and relative risk of fracture amongst ADHD patients and non-ADHD comparators between 1/1/2004 and 31/12/2013
Individuals with at least one Read or
ICD-10 code indicating:
ADHD cohort (% of cohort)
Prevalence (cases per
10,000 pyar)
Comparison cohort (% of
cohort)
Prevalence (cases per
10,000 pyar)
Risk ratio (cases v
comparators) [95% CI]
Any fracture 1029 (20.13%)
268.64 8461 (17.10%)
239.09 1.18 [1.11 -1.25]
Head, neck or facial fracture
67 (1.31%)
17.49 466 (0.94%)
13.17 1.39 [1.08 – 1.80]
Fracture of skull or facial bones
67 (1.31%)
17.49 461 (0.93%)
13.03 1.41 [1.09 – 1.82]
Fracture of neck 0 (0%)
0 5 (0.01%)
0.14 N/A
Head or neck fracture
(specific bone/ location
unspecified)
0 (0%)
0 0 (0%)
0 N/A
Trunk fracture 8 (0.16%)
2.09 51 (0.10%)
1.44 1.51 [0.72 – 3.20]
Fracture of rib(s), sternum or thoracic
spine
omitted 1.31 15 (0.03%)
0.42 3.23 [1.17 – 8.88]
Fracture of lumbar spine or pelvis
omitted <1.31 34 (0.07%)
0.96 0.85 [0.26 – 2.78]
Spine fracture (specific bone/
location unspecified)
0 (0%)
0 6 (0.01%)
0.17 N/A
Upper limb fracture
623 (12.19%)
162.65 5138 (10.38%)
145.19 1.17 [1.09 – 1.27]
Fracture of shoulder or upper arm
115 (2.25%)
30.02 1014 (2.05%)
28.65 1.10 [0.91 – 1.33]
Fracture of forearm 275 (5.38%)
71.79 2445 (4.94%)
69.09 1.09 [0.96 – 1.23]
Fracture of wrist or hand
269 (5.26%)
70.23 2002 (4.05%)
56.57 1.30 [1.15 – 1.47]
Upper limb fracture (specific
bone/location unspecified)
50 (0.98%)
13.05 415 (0.84%)
11.73 1.17 [0.87 – 1.56]
Lower limb fracture
196 (3.83%)
51.17 1431 (2.89%)
40.44 1.33 [1.15 – 1.54]
Fracture of femur (hip or thigh)
17 (0.33%)
4.44 131 (0.26%)
3.70 1.26 [0.76 – 2.08]
Fracture of lower leg or ankle
95 (1.86%)
24.80 727 (1.47%)
20.54 1.27 [1.02 – 1.56]
Fracture of foot, except ankle
78 (1.53%)
19.84 555 (1.12%)
15.68 1.36 [1.08 – 1.72]
Lower limb fracture (specific bone/
location unspecified)
21 (0.41%)
5.48 91 (0.18%)
2.57 2.23 [1.39 – 3.59]
Other fracture (unspecified
location) or follow-up relating to
fracture
504 (9.86%)
131.58 4232 (8.55%)
119.59 1.15 [1.06 – 1.26]
Cell counts less than 5 not specified in line with CPRD reporting requirements
134
Table 16: Fracture ascertainment using primary and secondary care data
Fracture type
Total individuals with either a Read code or an ICD-10 code for fracture,
or both
Individuals with a Read
code for fracture only
Additional individuals with
a fracture identified using
HES data (% of total)
Head, neck or facial fracture
533 315 218 (40.90%)
Trunk fracture 59 38 21 (35.59%)
Upper limb fracture 5761 5097 664 (11.53%)
Lower limb fracture 1627 1442 185 (11.37%)
Other fracture (unspecified location) or follow-up relating to
fracture
4736 4716 20 (0.42%)
As shown in Table 16, combining primary care data with secondary care data
identified additional individuals who sustained a fracture during the study period. In
the case of head, neck and facial fractures, over 40% of individuals who sustained
these fractures would not have been detected without the introduction of HES data
(n = 218). A comparable proportion of individuals with a trunk fracture were
detected through the use of HES data (35.6%, n = 21). Individuals with a fracture
involving an unspecified body part, or who received follow-up care relating to a
fracture, were far less likely to be identified using secondary care data. Of the 4736
individuals with a code for an unspecified fracture/follow-up care, only 0.4% were
identifiable using secondary care data alone.
7.3.2 Pre-existing ADHD and fracture risk
As shown in table 17, 9.2% of the ADHD cohort sustained a fracture during
observation, and following their index date (ie following their ADHD diagnosis
date). This compared to just under 8% of comparators. The rate of fracture amongst
patients with pre-existing ADHD (259 cases per 10,000 pyar) was higher than that
amongst comparators (225 cases per 10,000 pyar). Socioeconomic status may play
a role in a patients’ risk of fracture (Ramaesh et al. 2015). After adjusting for
postcode-level IMD, a prior diagnosis of ADHD constituted an independent risk
135
factor for fracture. Compared to the comparison cohort, members of the ADHD
cohort were HR 1.17 (95% CI 1.06 – 1.30) times as likely to sustain a fracture
following their index date.
Table 17: Rate of fracture following index date in the ADHD and comparison cohorts
Cohort
Individuals who
sustained a
fracture
following index
date*
(% of cohort)
Person-years
at risk
between index
date and end
of observation
Rate of
fracture
post-index
date
(per 10,000
pyar)
Crude hazard
ratio [95% CI]
Adjusted hazard ratio*
[95% CI]
Comparator
cohort
3932 (7.95%) 174,879 224.84 1.00 (Ref) 1.00 (Ref)
ADHD
cohort
470 (9.20%) 18,151 258.94 1.18 [1.08 -1.30]
1.17 [1.06 –1.30]
^Specific fractures only; codes denoting follow-up care for fracture excluded *Adjusted for postcode-level index of multiple deprivation quintile
7.4 Discussion
Patients diagnosed with ADHD between 1/1/2004 31/12/2013 were
significantly more likely to sustain a fracture during that period than comparators who
did not develop the disorder [RR 1.18 (95% CI 1.11 – 1.25)]. A prior diagnosis of ADHD
appeared to be an independent risk factor for subsequent fracture. The rate of fracture
amongst individuals with a prior diagnosis of ADHD was significantly higher than
that amongst comparators without the disorder [HR 1.17 (95% CI 1.06 – 1.30)].
Taken together, these findings suggest that children and adolescents with ADHD, or
who are subsequently diagnosed with ADHD, have a significantly higher risk of
accidental fractures than unaffected children and adolescents.
The rate of fracture among patients with pre-existing ADHD was 259 cases per
10,000 person years; this compared to 225 cases per 10,000 person years in
comparators. Both rates were notably higher than the incidence of fracture in UK
children and adolescents determined by Moon et al. (2016). That study, examining
CPRD data covering the years 1988-2012, determined the incidence of fracture
amongst under 18s to be 137 events per 10,000 pyar. Despite this contrast, the
incidence of fracture reported by the current study was not implausibly high
compared to other studies of fracture in children. Brudvik & Hove (2003) observed
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a fracture incidence of 245 instances per 10,000 pyar in Norwegian children and
adolescents; a similar fracture rate was reported in Swedes aged 0-16 years of age
(Tiderius et al. 1999). It must also be noted that the earlier UK study used just one
data source (CPRD) in the identification of fracture patients, whereas the current
study used two (CPRD and HES). Using two data sources increased the number of
fracture patients identified, and would have contributed to the higher incidence of
fracture reported by this study. In addition, this study examined fracture incidence
in a cohort of ADHD patients and matched comparators. This meant that both
cohorts contained a higher proportion of males than would be found in a ‘general’
population sample, given that ADHD is significantly more prevalent in males than
females. As demonstrated by this and other studies, being male is a known risk
factor for childhood fracture (Moon et al. 2016; Hedström et al. 2010); the
overwhelmingly male composition of this study’s cohorts would be expected to
produce a higher rate of fractures than a more ‘gender-balanced’ cohort.
Though few previous studies have focused on fractures as an outcome, the
study’s findings add to a growing body of evidence that ADHD is associated with a
higher rate of accidental injury (Shilon et al. 2012; Dalsgaard et al. 2015). The
current study design cannot conclusively explain the mechanism linking ADHD and
accidental fracture. However, a general theory can be offered based on the core
behavioural characteristics of individuals with ADHD – hyperactivity, impulsivity and
inattentiveness. Children with ADHD often exhibit hyperactive behaviour; running
around, climbing and generally engaging in high levels of physical activity. Such
activity is arguably more likely to lead to falls and other accidents than more
sedentary behaviour. The impulsivity and inattentiveness exhibited by individuals
with ADHD potentially augments this risk of injury. Children and adolescents with
the disorder may give less thought to the consequences of their actions, and
engage in activities with a high risk of accidental injury. By not devoting the
required level of attention to the activities they are engaged in (such as riding a
bike, or crossing a road), individuals with ADHD may put themselves at a higher risk
of accidental injuries such as fractures.
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Returning to the current study, the Cox regression model allowed the
impact of pre-existing ADHD on fracture risk to be determined. The two cohorts
that were compared were matched on the basis of gender, general practice
location and year of birth; after adjusting for socioeconomic status, individuals in
the ADHD cohort were significantly more likely to sustain an accidental fracture
following their index date than those in the comparison cohort [HR 1.17 (95% CI
1.06 – 1.30)]. This would seem to demonstrate that ADHD constitutes an independent
risk factor for fractures in children registered with general practices in England. A
similar study conducted using Taiwanese healthcare data found ADHD to have a
greater impact on fracture risk [HR 1.32 (95% CI 1.17 – 1.49)], though that study
adjusted for a somewhat different range of confounders (such as parental
occupation, and urbanisation level; Chou et al. 2014). Making a direct comparison
between these studies is difficult. The sample of children examined by this study
could be different to the sample drawn from the Taiwanese Longitudinal Health
Insurance Database in any number of ways relevant to fracture. Genetic or lifestyle
differences (for example) could give children in England and Taiwan different
baseline levels of fracture risk; this in turn might affect the apparent contribution of
ADHD to subsequent fracture risk.
Fractures involving the forearm and wrist constitute the most common
fractures observed in UK under 18s (Moon et al. 2016). It was therefore unsurprising
that fractures of the wrist, forearm and hand represented the most common types of
fracture in both cohorts examined. The risk of sustaining an upper limb fracture was
found to be significantly higher amongst ADHD patients than comparators, a finding
that had been reported previously by both Taiwanese and Turkish studies (Chou et
al. 2014; Erdogan et al. 2014). Fractures involving the wrist, forearm and hand are
most commonly associated with an accidental fall (NHS Choices 2015; Hedström et
al. 2010); the finding that ADHD patients were at a significantly higher risk of such
fractures may reflect that they are at higher risk of such accidents. There is some
evidence that sustaining an upper limb fracture as a child can increase the
likelihood of a fragility fracture in later life (Amin et al. 2013; Jerrhag et al. 2016). As
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such, the impacts of these fractures on children with ADHD, and on healthcare
systems, may be felt long into their adulthood.
In common with upper limb fractures, lower limb fractures in children and
adolescents are generally the result of falls and other accidents (Loder et al. 2006;
Kemp et al. 2008; Joeris et al. 2014). Though less prevalent than upper limb
fractures, lower limb fractures were still significantly more common among ADHD
patients than comparators. Again, this replicated the findings of the earlier
Taiwanese study (Chou et al. 2014). Fractures involving the head, neck and face
were relatively rare in both cohorts. Just 0.9% of comparators and 1.3% of ADHD
patients had a Read code or ICD-10 code denoting these fractures. However, this
still represented a significantly higher risk of fracture in ADHD patients compared to
non-ADHD comparators [RR 1.39 (1.08 – 1.80)]. A recent meta-analysis concluded
that there was significant evidence of an association between ADHD and mild
traumatic injuries to the brain (Adeyemo et al. 2014), and the current study’s
findings would appear to support this. However, it must be noted that injuries this
study classified as involving the head, neck and face may well have included injuries
that were not associated with any sort of brain trauma.
7.5 Conclusion
Individuals who were diagnosed with ADHD between 1/1/2004 and
31/12/2013 were significantly more likely to sustain a fracture during that period
than individuals who did not develop ADHD [RR 1.18 (95% CI 1.11 – 1.25)]. The
most common fractures observed in both cohorts were upper limb fractures.
During the period studied, 10.4% of comparators (n = 5138) and 12.2% of ADHD
patients (n = 623) sustained an upper limb fracture [RR 1.17 (95% CI 1.09 – 1.27)]. A
prior diagnosis of ADHD constituted an independent risk factor for subsequent
fracture [adjusted HR 1.17 (95% CI 1.06 – 1.30)]. Given that fractures can have
significant impacts on individuals, their families, and healthcare systems, it is
important that the role of ADHD in fracture risk is clarified and potential mitigating
strategies developed.
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Chapter 8
Discussion
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8.1 Discussion
This chapter summarises and discusses the key findings of this thesis; their novelty
and their possible impacts on practice are considered. In addition, the strengths
and potential limitations of the current work are addressed, and suggestions for
future work are proposed.
8.1.1 Chapter 4: ADHD in the United Kingdom: Regional and Socioeconomic
Variations in Incidence Rates Amongst Children and Adolescents (2004-2013)
8.1.1.1 Incidence of ADHD in children and adolescents 2004-2013
The study aimed to answer the fundamental question relating to ADHD in
the UK: were diagnostic rates amongst children and adolescents increasing,
decreasing or constant? Concerns had been raised that ADHD was being over-
diagnosed in the young (Thomas et al. 2014); this study aimed to establish if this
was evidenced by an increase in annual diagnostic rates over the last decade. The
ten-year period chosen for study was the years 2004 through to the end of 2013,
the most recent point for which data was available. This period had the potential to
be highly informative. It covered the five years leading up to, and the five years
following, the release of NICE’s first ever guidance on the diagnosis and
management of ADHD (in September 2008). As such, the study could assess
diagnostic rates over a decade, and discern if any noticeable changes had occurred
in the years following the publication of NICE’s guidance on the disorder.
Earlier population studies had suggested that ADHD was an increasingly
prevalent diagnosis amongst young people in the United Kingdom (Holden et al.
2013; McCarthy et al. 2012). However, the evidence for rising incidence rates was
not definitive. Many studies proposing that ADHD incidence was on the rise had
based their conclusions (either wholly or in part) on increasing numbers of
prescriptions being issued for licensed ADHD medications (McCarthy et al. 2012;
Beau-Lejdstrom et al. 2016; Renoux et al. 2016). In other words, they determined
that annual increases in the number of prescriptions issued for ADHD, or increases
in the number of patients receiving licensed ADHD drugs, reflected annual increases
in the number of patients being diagnosed with ADHD. However, prescribing
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prevalence is not an exact proxy for diagnostic incidence. Pharmaceutical treatment
is not necessary or recommended in all children and adolescents diagnosed with
ADHD (National Institute for Health and Care Excellence 2008). Non-pharmaceutical
interventions such as behavioural therapies may be employed as an alternative to
drugs, or may be used in children and adolescents with ADHD before commencing
pharmaceutical treatment. Identifying newly-diagnosed ADHD patients by the
timing of their first prescription would obviously not detect untreated patients; it
may also give a misleading impression of when patients were diagnosed with the
disorder. As such, determining ADHD diagnostic rates for a particular year by
analysing the number of individuals receiving ADHD medications during that year is
potentially inaccurate.
By identifying individuals with a diagnosis of ADHD documented in their
records (in the form of a diagnostic Read code) and identifying when these
diagnoses were first recorded, the current study sought to avoid the uncertainties
of using prescriptions as a surrogate measure of ADHD diagnosis. Using this
methodology, the annual incidence of ADHD amongst children and adolescents was
found to be relatively stable between the years 2004 and 2013. Though incidence
rates were highest in the last two years studied (2012 and 2013), there was no
evidence to suggest that diagnostic rates were on a constant upward trend during
the decade studied, or even during the last five years of that period. As discussed
above, NICE released its first guidance on the diagnosis and management of ADHD
in September 2008; it would not appear that it has had any notable impact on
diagnostic rates (though of course it may have influenced diagnostic and
management practices in other ways). These findings would appear to demonstrate
that a rise in prescriptions issued for ADHD, and the apparent rise in the number of
individuals commencing drug treatment for ADHD, does not reflect an increase in
the number of individuals being diagnosed with the disorder. What it may reflect is
an increased willingness or ability to prescribe medications in ADHD patients,
whether at the point they were diagnosed or subsequently.
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The findings of Renoux et al. (2016) offer some support for this hypothesis.
Their research, published after the completion of the current study, examined
prescribing trends of ADHD medications in UK primary care between 1995 and
2015. Prescribing rates for ADHD medications rose year-on-year for the entire
duration of the study period. However, a secondary analysis examined whether the
increasing number of prescriptions corresponded to year-on-year increases in the
number of patients being newly diagnosed with ADHD (as denoted by a diagnostic
Read code). Between 1995 and 2003, a period not analysed by the current study,
the number of individuals diagnosed with ADHD did increase annually. However,
between 2004 and 2013 there was less correspondence between the number of
new diagnoses made and the number of prescriptions being issued. Whilst
prescription numbers rose year-on-year, the actual number of patients receiving a
new diagnosis of ADHD did not. It would appear then that diagnosed ADHD and
pharmaceutically-treated ADHD are two closely related, but different, subjects. The
finding that diagnostic rates remained relatively stable between 2004 and 2013
appears compatible with increasing prescribing for ADHD during the same period.
8.1.1.2 Characteristics of UK children and adolescents diagnosed with ADHD 2004-
2013
Establishing the characteristics of those being diagnosed with ADHD was an
important goal of this study. As touched upon previously, several studies have
examined the numbers of individuals being prescribed drugs for ADHD in the UK.
However, useful demographic information relating to these patients was relatively
sparse. Identifying who was being diagnosed with ADHD had the potential to
highlight ‘at risk’ groups, and inform the targeting of finite diagnostic and
management resources. In addition, differences in diagnostic rates across the UK
could point to inconsistencies in diagnostic practices, a concern frequently raised
given the subjective nature of ADHD’s diagnostic criteria (Thomas et al. 2014).
Of particular interest was whether or not ADHD was associated with
socioeconomic deprivation. As stated by Apperley and Mittal: “there is a general
perception that ADHD is linked to deprivation, but there are not enough studies in
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the literature to prove or disprove this assumption” (Apperley & Mittal 2013, p.92).
Earlier UK studies had suggested that patients with ADHD were more likely to come
from a deprived background (Russell et al. 2013; Russell et al. 2015). However,
these studies featured comparatively low numbers of ADHD patients, and identified
their cohorts through parental/caregiver questioning rather than medical record
scrutiny. The current study, using a large and representative sample of the UK
population, appeared to confirm that there is a statistically significant association
between ADHD incidence and deprivation level in UK children and adolescents. As
deprivation quintile increased, so did the incidence of ADHD. This finding has
important implications for service provision. Though the day-to-day management of
ADHD is typically handled by general practitioners (Holden et al. 2013; Rowlingson
et al. 2013; Beau-Lejdstrom et al. 2016), children and adolescent mental health
services (CAMHS) often provide specialist input on the diagnosis and treatment of
the disorder. Indeed, ADHD is the most common reason for a child to be referred to
CAMHS (Parker et al. 2013). It would appear crucial that finite CAMHS and other
specialist ADHD services are retained, and targeted towards, socioeconomically-
deprived areas. It is in these areas that the need for specialist ADHD services is
likely to be greatest. Effective management of ADHD can help to ameliorate its
impacts (Kooij et al. 2010); by targeting services to where they are needed, their
cost-effectiveness and clinical impact can be maximised.
Variations in service provision may have contributed to another notable
observation made by this study. Statistically significant variations in ADHD incidence
were observed between the UK’s four constituent nations, and between regions
within England. Though some degree of variation between regions is probably to be
expected, and is in line with findings from other countries (Fulton et al. 2009;
McDonald & Jalbert 2013), this study appears to be the first to report such
diagnostic variations in the UK. The actual practical significance of these variations
is hard to evaluate using CPRD data alone, but it has the potential to inform future
research into the aetiology of ADHD. As raised previously, populations in some
parts of the United Kingdom may have a higher proportion of individuals with some
genetic susceptibility to ADHD and/or higher exposure to environmental risk factors
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that promote its onset. This may contribute to the regional variations in incidence
observed. The current UK-wide study identified ADHD incidence rates as being
highest in CPRD’s South East Coast region; future studies could focus on this region
and assess if particular genetic or environmental risk factors are strongly
represented within its population. On the other hand, this region’s high incidence
could be related to some idiosyncracy in its diagnostic and management practices
for ADHD. By comparing the availability and setup of ADHD services in the South
East of England and the Yorkshire/Humber region (which had the lowest incidence
rate of all England’s regions), some procedural reason for the differences in ADHD
incidence may become apparent.
The findings made in relation to gender and age of diagnosis are largely in
line with earlier epidemiological studies. However, determining the impact of
gender and age at diagnosis ultimately proved a useful point of reference for the
next element of the study, which separately examined if these characteristics
influenced patients’ likelihood of receiving pharmaceutical treatment for ADHD.
8.1.1.3 Strengths and limitations
Before addressing the limitations of the research, it is important to
summarise its strengths. The study’s main asset was its data source. CPRD is one of
the largest primary care databases in the world (Thomas et al. 2013). It provided a large
sample of real-life patient data, allowing several thousand real-world ADHD patients to
be identified, their characteristics scrutinised, and statistically significant observations
to be made. Its population is drawn from all four nations of the United Kingdom, and
has been evaluated as being broadly representative of the United Kingdom’s general
population in terms of age, gender and ethnicity (Bushe et al. 2015; Herrett et al. 2015;
Holden et al. 2013; Thomas et al. 2013; West et al. 2014). As such, this study’s findings
should be generalisable to the UK population as a whole (Thomas et al. 2013).
Furthermore, the validity of medical diagnoses in CPRD has been confirmed by several
studies and for several different conditions (Herrett et al. 2015; Herrett et al. 2010),
though not for ADHD specifically.
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The reliable identification of children and adolescents with ADHD
represented the study’s biggest challenge. As stated in NICE’s guidance on the
management of ADHD, diagnosed ADHD may not require pharmacological
intervention in all cases (National Institute for Health and Care Excellence 2008).
However, identifying these diagnosed, non-pharmaceutically treated patients in
CPRD posed potential problems. It is possible that the presence of a single Read
code for ADHD in a patient’s CPRD record did not conclusively denote a diagnosed,
untreated ADHD patient in every case. Holden et al. (2013) determined that, in
untreated patients, the presence of two ADHD-related diagnostic codes was
required to denote a diagnosis of ADHD. They hypothesised that, in cases of
suspected ADHD, GPs would document a provisional diagnosis of ADHD in a patient’s
records before referring them for specialist assessment. If specialist assessment
confirmed a diagnosis of ADHD, this would be confirmed by the presence of a second
ADHD-related Read code in patients’ records. This ‘two code’ hypothesis assumed that
prescribers acted uniformly in their diagnostic and documentary practices, and the
authors conceded that it may have led to “fully diagnosed” ADHD patients being
overlooked. It is unclear whether this or the earlier study’s approach to identifying
untreated patients was best. However, a sensitivity analysis revealed that the majority
of untreated patients as defined by this study (82%) had at least two ADHD-related
diagnostic codes in their CPRD record. In comparison, identifying treated ADHD
patients was more straightforward, though not entirely without caveats. These will be
discussed further in section 8.2.1.1
Estimating patients’ deprivation status using the IMD details of their general
practice made use of readily available data, but posed the risk of ecological fallacy.
It was recognised that patients would not always reside in the same LSOA/DZ as
their general practice; in some cases, they may live in areas with a radically
different level of socioeconomic deprivation. In these patients, their practice-level
IMD would not give an accurate impression of their exposure to deprivation.
Despite this, in the sample of patients for whom data were available, practice-level
IMD and home postcode-level IMD showed relatively close correspondence.
Postcode-level deprivation data were accessible for 80.5% of England’s ADHD
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patients (n = 6424). In 4476 of these patients, their postcode-level IMD quintile was
either the same as their practice-level quintile or higher. That is to say, in 69.7% of
instances, patients resided in an area either as deprived as their practice-level IMD
suggested, or more deprived (though again it must be acknowledged that individual
households within a postcode area may experience somewhat different levels of
deprivation).
8.2.1 Chapter 5: ADHD in children and adolescents: Prevalence and predictors of
medication use in UK primary care
8.2.1.1 Prevalence and timing of pharmaceutical treatment in ADHD patients
Pharmaceutical treatment for ADHD, though effective and well-tolerated in
many patients, is not recommended for all (National Institute for Health and Care
Excellence 2008). When drugs are used they should be prescribed cautiously, and
according to their licensed indications. Against a backdrop of increasing
methylphenidate usage (National Institute for Health and Care Excellence 2013),
evidence of unlicensed prescribing (Hill & Turner 2015) and cuts to the provision of
non-pharmaceutical interventions for ADHD (Price 2014), concerns had been raised
that drugs had become the ‘go-to’ option for children diagnosed with ADHD in the
UK. As summarised by the Chief Executive Officer of the ADHD Foundation: “The
problem is that, in most parts of the UK, medication is not only the first-line of
treatment but the only line of treatment…the reality is that overstretched children’s
mental health services do not offer an alternative to medication or such
psychosocial interventions as an adjunct to pharmacology” (Lloyd 2015). The
current study sought to clarify if a diagnosis of ADHD was invariably followed by
pharmaceutical treatment in primary care, and if drugs were often initiated at the
point of diagnosis in primary care.
Examining the cohort of patients diagnosed with ADHD between 1/1/2004
and 31/12/2013, 57% had a primary care prescription for an ADHD medication
documented during follow-up. Patients were followed-up for a mean period of
1229 days following their ADHD diagnosis. This long period of observation allowed
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prescriptions for ADHD medications to be detected even if they occurred several
years after individuals’ first diagnosis, and the mean follow-up time for treated and
untreated patients was comparable (1453 days v 1197 days). This would seemingly
reduce the likelihood of patients being labelled ‘untreated’ purely because they
were not observed for a long time post-diagnosis. These findings would appear to
demonstrate that a documented diagnosis of ADHD does not always lead to the
initiation of pharmaceutical treatment in primary care. It does not seem to be the
case that once a formal diagnosis of ADHD is made, GPs invariably commence
pharmaceutical treatment.
In pharmaceutically-treated patients there was significant heterogeneity in
the time that passed between diagnosis and the initiation of medication in primary
care. However, in approximately 14% of treated patients their first prescription for
an ADHD medication appeared to precede a formal, documented diagnosis of
ADHD. This finding may indicate that some GPs are referring patients to secondary
care for a confirmed diagnosis of ADHD (in accordance with NICE guidance), but
commencing medication in the meantime. This would be contrary to NICE’s
guidance on the diagnosis and management of ADHD, but may be necessary due to
the long waiting lists often associated with these specialist services (Merriman
2013; Price 2014). In areas where specialist ADHD services are particularly
stretched, GPs have been known to diagnose and commence prescribing for ADHD
without seeking any specialist input (Kirby 2015). The current study’s results seem
to demonstrate that this practice is far from uncommon. In 11% of treated patients,
their first prescription for an ADHD medication was recorded on the same day as
their initial diagnosis of ADHD (denoted by an initial Read code for the disorder). In
these patients, it would appear that GPs diagnosed ADHD and commenced
medication themselves, with no pause to seek input from secondary care. However,
this conclusion is made with considerable caution.
The occurrence of prescribing before formal diagnosis, or on the same date
as diagnosis, could be the result of documentary rather than clinical practices. For
example, a GP may assess a patient and make a provisional diagnosis of ADHD,
pending referral and assessment by a specialist. Rather than document this using a
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Read code for ADHD, the GP may instead document their thoughts via a “free text”
entry in their patient’s records. This would not have been detected by the current
study; access to free text information is restricted by CPRD as it may contain
information that could compromise patient anonymity (Herrett et al. 2015). Once the
patient has been seen by a specialist, the GP would then be informed of any diagnosis
and prescribing recommendations made. It may only be at this point, when they come
to issue an initial primary care prescription for ADHD, that a GP would record a formal
diagnosis of ADHD using a Read code. This sequence of events would result in a
diagnosis of ADHD and a first primary care prescription for its treatment occurring on
the same date in CPRD. Whilst the data would suggest that the GP had unilaterally
diagnosed and commenced treatment for ADHD on the same day, this would not be an
accurate reflection of what really happened.
8.2.1.2 Predictors of medication use in primary care
The study also examined if any patient characteristics appeared to influence
the likelihood of receiving pharmaceutical treatment for ADHD. To our knowledge,
the current study was the first to explore this in the UK. The first characteristic
examined was gender. It had already been established that males were significantly
more likely to be diagnosed with ADHD than females (Hire et al. 2015). However,
once diagnosed, males and females were equally likely to go on to receive
treatment with a licensed ADHD medication. This finding highlighted the benefit of
regarding diagnosis and pharmaceutical treatment as two discrete elements. It had
been hypothesised that lower prescribing rates in females reflected either a
difference in symptom severity in males and females, or some sort of bias against
pharmaceutical treatment in females (Rucklidge 2010; Gershon 2002). The current
study seemed to demonstrate that, once diagnosed with ADHD, a patient’s
likelihood of receiving medication was largely unaffected by their gender. Whatever
biological or psychosocial reasons underlie the higher incidence of ADHD amongst
males, once diagnosed with ADHD a comparable proportion of males and females
appear to require, and are prescribed, medication.
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A similar picture was observed in relation to socioeconomic deprivation. A
strong association was observed between deprivation quintile and the likelihood of
being diagnosed with ADHD (Hire et al. 2015). However, once diagnosed, the least
deprived ADHD patients were just as likely to receive medication as the most
deprived ADHD patients. This would seem to illustrate that once a child has been
diagnosed with ADHD, socioeconomic status does not appear to influence their
likelihood of being prescribed medication by their general practitioner. This
contrasts with findings from the United States, where it has been observed that
poorer children with ADHD are less likely to receive medication than children from
wealthier backgrounds (Morley 2010; Froehlich et al. 2007). Possibly the most
intuitive reason for this difference is the different healthcare models that exist in
the United States and the United Kingdom. In the United States, access to
medication may be determined by an individuals’ ability to pay for it, or whether or
not they possess the requisite medical insurance. Financial constraints may mean
that poorer patients are simply unable to take up the option of pharmaceutical
treatment. In contrast, medications prescribed for children in the UK generally incur
no cost to the patient or their carer. This ensures there is no financial disincentive
to accessing medication if it is recommended and prescribed by a healthcare
practitioner.
An individuals’ likelihood of receiving a primary care prescription for ADHD
appeared to be highest if registered with a Scottish general practice. The proportion
of ADHD patients treated in Scotland was significantly higher than that in England,
Wales or Northern Ireland. This contrasted with the observation that Scotland had
the lowest diagnostic incidence of ADHD of the UK’s four constituent nations (Hire
et al. 2015). There are several possible explanations for this dichotomy. It may be
that in Scotland a higher diagnostic threshold is set for ADHD than elsewhere in the
UK. If this was the case, it would potentially explain the lower diagnostic incidence,
and the relatively higher proportion of patients treated (as those that were
diagnosed would presumably have more severe ADHD on average). It is true that
two slightly different sets of diagnostic criteria exist for ADHD. A diagnosis of ADHD
made using the ICD-10 criteria (which terms the condition ‘hyperkinetic disorder’)
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may be conceptualised as a symptomatically severe form of ADHD as defined by the
DSM (Bolea-Alamañac et al. 2014). As such, if the ICD-10 criteria was used in ADHD
screening in Scotland, and the DSM criteria predominated elsewhere in the UK, this
would potentially explain Scotland’s lower ADHD incidence and higher proportion
of pharmaceutically-treated patients. However, actual evidence for this is sparse.
NICE’s 2008 guidance on ADHD would be expected to influence diagnostic practice
in all areas of the UK; it recognises both the ICD-10 and DSM-IV diagnostic criteria
for ADHD and doesn’t express a preference for one over the other (National
Institute for Health and Care Excellence 2008). Perhaps more importantly, ADHD
guidance published by the Scottish Intercollegiate Guidelines Network refers to
‘attention deficit and hyperkinetic disorders’, and makes no specification as to
which set of diagnostic criteria is preferred (Forbes 2010; Scottish Intercollegiate
Guidelines Network 2009).
There may be no direct link between Scotland’s lower diagnostic incidence
and higher treatment incidence in primary care. As discussed in Chapter 5, it may
simply be the case that GPs in Scotland manage prescribing in a relatively high
proportion of ADHD patients. All Scottish Health Boards have shared care
arrangements in place that allow them to prescribe medications for ADHD
(Healthcare Improvement Scotland 2012). This would potentially allow Scotland’s
GPs to manage routine prescribing in all ADHD patients who required medication.
Whilst it is likely that most, if not all, general practitioners in England, Wales and
Northern Ireland would participate in similar shared care arrangements, there is no
data affirming this. As such, the universal provision of shared care arrangements
offers a theoretical explanation for the higher proportion of ADHD patients treated
by their GPs in Scotland. However, further research would be needed to definitively
explain this difference.
Patients’ age at diagnosis appeared to predict their likelihood of subsequent
pharmaceutical treatment in primary care. Pharmaceutical treatment following
diagnosis was most likely in children diagnosed between 13 and 15 years of age.
However, patients diagnosed between the ages of 10 and 12 were equally likely to
receive medication in primary care. This is possibly a reflection of two factors.
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Across this age span, all four medications we examined can be used within the
terms of their product licence for ADHD. In addition, this age range would cover the
vast majority of a patients’ secondary schooling, when the symptom control
provided by medication would perhaps be of greatest benefit.
In contrast, pharmaceutical treatment was significantly less likely in children
diagnosed between the ages of 4 and 6 years of age and (especially) 1 to 3 years of
age. Fewer than five individuals received medication in primary care between the
ages of 1 and 3 years. Only 2.5% of treated patients received medication in primary
care before the age of six. This finding would seemingly dispel any notion that drug
use has become commonplace in pre-school children, a concern highlighted by Hill
and Turner (2015). In addition, a 2016 paper by Beau-Ljedstrom and colleagues
appears to support the current study’s conclusions. Examining UK prescribing data
for the years 1992 through to 2013, they determined that just 4% of patients in
receipt of an ADHD medication were younger than six years of age (with the
majority of those being five years of age). The simplest explanation for this study’s
findings is that none of the drugs examined by the study are licensed for use in
children below the age of six. As such, they have not been extensively tested or
proven to be safe and effective in very young children. It would seem logical that
general practitioners would exercise caution in prescribing such drugs when the
risks and benefits are open to question. In cases where very young children do
require pharmaceutical treatment, it may be the case that they are managed
entirely by specialists, given the additional monitoring and bespoke management
these patients may require. The data offers some support for this theory. In
patients diagnosed between 1 and 3, the median interval between their diagnosis
and the start of pharmaceutical treatment in primary care was 1134 days (IQR =
707 – 1547). This was a far longer interval than was observed in the population as a
whole (median of 84 days [IQR = 21 – 258 days]). This would seemingly confirm that
when very young children are diagnosed with ADHD, they do not have their medication
managed in primary care until they are several years older. Further research would be
required to verify this assertion. However, the study’s findings demonstrate that GPs
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remain cautious about prescribing ADHD medications in the youngest children with the
disorder.
8.2.1.3 Drug most commonly initiated first-line in primary care
Methylphenidate was the first drug prescribed in 92% of pharmaceutically-
treated children and adolescents with ADHD. This was in line with the findings of other
prescribing studies in the UK (Renoux et al. 2016; Beau-Lejdstrom et al. 2016; McCarthy
et al. 2012), and studies from elsewhere in Europe (Zoëga et al. 2011).
Methylphenidate has a long history of use in the treatment of ADHD (Wong et al.
2009), and NICE recommends methylphenidate as the first-line drug of choice in most
children with ADHD (National Institute for Health and Care Excellence 2008). Whilst all
four medications examined are licensed from the age of six upwards, the BNF for
Children gives dosing guidance for methylphenidate in children aged as young as four
(Paediatric Formulary Committee 2015). All these factors probably contributed to
methylphenidate being the first-choice drug in most children who required
pharmacotherapy for ADHD. In contrast, less than 1% of children and adolescents
received either dexamfetamine or lisdexamfetamine as a first-line agent for ADHD. In
the case of lisdexamfetamine, its relatively recent introduction to the UK market (in
2013) undoubtedly influenced its low levels of prescribing. In the case of
dexamfetamine, it appears that it is rarely utilised first-line in primary care, which is in
accordance with its NICE and BNFC indications (National Institute for Health and Care
Excellence 2008; Paediatric Formulary Committee 2015). The final medication
examined was atomoxetine. Introduced to the UK market in 2004, atomoxetine offers
a non-stimulant treatment option for ADHD where stimulants are felt to be
inappropriate or have not produced a response (National Institute for Health and Care
Excellence 2008). It was used first-line in a sizeable minority of ADHD patients, though
annnual usage did not appear to increase over the ten year study period. This suggests
that long-standing concerns surrounding the use of stimulants in childhood have not
resulted in atomoxetine becoming the preferred agent for childhood ADHD. However,
the study pre-dated two influential Cochrane reviews that reiterated the need for
caution when prescribing stimulants in children (Storebø et al. 2015; Punja et al. 2016).
In the coming years it may be the case that non-stimulant medications assume a
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greater role in the treatment of ADHD, and account for a greater proportion of first-line
prescribing in the UK (particularly following the introduction of guanfacine to the UK
market in 2016).
8.2.1.4 Limitations
The study’s findings suggested that children and adolescents with ADHD
were not always referred to secondary care prior to a diagnosis of ADHD being
made, or before commencing medication. It was hoped that an analysis of CPRD’s
referral data would provide definitive answers. This data had the potential to reveal
if, and when, ADHD patients were referred to secondary care, and the reasons for
said referrals. This would clarify what proportion of ADHD patients had received
secondary care input into their diagnosis, and whether any input had been sought
prior to the commencement of medication. Unfortunately, the referral data did not
provide the detail required to draw firm conclusions. Whilst patients with ADHD
were often referred to CAMHS or other services around the time of their diagnosis,
the reasons for the referrals were often unclear. For example, a proportion of
patients were referred to CAMHS for behavioural problems, or problems at school.
Given the behavioural symptoms of ADHD, and its potential impacts on schooling, it
might be reasonable to hypothesise that such referrals may have been ADHD-
related. However, other referrals to psychologists, psychiatrists, behavioural
therapists and paediatricians for the purposes of ‘further care’, or ‘for follow-up’,
were obviously far too vague to interpret. Even if such referrals occurred around
the time patients were diagnosed with ADHD or started treatment, it would be
questionable to claim that such referrals were related to ADHD specifically.
With regard to treatment, it is important to re-emphasise that this study’s
findings regarding treatment rates only have relevance to UK primary care. Routine
prescribing for ADHD is typically managed in primary care (Beau-Lejdstrom et al. 2016;
Rowlingson et al. 2013; Holden et al. 2013). However, whilst 43% of ADHD patients
were found to be untreated in primary care, it remains possible that these patients
were prescribed pharmaceutical treatment elsewhere (for example privately, or via
secondary care). In addition, it must also be noted that CPRD documents prescriptions
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issued to patients; it cannot be guaranteed that every prescription that was issued
was actually dispensed and taken as directed. A further technical point with regard
to CPRD is that prescriptions for drugs are not directly linked with their indication
for use. Therefore, a patient with Read code(s) referring to ADHD in their records,
plus documented prescriptions for a licensed ADHD medication may not
conclusively represent a diagnosed, pharmaceutically-treated ADHD patient
(however suggestive this combination may be).
8.3.1 Chapter 6: Mental, behavioural and neurological comorbidity and psychotropic
treatment in children and adolescents with ADHD: A cohort study using linked CPRD
and HES data
Chapter 6 examines the prevalence of seven comorbidities, and the use of several
distinct groups of drugs amongst ADHD patients and a cohort of matched
comparators. To avoid excessive repetition, this section addresses only the key
findings, strengths and limitations of this work.
8.3.1.1 Key findings
Almost 27% of children and adolescents diagnosed with ADHD between
1/1/2004 and 31/12/2013 had a comorbidity of interest documented during that
period. Every mental, behavioural and neurological comorbidity examined was
significantly more common in ADHD patients than in matched comparators without
ADHD. It is worth emphasising that, in every individual with a comorbidity, their
comorbid diagnosis was documented before the age of nineteen. All this would
seem to support the assertion that comorbidity in ADHD is closer to the rule than
the exception (Findling et al. 2008; Kooij et al. 2010), particularly as comorbidity
may become even more prevalent once ADHD patients reach adulthood (Kooij et al.
2010; Sobanski 2006). This study’s findings emphasise the need for a holistic
approach in patients with ADHD. General practitioners and other specialists
encountering children with ADHD should remain alert to the possibility (if not the
probability) that other mental and behavioural problems are present. That said, the
high prevalence of comorbid diagnoses amongst ADHD patients may illustrate that
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medical practitioners are already effectively identifying and diagnosing such
disorders where they are present.
The study also compared psychotropic prescribing in children with ADHD
and matched comparators. This constituted a strength of the study. By assessing
the prevalence of psychotropic prescribing alongside the prevalence of mental,
behavioural and neurological comorbidity, the clinical significance of such
comorbidity could be gauged (as the requirement for medication may be an
indicator of clinical significance). The risk of receiving a psychotropic of interest
between 1/1/2004 and 31/12/2013 was over seven times higher amongst the
ADHD cohort (RR 7.14 [95% CI 6.66 – 7.65]). It was not possible to confirm with
absolute certainty if a particular psychotropic was prescribed to treat a particular
comorbidity. However, the fact that ADHD patients had significantly higher
exposure to second generation antipsychotics, antidepressants and
anxiolytics/hypnotics compared to children without the disorder remained highly
informative. Psychotropic medications are generally indicated for the treatment of
mental and behavioural disorders. Their markedly increased use among ADHD
patients strongly supports the hypothesis that these disorders are more prevalent
in ADHD patients than children and adolescents without ADHD.
ADHD patients were more likely to receive a psychotropic prescription in the
year following their index date than they were in the year before their index date
(their index date being their date of diagnosis with ADHD). Specifically, second
generation antipsychotics, SSRIs and melatonin were all significantly more likely to
be prescribed in ADHD patients in the year following their diagnosis with ADHD,
compared to the year before. In contrast, non-ADHD comparators were no more
likely to receive any psychotropic in the year following their index date than they
were the year before, and were significantly less likely to receive these medications
in general than ADHD patients.
The use of melatonin in patients recently diagnosed with ADHD is likely
related to the condition itself. Melatonin is used to treat sleep disorders, which are
often a symptom of ADHD itself, or a side effect of its treatments (Stein et al. 2012).
However, the use of SSRIs and second generation antipsychotics in children
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following their diagnosis with ADHD warrants further investigation. Neither group
of drugs has an evidence base supporting its use in the treatment of ADHD
specifically (Birnbaum et al. 2013), and unlicensed use of powerful psychotropic
drugs without good reason is probably ill-advised. Alternatively, it may be that
newly-diagnosed ADHD patients have more frequent contact with medical and
psychiatric services than they did prior to their diagnosis. This might increase the
likelihood of them receiving comorbid diagnoses in the year following their
diagnosis (discussed further in section 8.3.1.3), leading to antipsychotics or SSRIs
being commenced for the treatment of those comorbidities rather than ADHD
itself. Further dedicated investigation would be required to come to a firm
conclusion.
8.3.1.2 Strengths
Numerous studies have examined the association between ADHD and
individual mental, behavioural and neurological disorders. However, the focus,
methods and scale of these studies is highly varied. This study was, to my
knowledge, the first to examine UK ADHD patients for the presence of multiple
mental, behavioural and neurological comorbidities. In addition, using both primary
and secondary care data in the detection of comorbidity was a unique strength of
the study. This allowed the detection of real-world diagnoses made in routine
clinical practice, and avoided the uncertainties associated with patient/carer recall,
and the application of prospective screening measures to identify comorbidity. It
was beyond the capabilities of the study to scrutinise every single comorbidity that
has been associated with ADHD. However, the range of comorbidities investigated
was clinically-diverse and encompassed several of the disorders most commonly
linked with ADHD (Steinhausen et al. 2006; Williams et al. 2016; Kraut et al. 2013;
Jensen & Steinhausen 2015).
It was recognised that mental, behavioural and neurological comorbidities
could occur both before, and after a patient’s formal diagnosis with ADHD. For
example, an ADHD patient with comorbid tic disorder might have had their tic
disorder recognised and diagnosed either before or after their diagnosis with
157
ADHD. By focusing on diagnoses made after a patient was diagnosed with ADHD,
comorbid diagnoses made before this point might have been missed. The study
therefore made an attempt to assess sequential comorbidity, the co-occurrence of
disorders in a time-independent manner (Jensen & Steinhausen 2015). Patients
diagnosed with ADHD between 1/1/2004 and 31/12/2013 were screened for
comorbid diagnoses made during this period. This captured patients diagnosed with
comorbidities both before and after their diagnosis of ADHD. This improved the
detection of individuals with comorbid conditions, but complicated the analysis
somewhat. The patients with comorbidities identified by this study had these
comorbid conditions diagnosed at some point between 1/1/2004 and 31/12/2013;
the comorbidities were not necessarily diagnosed in patients following their
diagnosis with ADHD. For example, ADHD patients with comorbid depression may
have had a transient episode of depression that had resolved by the time they
received their diagnosis with ADHD. A similar approach was taken to psychotropic
use. Concerns have been raised regarding the use of psychotropic drugs in children;
the long-term effects of such drugs on the developing body and brain are not yet
fully understood (Birnbaum et al. 2013; Bottelier et al. 2014). As such it was felt
important to capture patients exposed to such drugs during the study period,
whether such exposure occurred before or after they were diagnosed with ADHD.
8.3.1.3 Limitations
The risk ratios presented in Chapter 6 (in Table 9, and Table 11) were
derived by comparing the proportions of ADHD patients and comparators who
were diagnosed with a psychotropic comorbidity, or who received a psychotropic
prescription, between 1/1/2004 and 31/12/2013. These measures of relative risk
were readily derived; they gave a clear impression of the relative burden of
comorbidity and psychotropic exposure in these cohorts. They were felt to be
appropriate given that the cohorts were well-matched demographically, and the
follow-up time per subject was comparable in both cohorts. However, this form of
analysis did not allow the specific impact of ADHD on the risk of these outcomes to
be quantified, and compared to other factors (such as gender).
158
Furthermore, the current study could not explain why ADHD appears to be
associated with an increased risk of mental, behavioural and neurological
comorbidity. Research has suggested that ADHD, autism, bipolar disorder,
schizophrenia, depression, and potentially many other such disorders share a
common genetic basis (Cross-Disorder Group of the Psychiatric Genomics
Consortium 2013). However, looking again at the current study’s findings, there is a
possibility that detection bias plays some role in the finding of frequent comorbidity
in ADHD patients. Being diagnosed with ADHD may involve contact with mental
health services, who are expertly placed to recognise and diagnose comorbidities
such as those examined by this study. In contrast, the comparators selected may
not have had contact with these experts, unless referred to them for some other
reason. As such, it may be that comparators were just as likely to have mental,
behavioural and neurological comorbidities as ADHD patients, but were less likely
to have these conditions recognised, formally diagnosed, and subsequently treated.
This is probably a less parsimonious explanation for the study’s findings, but
without further investigation it cannot be discounted completely.
A further complication may arise because the ADHD cohort comprised
patients who received pharmaceutical treatment with a licensed medication for
ADHD, and individuals who did not receive stimulants/atomoxetine. By not
analysing treated and untreated ADHD patients separately, this study could not
examine if the apparent impact of ADHD on the outcomes investigated was due to
ADHD itself, or due to its pharmaceutical treatments. For example, the risk of being
diagnosed with epilepsy or an SMI was found to be significantly higher amongst
ADHD patients. This might suggest that ADHD shares some common
neurobiological basis with these disorders, leading them to be more commonly
observed amongst ADHD patients than the general population. However,
methylphenidate, atomoxetine, dexamfetamine and lisdexamfetamine all have the
potential to lower a patient’s seizure threshold. In addition, all may produce
psychotic symptoms as an adverse effect. As such, the higher risk of comorbid
epilepsy/SMI in ADHD patients may simply reflect that ADHD patients were more
likely to receive these drugs (rather than anything to do with ADHD specifically).
159
Without examining treated and treated ADHD patients separately, and comparing
the relative risk of these comorbidities in each group, it is impossible to draw any
firm conclusions. A stratified Cox analysis would potentially help to answer such
outstanding questions; a potential plan for such an analysis is discussed further in
section 8.5.
With regard to diagnostic codes, the study assumed that a documented
Read code/ICD-10 code in a patient’s primary/secondary care records denoted a
real-world diagnosis for that disorder. As addressed previously, the validity of
diagnostic coding in CPRD/HES has been verified for a number of different
conditions (Herrett et al. 2010; Khan et al. 2010; Wright et al. 2012). However, it
has not been assessed for many of the comorbidities examined by this study. As
such, it cannot be guaranteed that a Read code/ICD-10 code for a comorbidity of
interest represented a full clinical diagnosis of that comorbidity in every single
instance. There is no reason to suppose this issue affected cases and comparators
differentially (if at all). As such, comparisons involving the proportions of ADHD
cases and comparators affected by particular comorbidities should remain valid.
The comorbidity/fractures aspect of this research was not conducted using
the entire incident cohort previously identified (n = 10,284, encompassing ADHD
patients registered with English, Scottish, Welsh and Northern Irish practices).
Instead, a sub-sample consisting of 5111 of these patients was selected and utilised.
This decision was driven by a desire to utilise both primary and secondary care data
in the detection of patients with comorbidities, and individuals who had sustained
fractures. Using both primary and secondary care data enhanced the detection of
patients with a history of comorbidity/fracture. However, it necessitated using only
patients registered with English general practices, as Hospital Episode Statistics data
is only available for these patients. As result of this trade-off, the study’s findings in
relation to comorbidity/fracture can only be taken as applying to children and
adolescents with ADHD in England. In addition, the conclusions made regarding
psychotropic prescribing relate to primary care only, as the available HES data did
not provide information on prescriptions issued in secondary care.
160
8.4.1 Chapter 7: Fracture risk in children in adolescents with ADHD: a cohort study
using linked CPRD and HES data
8.4.1.1 Strengths Though the potential for a link between ADHD and accidental injury seems
intuitive, at the time of the study this remained a relatively novel area of research.
In addition, though fractures constitute up to a quarter of significant accidental
injuries in children (Cooper et al. 2004), studies examining the relationship between
ADHD and fracture risk were relatively scarce. To my knowledge, no such
investigation had previously been conducted in the UK. The findings of this study
appear to demonstrate that pre-existing ADHD is associated with an increased risk
of fracture amongst children and adolescents in England (HR 1.17 [95% CI 1.06 –
1.30]). This is a novel and potentially important finding, given the significant health
impacts and costs associated with fracture.
8.4.2 Limitations
The study sought to identify fractures stemming from accidents. However,
Read codes and ICD-10 codes denoting fractures generally indicate the bone or
bodily region affected, but not the specific cause. For example, two children who
sustained a fractured ulna could both have the same code in their electronic
healthcare records even if one sustained the fracture as the result of an accidental
fall and the other sustained the fracture as the result of a non-accidental cause (for
example, child abuse). The study’s findings need to viewed with this in mind; it may
be the case that a proportion of fractures in both cases and comparators were not
accidental events. However, it was hoped that the exclusion of fracture codes
specifically associated with underlying disease processes and non-accidental causes
would prevent such fractures being miscounted as accidental events. In addition,
existing research suggests that the vast majority of fractures in children arise
through accidental trauma rather than underlying disease or deliberate trauma
(Kemp et al. 2008; Rennie et al. 2007; Mathison & Agrawal 2010). Making the
assumption that fractures in children or adolescents are generally the result of
161
accidents (unless otherwise specified) is not a perfect option, but it is supported by
previous research.
The study did not consider the potential role of ethnicity in fracture risk. There
is some evidence that ethnicity can impact upon fracture risk in UK children and adults
(Curtis et al. 2016; Moon et al. 2016), and ideally this would have been examined as a
potential confounding variable by this study. However, whilst CPRD and HES data can
provide information on patient ethnicity, this aspect of the data is often incomplete.
The ADHD cohort selected for this study was mainly white (n=3642; 71% of individuals).
Of those that remained, more than 86% lacked any specific indication of their ethnicity.
The situation amongst the comparison cohort was much the same. As such, accurately
adjusting for the impact of ethnicity was felt to be both problematic and unlikely to
provide useful insights in this instance.
8.5 Future work
The study established that ADHD is strongly associated with a host of
negative health outcomes. However, the ADHD cohort examined by this study
contained both treated individuals (who had a diagnosis of ADHD, and received a
medication licensed to treat the disorder) and untreated individuals (who had a
diagnosis of ADHD, but did not receive medication for the disorder in primary care).
For the purposes of this study, no distinction was made between these treated and
untreated patients; their outcomes were not examined separately. A future analysis
could examine this distinction in more detail, to establish if those diagnosed with
ADHD and treated for the condition had a greater risk of new-onset
comorbidity/psychotropic treatment/fracture relative to untreated children, and
children with no history of ADHD whatsoever. This could be achieved using Cox
proportional hazards regression models. The rate, and hazard ratios for each
outcome of interest (a new, comorbid diagnosis, or an incident prescription for a
psychotropic drug), could be presented for various subgroups using a stratified Cox
analysis. With regard to ADHD, these subgroups would be diagnosed children with
no prior exposure to a licensed ADHD medication, diagnosed children who had
previously received pharmaceutical treatment for their ADHD, and children with no
162
prior history of ADHD. Chou et al. (2014) used this approach to describe the risk of
fractures in Ritalin-treated ADHD patients, ADHD patients who had not received
Ritalin previously, and a comparator cohort of unaffected patients. In that paper,
the authors determined that children with untreated ADHD had a significantly
higher risk of fracture than children without ADHD [HR 1.64 (95% CI 1.37 – 1.96)].
There was no significant difference in fracture risk between children without ADHD,
and those children with ADHD who were treated pharmaceutically [HR 1.12 (95% CI
0.97 – 1.29]). That example would seem to confirm that scrutinising treated and
untreated ADHD patients separately may provide new insights into the apparent
role of ADHD in clinical outcomes, beyond those provided by the current study.
If treated ADHD patients had a significantly higher/lower risk of comorbidity
relative to the other groups examined, this too could be explored in more depth.
Hill et al. (2015) examined a cohort of patients diagnosed with incident depression
between 1/1/2000 and 31/7/2011. Using Cox proportional hazards models, it was
determined if antidepressant choice in these patients impacted on their likelihood
of being diagnosed with epilepsy/new-onset seizures during follow-up.
Antidepressant use was treated as a time-varying exposure; follow-up time for each
patient was partitioned into periods in which they were receiving treatment with
one or more major class of antidepressant, and untreated periods in which no
antidepressant was being taken. By doing this, the risk of seizure/epilepsy diagnosis
could be compared during untreated and treated periods, and periods of treatment
with different classes of antidepressant. This more sophisticated technique could
be used to examine the treated ADHD patients identified by this study. Having
already established that comorbidity and fractures were more likely to occur in
ADHD patients relative to non-ADHD comparators, it could be established if
patients with ADHD were more likely to sustain fractures, and receive comorbid
diagnoses, during periods of treatment with licensed ADHD medications, or during
periods where their ADHD was not controlled pharmaceutically. This information
would help discern if pharmaceutical treatment in ADHD reduces the likelihood of
certain adverse events and/or increases the risk of others.
163
Whilst this study examined morbidity in ADHD, a recent research paper
from Denmark has suggested that ADHD is linked with increased mortality rates,
with accidents being the most common cause of death (Dalsgaard et al. 2015). This
novel finding has yet to be replicated elsewhere. An earlier GPRD study focussing
on death in stimulant users aged 21 or younger produced inconclusive results
(McCarthy et al. 2009). The current study cohort was not well-suited to a study of
mortality due to its relatively youthful composition. Very few ADHD patients died of
any cause during follow-up. However, the fact that this young cohort was at an
increased risk of accidental fractures suggests that a UK study of cause-specific
mortality in ADHD might be worthwhile (given the large role accidental deaths
played in the study by Dalsgaard and colleagues). A broader inclusion criteria and a
longer study period would increase the number of deaths detected. By linking
CPRD, HES and ONS mortality data, deaths resulting from accidents could be
robustly identified. As discussed above, it could also be assessed whether or not
treatment with a licensed ADHD medication had any effect on individuals’
likelihood of accidental death, or death in general.
164
Chapter 9
Conclusion
165
9.1 Conclusion
Prescribing of ADHD medications in UK primary care increased year-on-year
between 2004 and 2013 (Renoux et al. 2016). However, this study determined that
ADHD diagnostic rates were relatively stable during this period. This seems to dispel
the notion that increasing prescription numbers directly corresponded to increases
in the number of children and adolescents being diagnosed with the disorder. With
regard to treatment, 57% of patients with a diagnosis of ADHD received a
prescription for a licensed ADHD treatment in primary care; unlicensed prescribing
in children below the age of six was rare. This would seem to allay concerns that
ADHD is being treated with drugs as a matter of course, even in young children.
ADHD was found to be significantly more likely amongst patients registered with
general practices in socioeconomically deprived areas, suggesting that deprivation
may play some role in the aetiology of ADHD. This finding also emphasises the
importance of adequate service provision for the diagnosis and management of
ADHD in deprived areas. Regional differences in diagnostic incidence were observed
in the UK. These may be the result of regional variations in diagnostic and
management procedures. However, further research could help to determine if
areas with a high ADHD incidence had a higher proportion of individuals with some
genetic susceptibility to ADHD and/or higher exposure to environmental risk factors
that promote its onset.
The study found that comorbidity was highly prevalent among UK children
with ADHD. Almost 27% of ADHD patients examined had a documented diagnosis
for a mental, behavioural or neurological comorbidity of interest. This compared to
just 7.5% of comparators. In addition, children and adolescents with ADHD were
significantly more likely to have received second generation antipsychotics,
antidepressants and anxiolytics/hypnotics, relative to comparators. This would
seem to support the conclusion that clinically-significant mental, behavioural and
neurological disorders are more common in ADHD; medical professionals who
encounter ADHD patients should be alert to the possibility that such conditions are
also present. Accidental fractures were also significantly more likely to occur
amongst children and adolescents with ADHD. This adds to a growing body of
166
evidence that ADHD is linked with a higher risk of physical injury, possibly as result
of its impacts on impulse control. Having established that fracture risk is higher in
UK children and adolescents with ADHD, further research may be able to establish
whether certain fracture types are strongly predictive of ADHD and may be useful in
the identification of the disorder.
167
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Appendix 1: ISAC Approval Notification and Protocol (15_036RAR)
ISAC EVALUATION OF PROTOCOLS FOR RESEARCH INVOLVING
CPRD DATA
FEEDBACK TO APPLICANTS
CONFIDENTIAL BY E-MAIL
PROTOCOL NO: 15_036RAR
PROTOCOL TITLE: Attention deficit hyperactivity disorder (ADHD): an epidemiological study
using UK primary care data
APPLICANT: Adrian Hire, Postgraduate Research Student, Centre for
Pharmacoepidemiology and Drug Safety, Manchester Pharmacy School,
University of Manchester
APPROVED
APPROVED WITH
COMMENTS
(resubmission not required)
REVISION/
RESUBMISSION
REQUESTED
REJECTED
INSTRUCTIONS:
Please include your response/s to the Reviewer’s feedback below only if you are required to
Revise/ Resubmit your protocol.
Protocols with an outcome of ‘Approved’ or ‘Approved with comments’ do not require
resubmission to the ISAC.
Please address the following comments, revising the protocol as necessary and highlighting all
changes:
REVIEWER COMMENTS:
Protocol 15_036RAR is approved.
DATE OF ISAC FEEDBACK: 9th February 2016
DATE OF APPLICANT
FEEDBACK:
For protocols approved from 01 April 2014 onwards, applicants are required to
include the ISAC protocol in their journal submission with a statement in the
manuscript indicating that it had been approved by the ISAC (with the reference
number) and made available to the journal reviewers. If the protocol was subject to
any amendments, the last amended version should be the one submitted.** Please
refer to the ISAC advice about protocol amendments provided below**
188
ISAC APPLICATION FORM
PROTOCOLS FOR RESEARCH USING THE CLINICAL PRACTICE RESEARCH DATALINK (CPRD)
ISAC use only: Protocol Number Date submitted
............................. .............................
IMPORTANT If you have any queries, please contact ISAC Secretariat:
Study Title Attention deficit hyperactivity disorder (ADHD): an epidemiological study using UK primary care data
Principal Investigator (full name, job title, organisation & e-mail address for correspondence regarding this protocol) Adrian Hire, Postgraduate Research Student, Centre for Pharmacoepidemiology and Drug Safety, Manchester Pharmacy School, University of Manchester [email protected]
Affiliation (full address) Centre for Pharmacoepidemiology and Drug Safety Manchester Pharmacy School University of Manchester 1.134 Stopford Building Oxford Road Manchester M13 9PT
Protocol’s Author (if different from the principal investigator) N/A
List of all investigators/collaborators (please list the names, affiliations and e-mail addresses* of all collaborators, other than the principal investigator) Dr. Doug Steinke, Senior Lecturer of Pharmacoepidemiology, Manchester Pharmacy School, University of Manchester [email protected] Prof. Darren Ashcroft, Professor of Pharmacoepidemiology, Manchester Pharmacy School, University of Manchester [email protected] Dr. David Springate, Research Fellow in Biostatistics, Institute of Population Health, University of Manchester [email protected] *Please note that your ISAC application form and protocol must be copied to all e-mail addresses listed above at the time of submission of your application to the ISAC mailbox. Failure to do so will result in delays in the processing of your application.
Type of Institution (please tick one box below) Academia Research Service Provider Pharmaceutical Industry NHS Government Departments Others
Financial Sponsor of study Pharmaceutical Industry (please specify) Academia Government / NHS (please specify) None Other (please specify) Study conducted as part of an academia-sponsored PhD
Data source (please tick one box below) Sponsor has on-line access Purchase of ad hoc dataset Commissioned study Other (please specify)
Has this protocol been peer reviewed by another Committee? Yes* No * Please state in your protocol the name of the reviewing Committee(s) and provide an outline of the review process and outcome.
Type of Study (please tick all the relevant boxes which apply) Adverse Drug Reaction/Drug Safety Drug Use Disease Epidemiology Drug Effectiveness Pharmacoeconomic Other
189
This study is intended for: Publication in peer reviewed journals Presentation at scientific conference Presentation at company/institutional meetings Other
Does this protocol also seek access to data held under the CPRD Data Linkage Scheme? Yes No
If you are seeking access to data held under the CPRD Data Linkage Scheme*, please select the source(s) of linked data being requested.
Hospital Episode Statistics Cancer Registry Data** MINAP ONS Mortality Data Index of Multiple Deprivation/ Townsend Score
Mother Baby Link Other: (please specify)
* As part of the ISAC review of linkages, the protocol may be shared - in confidence - with a representative of the requested linked data set(s) and summary details may be shared - in confidence - with the Confidentiality Advisory Group of the Health Research Authority. **Please note that applicants seeking access to cancer registry data must provide consent for publication of their study title and study institution on the UK Cancer Registry website. Please contact the CPRD Research Team on +44
(20) 3080 6383 or email [email protected] to discuss this requirement further.
If you are seeking access to data held under the CPRD Data Linkage Scheme, have you already discussed your request with a member of the Research team? Yes No*
*Please contact the CPRD Research Team on +44 (20) 3080 6383 or email [email protected] to discuss your requirements before submitting your application. Please list below the name of the person/s at the CPRD with whom you have discussed your request. Tarita Murray Thomas has provided feedback on data linkage proposals (email correspondence 22/12/14)
If you are seeking access to data held under the CPRD Data Linkage Scheme, please provide the following information: The number of linked datasets requested: 2 A synopsis of the purpose(s) for which the linkages are required: Patient-level IMD scores will be requested to compare ADHD diagnosis rates between different socioeconomic populations (high deprivation vs low deprivation) Linkage with Hospital Episode Statistics (HES) will be used to ascertain if ADHD patients identified in CPRD had secondary care involvement in the diagnosis and management of their condition. This will be indicated by the presence of ICD-10 codes in their records relating to ADHD (see Appendix 3). Is linkage to a local dataset with <1 million patients being requested? Yes* No * If yes, please provide further details:
If you have requested linked data sets, please indicate whether the Principal Investigator or any of the collaborators listed in response to question 5 above, have access to any of the linked datasets in a patient identifiable form, or associated with a patient index. Yes* No * If yes, please provide further details:
Does this protocol involve requesting any additional information from GPs? Yes* No * Please indicate what will be required:
Completion of questionnaires by the GP Yes No Provision of anonymised records (e.g. hospital discharge summaries) Yes No Other (please describe)
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Any questionnaire for completion by GPs or other health care professional must be approved by ISAC before circulation for completion.
Does this protocol describe a purely observational study using CPRD data (this may include the review of anonymised free text)? Yes* No** * Yes: If you will be using data obtained from the CPRD Group, this study does not require separate ethics approval from an NHS Research Ethics Committee. ** No: You may need to seek separate ethics approval from an NHS Research Ethics Committee for this study. The ISAC will provide advice on whether this may be needed.
Does this study involve linking to patient identifiable data from other sources? Yes No
Does this study require contact with patients in order for them to complete a questionnaire? Yes No N.B. Any questionnaire for completion by patients must be approved by ISAC before circulation for completion.
Does this study require contact with patients in order to collect a sample? Yes* No * Please state what will be collected
Experience/expertise available Please complete the following questions to indicate the experience/expertise available within the team of researchers actively involved in the proposed research, including analysis of data and interpretation of results
Previous GPRD/CPRD Studies Publications using GPRD/CPRD data None 1-3 > 3
Yes No Is statistical expertise available within the research team? Principal investigator has undertaken training in statistics and statistical methods. Collaborators have extensive statistical expertise, as do colleagues working within the Centre for Pharmacoepidemiology and Drug Safety at the Manchester Pharmacy School. Is experience of handling large data sets (>1 million records) available within the research team? Collaborators have conducted/overseen projects involving large CPRD datasets previously. Is UK primary care experience available within the research team? Principal investigator has experience of working within UK primary care. The Centre for Pharmacoepidemiology and Drug Safety has close links with the Centre for Primary Care at the University of Manchester, providing expertise and advice relating to UK primary care.
References relating to your study Please list up to 3 references (most relevant) relating to your proposed study: Holden, S. E., Jenkins-Jones, S., Poole, C. D., Morgan, C. L., Coghill, D., & Currie, C. J. (2013). The prevalence and incidence, resource use and financial costs of treating people with attention deficit/hyperactivity disorder (ADHD) in the United Kingdom (1998 to 2010). Child and adolescent psychiatry and mental health, 7(1), 34. doi:10.1186/1753-2000-7-34 McCarthy, S., Wilton, L., Murray, M. L., Hodgkins, P., Asherson, P., & Wong, I. C. K. (2012b). The epidemiology of pharmacologically treated attention deficit hyperactivity disorder (ADHD) in children, adolescents and adults in UK primary care. BMC pediatrics, 12(1), 78. doi:10.1186/1471-2431-12-78 Russell, G., Ford, T., Rosenberg, R., & Kelly, S. (2013). The association of attention deficit hyperactivity disorder with socioeconomic disadvantage: Alternative explanations and evidence. Journal of Child Psychology and Psychiatry, 1–10. doi:10.1111/jcpp.12170
[PLEASE INSERT THE STUDY PROTOCOL DOCUMENT HERE]
Lay Summary
ADHD is a common developmental disorder of childhood, associated with numerous detrimental impacts on its patients and
society as a whole. Previous research found that the prescribing of drugs for ADHD rose annually in the UK between 1998 and
2007, suggesting that its prevalence was increasing. However, little in-depth research into the demographics of ADHD has
been carried out on a national scale.
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This study will use data from the Clinical Practice Research Datalink (CPRD) to provide an updated snapshot of ADHD in the
UK. CPRD contains clinical and prescribing information for 680 UK GP practices and over 13 million individuals. By examining
this resource a host of information on ADHD can be derived, including rates of diagnosis over time, trends in prescribing for
ADHD and the characteristics of patients diagnosed with the disorder.
A potentially novel aspect of this study will be the assessment of whether incidence rates and prescribing practices for ADHD
vary significantly according to geographical location and patients’ socioeconomic status. This may identify inconsistencies in
prescribing practice, or assist the effective targeting of healthcare resources. It may also support or undermine the theory
that socioeconomic deprivation plays a major role in the development of ADHD.
Background
Selected studies addressing the epidemiology of ADHD in the UK:
Authors Year of
publication
Study design
(number of ADHD
patients)
Key Findings
McCarthy et al. 2012
Retrospective cohort
study
(n=4530*)
Population prevalence of pharmacologically-treated ADHD
increased year-on-year between 2003-2008
Prevalence doubled in children and adolescents and those
aged 45+; in adults aged 18–24 years and 25–45 years
prevalence increased four-fold
Holden et al. 2013
Retrospective cohort
study
(n=3229**)
Prevalence and incidence of diagnosed ADHD in primary
care rose between 1998-2007
Healthcare costs of patients with ADHD were
approximately four times higher than those of matched
controls
Rowlingson et
al. 2013
Analysis of
prescribing data
Primary care spending on methylphenidate varied
significantly across England; certain areas exhibited
substantially and significantly higher spending per child
Russell et al. 2013
Retrospective cohort
study
(n=187)
ADHD significantly associated with several indicators of
socioeconomic deprivation
*Total number of ADHD patients identified during period scrutinized (2003-2008)
**Number of ADHD patients identified at the outset of the study (1998)
This study will build upon the findings of the earlier studies quoted above, as well as contributing new information regarding
ADHD in the UK.
It will seek to establish if the increase in annual incidence rates observed by McCarthy et al. (2012) and Holden et al. (2013)
are observed using CPRD data; it will also establish if ADHD incidence rates have continued to rise in the years up to 2013.
Incident ADHD cases for the years 2004 through to 2013 will be described according to age, gender, UK region and
socioeconomic status (discussed below).
The study will investigate in detail prescribing patterns for all four drugs licensed for the treatment of ADHD in the UK.
Rowlingson et al. (2013) found that methylphenidate prescribing varied significantly across England; this study will seek to
verify this finding, and see if such geographical variability is observed with atomoxetine, dexamfetamine and
lisdexamfetamine. This study will seek to establish if any regional variations in prescribing are reflective of regional
differences in ADHD incidence.
A systematic review carried out by Reiss (2013) established that socioeconomically-disadvantaged children and adolescents
were two to three times more likely to develop mental health problems in general (Reiss, 2013). In addition, several studies
have suggested a link between socioeconomic status and ADHD specifically (Hjern et al., 2010; Nomura et al., 2012; Russell et
al., 2013). In the UK, Russell and colleagues (2013) found that ADHD was associated with several indicators of social and
economic disadvantage, including poverty status, household income, housing tenure and maternal education level.
Establishing a definitive, causative link is beyond the remit of this study. However, it will be possible to describe ADHD
patients according to the socioeconomic status of their registered GP (based on the Index of Multiple Deprivation/IMD score
of the area in which it is sited). It can then be established if patients registered with GPs in socioeconomically deprived areas
contribute disproportionately to the overall number of ADHD patients.
It has been estimated that 65% of children with ADHD have one or more significant comorbidities (Kooij et al., 2010). This
study will assess how prevalent comorbidities are within the ADHD cohort identified; it will describe the classes of
psychotropic drugs (such as antidepressants and antipsychotics) these patients are prescribed.
Aims and objectives
To calculate annual incidence rates of newly-diagnosed ADHD in the years 2004 through to 2013. Annual incidence rates will
also be provided according to patient gender, registered GP region and deprivation (IMD) decile. For the study period as a
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whole, incidence rates for the age ranges 0-6, 7-12, and 13-18 years will be calculated. For all cases identified, the age at
which ADHD diagnosis was made will be ascertained and grouped according to these categories. This will serve as the
numerator. The annual ‘at risk’ populations will then be estimated, totalled and grouped according to these age categories.
This will serve as the denominator. This will ascertain if and how ADHD diagnosis rates have changed over the decade, and
provide demographic details about those patients diagnosed with ADHD. Differences in regional incidence rates may highlight
inconsistencies in diagnostic practice or genuine differences in incidence. Regional and socioeconomic differences in
diagnostic rates may support or undermine the theory that socioeconomic deprivation plays a major role in the development
of ADHD.
To calculate what proportion of patients with a recorded diagnosis of ADHD additionally received a prescription for one of its
four licensed treatments (methylphenidate, atomoxetine, dexamfetamine and lisdexamfetamine). This will ascertain if ADHD
diagnosis is routinely accompanied by pharmacological treatment.
To calculate the number of patients who received a prescription for one of the four licensed ADHD treatments in each year
from 2004 through to 2013. This will assess if drug use in the treatment of ADHD has increased over time. Each individual
drug prescribed to patients has a distinct prodcode. When a prescription for a specific drug is issued, this date is recorded in
a patient’s therapy file along with the quantity and dose prescribed. It will therefore be possible to estimate when courses of
ADHD medications start and stop, and to discern if individuals were prescribed different ADHD products concurrently.
To calculate the number of ADHD patients with recorded diagnostic and or/treatment codes relating to depression, autism,
personality disorders, tic disorder and Tourette’s syndrome. These comorbidities have been associated with ADHD, and this
study will ascertain to what extent they are present in a large UK patient cohort. As ADHD’s comorbidities are often
neuropsychiatric in nature, the use of psychotropic drugs in the ADHD cohort will be also be investigated. The clinical files of
patients with ADHD will be scrutinized for the presence of codes relating to comorbidities of interest (such as autism,
Tourette’s disorder and tic disorder, which previous research has associated with ADHD [Kooij et al., 2010; McCarthy et al.,
2012; Lakhan & Kirchgessner, 2012]). Similarly, the therapy files of the ADHD cohort will be assessed for the presence of
prescriptions for drugs of interest (psychotropic drug such as antipsychotics and antidepressants). These will give an
indication of the prevalence of psychiatric comorbidities amongst patients with ADHD. The time window assessed for each
ADHD patient will be from their current registration date to the end of the study on 31/12/13. This will detect
diagnoses/prescriptions made before and after patients received their diagnosis of ADHD. As such, there will be no attempt to
assess if comorbidities or psychotropic prescriptions precede or follow a diagnosis of ADHD. The aim will be to assess if the
selected comorbidities are prevalent within the ADHD cohort, and what proportion of that cohort have received treated with
psychotropic drugs.
Study type
The study will be descriptive in nature. Depending on its findings, it may also generate hypotheses relating to the
epidemiology and treatment of ADHD in the UK.
Study design and study population
The study will be a retrospective cohort study, examining trends in incidence and drug use. The study population will
comprise of patients diagnosed with ADHD before the age of 19, between 1/1/2004 and 31/12/13. Patients with a diagnosis
of ADHD will be identified by the presence of one or more Read codes relating to the disorder in their CPRD record. A list of
Read codes denoting a diagnosis of ADHD (see Appendix 1), and a further list of Read codes denoting drugs used in its
treatment have been compiled (see Appendix 2). These drugs encompass all agents currently licensed for the treatment of
ADHD in the UK.
Using the Read code lists, the study population will be identified and sub-divided into two groups; diagnosed, untreated
cases of ADHD, and diagnosed, pharmacologically-treated cases of ADHD.
Diagnosed, untreated cases of ADHD:
These will be defined as patients with one or more Read code(s) indicating a diagnosis of ADHD present in their records
during the study period, but no recorded prescription for any of the drugs of interest.
Diagnosed, pharmacologically-treated cases of ADHD:
These will be defined as patients with one or more Read code(s) indicating a diagnosis of ADHD present in their records
during the study period, plus at least at one recorded prescription for a drug of interest (indicated by the presence of a
product code denoting methylphenidate, atomoxetine, dexamfetamine or lisdexamfetamine).
Inclusion criteria
Patients aged under 19 during each year studied will be eligible for inclusion. To qualify as incident cases of ADHD, patients
must have at least 365 days of continuous registration prior to their first recorded diagnostic code/prescription for a drug of
interest (whichever occurs first). Only patient data from ‘up to standard’ practices will be included in the study.
Exclusion criteria
Patients temporarily registered with GP practices will be excluded from analysis. Data cleaning measures will be performed to
exclude patients with erroneous/incomplete data.
Incidence calculation
Read codes denoting a diagnosis of ADHD/treatment for ADHD will be used in the identification of incident cases. The earliest
occurrence of an ADHD-related diagnostic/treatment code in each patient’s records will be ascertained, and the calendar year
in which this occurred will be noted. The patient will then be counted as a newly-diagnosed incident case for that calendar
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year. It is anticipated that, in diagnosed and treated patients, a patient’s earliest diagnostic code would precede their earliest
treatment code (ie a recorded diagnosis of ADHD would precede a prescription for an ADHD treatment). However, in cases
where the earliest ADHD-related treatment code in a patient’s record precedes the earliest ADHD diagnostic code, the year in
which the first ADHD treatment occurred will be classed as the incident ‘diagnostic’ event.
The incidence of ADHD amongst the CPRD population during a given year will be calculated using the following equation:
Incidence of ADHD = Number of incident cases in year X
in year X Person years at risk in CPRD in year X
(per person year)*
*depending on figures involved, may be expressed per 1000, per 10,000 or per 100,000 person years
Sample size/power calculation
An earlier study carried out using CPRD, with a case definition broadly similar to that proposed by this study, identified an
initial cohort of 3229 ADHD patients in 1998. The study also found that ADHD incidence rates rose year on year until 2007.
Since that study was carried out, CPRD has expanded to include patient data from more general practices; as of January 2014,
CPRD held data for 680 ‘up to standard’ practices and contained research standard data for over 13 million patients (CPRD,
2014). Taking these factors into consideration, it would be expected that a sample of several thousand ADHD patients will be
identified by this study.
Selection of comparison group(s) or controls
A comparison/control group will not be utilised during the study. Total population sizes will be used in the calculation of
disease incidence.
Use of linked data
1. Index of Multiple Deprivation (IMD)
This study will seek to ascertain if there is any association between ADHD and socioeconomic status. The Index of Multiple
Deprivation (IMD) is a relative measure of socioeconomic deprivation in an area based on several indicators of deprivation
(such as income, crime level and employment status). IMD scores are available for all general practices within CPRD, based on
the lower layer super output area (LSOA) in which they are sited. These ‘practice-level’ IMD scores will initially be used as a
surrogate measure of patients’ deprivation status, as it would be expected that patients would generally reside in the area
local to their general practice. Therefore the study will initially assess if there is an association between practice-level IMD
score and ADHD incidence.
However, an IMD score based on patients' own residential postcode (obtained via data linkage) is obviously a more accurate
reflection of patients' deprivation status. These ‘patient-level’ IMD scores are available for approximately 70% of English
practices (covering just over 50% of all patients in CPRD). These scores will be requested for the subset of ADHD patients for
whom patient-level IMD decile is available. This will serve as a sensitivity analysis, establishing if practice-level IMD scores
provide an accurate reflection of patient-level IMD scores.
2. Outpatient Hospital Episode Statistics (HES)
According to NICE’s guidance on the diagnosis and management of ADHD, the management of ADHD may be shared by
primary and secondary care. However, it is stipulated that diagnosis should only be made by a specialist psychiatrist,
paediatrician or other healthcare professional with expertise in the diagnosis of ADHD. It would be envisaged that, in many
cases, this would involve referring patients with suspected ADHD to a hospital setting. By requesting linked HES data, it will be
possible to establish if English patients attended hospital and received a diagnosis of ADHD following consultation with
secondary care specialists. Patients with secondary care involvement in their ADHD management would have an outpatient
consultation record containing an ICD-10 code relevant to ADHD.
Data/Statistical Analysis Plan
Data will be extracted from CPRD, and descriptive analysis will be performed using STATA version 13.
Annual incidence rates will be expressed by dividing the number of new ADHD cases in a specific year by the number of
person-years at risk in CPRD during that year. Incidence rates will be stratified according to patient gender, age group (0-6, 7-
12, 13-18 years), registered GP region and deprivation (IMD) decile.
Proportions of ‘diagnosed, untreated’ and ‘diagnosed, pharmacologically-treated’ patients will be ascertained and presented.
These will be stratified according to patient gender, age group (0-6, 7-12, 13-18 years), registered GP region and deprivation
(IMD) decile.
The number of patients receiving a prescription for each of the four licensed ADHD treatments will be presented for each year
2004-2013.
Logistic regression will be used to assess the relative effect that gender, GP region and deprivation decile has on the
presence/absence of ADHD. Results will be expressed as odds ratios with 95% confidence intervals, significance will be set at
p= ≤0.05. A study period analysis will be performed using data for the whole ‘at risk’ population between 1/1/2004 and
31/12/2013.
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Sensitivity analysis will be performed to assess if the diagnostic definitions of ADHD chosen have an impact on the number of
cases identified. Diagnosed, untreated cases are required to have at least one Read code indicating a diagnosis of ADHD
recorded in their records during the study period. It will be assessed whether increasing this requirement to a minimum of
two codes has an impact on the number of cases identified.
Missing data and confounding
Only subjects with complete, ‘up to standard’ data will be included in the study. The sensitivity analyses described above will
be used to assess if methodological decisions taken by this study have a confounding effect on its results.
Limitations of the study design, data sources and analytic methods:
CPRD does not directly link prescriptions for drugs with their indication for use (whether this use is licensed or unlicensed). As
such, it will not be possible to determine with absolute certainty that drugs are being prescribed to treat specifically ADHD.
However, our case definition criteria should help reduce misidentifications.
This study will identify and discern between ADHD patients who received pharmacological treatment from their GPs, and
ADHD patients who received no pharmacological treatment from their GPs (‘diagnosed, untreated cases of ADHD’). It is
possible that, in some instances, ‘untreated’ patients will have received pharmacological treatment elsewhere (eg secondary
care). This ‘outside prescribing’ will be difficult to detect through CPRD, and may give a misleading impression as to what
proportion of ADHD patients are pharmacologically treated.
Only around 70% of English general practices within CPRD have consented to participate in patient-level CPRD data linkage.
As such, IMD scores based on patient postcode will only accessible for ADHD patients at this subset of general practices.
Plans for disseminating and communicating study results
The study’s findings will add to the existing knowledge base regarding ADHD in the UK. The aim will be to present the findings
of this research in high impact peer-reviewed journals and at scientific conferences. Potential ‘target’ journals include the
British Journal of Psychiatry, BMC Psychiatry and BMC Pediatrics. The papers produced will also contribute to my PhD thesis.
Appendix 1: Read codes indicating a diagnosis of ADHD
medcode readcode desc
9972 E2E..11 Overactive child syndrome
3775 E2E..00 Childhood hyperkinetic syndrome
5565 E2E0.00 Child attention deficit disorder*
34199 E2E0000 Attention deficit without hyperactivity*
9715 E2E0100 Attention deficit with hyperactivity*
20467 E2E0z00 Child attention deficit disorder NOS*
58069 E2E1.00 Hyperkinesis with developmental delay
45263 E2E2.00 Hyperkinetic conduct disorder
25469 E2Ey.00 Other hyperkinetic manifestation
41769 E2Ez.00 Hyperkinetic syndrome NOS
1458 Eu90.00 [X]Hyperkinetic disorders
6512 Eu90000 [X]Disturbance of activity and attention
6519 Eu90011 [X]Attention deficit hyperactivity disorder*
33505 Eu90100 [X]Hyperkinetic conduct disorder
45799 Eu90111 [X]Hyperkinetic disorder associated with conduct disorder
55322 Eu90200 [X]Deficits in attention, motor control and perception
6510 Eu90y00 [X]Other hyperkinetic disorders
50015 Eu90z00 [X]Hyperkinetic disorder, unspecified
97421 Eu90z11 [X]Hyperkinetic reaction of childhood or adolescence NOS
96770 Eu90z12 [X]Hyperkinetic syndrome NOS
26285 Eu9y700 [X]Attention deficit disorder*
37994 ZS9..00 Disorders of attention and motor control
28543 ZS91.00 Attention deficit disorder*
24808 ZS91.11 ADD - Attention deficit disorder*
24753 ZS91.12 [X]Attention deficit disorder*
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37894 ZS94.00 Minimal brain dysfunction
61701 ZS94.11 MBD - Minimal brain dysfunction
10918 1P00.00 Hyperactive behaviour
39920 ZS93.00 Deficits in attention motor control and perception
35161 ZS93.11 DAMP - Deficits in attention motor control and perception
Attention deficit hyperactivity disorder has been known by a number of official names historically including ‘minimal brain
dysfunction’, ‘hyperkinetic reaction of childhood’ and ‘attention deficit disorder with or without hyperactivity’. Furthermore,
current NICE guidance relating to ADHD (a disorder listed by the Diagnostic and Statistical Manual of Mental Disorders/DSM)
acknowledges that it is analogous to hyperkinetic disorder, a diagnosis currently listed by the International Classification of
Diseases revision 10 (ICD-10). Hyperkinetic disorder itself may be described using more than one diagnostic term. For example,
it may exist alongside conduct disorder; ‘hyperkinetic conduct disorder’ and ‘hyperkinetic disorder associated with conduct
disorder’ are two terms that could be applied to such patients. As such, the list of 30 codes selected to denote a diagnosis of
ADHD was compiled to comprehensively encompass historical and contemporary terms that may be applied to patients with
symptoms of ADHD. This measure was designed to ensure that no cases of ADHD were missed, and is in line with at least one
previous GPRD study which used 51 codes in total (Wong et al., 2009).
It is envisaged that the majority of patients identified will have been assigned a diagnostic term featuring the keywords
‘attention deficit’, in line with the common, contemporary name for the disorder. As shown above(*), there are nine codes
associated with diagnostic terms featuring the keywords ‘attention deficit’. The number of patients with these nine diagnostic
codes will be compared to the total number of patients with any of the 30 codes listed. This will serve as a sensitivity analysis.
It will gauge if the large number of codes chosen to signify a diagnosis of ADHD has an appreciable impact on the number of
cases identified. We have also consulted with members of our Centre for Primary Care at the University of Manchester who
feel that this is an appropriate approach to take.
Appendix 2: Product codes for drugs of interest
prodcode productname
6643 Atomoxetine 40mg capsules
6644 Atomoxetine 60mg capsules
6645 Atomoxetine 25mg capsules
7100 Atomoxetine 10mg capsules
14129 Atomoxetine 18mg capsules
40279 Atomoxetine 80mg capsules
55635 Atomoxetine 100mg capsules
14119 Strattera 10mg capsules (Eli Lilly and Company Ltd)
16949 Strattera 25mg capsules (Eli Lilly and Company Ltd)
17014 Strattera 40mg capsules (Eli Lilly and Company Ltd)
17588 Strattera 60mg capsules (Eli Lilly and Company Ltd)
18832 Strattera 18mg capsules (Eli Lilly and Company Ltd)
41492 Strattera 80mg capsules (Eli Lilly and Company Ltd)
59365 Strattera 100mg capsules (Eli Lilly and Company Ltd)
55169 Lisdexamfetamine 50mg capsules
55987 Lisdexamfetamine 30mg capsules
57786 Lisdexamfetamine 70mg capsules
55747 Elvanse 30mg capsules (Shire Pharmaceuticals Ltd)
56336 Elvanse 50mg capsules (Shire Pharmaceuticals Ltd)
56576 Elvanse 30mg capsules (Shire Pharmaceuticals Ltd)
56742 Elvanse 70mg capsules (Shire Pharmaceuticals Ltd)
7101 Methylphenidate 5mg tablets
576 Methylphenidate 10mg tablets
11733 Methylphenidate 20mg tablets
2679 Ritalin 10mg tablets (Novartis Pharmaceuticals UK Ltd)
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56713 Ritalin-SR 20mg tablets (Imported (United States))
5810 Concerta XL 18mg tablets (Janssen-Cilag Ltd)
5811 Concerta XL 36mg tablets (Janssen-Cilag Ltd)
35159 Concerta XL 27mg tablets (Janssen-Cilag Ltd)
58678 Concerta 54mg modified-release tablets (Imported (Belgium))
6107 Methylphenidate 18mg modified-release tablets
6169 Methylphenidate 36mg modified-release tablets
35469 Methylphenidate 27mg modified-release tablets
52233 Methylphenidate 54mg modified-release tablets
54504 Methylphenidate 20mg modified-release tablets
6868 Equasym XL 20mg capsules (Shire Pharmaceuticals Ltd)
14331 Equasym XL 30mg capsules (Shire Pharmaceuticals Ltd)
14346 Equasym XL 10mg capsules (Shire Pharmaceuticals Ltd)
13914 Equasym 5mg tablets (Shire Pharmaceuticals Ltd)
52461 Equasym XL 10mg capsules (Waymade Healthcare Plc)
53527 Equasym XL 30mg capsules (Waymade Healthcare Plc)
21399 Equasym xl 20mg Capsule (Celltech Pharma Europe Ltd)
54804 Equasym XL 10mg capsules (DE Pharmaceuticals)
11536 Methylphenidate 20mg modified-release capsules
13212 Methylphenidate 10mg modified-release capsules
14848 Methylphenidate 30mg modified-release capsules
35515 Methylphenidate 40mg modified-release capsules
46607 Methylphenidate 5mg modified-release capsules
35658 Medikinet XL 30mg capsules (Flynn Pharma Ltd)
35659 Medikinet XL 20mg capsules (Flynn Pharma Ltd)
36628 Medikinet XL 10mg capsules (Flynn Pharma Ltd)
37658 Medikinet XL 40mg capsules (Flynn Pharma Ltd)
46593 Medikinet XL 5mg capsules (Flynn Pharma Ltd)
36910 Medikinet 20mg tablets (Flynn Pharma Ltd)
37097 Medikinet 5mg tablets (Flynn Pharma Ltd)
37237 Medikinet 10mg tablets (Flynn Pharma Ltd)
23161 Tranquilyn 5mg tablets (Genesis Pharmaceuticals Ltd)
23173 Tranquilyn 10mg tablets (Genesis Pharmaceuticals Ltd)
57405 Methylphenidate 5mg/5ml oral solution
58691 Methylphenidate 10mg/5ml oral solution
9738 Dexamfetamine 5mg tablets
14512 Dexedrine 5mg tablets (Auden McKenzie (Pharma Division) Ltd)
47481 Dexamfetamine 10mg modified-release capsules
47679 Dexamfetamine 15mg modified-release capsules
16185 Dexamfetamine 15mg modified-release capsules
47609 Dexamfetamine 5mg modified-release capsules
31623 Dexedrine 15mg Spansules (Imported (United States))
18996 Durophet 20mg Capsule (3M Health Care Ltd)
18998 Durophet 7.5mg Capsule (3M Health Care Ltd)
24116 Durophet 12.5mg Capsule (3M Health Care Ltd)
47099 Dexamfetamine with amfetamine 10mg with 10mg modified-release capsules
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55495 Dexamfetamine with amfetamine 10mg with 10mg capsules
49392 Amfetamine 10mg / Dexamfetamine 10mg modified-release capsules
51453 Dexamfetamine 5mg/5ml oral solution
13238 Dexamfetamine 1mg/ml oral liquid
Appendix 3: ICD-10 codes indicating a diagnosis of ADHD
F90 Hyperkinetic disorders
A group of disorders characterized by an early onset (usually in the first five years of life), lack of persistence in activities that
require cognitive involvement, and a tendency to move from one activity to another without completing any one, together
with disorganized, ill-regulated, and excessive activity. Several other abnormalities may be associated. Hyperkinetic children
are often reckless and impulsive, prone to accidents, and find themselves in disciplinary trouble because of unthinking
breaches of rules rather than deliberate defiance. Their relationships with adults are often socially disinhibited, with a lack of
normal caution and reserve. They are unpopular with other children and may become isolated. Impairment of cognitive
functions is common, and specific delays in motor and language development are disproportionately frequent. Secondary
complications include dissocial behaviour and low self-esteem.
Excl.: anxiety disorders (F41.-)
mood [affective] disorders (F30-F39)
pervasive developmental disorders (F84.-)
schizophrenia (F20.-)
F90.0 Disturbance of activity and attention
Attention deficit:
disorder with hyperactivity
hyperactivity disorder
syndrome with hyperactivity
Excl.: hyperkinetic disorder associated with conduct disorder (F90.1)
F90.1 Hyperkinetic conduct disorder
Hyperkinetic disorder associated with conduct disorder
F90.8 Other hyperkinetic disorders
F90.9 Hyperkinetic disorder, unspecified
Hyperkinetic reaction of childhood or adolescence NOS
Hyperkinetic syndrome NOS
References
CPRD (2014). Release notes - CPRD GOLD – January 2014.
Hjern, A., Weitoft, G. R., & Lindblad, F. (2010). Social adversity predicts ADHD-medication in school children--a national cohort
study. Acta paediatrica (Oslo, Norway : 1992), 99(6), 920–4. doi:10.1111/j.1651-2227.2009.01638.x
Holden, S. E., Jenkins-Jones, S., Poole, C. D., Morgan, C. L., Coghill, D., & Currie, C. J. (2013). The prevalence and incidence,
resource use and financial costs of treating people with attention deficit/hyperactivity disorder (ADHD) in the United Kingdom
(1998 to 2010). Child and adolescent psychiatry and mental health, 7(1), 34. doi:10.1186/1753-2000-7-34
Kooij, S. J. J., Bejerot, S., Blackwell, A., Caci, H., Casas-Brugué, M., Carpentier, P. J., Edvinsson, D., et al. (2010). European
consensus statement on diagnosis and treatment of adult ADHD: The European Network Adult ADHD. BMC psychiatry, 10, 67.
Lakhan, S. E., & Kirchgessner, A. (2012). Prescription stimulants in individuals with and without attention deficit hyperactivity
disorder: misuse, cognitive impact, and adverse effects. Brain and behavior, 2(5), 661–77. doi:10.1002/brb3.78
McCarthy, S., Wilton, L., Murray, M. L., Hodgkins, P., Asherson, P., & Wong, I. C. K. (2012b). The epidemiology of
pharmacologically treated attention deficit hyperactivity disorder (ADHD) in children, adolescents and adults in UK primary
care. BMC pediatrics, 12(1), 78. doi:10.1186/1471-2431-12-78
Nomura, Y., Marks, D. J., Grossman, B., Yoon, M., Loudon, H., Stone, J., & Halperin, J. M. (2012). Exposure to gestational
diabetes mellitus and low socioeconomic status: effects on neurocognitive development and risk of attention-
deficit/hyperactivity disorder in offspring. Archives of pediatrics & adolescent medicine, 166(4), 337–43.
doi:10.1001/archpediatrics.2011.784
Reiss, F. (2013). Socioeconomic inequalities and mental health problems in children and adolescents: a systematic review.
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Rowlingson, B., Lawson, E., Taylor, B., & Diggle, P. J. (2013). Mapping English GP prescribing data: a tool for monitoring health-
service inequalities. BMJ open, 3(1). doi:10.1136/bmjopen-2012-001363
Russell, G., Ford, T., Rosenberg, R., & Kelly, S. (2013). The association of attention deficit hyperactivity disorder with
socioeconomic disadvantage: Alternative explanations and evidence. Journal of Child Psychology and Psychiatry, 1–10.
doi:10.1111/jcpp.12170
198
Amendments – proposed 2/2/2016, approved 9/2/2016
We propose the following amendments:
1. Examination of additional comorbidities
I wish to examine several additional neuropsychiatric comorbidities that are identified as being potentially linked with ADHD
in the literature (namely bipolar depression, anxiety, schizophrenia, conduct disorder and oppositional defiant disorder). In
response to new research suggesting that patients with ADHD are at increased risk of sustaining accidental injuries (Dalsgaard
et al., 2015), I also wish to explore the prevalence of accidental injuries (such as fractures and burns) amongst patients with
ADHD in the UK. To our knowledge, no large scale study has previously examined the link between diagnosed ADHD and the
risk of accidental injury in the UK.
2. Introduction of a control group
The original study protocol aimed to describe the prevalence of neuropsychiatric comorbidities and the prescribing of
psychotropic drugs amongst a cohort of ADHD patients. Selecting a non-ADHD control cohort will allow the relative rates of
neuropsychiatric comorbidity/psychotropic prescribing amongst ADHD and non-ADHD populations to be compared. The
addition of this control group will help highlight if ADHD appears to increase the likelihood of individuals having other
neuropsychiatric disorders/receiving treatment with psychotropics (other than licensed ADHD treatments). Prevalence of
psychiatric comorbidity amongst cases and controls will be compared using chi squared tests to assess if the proportion of
ADHD patients receiving neuropsychiatric diagnoses/psychotropic treatments was significantly higher than their non-ADHD
counterparts, and logistic regression will be used to assess if certain demographic characteristics (such as gender, GP region
and deprivation decile) impact on patients likelihood of neuropsychiatric comorbidity.
Likewise, the addition of a control group will allow the relative rates of accidental injury amongst ADHD and non-ADHD
populations to be compared to assess if ADHD patients sustained significantly more accidental injuries per unit-time than
their non-ADHD counterparts. Again, chi squared tests will be used to assess if the proportion of ADHD patients sustaining
accidental injuries was significantly higher than their non-ADHD counterparts; logistic regression will be used to assess if
certain demographic characteristics (such as gender, GP region and deprivation decile) impact on patients likelihood of
accidental injury.
Control patients are defined as patients with no recorded diagnosis of ADHD prior to the end of the study period
(31/12/2013). The control cohort selected will be matched to the ADHD cohort by gender, practice and year of birth. The aim
will be to select up to ten control individuals for every ADHD patient identified (if possible). For this control cohort HES data
will be requested, to ascertain if any neuropsychiatric disorders/fractures/burns were identified in secondary care. HES data
will be requested for the proportion of ADHD patients for whom it is available.
Additional reference: Dalsgaard, S., Leckman, J. F., Mortensen, P. B., Nielsen, H. S., & Simonsen, M. (2015). Effect of drugs on
the risk of injuries in children with attention deficit hyperactivity disorder: a prospective cohort study. The Lancet Psychiatry,
2(8), 702–709. doi:10.1016/S2215-0366(15)00271-0
199
Appendix 2: Read codes used to identify patients with ADHD
Medical code
Read code
Read term
24753 ZS91.12 [X]Attention deficit disorder
26285 Eu9y700 [X]Attention deficit disorder
6519 Eu90011 [X]Attention deficit hyperactivity disorder
55322 Eu90200 [X]Deficits in attention, motor control and perception
6512 Eu90000 [X]Disturbance of activity and attention
33505 Eu90100 [X]Hyperkinetic conduct disorder
45799 Eu90111 [X]Hyperkinetic disorder associated with conduct disorder
50015 Eu90z00 [X]Hyperkinetic disorder, unspecified
1458 Eu90.00 [X]Hyperkinetic disorders
97421 Eu90z11 [X]Hyperkinetic reaction of childhood or adolescence NOS
96770 Eu90z12 [X]Hyperkinetic syndrome NOS
6510 Eu90y00 [X]Other hyperkinetic disorders
24808 ZS91.11 ADD - Attention deficit disorder
28543 ZS91.00 Attention deficit disorder
9715 E2E0100 Attention deficit with hyperactivity
34199 E2E0000 Attention deficit without hyperactivity
5565 E2E0.00 Child attention deficit disorder
20467 E2E0z00 Child attention deficit disorder NOS
3775 E2E..00 Childhood hyperkinetic syndrome
35161 ZS93.11 DAMP - Deficits in attention motor control and perception
39920 ZS93.00 Deficits in attention motor control and perception
37994 ZS9..00 Disorders of attention and motor control
10918 1P00.00 Hyperactive behaviour
58069 E2E1.00 Hyperkinesis with developmental delay
45263 E2E2.00 Hyperkinetic conduct disorder
41769 E2Ez.00 Hyperkinetic syndrome NOS
61701 ZS94.11 MBD - Minimal brain dysfunction
37894 ZS94.00 Minimal brain dysfunction
25469 E2Ey.00 Other hyperkinetic manifestation
9972 E2E..11 Overactive child syndrome
200
Appendix 3: Product codes used to identify patients who were prescribed a medication licensed for the treatment of ADHD (methylphenidate, atomoxetine,
dexamfetamine, lisdexamfetamine)
Product code
Product name Drug substance
6643 Atomoxetine 40mg capsules, atomoxetine
6644 Atomoxetine 60mg capsules, atomoxetine
6645 Atomoxetine 25mg capsules, atomoxetine
7100 Atomoxetine 10mg capsules, atomoxetine
14129 Atomoxetine 18mg capsules, atomoxetine
40279 Atomoxetine 80mg capsules, atomoxetine
55635 Atomoxetine 100mg capsules, atomoxetine
14119 Strattera 10mg capsules (Eli Lilly and Company Ltd), atomoxetine
16949 Strattera 25mg capsules (Eli Lilly and Company Ltd), atomoxetine
17014 Strattera 40mg capsules (Eli Lilly and Company Ltd), atomoxetine
17588 Strattera 60mg capsules (Eli Lilly and Company Ltd), atomoxetine
18832 Strattera 18mg capsules (Eli Lilly and Company Ltd), atomoxetine
41492 Strattera 80mg capsules (Eli Lilly and Company Ltd), atomoxetine
59365 Strattera 100mg capsules (Eli Lilly and Company Ltd), atomoxetine
55169 Lisdexamfetamine 50mg capsules, lisdexamfetamine
55987 Lisdexamfetamine 30mg capsules, lisdexamfetamine
57786 Lisdexamfetamine 70mg capsules, lisdexamfetamine
55747 Elvanse 30mg capsules (Shire Pharmaceuticals Ltd), lisdexamfetamine
56336 Elvanse 50mg capsules (Shire Pharmaceuticals Ltd), lisdexamfetamine
56576 Elvanse 30mg capsules (Shire Pharmaceuticals Ltd), lisdexamfetamine
56742 Elvanse 70mg capsules (Shire Pharmaceuticals Ltd), lisdexamfetamine
7101 Methylphenidate 5mg tablets, methylphenidate
576 Methylphenidate 10mg tablets, methylphenidate
11733 Methylphenidate 20mg tablets, methylphenidate
2679 Ritalin 10mg tablets (Novartis Pharmaceuticals UK Ltd), methylphenidate
56713 Ritalin-SR 20mg tablets (Imported (United States)), methylphenidate
5810 Concerta XL 18mg tablets (Janssen-Cilag Ltd), methylphenidate
5811 Concerta XL 36mg tablets (Janssen-Cilag Ltd), methylphenidate
35159 Concerta XL 27mg tablets (Janssen-Cilag Ltd), methylphenidate
58678 Concerta 54mg modified-release tablets (Imported (Belgium)), methylphenidate
6107 Methylphenidate 18mg modified-release tablets, methylphenidate
6169 Methylphenidate 36mg modified-release tablets, methylphenidate
35469 Methylphenidate 27mg modified-release tablets, methylphenidate
52233 Methylphenidate 54mg modified-release tablets, methylphenidate
54504 Methylphenidate 20mg modified-release tablets, methylphenidate
6868 Equasym XL 20mg capsules (Shire Pharmaceuticals Ltd), methylphenidate
14331 Equasym XL 30mg capsules (Shire Pharmaceuticals Ltd), methylphenidate
14346 Equasym XL 10mg capsules (Shire Pharmaceuticals Ltd), methylphenidate
13914 Equasym 5mg tablets (Shire Pharmaceuticals Ltd), methylphenidate
52461 Equasym XL 10mg capsules (Waymade Healthcare Plc), methylphenidate
53527 Equasym XL 30mg capsules (Waymade Healthcare Plc), methylphenidate
21399 Equasym xl 20mg Capsule (Celltech Pharma Europe Ltd), methylphenidate
54804 Equasym XL 10mg capsules (DE Pharmaceuticals), methylphenidate
201
11536 Methylphenidate 20mg modified-release capsules, methylphenidate
13212 Methylphenidate 10mg modified-release capsules, methylphenidate
14848 Methylphenidate 30mg modified-release capsules, methylphenidate
35515 Methylphenidate 40mg modified-release capsules, methylphenidate
46607 Methylphenidate 5mg modified-release capsules, methylphenidate
35658 Medikinet XL 30mg capsules (Flynn Pharma Ltd), methylphenidate
35659 Medikinet XL 20mg capsules (Flynn Pharma Ltd), methylphenidate
36628 Medikinet XL 10mg capsules (Flynn Pharma Ltd), methylphenidate
37658 Medikinet XL 40mg capsules (Flynn Pharma Ltd), methylphenidate
46593 Medikinet XL 5mg capsules (Flynn Pharma Ltd), methylphenidate
36910 Medikinet 20mg tablets (Flynn Pharma Ltd), methylphenidate
37097 Medikinet 5mg tablets (Flynn Pharma Ltd), methylphenidate
37237 Medikinet 10mg tablets (Flynn Pharma Ltd), methylphenidate
23161 Tranquilyn 5mg tablets (Genesis Pharmaceuticals Ltd), methylphenidate
23173 Tranquilyn 10mg tablets (Genesis Pharmaceuticals Ltd), methylphenidate
57405 Methylphenidate 5mg/5ml oral solution, methylphenidate
58691 Methylphenidate 10mg/5ml oral solution, methylphenidate
9738 Dexamfetamine 5mg tablets, dexamfetamine
14512 Dexedrine 5mg tablets (Auden McKenzie (Pharma Division) Ltd), dexamfetamine
47481 Dexamfetamine 10mg modified-release capsules, dexamfetamine
47679 Dexamfetamine 15mg modified-release capsules, dexamfetamine
16185 Dexamfetamine 15mg modified-release capsules, dexamfetamine
47609 Dexamfetamine 5mg modified-release capsules, dexamfetamine
31623 Dexedrine 15mg Spansules (Imported (United States)), dexamfetamine
18996 Durophet 20mg Capsule (3M Health Care Ltd), dexamfetamine
18998 Durophet 7.5mg Capsule (3M Health Care Ltd), dexamfetamine
24116 Durophet 12.5mg Capsule (3M Health Care Ltd), dexamfetamine
47099 Dexamfetamine with amfetamine 10mg with 10mg modified-release capsules, dexamfetamine
55495 Dexamfetamine with amfetamine 10mg with 10mg capsules, dexamfetamine
49392 Amfetamine 10mg / Dexamfetamine 10mg modified-release capsules, dexamfetamine
51453 Dexamfetamine 5mg/5ml oral solution, dexamfetamine
13238 Dexamfetamine 1mg/ml oral liquid, dexamfetamine
202
Appendix 4: Read and ICD-10 codes used in the identification of comorbidities of interest
Note: all codes with a * were observed to occur in the electronic healthcare record of at least one individual
Medical code
Read code Read term Comorbidity
1276 E140.12 autism* Autism/ASD 2950 Eu84500 [x]asperger's syndrome* Autism/ASD 3637 Eu84000 [x]childhood autism* Autism/ASD 7302 E140.13 childhood autism* Autism/ASD 9982 Eu84011 [x]autistic disorder* Autism/ASD 22098 E140.00 infantile autism* Autism/ASD 24044 Eu84100 [x]atypical autism* Autism/ASD 36662 E140z00 infantile autism nos* Autism/ASD 42941 Eu84z11 [x]autistic spectrum disorder* Autism/ASD 50337 Eu84012 [x]infantile autism* Autism/ASD 34174 Eu84112 [x]mental retardation with autistic features Autism/ASD 51375 Eu84511 [x]autistic psychopathy Autism/ASD 63251 E140000 active infantile autism Autism/ASD 69016 E140100 residual infantile autism Autism/ASD 43444 E140.11 kanner's syndrome Autism/ASD 24244 E14y000 atypical childhood psychoses Autism/ASD 61304 Eu84013 [x]infantile psychosis Autism/ASD 24062 Eu84111 [x]atypical childhood psychosis Autism/ASD 59285 Eu84512 [x]schizoid disorder of childhood Autism/ASD 131 1B13.00 anxiousness* Anxiety 462 E200111 panic attack* Anxiety 636 E200.00 anxiety states* Anxiety 655 E200300 anxiety with depression* Anxiety 1758 E200400 chronic anxiety* Anxiety 3076 E202100 agoraphobia with panic attacks* Anxiety 3407 1466 h/o: anxiety state* Anxiety 4069 E200100 panic disorder* Anxiety 4534 E200z00 anxiety state nos* Anxiety 4659 E200200 generalised anxiety disorder* Anxiety 5385 Eu41.00 [x]other anxiety disorders* Anxiety 5902 1B13.11 anxiousness - symptom* Anxiety 6221 E292000 separation anxiety disorder* Anxiety 6408 Eu41011 [x]panic attack* Anxiety 6939 E200000 anxiety state unspecified* Anxiety 9386 Eu40.00 [x]phobic anxiety disorders* Anxiety 10344 Eu41100 [x]generalized anxiety disorder* Anxiety 11890 1B1V.00 c/o - panic attack* Anxiety 11913 Eu41200 [x]mixed anxiety and depressive disorder* Anxiety 19000 225J.00 o/e - panic attack* Anxiety 23838 Eu41z00 [x]anxiety disorder, unspecified* Anxiety 28167 Eu41y11 [x]anxiety hysteria* Anxiety 29907 Eu93200 [x]social anxiety disorder of childhood* Anxiety 93401 1B13.12 anxious* Anxiety 962 Eu41111 [x]anxiety neurosis Anxiety 4081 Eu41012 [x]panic state Anxiety 4634 E200500 recurrent anxiety Anxiety 7749 Eu41211 [x]mild anxiety depression Anxiety 7999 Z4L1.00 anxiety counselling Anxiety 8205 Eu41000 [x]panic disorder [episodic paroxysmal anxiety] Anxiety 8424 Eu60600 [x]anxious [avoidant] personality disorder Anxiety 9125 8G94.00 anxiety management training Anxiety 11940 E280.00 acute panic state due to acute stress reaction Anxiety 13124 2258 o/e - anxious Anxiety 14890 Eu40012 [x]panic disorder with agoraphobia Anxiety 15220 Eu34114 [x]persistant anxiety depression Anxiety 18032 Eu93000 [x]separation anxiety disorder of childhood Anxiety 22159 Z4I7.00 acknowledging anxiety Anxiety 24066 Eu41y00 [x]other specified anxiety disorders Anxiety 24351 Eu93100 [x]phobic anxiety disorder of childhood Anxiety 25638 Eu41z11 [x]anxiety nos Anxiety 26295 Z4I7211 reducing anxiety Anxiety 27685 Eu40y00 [x]other phobic anxiety disorders Anxiety 28381 Z4I7200 alleviating anxiety Anxiety 28925 8HHp.00 referral for guided self-help for anxiety Anxiety 31522 E2D0.00 disturbance of anxiety and fearfulness childhood/adolescent Anxiety 34064 Eu40z00 [x]phobic anxiety disorder, unspecified Anxiety 35594 E2D0z00 disturbance anxiety and fearfulness childhood/adolescent nos Anxiety 35619 E2D0000 childhood and adolescent overanxiousness disturbance Anxiety 35825 Eu41112 [x]anxiety reaction Anxiety 44321 Eu41300 [x]other mixed anxiety disorders Anxiety 50191 Eu41113 [x]anxiety state Anxiety 61430 Eu93y12 [x]childhood overanxious disorder Anxiety 62935 Z4I7100 recognising anxiety Anxiety
203
107410 173f.00 anxiety about breathlessness Anxiety 573 F25..00 epilepsy* Epilepsy 988 F251000 grand mal (major) epilepsy* Epilepsy 1715 F250011 epileptic absences* Epilepsy 2907 F250000 petit mal (minor) epilepsy* Epilepsy 3175 F254000 temporal lobe epilepsy* Epilepsy 3607 F25.z.11 fit (in known epileptic) nos* Epilepsy 3783 1473 h/o: epilepsy* Epilepsy 4093 F253.11 status epilepticus* Epilepsy 4478 F256.00 infantile spasms* Epilepsy 4602 667b.00 nocturnal epilepsy* Epilepsy 4801 F251300 epileptic seizures - myoclonic* Epilepsy 5117 F253.00 grand mal status* Epilepsy 5152 F251400 epileptic seizures - tonic* Epilepsy 5525 F255011 focal epilepsy* Epilepsy 5668 F251600 grand mal seizure* Epilepsy 6271 F25X.00 status epilepticus, unspecified* Epilepsy 7809 2823 o/e - petit mal fit* Epilepsy 7945 F256000 hypsarrhthymia* Epilepsy 8097 2828 absence seizure* Epilepsy 8187 F251500 tonic-clonic epilepsy* Epilepsy 9747 F25z.00 epilepsy nos* Epilepsy 9887 F25y200 locl-rlt(foc)(part)idiop epilep&epilptic syn seiz locl onset* Epilepsy 9979 F25yz00 other forms of epilepsy nos* Epilepsy 11186 F250.00 generalised nonconvulsive epilepsy* Epilepsy 11394 F254500 complex partial epileptic seizure* Epilepsy 17399 F250400 juvenile absence epilepsy* Epilepsy 18471 F251200 epileptic seizures - clonic* Epilepsy 19170 F25y400 benign rolandic epilepsy* Epilepsy 19363 F25a.00 juvenile myoclonic epilepsy* Epilepsy 22341 1O30.00 epilepsy confirmed* Epilepsy 22804 F251011 tonic-clonic epilepsy* Epilepsy 24309 F250200 epileptic seizures - atonic* Epilepsy 25330 F25y300 complex partial status epilepticus* Epilepsy 26015 F255.00 partial epilepsy without impairment of consciousness* Epilepsy 26144 F251.00 generalised convulsive epilepsy* Epilepsy 26733 F255y00 partial epilepsy without impairment of consciousness os* Epilepsy 30635 F25F.00 photosensitive epilepsy* Epilepsy 31830 F250300 epileptic seizures - akinetic* Epilepsy 31920 F254z00 partial epilepsy with impairment of consciousness nos* Epilepsy 32288 F254.00 partial epilepsy with impairment of consciousness* Epilepsy 34792 F250500 lennox-gastaut syndrome* Epilepsy 37644 F132100 progressive myoclonic epilepsy* Epilepsy 37782 F251100 neonatal myoclonic epilepsy* Epilepsy 38307 F25y.00 other forms of epilepsy* Epilepsy 40105 F255600 simple partial epileptic seizure* Epilepsy 40806 F251z00 generalised convulsive epilepsy nos* Epilepsy 49322 F256z00 infantile spasms nos* Epilepsy 96641 F25y500 panayiotopoulos syndrome* Epilepsy 4109 SC20000 traumatic epilepsy Epilepsy 6709 Eu05y11 [x]epileptic psychosis nos Epilepsy 9569 F255000 jacksonian, focal or motor epilepsy Epilepsy 9886 F252.00 petit mal status Epilepsy 22991 667N.00 epilepsy severity Epilepsy 23415 F256100 salaam attacks Epilepsy 23634 F254100 psychomotor epilepsy Epilepsy 27526 F255z00 partial epilepsy without impairment of consciousness nos Epilepsy 30604 F25b.00 alcohol-induced epilepsy Epilepsy 30816 F25C.00 drug-induced epilepsy Epilepsy 31877 Eu05212 [x]schizophrenia-like psychosis in epilepsy Epilepsy 34079 F254400 epileptic automatism Epilepsy 36203 F254200 psychosensory epilepsy Epilepsy 37592 F255200 somatosensory epilepsy Epilepsy 37906 F259.00 early infant epileptic encephalopathy with suppression bursts Epilepsy 38919 1b1W.00 transient epileptic amnesia Epilepsy 39023 F256.12 west syndrome Epilepsy 39530 2824.11 o/e - jacksonian fit Epilepsy 43679 Eu80300 [x]acquired aphasia with epilepsy [landau - kleffner] Epilepsy 44252 F250z00 generalised nonconvulsive epilepsy nos Epilepsy 45602 F132200 myoclonic encephalopathy Epilepsy 45927 F251y00 other specified generalised convulsive epilepsy Epilepsy 48134 F255100 sensory induced epilepsy Epilepsy 48462 Eu06013 [x]limbic epilepsy personality Epilepsy 49340 F251111 otohara syndrome Epilepsy 49889 ZS82.00 acquired epileptic aphasia Epilepsy 51517 2825 o/e - psychomotor fit Epilepsy 51998 F259.11 ohtahara syndrome Epilepsy 53483 F25y100 gelastic epilepsy Epilepsy 55260 F25y000 cursive (running) epilepsy Epilepsy 55665 F254300 limbic system epilepsy Epilepsy 55739 F255400 visual reflex epilepsy Epilepsy 56359 F25D.00 menstrual epilepsy Epilepsy
204
57277 2824 o/e - focal (jacksonian) fit Epilepsy 59120 Fyu5200 [x]other status epilepticus Epilepsy 59185 F250y00 other specified generalised nonconvulsive epilepsy Epilepsy 59806 ZS82.11 landau-kleffner syndrome Epilepsy 65673 F25E.00 stress-induced epilepsy Epilepsy 65699 F255012 motor epilepsy Epilepsy 68946 F255500 unilateral epilepsy Epilepsy 69831 Fyu5100 [x]other epilepsy Epilepsy 71719 F257.00 kojevnikov's epilepsy Epilepsy 71801 Fyu5900 [x]status epilepticus, unspecified Epilepsy 73542 F255300 visceral reflex epilepsy Epilepsy 98870 F255311 partial epilepsy with autonomic symptoms Epilepsy 99731 Fyu5000 [x]other generalized epilepsy and epileptic syndromes Epilepsy 108409 F25G.00 severe myoclonic epilepsy in infancy Epilepsy 215809 F252.00 petit mal status Epilepsy 224846 F256.11 lightning spasms Epilepsy 99548 F250100 pykno-epilepsy Epilepsy 324 E2B..00 depressive disorder nec* Depression 543 Eu32z11 [x]depression nos* Depression 595 E112.14 endogenous depression* Depression 1131 E204.00 neurotic depression reactive type* Depression 1908 2257 o/e - depressed* Depression 1996 1B17.00 depressed* Depression 2639 E204.11 postnatal depression* Depression 2716 1465 h/o: depression* Depression 2970 Eu32z00 [x]depressive episode, unspecified* Depression 2972 E2B0.00 postviral depression* Depression 3291 Eu32z12 [x]depressive disorder nos* Depression 3292 Eu33.00 [x]recurrent depressive disorder* Depression 4323 E2B1.00 chronic depression* Depression 4639 Eu32.00 [x]depressive episode* Depression 4824 1B17.11 c/o - feeling depressed* Depression 5987 Eu32z14 [x] reactive depression nos* Depression 6482 E113700 recurrent depression* Depression 6546 E112.12 endogenous depression first episode* Depression 6932 E113.11 endogenous depression - recurrent* Depression 6950 E112.13 endogenous depression first episode* Depression 7604 Eu32.13 [x]single episode of reactive depression* Depression 7953 Eu34100 [x]dysthymia* Depression 8584 Eu34111 [x]depressive neurosis* Depression 8928 1BT..11 low mood* Depression 9211 Eu32100 [x]moderate depressive episode* Depression 9667 Eu32200 [x]severe depressive episode without psychotic symptoms* Depression 9796 1B1U.00 symptoms of depression* Depression 10015 1BT..00 depressed mood* Depression 10438 1B1U.11 depressive symptoms* Depression 10610 E112.00 single major depressive episode* Depression 10667 Eu32400 [x]mild depression* Depression 11717 Eu32000 [x]mild depressive episode* Depression 12099 Eu32300 [x]severe depressive episode with psychotic symptoms* Depression 12122 9H91.00 depression medication review* Depression 15155 E112200 single major depressive episode, moderate Depression 16506 E112100 single major depressive episode, mild* Depression 17770 E130.11 psychotic reactive depression* Depression 19439 212S.00 depression resolved* Depression 24112 Eu32313 [x]single episode of psychotic depression* Depression 28970 9hC0.00 excepted from depression quality indicators: patient unsuitable* Depression 29520 Eu33100 [x]recurrent depressive disorder, current episode moderate* Depression 30405 9H92.00 depression interim review* Depression 30483 8CAa.00 patient given advice about management of depression* Depression 32159 E112400 single major depressive episode, severe, with psychosis* Depression 42931 9HA0.00 on depression register* Depression 43239 9hC1.00 excepted from depression quality indicators: informed dissent* Depression 51258 9Ov..00 depression monitoring administration* Depression 71009 9Ov0.00 depression monitoring first letter* Depression 72966 9Ov1.00 depression monitoring second letter* Depression 88644 9Ov3.00 depression monitoring verbal invite* Depression 100977 1JJ..00 suspected depression* Depression 1055 E135.00 agitated depression Depression 1533 E290.00 brief depressive reaction Depression 2560 E11..12 depressive psychoses Depression 2923 62T1.00 puerperal depression Depression 4979 Eu53012 [x]postpartum depression nos Depression 5879 E112.11 agitated depression Depression 6854 Eu32y00 [x]other depressive episodes Depression 7011 E112z00 single major depressive episode nos Depression 7737 Eu34113 [x]neurotic depression Depression 8478 E130.00 reactive depressive psychosis Depression 8851 Eu33.11 [x]recurrent episodes of depressive reaction Depression 8902 Eu33.13 [x]recurrent episodes of reactive depression Depression 9055 Eu32.11 [x]single episode of depressive reaction Depression 9183 E11z200 masked depression Depression
205
10290 Eu34112 [x]depressive personality disorder Depression 10455 E211200 depressive personality disorder Depression 10720 Eu32y11 [x]atypical depression Depression 11252 Eu33212 [x]major depression, recurrent without psychotic symptoms Depression 11329 Eu33211 [x]endogenous depression without psychotic symptoms Depression 12399 9H90.00 depression annual review Depression 12707 E211300 cyclothymic personality disorder Depression 13307 Eu53011 [x]postnatal depression nos Depression 14709 E113200 recurrent major depressive episodes, moderate Depression 15099 E113.00 recurrent major depressive episode Depression 15219 E112300 single major depressive episode, severe, without psychosis Depression 16632 E291.00 prolonged depressive reaction Depression 16861 Eu33315 [x]recurrent severe episodes of psychotic depression Depression 18510 Eu32.12 [x]single episode of psychogenic depression Depression 18702 6G00.00 postnatal depression counselling Depression 19054 Eu3y111 [x]recurrent brief depressive episodes Depression 19696 Eu33.12 [x]recurrent episodes of psychogenic depression Depression 20785 Eu20400 [x]post-schizophrenic depression Depression 21540 Eu34000 [x]cyclothymia Depression 21887 E002100 senile dementia with depression Depression 22116 Eu33400 [x]recurrent depressive disorder, currently in remission Depression 22806 Eu32212 [x]single episode major depression w'out psychotic symptoms Depression 23731 Eu33311 [x]endogenous depression with psychotic symptoms Depression 23854 Eu34013 [x]cyclothymic personality Depression 24117 Eu32311 [x]single episode of major depression and psychotic symptoms Depression 24171 E113400 recurrent major depressive episodes, severe, with psychosis Depression 25563 E113z00 recurrent major depressive episode nos Depression 25697 E113300 recurrent major depressive episodes, severe, no psychosis Depression 26028 1BT..12 sad mood Depression 27491 E11y200 atypical depressive disorder Depression 27677 E001300 presenile dementia with depression Depression 27759 Eu02z16 [x] senile dementia, depressed or paranoid type Depression 28248 Eu32z13 [x]prolonged single episode of reactive depression Depression 28756 Eu33.14 [x]seasonal depressive disorder Depression 28863 Eu32314 [x]single episode of reactive depressive psychosis Depression 29342 E113100 recurrent major depressive episodes, mild Depression 29527 R007z13 [d]postoperative depression Depression 29784 Eu33000 [x]recurrent depressive disorder, current episode mild Depression 30583 9k4..00 depression - enhanced services administration Depression 31757 Eu33314 [x]recurr severe episodes/psychogenic depressive psychosis Depression 32841 8HHq.00 referral for guided self-help for depression Depression 32941 Eu33313 [x]recurr severe episodes/major depression+psychotic symptom Depression 34390 E112000 single major depressive episode, unspecified Depression 35671 E113000 recurrent major depressive episodes, unspecified Depression 36246 E290z00 brief depressive reaction nos Depression 36616 Eu33z11 [x]monopolar depression nos Depression 37764 Eu33316 [x]recurrent severe episodes/reactive depressive psychosis Depression 41022 Eu25112 [x]schizophreniform psychosis, depressive type Depression 41089 E002z00 senile dementia with depressive or paranoid features nos Depression 43292 E004300 arteriosclerotic dementia with depression Depression 43324 E112500 single major depressive episode, partial or unspec remission Depression 44300 Eu33z00 [x]recurrent depressive disorder, unspecified Depression 44674 E002.00 senile dementia with depressive or paranoid features Depression 44848 8BK0.00 depression management programme Depression 44936 9HA1.00 removed from depression register Depression 46244 E02y300 drug-induced depressive state Depression 47731 Eu33y00 [x]other recurrent depressive disorders Depression 48970 9hC..00 exception reporting: depression quality indicators Depression 52678 Eu32312 [x]single episode of psychogenic depressive psychosis Depression 54848 Eu34012 [x]cycloid personality Depression 55384 E113600 recurrent major depressive episodes, in full remission Depression 56273 E113500 recurrent major depressive episodes,partial/unspec remission Depression 56609 Eu32y12 [x]single episode of masked depression nos Depression 57409 E112600 single major depressive episode, in full remission Depression 59386 Eu32213 [x]single episode vital depression w'out psychotic symptoms Depression 65435 9k40.00 depression - enhanced service completed Depression 73991 Eu33214 [x]vital depression, recurrent without psychotic symptoms Depression 85852 9Ov4.00 depression monitoring telephone invite Depression 91105 9Ov2.00 depression monitoring third letter Depression 96995 9kQ..00 on full dose long term treatment depression - enh serv admin Depression 98252 Eu32600 [x]major depression, moderately severe Depression 98346 Eu32500 [x]major depression, mild Depression 98414 Eu32700 [x]major depression, severe without psychotic symptoms Depression 98417 Eu32800 [x]major depression, severe with psychotic symptoms Depression 101401 8ID..00 postnatal depression not discussed Depression 103677 Eu32B00 [x]antenatal depression Depression 2040 E2C0.00 aggressive unsocial conduct disorder CD/ODD 2235 E2C..00 disturbance of conduct nec CD/ODD 3787 Eu91.00 [x]conduct disorders CD/ODD 4919 Eu92.00 [x]mixed disorders of conduct and emotions CD/ODD 6126 Eu91200 [x]socialized conduct disorder CD/ODD 6511 Eu92z00 [x]mixed disorder of conduct and emotions, unspecified CD/ODD
206
17721 E2Cz.00 unspecified disturbance of conduct CD/ODD 23881 E2Dy000 childhood and adolescent oppositional disorder CD/ODD 27724 E2Czz00 disturbance of conduct nos CD/ODD 34977 Eu91z00 [x]conduct disorder, unspecified CD/ODD 35005 Eu91100 [x]unsocialized conduct disorder CD/ODD 35871 Eu91000 [x]conduct disorder confined to the family context CD/ODD 43359 E2C2.00 socialised conduct disorder CD/ODD 45263 E2E2.00 hyperkinetic conduct disorder CD/ODD 49615 Eu91y00 [x]other conduct disorders CD/ODD 72887 Eu91z12 [x]childhood conduct disorder nos CD/ODD 95346 Eu92y11 [x]conduct disorder associated with emotional disorder CD/ODD 103242 Eu92y12 [x]conduct disorder associated with neurotic disorder CD/ODD 33906 Eu91111 [x]conduct disorder, solitary aggressive type CD/ODD 32845 Eu92000 [x]depressive conduct disorder CD/ODD 33505 Eu90100 [x]hyperkinetic conduct disorder CD/ODD 45799 Eu90111 [x]hyperkinetic disorder associated with conduct disorder CD/ODD 7305 Eu92y00 [x]other mixed disorders of conduct and emotions CD/ODD 45603 E294.00 adjustment reaction with disturbance emotion and conduct CD/ODD 104891 E293z00 adjustment reaction with predominant disturbance conduct nos CD/ODD 16415 E293.00 adjustment reaction with predominant disturbance of conduct CD/ODD 24352 E2C0z00 aggressive unsocial conduct disorder nos CD/ODD 41599 E2C4.00 mixed disturbance of conduct and emotion CD/ODD 6121 E2C4z00 mixed disturbance of conduct and emotion nos CD/ODD 46452 E2C1.00 nonaggressive unsocial conduct disorder CD/ODD 20182 E2C1z00 nonaggressive unsocial conduct disorder nos CD/ODD 4911 E2Cy.00 other conduct disturbances CD/ODD 54696 E2Cyz00 other conduct disturbances nos CD/ODD 41842 E2C2z00 socialised conduct disorder nos CD/ODD 23869 E284.00 stress reaction causing mixed disturbance of emotion/conduct CD/ODD 1558 1B24.00 has a tic* Tic/Tourettes 5346 E272.00 tics* Tic/Tourettes 6081 2974.12 o/e - tic* Tic/Tourettes 8012 1B24.11 tic - symptom* Tic/Tourettes 12344 E272300 gilles de la tourette's disorder* Tic/Tourettes 15164 E272000 tic disorder unspecified* Tic/Tourettes 16726 Eu95200 [x]comb vocal multiple motor tic disorder - de la tourette* Tic/Tourettes 21429 Eu95.00 [x]tic disorders* Tic/Tourettes 27544 E272100 transient childhood tic* Tic/Tourettes 27571 E272200 chronic motor tic disorder* Tic/Tourettes 28044 E272z00 tic nos* Tic/Tourettes 42827 Eu95100 [x]chronic motor or vocal tic disorder* Tic/Tourettes 43751 Eu95000 [x]transient tic disorder* Tic/Tourettes 66949 Eu95y00 [x]other tic disorders Tic/Tourettes 44322 Eu95z00 [x]tic disorder, unspecified Tic/Tourettes 49867 2974 o/e - spasm/tic Tic/Tourettes 56972 F133.00 tics of organic origin Tic/Tourettes 694 Eu2z.11 [x]psychosis nos* SMI 854 E10..00 schizophrenic disorders* SMI 1494 E103.00 paranoid schizophrenia* SMI 1915 1BH..00 delusions* SMI 2113 Eu22011 [x]paranoid psychosis* SMI 2455 R001.00 [d]hallucinations* SMI 3636 E13z.11 psychotic episode nos* SMI 4261 E12..00 paranoid states* SMI 4843 Eu22015 [x]paranoia* SMI 6874 Eu31.00 [x]bipolar affective disorder* SMI 12064 R001400 [d]visual hallucinations* SMI 12120 R001000 [d]hallucinations, auditory* SMI 13024 Eu30100 [x]mania without psychotic symptoms* SMI 14743 E120.00 simple paranoid state* SMI 15066 F481K00 visual hallucinations* SMI 19518 1B1b.00 transient hallucinations* SMI 21065 Eu30200 [x]mania with psychotic symptoms* SMI 21540 Eu34000 [x]cyclothymia* SMI 25019 Eu23.00 [x]acute and transient psychotic disorders* SMI 33751 Eu31z00 [x]bipolar affective disorder, unspecified* SMI 85102 212V.00 bipolar affective disorder resolved* SMI 576 E104.00 acute schizophrenic episode SMI 1531 Eu31.11 [x]manic-depressive illness SMI 2114 E03y300 unspecified puerperal psychosis SMI 3369 E212.00 schizoid personality disorder SMI 3702 E114.00 bipolar affective disorder, currently manic SMI 3890 E121.00 chronic paranoid psychosis SMI 3984 E100200 chronic schizophrenic SMI 4390 285..11 psychotic condition, insight present SMI 4677 E115.00 bipolar affective disorder, currently depressed SMI 4678 Eu30z11 [x]mania nos SMI 4732 Eu31500 [x]bipolar affect dis cur epi severe depres with psyc symp SMI 6325 1464 h/o: schizophrenia SMI 6710 Eu31.12 [x]manic-depressive psychosis SMI 8407 E10z.00 schizophrenia nos SMI 8567 E11..11 bipolar psychoses SMI
207
8766 Eu0z.12 [x]symptomatic psychosis nos SMI 9281 E103z00 paranoid schizophrenia nos SMI 9521 Eu30.11 [x]bipolar disorder, single manic episode SMI 11548 146D.00 h/o: manic depressive disorder SMI 11596 E11y000 unspecified manic-depressive psychoses SMI 11778 Eu23200 [x]acute schizophrenia-like psychotic disorder SMI 11973 Eu24.13 [x]induced psychotic disorder SMI 12173 Eu30.00 [x]manic episode SMI 12228 E211100 hypomanic personality disorder SMI 12472 225E.00 o/e - paranoid delusions SMI 12771 E12z.00 paranoid psychosis nos SMI 12831 E115.11 manic-depressive - now depressed SMI 14728 E110100 single manic episode, mild SMI 14747 E212z00 schizoid personality disorder nos SMI 14784 E117.00 unspecified bipolar affective disorder SMI 14971 E122.00 paraphrenia SMI 15053 E133.00 acute paranoid reaction SMI 15733 E100000 unspecified schizophrenia SMI 15923 E115000 bipolar affective disorder, currently depressed, unspecified SMI 16333 E13y.00 other reactive psychoses SMI 16347 E114300 bipolar affect disord, currently manic, severe, no psychosis SMI 16562 Eu31300 [x]bipolar affect disorder cur epi mild or moderate depressn SMI 16764 Eu20000 [x]paranoid schizophrenia SMI 16808 Eu31000 [x]bipolar affective disorder, current episode hypomanic SMI 16905 Eu25011 [x]schizoaffective psychosis, manic type SMI 17281 Eu2..00 [x]schizophrenia, schizotypal and delusional disorders SMI 17385 E114.11 manic-depressive - now manic SMI 17614 Eu53111 [x]puerperal psychosis nos SMI 17982 1BH..11 delusion SMI 18053 Eu20y13 [x]schizophrenifrm psychos nos SMI 18909 E110.11 hypomanic psychoses SMI 19345 212T.00 psychosis, schizophrenia + bipolar affective disord resolved SMI 19916 R001z00 [d]hallucinations nos SMI 19967 E111000 recurrent manic episodes, unspecified SMI 20110 E110000 single manic episode, unspecified SMI 20228 E13..11 reactive psychoses SMI 20572 Eu20211 [x]catatonic stupor SMI 20785 Eu20400 [x]post-schizophrenic depression SMI 21455 Eu23012 [x]cycloid psychosis SMI 21595 Eu23100 [x]acute polymorphic psychot disord with symp of schizophren SMI 22080 ZV11112 [v]personal history of manic-depressive psychosis SMI 22104 ZV11000 [v]personal history of schizophrenia SMI 22644 286..11 poor insight into psychotic condition SMI 22713 1S42.00 manic mood SMI 23538 E13y100 brief reactive psychosis SMI 23616 E100100 subchronic schizophrenia SMI 23713 Eu31400 [x]bipol aff disord, curr epis sev depress, no psychot symp SMI 23963 ZV11111 [v]personal history of manic-depressive psychosis SMI 24230 E117600 unspecified bipolar affective disorder, in full remission SMI 24345 E134.00 psychogenic paranoid psychosis SMI 24640 E110200 single manic episode, moderate SMI 24689 E116100 mixed bipolar affective disorder, mild SMI 25283 R001200 [d]hallucinations, olfactory SMI 25546 E102.00 catatonic schizophrenia SMI 26119 E13yz00 other reactive psychoses nos SMI 26143 Eu23112 [x]cycloid psychosis with symptoms of schizophrenia SMI 26161 E11..13 manic psychoses SMI 26178 8HHs.00 referral to psychosis early intervention service SMI 26227 E111.00 recurrent manic episodes SMI 26299 Eu31100 [x]bipolar affect disorder cur epi manic wout psychotic symp SMI 26859 Eu21.18 [x]schizotypal personality disorder SMI 27584 Eu31700 [x]bipolar affective disorder, currently in remission SMI 27739 E111200 recurrent manic episodes, moderate SMI 27770 Eu23312 [x]psychogenic paranoid psychosis SMI 27890 E115200 bipolar affective disorder, currently depressed, moderate SMI 27986 E117z00 unspecified bipolar affective disorder, nos SMI 28168 Eu44.14 [x]hysterical psychosis SMI 28277 Eu31200 [x]bipolar affect disorder cur epi manic with psychotic symp SMI 28562 Eu22.00 [x]persistent delusional disorders SMI 28677 Eu33312 [x]manic-depress psychosis,depressed type+psychotic symptoms SMI 29451 Eu33213 [x]manic-depress psychosis,depressd,no psychotic symptoms SMI 29651 Eu23z12 [x]reactive psychosis SMI 29937 E131.00 acute hysterical psychosis SMI 30619 E101.00 hebephrenic schizophrenia SMI 31316 E116.00 mixed bipolar affective disorder SMI 31362 E103200 chronic paranoid schizophrenia SMI 31455 E12yz00 other paranoid states nos SMI 31493 Eu20214 [x]schizophrenic flexibilatis cerea SMI 31535 E116000 mixed bipolar affective disorder, unspecified SMI 31589 E12y.00 other paranoid states SMI 31707 Eu23z11 [x]brief reactive psychosis nos SMI 31738 Eu2y.11 [x]chronic hallucinatory psychosis SMI
208
32088 Eu30y00 [x]other manic episodes SMI 32222 E100.00 simple schizophrenia SMI 32295 E111400 recurrent manic episodes, severe, with psychosis SMI 32875 1BH1.00 grandiose delusions SMI 33338 E10y000 atypical schizophrenia SMI 33383 E103000 unspecified paranoid schizophrenia SMI 33426 E11yz00 other and unspecified manic-depressive psychoses nos SMI 33847 Eu25000 [x]schizoaffective disorder, manic type SMI 34168 Eu23z00 [x]acute and transient psychotic disorder, unspecified SMI 34236 Eu20.00 [x]schizophrenia SMI 34389 Eu22000 [x]delusional disorder SMI 34966 Eu20z00 [x]schizophrenia, unspecified SMI 35607 E115300 bipolar affect disord, now depressed, severe, no psychosis SMI 35734 E115100 bipolar affective disorder, currently depressed, mild SMI 35738 E114000 bipolar affective disorder, currently manic, unspecified SMI 35848 Eu20600 [x]simple schizophrenia SMI 35877 Eu20213 [x]schizophrenic catatonia SMI 36126 E114100 bipolar affective disorder, currently manic, mild SMI 36172 E103500 paranoid schizophrenia in remission SMI 36611 E110z00 manic disorder, single episode nos SMI 36720 Eu23000 [x]acute polymorphic psychot disord without symp of schizoph SMI 37070 E110.00 manic disorder, single episode SMI 37102 Eu30211 [x]mania with mood-congruent psychotic symptoms SMI 37178 E111600 recurrent manic episodes, in full remission SMI 37296 E115z00 bipolar affective disorder, currently depressed, nos SMI 37395 E14z.11 childhood schizophrenia nos SMI 38063 E106.00 residual schizophrenia SMI 38371 Eu60100 [x]schizoid personality disorder SMI 39062 E10y.00 other schizophrenia SMI 39316 Eu21.00 [x]schizotypal disorder SMI 40386 Eu21.15 [x]prodromal schizophrenia SMI 40981 Eu22y11 [x]delusional dysmorphophobia SMI 43093 E110300 single manic episode, severe without mention of psychosis SMI 43225 E14..00 psychoses with origin in childhood SMI 43405 Eu20100 [x]hebephrenic schizophrenia SMI 43462 1BH0.00 delusion of persecution SMI 44307 Eu23300 [x]other acute predominantly delusional psychotic disorders SMI 44498 E100400 acute exacerbation of chronic schizophrenia SMI 44503 Eu23y00 [x]other acute and transient psychotic disorders SMI 44513 Eu30z00 [x]manic episode, unspecified SMI 44693 Eu31600 [x]bipolar affective disorder, current episode mixed SMI 46415 E111z00 recurrent manic episode nos SMI 46425 E111100 recurrent manic episodes, mild SMI 46434 E114200 bipolar affective disorder, currently manic, moderate SMI 47230 Eu24.12 [x]induced paranoid disorder SMI 47947 Eu22013 [x]paraphrenia - late SMI 48054 E101z00 hebephrenic schizophrenia nos SMI 48632 Eu30212 [x]mania with mood-incongruent psychotic symptoms SMI 49223 Eu22z00 [x]persistent delusional disorder, unspecified SMI 49420 Eu20y00 [x]other schizophrenia SMI 49761 E10yz00 other schizophrenia nos SMI 49763 E117000 unspecified bipolar affective disorder, unspecified SMI 49852 Eu21.16 [x]pseudoneurotic schizophrenia SMI 50023 Eu23011 [x]bouffee delirante SMI 50060 Eu20011 [x]paraphrenic schizophrenia SMI 50218 E110400 single manic episode, severe, with psychosis SMI 50248 Eu22y12 [x]involutional paranoid state SMI 50868 E123.11 folie a deux SMI 51032 Eu31y12 [x]recurrent manic episodes SMI 51302 Eu24.00 [x]induced delusional disorder SMI 51322 E103300 acute exacerbation of subchronic paranoid schizophrenia SMI 51494 E00y.11 presbyophrenic psychosis SMI 51903 Eu25012 [x]schizophreniform psychosis, manic type SMI 52523 225F.00 o/e - delusion of persecution SMI 52849 E14z.00 child psychosis nos SMI 53032 E103400 acute exacerbation of chronic paranoid schizophrenia SMI 53625 E100z00 simple schizophrenia nos SMI 53761 Ryu5300 [x]other hallucinations SMI 53840 Eu31y00 [x]other bipolar affective disorders SMI 53848 Eu84314 [x]symbiotic psychosis SMI 53985 Eu20111 [x]disorganised schizophrenia SMI 53990 R001100 [d]hallucinations, gustatory SMI 54195 E116400 mixed bipolar affective disorder, severe, with psychosis SMI 54387 Eu21.12 [x]borderline schizophrenia SMI 55064 E116600 mixed bipolar affective disorder, in full remission SMI 55221 Eu22111 [x]capgras syndrome SMI 55236 Eu22y13 [x]paranoia querulans SMI 55829 E114400 bipolar affect disord, currently manic,severe with psychosis SMI 57376 ZS7C611 schizophrenic language SMI 57465 E115600 bipolar affective disorder, now depressed, in full remission SMI 57605 E114z00 bipolar affective disorder, currently manic, nos SMI 57666 E100300 acute exacerbation of subchronic schizophrenia SMI
209
58687 E100500 schizophrenia in remission SMI 58716 E102000 unspecified catatonic schizophrenia SMI 58863 E111500 recurrent manic episodes, partial or unspecified remission SMI 59011 E114500 bipolar affect disord,currently manic, part/unspec remission SMI 59096 Eu23211 [x]brief schizophreniform disorder SMI 60013 Eu20300 [x]undifferentiated schizophrenia SMI 60178 E11y.00 other and unspecified manic-depressive psychoses SMI 61501 Eu20200 [x]catatonic schizophrenia SMI 61969 E212200 schizotypal personality SMI 62405 Eu22100 [x]delusional misidentification syndrome SMI 62449 Eu21.14 [x]prepsychotic schizophrenia SMI 62680 E123.00 shared paranoid disorder SMI 63150 E116200 mixed bipolar affective disorder, moderate SMI 63284 E116300 mixed bipolar affective disorder, severe, without psychosis SMI 63583 E116z00 mixed bipolar affective disorder, nos SMI 63651 E116500 mixed bipolar affective disorder, partial/unspec remission SMI 63698 E117100 unspecified bipolar affective disorder, mild SMI 63701 E115400 bipolar affect disord, now depressed, severe with psychosis SMI 63784 E114600 bipolar affective disorder, currently manic, full remission SMI 63867 E102z00 catatonic schizophrenia nos SMI 64131 R001300 [d]hallucinations, tactile SMI 64264 Eu20500 [x]residual schizophrenia SMI 64533 Eu20212 [x]schizophrenic catalepsy SMI 64993 Eu21.13 [x]latent schizophrenia SMI 65127 Eu22014 [x]sensitiver beziehungswahn SMI 65811 E111300 recurrent manic episodes, severe without mention psychosis SMI 66077 Eu22y00 [x]other persistent delusional disorders SMI 66153 Eu31.13 [x]manic-depressive reaction SMI 66410 E105.00 latent schizophrenia SMI 66506 E101000 unspecified hebephrenic schizophrenia SMI 66757 E14yz00 other childhood psychoses nos SMI 66766 E12y000 paranoia querulans SMI 67130 E212000 unspecified schizoid personality disorder SMI 67768 E101500 hebephrenic schizophrenia in remission SMI 68058 E133.11 bouffee delirante SMI 68326 E117400 unspecified bipolar affective disorder,severe with psychosis SMI 68647 E117200 unspecified bipolar affective disorder, moderate SMI 69155 E14y100 borderline psychosis of childhood SMI 70000 E110600 single manic episode in full remission SMI 70399 E11y300 other mixed manic-depressive psychoses SMI 70721 E117500 unspecified bipolar affect disord, partial/unspec remission SMI 70884 Eu23212 [x]brief schizophrenifrm psych SMI 70925 E11y100 atypical manic disorder SMI 71250 Eu21.17 [x]pseudopsychopathic schizophrenia SMI 71819 E14y.00 other childhood psychoses SMI 72026 E115500 bipolar affect disord, now depressed, part/unspec remission SMI 73295 E100.11 schizophrenia simplex SMI 73423 E117300 unspecified bipolar affective disorder, severe, no psychosis SMI 73924 Eu31y11 [x]bipolar ii disorder SMI 85972 212X.00 psychosis resolved SMI 86762 1B1d.00 hypnagogic hallucination SMI 88275 212W.00 schizophrenia resolved SMI 91511 Eu21.11 [x]latent schizophrenic reaction SMI 91547 Eu20311 [x]atypical schizophrenia SMI 92994 E10y.11 cenesthopathic schizophrenia SMI 93167 E104.11 oneirophrenia SMI 94001 Eu20y12 [x]schizophreniform disord nos SMI 94299 E105200 chronic latent schizophrenia SMI 94604 Eu23214 [x]schizophrenic reaction SMI 96883 E105500 latent schizophrenia in remission SMI 97919 E101400 acute exacerbation of chronic hebephrenic schizophrenia SMI 98821 Eu22200 [x]cotard syndrome SMI 99000 E107.11 cyclic schizophrenia SMI 99070 E10y100 coenesthopathic schizophrenia SMI 99199 E102100 subchronic catatonic schizophrenia SMI 101720 Eu22300 [x]paranoid state in remission SMI 102311 E105000 unspecified latent schizophrenia SMI 102427 E102500 catatonic schizophrenia in remission SMI 102446 E105z00 latent schizophrenia nos SMI 103915 Eu31900 [x]bipolar affective disorder type ii SMI 104051 Eu31911 [x]bipolar ii disorder SMI 104065 Eu31800 [x]bipolar affective disorder type i SMI 104760 E103100 subchronic paranoid schizophrenia SMI 104763 Eu25211 [x]cyclic schizophrenia SMI 105606 Eu24.11 [x]folie a deux SMI 107222 E102400 acute exacerbation of chronic catatonic schizophrenia SMI
210
ICD-10 code ICD-10 term Comorbidity F84.0 childhood autism* Autism/ASD F84.1 atypical autism* Autism/ASD F84.5 asperger syndrome* Autism/ASD F40.0 agoraphobia Anxiety F40.1 social phobias Anxiety F40.8 other phobic anxiety disorders Anxiety F40.9 phobic anxiety disorder, unspecified Anxiety F41.0 panic disorder [episodic paroxysmal anxiety]* Anxiety F41.1 generalized anxiety disorder* Anxiety F41.2 mixed anxiety and depressive disorder* Anxiety F41.3 other mixed anxiety disorders* Anxiety F41.8 other specified anxiety disorders* Anxiety F41.9 anxiety disorder, unspecified* Anxiety F93.2 social anxiety disorder of childhood Anxiety F80.3 acquired aphasia with epilepsy [landau-kleffner] Epilepsy G40.0 localization-related id epilepsy w/ seizures of localized onset * Epilepsy G40.1 localization-related symp epilepsy w/ simple partial seizures* Epilepsy G40.2 localization-related sympt epilepsy w/ complex partial seizures* Epilepsy G40.3 generalized idiopathic epilepsy and epileptic syndromes* Epilepsy G40.4 other generalized epilepsy and epileptic syndromes* Epilepsy G40.5 special epileptic syndromes* Epilepsy G40.6 grand mal seizures, unspecified (with or without petit mal)* Epilepsy G40.7 petit mal, unspecified, without grand mal seizures* Epilepsy G40.8 other epilepsy* Epilepsy G40.9 epilepsy, unspecified* Epilepsy G41.0 grand mal status epilepticus* Epilepsy G41.1 petit mal status epilepticus* Epilepsy G41.2 complex partial status epilepticus* Epilepsy G41.8 other status epilepticus* Epilepsy G41.9 status epilepticus, unspecified * Epilepsy G83.8 other specified paralytic syndromes* Epilepsy R56.8 other and unspecified convulsions* Epilepsy F32.0 mild depressive episode* Depression F32.1 moderate depressive episode* Depression F32.2 severe depressive episode without psychotic symptoms* Depression F32.3 severe depressive episode with psychotic symptoms* Depression F32.8 other depressive episodes* Depression F32.9 depressive episode, unspecified* Depression F33.0 recurrent depressive disorder, current episode mild Depression F33.1 recurrent depressive disorder, current episode moderate Depression F33.2 recurrent depressive disorder, current ep severe w/out psych symptoms Depression F33.3 recurrent depressive disorder, current ep severe w/ psych symptoms Depression F33.4 recurrent depressive disorder, currently in remission Depression F33.8 other recurrent depressive disorders Depression F33.9 recurrent depressive disorder, unspecified* Depression F34.1 dysthymia* Depression F90.1 hyperkinetic conduct disorder* CD/ODD F91.0 conduct disorder confined to the family context* CD/ODD F91.1 unsocialized conduct disorder* CD/ODD F91.2 socialized conduct disorder* CD/ODD F91.3 oppositional defiant disorder* CD/ODD F91.8 other conduct disorders* CD/ODD F91.9 conduct disorder, unspecified* CD/ODD F92.0 depressive conduct disorder CD/ODD F92.8 other mixed disorders of conduct and emotions* CD/ODD F92.9 mixed disorder of conduct and emotions, unspecified* CD/ODD F95.0 transient tic disorder Tic/Tourettes F95.1 chronic motor or vocal tic disorder* Tic/Tourettes F95.2 combined vocal and multiple motor tic disorder [de la Tourette]* Tic/Tourettes F95.8 other tic disorders Tic/Tourettes F95.9 tic disorder, unspecified* Tic/Tourettes F20.0 paranoid schizophrenia* SMI F20.1 hebephrenic schizophrenia SMI F20.2 catatonic schizophrenia SMI F20.3 undifferentiated schizophrenia SMI F20.4 post-schizophrenic depression SMI F20.5 residual schizophrenia SMI F20.6 simple schizophrenia SMI F20.8 other schizophrenia SMI F20.9 schizophrenia, unspecified* SMI F21 schizotypal disorder SMI F22.0 delusional disorder* SMI F22.8 other persistent delusional disorders SMI F22.9 persistent delusional disorder, unspecified SMI F23.0 acute polymorphic psychotic disorder w/out symptoms of schizophrenia SMI F23.1 acute polymorphic psychotic disorder w/ symptoms of schizophrenia* SMI F23.2 acute schizophrenia-like psychotic disorder* SMI F23.3 other acute predominantly delusional psychotic disorders* SMI F23.8 other acute and transient psychotic disorders SMI F23.9 acute and transient psychotic disorder, unspecified* SMI F24 induced delusional disorder SMI
211
F25.0 schizoaffective disorder, manic type SMI F25.1 schizoaffective disorder, depressive type* SMI F25.2 schizoaffective disorder, mixed type SMI F25.8 other schizoaffective disorders SMI F25.9 schizoaffective disorder, unspecified* SMI F28 other nonorganic psychotic disorders* SMI F29 unspecified nonorganic psychosis* SMI F30.0 hypomania SMI F30.1 mania without psychotic symptoms SMI F30.2 mania with psychotic symptoms SMI F30.8 other manic episodes SMI F30.9 manic episode, unspecified SMI F31.0 bipolar affective disorder, current ep hypomanic* SMI F31.1 bipolar affective disorder, current ep manic without psychotic symptoms* SMI F31.2 bipolar affective disorder, current ep manic with psychotic symptoms SMI F31.3 bipolar affective disorder, current ep mild or moderate depression* SMI F31.4 bip aff disorder, current ep severe depression w/out psychotic symptoms SMI F31.5 bip aff disorder, current ep severe depression w/ psychotic symptoms SMI F31.6 bipolar affective disorder, current episode mixed* SMI F31.7 bipolar affective disorder, currently in remission SMI F31.8 other bipolar affective disorders* SMI F31.9 bipolar affective disorder, unspecified* SMI F34.0 cyclothymia SMI R44.0 auditory hallucinations* SMI R44.1 visual hallucinations* SMI R44.2 other hallucinations* SMI R44.3 hallucinations, unspecified* SMI
212
Appendix 5: Product codes for psychotropic drugs of interest
Note: Product codes correspond to products containing the drug substance(s) listed; brand names of products not quoted for reasons of space
Antipsychotics Product code
Drug substance Drug class
38827 perphenazine & amitriptyline 1stgen 6894 perphenazine & amitriptyline 1stgen 1208 perphenazine & amitriptyline 1stgen 595 perphenazine & amitriptyline 1stgen 16323 perphenazine & amitriptyline 1stgen 1453 perphenazine & amitriptyline 1stgen 3490 perphenazine & amitriptyline 1stgen 2540 benperidol 1stgen 31796 benperidol 1stgen 21744 benperidol 1stgen 47365 benperidol 1stgen 247 chlorpromazine 1stgen 8045 chlorpromazine 1stgen 13479 chlorpromazine 1stgen 9965 chlorpromazine embonate 1stgen 15418 chlorpromazine embonate 1stgen 8506 chlorpromazine hydrochloride 1stgen 4434 chlorpromazine hydrochloride 1stgen 35929 chlorpromazine hydrochloride 1stgen 17221 chlorpromazine hydrochloride 1stgen 3348 chlorpromazine hydrochloride 1stgen 37871 chlorpromazine hydrochloride 1stgen 2814 chlorpromazine hydrochloride 1stgen 31184 chlorpromazine hydrochloride 1stgen 7493 chlorpromazine hydrochloride 1stgen 58702 chlorpromazine hydrochloride 1stgen 37705 chlorpromazine hydrochloride 1stgen 28862 chlorpromazine hydrochloride 1stgen 56862 chlorpromazine hydrochloride 1stgen 588 chlorpromazine hydrochloride 1stgen 46960 chlorpromazine hydrochloride 1stgen 8771 chlorpromazine hydrochloride 1stgen 31747 chlorpromazine hydrochloride 1stgen 34668 chlorpromazine hydrochloride 1stgen 34630 chlorpromazine hydrochloride 1stgen 31172 chlorpromazine hydrochloride 1stgen 44186 chlorpromazine hydrochloride 1stgen 17227 chlorpromazine hydrochloride 1stgen 3952 chlorpromazine hydrochloride 1stgen 7514 chlorpromazine hydrochloride 1stgen 55011 chlorpromazine hydrochloride 1stgen 57550 chlorpromazine hydrochloride 1stgen 34693 chlorpromazine hydrochloride 1stgen 2474 chlorpromazine hydrochloride 1stgen 3772 chlorpromazine hydrochloride 1stgen 12137 chlorpromazine hydrochloride 1stgen 8311 chlorpromazine hydrochloride 1stgen 58703 chlorpromazine hydrochloride 1stgen 45281 chlorpromazine hydrochloride 1stgen 12544 chlorpromazine hydrochloride 1stgen 9190 chlorpromazine hydrochloride 1stgen 55012 chlorpromazine hydrochloride 1stgen 8519 chlorpromazine hydrochloride 1stgen 31175 chlorpromazine hydrochloride 1stgen 10446 chlorpromazine hydrochloride 1stgen 25653 chlorpromazine hydrochloride 1stgen 22606 chlorpromazine hydrochloride 1stgen 2154 chlorpromazine hydrochloride 1stgen 30346 chlorpromazine hydrochloride 1stgen 41645 chlorpromazine hydrochloride 1stgen 19033 chlorpromazine hydrochloride 1stgen 10434 chlorpromazine hydrochloride 1stgen 19002 chlorpromazine hydrochloride 1stgen 31171 chlorpromazine hydrochloride 1stgen 58492 chlorpromazine hydrochloride 1stgen 34736 chlorpromazine hydrochloride 1stgen 28147 chlorprothixene 1stgen 30111 chlorprothixene 1stgen 21125 droperidol 1stgen 42229 droperidol 1stgen 3773 droperidol 1stgen 15171 droperidol 1stgen 22609 droperidol 1stgen 53634 droperidol 1stgen
213
13369 droperidol 1stgen 15128 droperidol 1stgen 19752 flupentixol 1stgen 25015 flupentixol 1stgen 14839 flupentixol decanoate 1stgen 2155 flupentixol decanoate 1stgen 57762 flupentixol decanoate 1stgen 2136 flupentixol decanoate 1stgen 2156 flupentixol decanoate 1stgen 14130 flupentixol decanoate 1stgen 8712 flupentixol decanoate 1stgen 19283 flupentixol decanoate 1stgen 18155 flupentixol decanoate 1stgen 18175 flupentixol decanoate 1stgen 2276 flupentixol decanoate 1stgen 57170 flupentixol decanoate 1stgen 1733 flupentixol decanoate 1stgen 14966 flupentixol decanoate 1stgen 59816 flupentixol decanoate 1stgen 18197 flupentixol decanoate 1stgen 14889 flupentixol decanoate 1stgen 27565 flupentixol decanoate 1stgen 59593 flupentixol dihydrochloride 1stgen 50592 flupentixol dihydrochloride 1stgen 5707 flupentixol dihydrochloride 1stgen 3951 flupentixol dihydrochloride 1stgen 55620 flupentixol dihydrochloride 1stgen 5712 flupentixol dihydrochloride 1stgen 3953 flupentixol dihydrochloride 1stgen 41971 fluphenazine decanoate 1stgen 35391 fluphenazine decanoate 1stgen 35487 fluphenazine decanoate 1stgen 3926 fluphenazine decanoate 1stgen 35445 fluphenazine decanoate 1stgen 23340 fluphenazine decanoate 1stgen 8043 fluphenazine decanoate 1stgen 35176 fluphenazine decanoate 1stgen 35122 fluphenazine decanoate 1stgen 33780 fluphenazine decanoate 1stgen 35530 fluphenazine decanoate 1stgen 10514 fluphenazine decanoate 1stgen 12128 fluphenazine decanoate 1stgen 22174 fluphenazine decanoate 1stgen 16229 fluphenazine decanoate 1stgen 26692 fluphenazine decanoate 1stgen 35723 fluphenazine decanoate 1stgen 35065 fluphenazine decanoate 1stgen 26684 fluphenazine decanoate 1stgen 41970 fluphenazine decanoate 1stgen 35455 fluphenazine decanoate 1stgen 9022 fluphenazine decanoate 1stgen 17190 fluphenazine enantate 1stgen 25835 fluphenazine enantate 1stgen 7918 fluphenazine hydrochloride 1stgen 24107 fluphenazine hydrochloride 1stgen 5212 fluphenazine hydrochloride 1stgen 8377 fluphenazine hydrochloride 1stgen 5597 fluphenazine hydrochloride 1stgen 5298 fluphenazine hydrochloride 1stgen 20703 fluphenazine hydrochloride 1stgen 20571 fluphenazine hydrochloride & nortriptyline 1stgen 7780 fluphenazine hydrochloride & nortriptyline 1stgen 2936 fluphenazine hydrochloride & nortriptyline 1stgen 8044 fluspirilene 1stgen 10827 fluspirilene 1stgen 3233 haloperidol 1stgen 52050 haloperidol 1stgen 5545 haloperidol 1stgen 43431 haloperidol 1stgen 43520 haloperidol 1stgen 38540 haloperidol 1stgen 12387 haloperidol 1stgen 45880 haloperidol 1stgen 36771 haloperidol 1stgen 8129 haloperidol 1stgen 30351 haloperidol 1stgen 53649 haloperidol 1stgen 28679 haloperidol 1stgen 10435 haloperidol 1stgen 47149 haloperidol 1stgen 43020 haloperidol 1stgen 5192 haloperidol 1stgen
214
47013 haloperidol 1stgen 3671 haloperidol 1stgen 2419 haloperidol 1stgen 47808 haloperidol 1stgen 13483 haloperidol 1stgen 42895 haloperidol 1stgen 13338 haloperidol 1stgen 12921 haloperidol 1stgen 41546 haloperidol 1stgen 6134 haloperidol 1stgen 2620 haloperidol 1stgen 34272 haloperidol 1stgen 9975 haloperidol 1stgen 55871 haloperidol 1stgen 475 haloperidol 1stgen 55848 haloperidol 1stgen 8153 haloperidol 1stgen 42000 haloperidol 1stgen 7436 haloperidol 1stgen 34339 haloperidol 1stgen 41420 haloperidol 1stgen 49207 haloperidol 1stgen 4234 haloperidol 1stgen 24494 haloperidol 1stgen 15645 haloperidol 1stgen 8136 haloperidol 1stgen 45810 haloperidol 1stgen 6523 haloperidol 1stgen 17379 haloperidol 1stgen 11213 haloperidol 1stgen 329 haloperidol 1stgen 42807 haloperidol 1stgen 34903 haloperidol 1stgen 13484 haloperidol 1stgen 2621 haloperidol 1stgen 22660 haloperidol 1stgen 28968 haloperidol 1stgen 8979 haloperidol 1stgen 23678 haloperidol 1stgen 34039 haloperidol 1stgen 32051 haloperidol 1stgen 25063 haloperidol 1stgen 12050 haloperidol 1stgen 13105 haloperidol 1stgen 38262 haloperidol 1stgen 32838 haloperidol 1stgen 13391 haloperidol 1stgen 2094 haloperidol decanoate 1stgen 15814 haloperidol decanoate 1stgen 12386 haloperidol decanoate 1stgen 10565 haloperidol decanoate 1stgen 4442 levomepromazine hydrochloride 1stgen 59938 levomepromazine hydrochloride 1stgen 52846 levomepromazine hydrochloride 1stgen 6064 levomepromazine hydrochloride 1stgen 60250 levomepromazine maleate 1stgen 53951 levomepromazine maleate 1stgen 7390 levomepromazine maleate 1stgen 4232 levomepromazine maleate 1stgen 28231 levomepromazine maleate 1stgen 40782 levomepromazine maleate 1stgen 21339 levomepromazine maleate 1stgen 49606 levomepromazine maleate 1stgen 5014 levomepromazine maleate 1stgen 14578 fluphenazine hydrochloride & nortriptyline 1stgen 8493 fluphenazine hydrochloride & nortriptyline 1stgen 27211 oxypertine 1stgen 8921 oxypertine 1stgen 29972 pericyazine 1stgen 15472 pericyazine 1stgen 21064 pericyazine 1stgen 7834 pericyazine 1stgen 8032 pericyazine 1stgen 8031 pericyazine 1stgen 39830 pericyazine 1stgen 13902 pericyazine 1stgen 22655 pericyazine 1stgen 40881 pericyazine 1stgen 12195 pericyazine 1stgen 7833 pericyazine 1stgen 14987 perphenazine 1stgen 24282 perphenazine 1stgen
215
609 perphenazine 1stgen 228 perphenazine 1stgen 20061 perphenazine 1stgen 840 perphenazine 1stgen 25909 perphenazine 1stgen 7919 perphenazine 1stgen 17087 perphenazine 1stgen 2157 perphenazine 1stgen 5821 pimozide 1stgen 8637 pimozide 1stgen 27148 pimozide 1stgen 15047 pimozide 1stgen 4524 pimozide 1stgen 2489 pimozide 1stgen 12340 pipotiazine palmitate 1stgen 35235 pipotiazine palmitate 1stgen 35488 pipotiazine palmitate 1stgen 10944 pipotiazine palmitate 1stgen 35684 pipotiazine palmitate 1stgen 36394 pipotiazine palmitate 1stgen 15438 prochlorperazine maleate 1stgen 39887 prochlorperazine maleate 1stgen 32876 prochlorperazine maleate 1stgen 4401 prochlorperazine maleate 1stgen 54458 prochlorperazine maleate 1stgen 32064 prochlorperazine maleate 1stgen 43420 prochlorperazine maleate 1stgen 3932 prochlorperazine maleate 1stgen 512 prochlorperazine maleate 1stgen 1434 prochlorperazine maleate 1stgen 32772 prochlorperazine maleate 1stgen 17849 prochlorperazine maleate 1stgen 51551 prochlorperazine maleate 1stgen 50462 prochlorperazine maleate 1stgen 85 prochlorperazine maleate 1stgen 8689 prochlorperazine maleate 1stgen 51579 prochlorperazine maleate 1stgen 55038 prochlorperazine maleate 1stgen 1990 prochlorperazine maleate 1stgen 34344 prochlorperazine maleate 1stgen 54429 prochlorperazine maleate 1stgen 5497 prochlorperazine maleate 1stgen 13607 prochlorperazine maleate 1stgen 227 prochlorperazine maleate 1stgen 32551 prochlorperazine maleate 1stgen 1234 prochlorperazine maleate 1stgen 49170 prochlorperazine maleate 1stgen 32122 prochlorperazine mesilate 1stgen 3246 prochlorperazine mesilate 1stgen 3738 prochlorperazine mesilate 1stgen 6036 prochlorperazine mesilate 1stgen 5510 prochlorperazine mesilate 1stgen 7593 prochlorperazine mesilate 1stgen 14356 prochlorperazine mesilate 1stgen 14364 prochlorperazine mesilate 1stgen 9590 prochlorperazine mesilate 1stgen 40001 prochlorperazine mesilate 1stgen 237 prochorperazine 1stgen 3024 prochorperazine 1stgen 41995 promazine hydrochloride 1stgen 8988 promazine hydrochloride 1stgen 12193 promazine hydrochloride 1stgen 43654 promazine hydrochloride 1stgen 2972 promazine hydrochloride 1stgen 33493 promazine hydrochloride 1stgen 15395 promazine hydrochloride 1stgen 46945 promazine hydrochloride 1stgen 15161 promazine hydrochloride 1stgen 6443 promazine hydrochloride 1stgen 17634 promazine hydrochloride 1stgen 3227 promazine hydrochloride 1stgen 13311 promazine hydrochloride 1stgen 14610 promazine hydrochloride 1stgen 41732 promazine hydrochloride 1stgen 10780 promazine hydrochloride 1stgen 40390 promazine hydrochloride 1stgen 3226 promazine hydrochloride 1stgen 60450 promazine hydrochloride 1stgen 26660 promazine hydrochloride 1stgen 55890 promazine hydrochloride 1stgen 3197 promazine hydrochloride 1stgen 38089 promazine hydrochloride 1stgen
216
3228 promazine hydrochloride 1stgen 15598 thioridazine hydrochloride 1stgen 35787 thioridazine hydrochloride 1stgen 3605 thioridazine hydrochloride 1stgen 45860 thioridazine hydrochloride 1stgen 47361 thioridazine hydrochloride 1stgen 34905 thioridazine hydrochloride 1stgen 1192 thioridazine hydrochloride 1stgen 42816 thioridazine hydrochloride 1stgen 17399 thioridazine hydrochloride 1stgen 3021 thioridazine hydrochloride 1stgen 1218 thioridazine hydrochloride 1stgen 10405 thioridazine hydrochloride 1stgen 1314 thioridazine hydrochloride 1stgen 2801 thioridazine hydrochloride 1stgen 28965 trifluoperazine 1stgen 10535 trifluoperazine 1stgen 22245 trifluoperazine 1stgen 19645 trifluoperazine 1stgen 10356 trifluoperazine 1stgen 2714 trifluoperazine hydrochloride 1stgen 1245 trifluoperazine hydrochloride 1stgen 8537 trifluoperazine hydrochloride 1stgen 29948 trifluoperazine hydrochloride 1stgen 40162 trifluoperazine hydrochloride 1stgen 18289 trifluoperazine hydrochloride 1stgen 8985 trifluoperazine hydrochloride 1stgen 1735 trifluoperazine hydrochloride 1stgen 2713 trifluoperazine hydrochloride 1stgen 55382 trifluoperazine hydrochloride 1stgen 1857 trifluoperazine hydrochloride 1stgen 57605 trifluoperazine hydrochloride 1stgen 3937 trifluoperazine hydrochloride 1stgen 11531 trifluoperazine hydrochloride 1stgen 41663 trifluoperazine hydrochloride 1stgen 27582 trifluoperazine hydrochloride 1stgen 7479 trifluoperazine hydrochloride 1stgen 29838 trifluoperazine hydrochloride 1stgen 13145 trifluoperazine hydrochloride 1stgen 18668 trifluoperazine hydrochloride 1stgen 1316 trifluoperazine hydrochloride 1stgen 1318 trifluoperazine hydrochloride 1stgen 3955 trifluoperazine hydrochloride 1stgen 8042 trifluoperazine hydrochloride 1stgen 1159 trifluoperazine hydrochloride 1stgen 24890 trifluoperazine hydrochloride 1stgen 8775 trifluoperazine hydrochloride 1stgen 3356 trifluoperazine hydrochloride 1stgen 21027 trifluperidol 1stgen 21047 trifluperidol 1stgen 23659 trifluperidol 1stgen 22814 trifluperidol 1stgen 36101 zuclopenthixol acetate 1stgen 14576 zuclopenthixol acetate 1stgen 24270 zuclopenthixol acetate 1stgen 5762 zuclopenthixol acetate 1stgen 31538 zuclopenthixol acetate 1stgen 31537 zuclopenthixol acetate 1stgen 28355 zuclopenthixol decanoate 1stgen 12073 zuclopenthixol decanoate 1stgen 12224 zuclopenthixol decanoate 1stgen 22049 zuclopenthixol decanoate 1stgen 3775 zuclopenthixol decanoate 1stgen 3774 zuclopenthixol decanoate 1stgen 13600 zuclopenthixol dihydrochloride 1stgen 1319 zuclopenthixol dihydrochloride 1stgen 25635 zuclopenthixol dihydrochloride 1stgen 9686 zuclopenthixol dihydrochloride 1stgen 13368 zuclopenthixol dihydrochloride 1stgen 9347 zuclopenthixol dihydrochloride 1stgen 12707 zuclopenthixol dihydrochloride 1stgen 52076 amisulpride 2ndgen 51558 amisulpride 2ndgen 46889 amisulpride 2ndgen 31576 amisulpride 2ndgen 41714 amisulpride 2ndgen 5071 amisulpride 2ndgen 55625 amisulpride 2ndgen 6109 amisulpride 2ndgen 11938 amisulpride 2ndgen 46969 amisulpride 2ndgen 4876 amisulpride 2ndgen
217
41702 amisulpride 2ndgen 34927 amisulpride 2ndgen 16768 amisulpride 2ndgen 6524 amisulpride 2ndgen 4992 amisulpride 2ndgen 5927 amisulpride 2ndgen 6482 amisulpride 2ndgen 26544 amisulpride 2ndgen 16561 aripiprazole 2ndgen 16575 aripiprazole 2ndgen 38375 aripiprazole 2ndgen 37606 aripiprazole 2ndgen 57114 aripiprazole 2ndgen 32076 aripiprazole 2ndgen 38080 aripiprazole 2ndgen 14344 aripiprazole 2ndgen 14858 aripiprazole 2ndgen 6573 aripiprazole 2ndgen 24358 aripiprazole 2ndgen 6561 aripiprazole 2ndgen 46705 aripiprazole 2ndgen 31098 aripiprazole 2ndgen 18132 aripiprazole 2ndgen 29879 aripiprazole 2ndgen 49699 aripiprazole 2ndgen 38010 aripiprazole 2ndgen 47280 asenapine 2ndgen 47167 asenapine 2ndgen 41428 clozapine 2ndgen 47233 clozapine 2ndgen 8047 clozapine 2ndgen 40587 clozapine 2ndgen 45444 clozapine 2ndgen 17958 clozapine 2ndgen 47302 clozapine 2ndgen 40586 clozapine 2ndgen 41070 clozapine 2ndgen 21199 clozapine 2ndgen 14112 clozapine 2ndgen 42242 clozapine 2ndgen 30487 clozapine 2ndgen 8046 clozapine 2ndgen 36163 olanzapine 2ndgen 50214 olanzapine 2ndgen 58854 olanzapine 2ndgen 47256 olanzapine 2ndgen 55622 olanzapine 2ndgen 56577 olanzapine 2ndgen 57160 olanzapine 2ndgen 29540 olanzapine 2ndgen 19976 olanzapine 2ndgen 58147 olanzapine 2ndgen 13820 olanzapine 2ndgen 5653 olanzapine 2ndgen 57616 olanzapine 2ndgen 47498 olanzapine 2ndgen 56193 olanzapine 2ndgen 59143 olanzapine 2ndgen 6850 olanzapine 2ndgen 1249 olanzapine 2ndgen 18024 olanzapine 2ndgen 53556 olanzapine 2ndgen 14717 olanzapine 2ndgen 3281 olanzapine 2ndgen 56072 olanzapine 2ndgen 57270 olanzapine 2ndgen 47063 olanzapine 2ndgen 16407 olanzapine 2ndgen 33883 olanzapine 2ndgen 23431 olanzapine 2ndgen 52001 olanzapine 2ndgen 6023 olanzapine 2ndgen 47394 olanzapine 2ndgen 2656 olanzapine 2ndgen 6838 olanzapine 2ndgen 45953 olanzapine 2ndgen 53848 olanzapine 2ndgen 47304 olanzapine 2ndgen 47098 olanzapine 2ndgen 47049 olanzapine 2ndgen 56265 olanzapine 2ndgen 47083 olanzapine 2ndgen
218
6412 olanzapine 2ndgen 18453 olanzapine 2ndgen 47103 olanzapine 2ndgen 18658 olanzapine 2ndgen 47093 olanzapine 2ndgen 47055 olanzapine 2ndgen 16103 olanzapine 2ndgen 13888 olanzapine 2ndgen 56143 olanzapine 2ndgen 47152 olanzapine 2ndgen 55667 olanzapine 2ndgen 21964 olanzapine 2ndgen 43914 olanzapine embonate monohydrate 2ndgen 46422 olanzapine embonate monohydrate 2ndgen 55268 olanzapine embonate monohydrate 2ndgen 37717 paliperidone 2ndgen 36954 paliperidone 2ndgen 37501 paliperidone 2ndgen 36116 paliperidone 2ndgen 46447 paliperidone palmitate 2ndgen 46224 paliperidone palmitate 2ndgen 46556 paliperidone palmitate 2ndgen 46436 paliperidone palmitate 2ndgen 47162 paliperidone palmitate 2ndgen 46351 paliperidone palmitate 2ndgen 46435 paliperidone palmitate 2ndgen 46434 paliperidone palmitate 2ndgen 58936 quetiapine 2ndgen 58067 quetiapine fumarate 2ndgen 38913 quetiapine fumarate 2ndgen 9794 quetiapine fumarate 2ndgen 51178 quetiapine fumarate 2ndgen 40779 quetiapine fumarate 2ndgen 58425 quetiapine fumarate 2ndgen 46871 quetiapine fumarate 2ndgen 46764 quetiapine fumarate 2ndgen 44326 quetiapine fumarate 2ndgen 55870 quetiapine fumarate 2ndgen 57034 quetiapine fumarate 2ndgen 39237 quetiapine fumarate 2ndgen 59215 quetiapine fumarate 2ndgen 18023 quetiapine fumarate 2ndgen 44024 quetiapine fumarate 2ndgen 6864 quetiapine fumarate 2ndgen 5283 quetiapine fumarate 2ndgen 38914 quetiapine fumarate 2ndgen 5039 quetiapine fumarate 2ndgen 10107 quetiapine fumarate 2ndgen 21709 quetiapine fumarate 2ndgen 56647 quetiapine fumarate 2ndgen 14859 quetiapine fumarate 2ndgen 57612 quetiapine fumarate 2ndgen 5040 quetiapine fumarate 2ndgen 38840 quetiapine fumarate 2ndgen 38906 quetiapine fumarate 2ndgen 58935 quetiapine fumarate 2ndgen 38912 quetiapine fumarate 2ndgen 7039 quetiapine fumarate 2ndgen 57613 quetiapine fumarate 2ndgen 49696 quetiapine fumarate 2ndgen 14813 quetiapine fumarate 2ndgen 38937 quetiapine fumarate 2ndgen 54483 quetiapine fumarate 2ndgen 45839 quetiapine fumarate 2ndgen 58821 quetiapine fumarate 2ndgen 53552 quetiapine fumarate 2ndgen 18013 quetiapine fumarate 2ndgen 56215 quetiapine fumarate 2ndgen 57412 quetiapine fumarate 2ndgen 52940 quetiapine fumarate 2ndgen 38885 quetiapine fumarate 2ndgen 40932 quetiapine fumarate 2ndgen 9475 risperidone 2ndgen 11799 risperidone 2ndgen 46677 risperidone 2ndgen 11821 risperidone 2ndgen 14767 risperidone 2ndgen 16425 risperidone 2ndgen 51240 risperidone 2ndgen 57217 risperidone 2ndgen 11828 risperidone 2ndgen 9659 risperidone 2ndgen
219
7382 risperidone 2ndgen 51444 risperidone 2ndgen 35548 risperidone 2ndgen 16006 risperidone 2ndgen 14789 risperidone 2ndgen 47832 risperidone 2ndgen 302 risperidone 2ndgen 16489 risperidone 2ndgen 16986 risperidone 2ndgen 5219 risperidone 2ndgen 54346 risperidone 2ndgen 35589 risperidone 2ndgen 55661 risperidone 2ndgen 16908 risperidone 2ndgen 667 risperidone 2ndgen 4820 risperidone 2ndgen 56387 risperidone 2ndgen 59548 risperidone 2ndgen 16434 risperidone 2ndgen 2787 risperidone 2ndgen 1321 risperidone 2ndgen 9340 risperidone 2ndgen 58822 risperidone 2ndgen 631 risperidone 2ndgen 2786 risperidone 2ndgen 35953 risperidone 2ndgen 35141 risperidone 2ndgen 1320 risperidone 2ndgen 6373 risperidone 2ndgen 5262 risperidone 2ndgen 59829 risperidone 2ndgen 12579 risperidone 2ndgen 31063 sertindole 2ndgen 19900 sertindole 2ndgen 17050 sertindole 2ndgen 12666 sertindole 2ndgen 23162 sertindole 2ndgen 16998 sertindole 2ndgen 25966 sertindole 2ndgen 41675 sulpiride 2ndgen 24069 sulpiride 2ndgen 24053 sulpiride 2ndgen 8903 sulpiride 2ndgen 34810 sulpiride 2ndgen 18352 sulpiride 2ndgen 43522 sulpiride 2ndgen 10666 sulpiride 2ndgen 2135 sulpiride 2ndgen 43423 sulpiride 2ndgen 18181 sulpiride 2ndgen 9247 sulpiride 2ndgen 13620 sulpiride 2ndgen 28759 zotepine 2ndgen 9515 zotepine 2ndgen 25336 zotepine 2ndgen 17504 zotepine 2ndgen 30088 zotepine 2ndgen
Antidepressants
Product code
Drug substance Drug class
42660 citalopram hydrobromide SSRI 49165 citalopram hydrobromide SSRI 53394 citalopram hydrobromide SSRI 52100 citalopram hydrobromide SSRI 41528 citalopram hydrobromide SSRI 36746 citalopram hydrobromide SSRI 33720 citalopram hydrobromide SSRI 58476 citalopram hydrobromide SSRI 52354 citalopram hydrobromide SSRI 45304 citalopram hydrobromide SSRI 55033 citalopram hydrobromide SSRI 54827 citalopram hydrobromide SSRI 53787 citalopram hydrobromide SSRI 34466 citalopram hydrobromide SSRI 46926 citalopram hydrobromide SSRI 46977 citalopram hydrobromide SSRI 2408 citalopram hydrobromide SSRI 52408 citalopram hydrobromide SSRI 52607 citalopram hydrobromide SSRI 67 citalopram hydrobromide SSRI 60568 citalopram hydrobromide SSRI
220
3861 citalopram hydrobromide SSRI 34356 citalopram hydrobromide SSRI 4770 citalopram hydrobromide SSRI 32848 citalopram hydrobromide SSRI 34822 citalopram hydrobromide SSRI 34413 citalopram hydrobromide SSRI 34871 citalopram hydrobromide SSRI 52824 citalopram hydrobromide SSRI 1712 citalopram hydrobromide SSRI 34722 citalopram hydrobromide SSRI 34970 citalopram hydrobromide SSRI 29756 citalopram hydrobromide SSRI 59193 citalopram hydrobromide SSRI 34966 citalopram hydrobromide SSRI 34415 citalopram hydrobromide SSRI 43519 citalopram hydrobromide SSRI 34586 citalopram hydrobromide SSRI 56355 citalopram hydrobromide SSRI 34499 citalopram hydrobromide SSRI 45223 citalopram hydrobromide SSRI 34498 citalopram hydrobromide SSRI 476 citalopram hydrobromide SSRI 45286 citalopram hydrobromide SSRI 32546 citalopram hydrobromide SSRI 56009 citalopram hydrobromide SSRI 26016 citalopram hydrobromide SSRI 59650 citalopram hydrobromide SSRI 48026 citalopram hydrobromide SSRI 34436 citalopram hydrobromide SSRI 34603 citalopram hydrobromide SSRI 57936 citalopram hydrochloride SSRI 815 citalopram hydrochloride SSRI 513 citalopram hydrochloride SSRI 56292 citalopram hydrochloride SSRI 41062 escitalopram oxalate SSRI 40726 escitalopram oxalate SSRI 6405 escitalopram oxalate SSRI 6218 escitalopram oxalate SSRI 20152 escitalopram oxalate SSRI 603 escitalopram oxalate SSRI 26056 escitalopram oxalate SSRI 785 escitalopram oxalate SSRI 648 escitalopram oxalate SSRI 6360 escitalopram oxalate SSRI 60138 fluoxetine SSRI 33410 fluoxetine hydrochloride SSRI 22 fluoxetine hydrochloride SSRI 42107 fluoxetine hydrochloride SSRI 34294 fluoxetine hydrochloride SSRI 57532 fluoxetine hydrochloride SSRI 19470 fluoxetine hydrochloride SSRI 33779 fluoxetine hydrochloride SSRI 14740 fluoxetine hydrochloride SSRI 29786 fluoxetine hydrochloride SSRI 37256 fluoxetine hydrochloride SSRI 34849 fluoxetine hydrochloride SSRI 45224 fluoxetine hydrochloride SSRI 34216 fluoxetine hydrochloride SSRI 42499 fluoxetine hydrochloride SSRI 34288 fluoxetine hydrochloride SSRI 34202 fluoxetine hydrochloride SSRI 19183 fluoxetine hydrochloride SSRI 34856 fluoxetine hydrochloride SSRI 4907 fluoxetine hydrochloride SSRI 36893 fluoxetine hydrochloride SSRI 38890 fluoxetine hydrochloride SSRI 2548 fluoxetine hydrochloride SSRI 33071 fluoxetine hydrochloride SSRI 60619 fluoxetine hydrochloride SSRI 4075 fluoxetine hydrochloride SSRI 42803 fluoxetine hydrochloride SSRI 60534 fluoxetine hydrochloride SSRI 30258 fluoxetine hydrochloride SSRI 59358 fluoxetine hydrochloride SSRI 45329 fluoxetine hydrochloride SSRI 45247 fluoxetine hydrochloride SSRI 45316 fluoxetine hydrochloride SSRI 418 fluoxetine hydrochloride SSRI 252 fluoxetine hydrochloride SSRI 34456 fluoxetine hydrochloride SSRI 48220 fluoxetine hydrochloride SSRI 2897 fluvoxamine maleate SSRI
221
12123 fluvoxamine maleate SSRI 48045 fluvoxamine maleate SSRI 43518 fluvoxamine maleate SSRI 23334 fluvoxamine maleate SSRI 44861 fluvoxamine maleate SSRI 2290 fluvoxamine maleate SSRI 2880 fluvoxamine maleate SSRI 55023 paroxetine hydrochloride SSRI 34419 paroxetine hydrochloride SSRI 34587 paroxetine hydrochloride SSRI 1397 paroxetine hydrochloride SSRI 59288 paroxetine hydrochloride SSRI 1575 paroxetine hydrochloride SSRI 40165 paroxetine hydrochloride SSRI 55537 paroxetine hydrochloride SSRI 35112 paroxetine hydrochloride SSRI 32899 paroxetine hydrochloride SSRI 40892 paroxetine hydrochloride SSRI 50 paroxetine hydrochloride SSRI 35021 paroxetine hydrochloride SSRI 841 paroxetine hydrochloride SSRI 3601 paroxetine hydrochloride SSRI 34351 paroxetine hydrochloride SSRI 527 paroxetine hydrochloride SSRI 33978 paroxetine hydrochloride SSRI 54081 sertraline SSRI 55146 sertraline hydrochloride SSRI 488 sertraline hydrochloride SSRI 59600 sertraline hydrochloride SSRI 54933 sertraline hydrochloride SSRI 49519 sertraline hydrochloride SSRI 54826 sertraline hydrochloride SSRI 4352 sertraline hydrochloride SSRI 45915 sertraline hydrochloride SSRI 42387 sertraline hydrochloride SSRI 32401 sertraline hydrochloride SSRI 58664 sertraline hydrochloride SSRI 727 sertraline hydrochloride SSRI 7328 sertraline hydrochloride SSRI 1612 sertraline hydrochloride SSRI 55488 sertraline hydrochloride SSRI 44944 sertraline hydrochloride SSRI 58723 sertraline hydrochloride SSRI 27876 amitriptyline TCA 13496 amitriptyline TCA 8250 amitriptyline TCA 23497 amitriptyline TCA 30738 amitriptyline TCA 873 amitriptyline TCA 20712 amitriptyline TCA 3771 amitriptyline TCA 57107 amitriptyline hydrochloride TCA 7751 amitriptyline hydrochloride TCA 16323 amitriptyline hydrochloride TCA 2525 amitriptyline hydrochloride TCA 45242 amitriptyline hydrochloride TCA 8878 amitriptyline hydrochloride TCA 34224 amitriptyline hydrochloride TCA 34197 amitriptyline hydrochloride TCA 182 amitriptyline hydrochloride TCA 55491 amitriptyline hydrochloride TCA 26213 amitriptyline hydrochloride TCA 2486 amitriptyline hydrochloride TCA 2985 amitriptyline hydrochloride TCA 11963 amitriptyline hydrochloride TCA 41729 amitriptyline hydrochloride TCA 34182 amitriptyline hydrochloride TCA 4682 amitriptyline hydrochloride TCA 3777 amitriptyline hydrochloride TCA 34916 amitriptyline hydrochloride TCA 46818 amitriptyline hydrochloride TCA 46801 amitriptyline hydrochloride TCA 40396 amitriptyline hydrochloride TCA 48065 amitriptyline hydrochloride TCA 34274 amitriptyline hydrochloride TCA 487 amitriptyline hydrochloride TCA 22070 amitriptyline hydrochloride TCA 8332 amitriptyline hydrochloride TCA 33624 amitriptyline hydrochloride TCA 59161 amitriptyline hydrochloride TCA 24134 amitriptyline hydrochloride TCA 34401 amitriptyline hydrochloride TCA
222
6312 amitriptyline hydrochloride TCA 34731 amitriptyline hydrochloride TCA 33090 amitriptyline hydrochloride TCA 34782 amitriptyline hydrochloride TCA 55139 amitriptyline hydrochloride TCA 34634 amitriptyline hydrochloride TCA 4690 amitriptyline hydrochloride TCA 34129 amitriptyline hydrochloride TCA 24152 amitriptyline hydrochloride TCA 24145 amitriptyline hydrochloride TCA 8726 amitriptyline hydrochloride TCA 52867 amitriptyline hydrochloride TCA 19779 amitriptyline hydrochloride TCA 27008 amitriptyline hydrochloride TCA 14534 amitriptyline hydrochloride TCA 34107 amitriptyline hydrochloride TCA 34251 amitriptyline hydrochloride TCA 34474 amitriptyline hydrochloride TCA 20026 amitriptyline hydrochloride TCA 49 amitriptyline hydrochloride TCA 34503 amitriptyline hydrochloride TCA 24147 amitriptyline hydrochloride TCA 60355 amitriptyline hydrochloride TCA 60410 amitriptyline hydrochloride TCA 1888 amitriptyline hydrochloride TCA 21081 amitriptyline hydrochloride TCA 45233 amitriptyline hydrochloride TCA 46970 amitriptyline hydrochloride TCA 42394 amitriptyline hydrochloride TCA 8831 amitriptyline hydrochloride TCA 32439 amitriptyline hydrochloride TCA 24141 amitriptyline hydrochloride TCA 83 amitriptyline hydrochloride TCA 59820 amitriptyline hydrochloride TCA 24680 amitriptyline hydrochloride TCA 6894 amitriptyline hydrochloride TCA 57972 amitriptyline hydrochloride TCA 42078 amitriptyline hydrochloride TCA 18342 amitriptyline hydrochloride TCA 54877 amitriptyline hydrochloride TCA 1208 amitriptyline hydrochloride/perphenazine TCA 1453 amitriptyline hydrochloride/perphenazine TCA 595 amitriptyline hydrochloride/perphenazine TCA 38827 amitriptyline hydrochloride/perphenazine TCA 3490 amitriptyline hydrochloride/perphenazine TCA 15380 amoxapine TCA 21357 amoxapine TCA 4411 amoxapine TCA 17319 amoxapine TCA 14398 amoxapine TCA 24723 amoxapine TCA 18932 butriptyline hydrochloride TCA 32457 butriptyline hydrochloride TCA 12227 butriptyline hydrochloride TCA 3195 clomipramine TCA 3657 clomipramine hydrochloride TCA 53161 clomipramine hydrochloride TCA 41597 clomipramine hydrochloride TCA 34245 clomipramine hydrochloride TCA 3194 clomipramine hydrochloride TCA 7693 clomipramine hydrochloride TCA 41628 clomipramine hydrochloride TCA 45350 clomipramine hydrochloride TCA 8661 clomipramine hydrochloride TCA 25036 clomipramine hydrochloride TCA 7894 clomipramine hydrochloride TCA 34866 clomipramine hydrochloride TCA 3925 clomipramine hydrochloride TCA 8720 clomipramine hydrochloride TCA 41563 clomipramine hydrochloride TCA 13318 clomipramine hydrochloride TCA 3670 clomipramine hydrochloride TCA 26513 clomipramine hydrochloride TCA 38274 clomipramine hydrochloride TCA 45318 clomipramine hydrochloride TCA 43561 clomipramine hydrochloride TCA 7515 clomipramine hydrochloride TCA 30375 clomipramine hydrochloride TCA 8719 clomipramine hydrochloride TCA 53187 clomipramine hydrochloride TCA 7981 desipramine TCA 7979 desipramine TCA
223
2320 dosulepin hydrochloride TCA 34745 dosulepin hydrochloride TCA 34641 dosulepin hydrochloride TCA 34058 dosulepin hydrochloride TCA 84 dosulepin hydrochloride TCA 19168 dosulepin hydrochloride TCA 21157 dosulepin hydrochloride TCA 31826 dosulepin hydrochloride TCA 19186 dosulepin hydrochloride TCA 15632 dosulepin hydrochloride TCA 34525 dosulepin hydrochloride TCA 21820 dosulepin hydrochloride TCA 33164 dosulepin hydrochloride TCA 27616 dosulepin hydrochloride TCA 42734 dosulepin hydrochloride TCA 30376 dosulepin hydrochloride TCA 10948 dosulepin hydrochloride TCA 51758 dosulepin hydrochloride TCA 1940 dosulepin hydrochloride TCA 23426 dosulepin hydrochloride TCA 21819 dosulepin hydrochloride TCA 1169 dosulepin hydrochloride TCA 34223 dosulepin hydrochloride TCA 26822 dosulepin hydrochloride TCA 34643 dosulepin hydrochloride TCA 31824 dosulepin hydrochloride TCA 50722 dosulepin hydrochloride TCA 29875 dosulepin hydrochloride TCA 6054 dosulepin hydrochloride TCA 74 dosulepin hydrochloride TCA 57926 dosulepin hydrochloride TCA 45737 dosulepin hydrochloride TCA 43024 dosulepin hydrochloride TCA 32121 dosulepin hydrochloride TCA 44853 dosulepin hydrochloride TCA 10413 doxepin hydrochloride TCA 3554 doxepin hydrochloride TCA 7059 doxepin hydrochloride TCA 40777 doxepin hydrochloride TCA 12125 doxepin hydrochloride TCA 35258 doxepin hydrochloride TCA 12129 doxepin hydrochloride TCA 5073 doxepin hydrochloride TCA 22872 doxepin hydrochloride TCA 35493 doxepin hydrochloride TCA 3842 doxepin hydrochloride TCA 14519 doxepin hydrochloride TCA 10649 imipramine TCA 7573 imipramine TCA 7784 imipramine TCA 3668 imipramine TCA 1310 imipramine hydrochloride TCA 4404 imipramine hydrochloride TCA 56501 imipramine hydrochloride TCA 1809 imipramine hydrochloride TCA 32863 imipramine hydrochloride TCA 2579 imipramine hydrochloride TCA 41681 imipramine hydrochloride TCA 34355 imipramine hydrochloride TCA 8055 imipramine hydrochloride TCA 33074 imipramine hydrochloride TCA 34813 imipramine hydrochloride TCA 41408 imipramine hydrochloride TCA 34872 imipramine hydrochloride TCA 34222 imipramine hydrochloride TCA 42247 imipramine hydrochloride TCA 7910 imipramine hydrochloride TCA 24700 iprindole TCA 27733 iprindole TCA 31672 iprindole TCA 27476 iprindole TCA 25070 lofepramine TCA 41627 lofepramine hydrochloride TCA 34950 lofepramine hydrochloride TCA 56229 lofepramine hydrochloride TCA 58450 lofepramine hydrochloride TCA 56703 lofepramine hydrochloride TCA 25444 lofepramine hydrochloride TCA 114 lofepramine hydrochloride TCA 34046 lofepramine hydrochloride TCA 60591 lofepramine hydrochloride TCA 4218 lofepramine hydrochloride TCA
224
34578 lofepramine hydrochloride TCA 43534 lofepramine hydrochloride TCA 2093 lofepramine hydrochloride TCA 34672 lofepramine hydrochloride TCA 12368 mianserin hydrochloride TCA 7468 mianserin hydrochloride TCA 8585 mianserin hydrochloride TCA 4329 mianserin hydrochloride TCA 3083 mianserin hydrochloride TCA 8144 mianserin hydrochloride TCA 6255 mianserin hydrochloride TCA 11956 mianserin hydrochloride TCA 47363 mianserin hydrochloride TCA 12192 mianserin hydrochloride TCA 3903 nortriptyline hydrochloride TCA 7678 nortriptyline hydrochloride TCA 20571 nortriptyline hydrochloride TCA 12353 nortriptyline hydrochloride TCA 7677 nortriptyline hydrochloride TCA 55970 nortriptyline hydrochloride TCA 12549 nortriptyline hydrochloride TCA 17183 nortriptyline hydrochloride TCA 48216 nortriptyline hydrochloride TCA 4118 nortriptyline hydrochloride TCA 3183 nortriptyline hydrochloride TCA 39145 nortriptyline hydrochloride TCA 8640 nortriptyline hydrochloride TCA 11187 protriptyline hydrochloride TCA 7756 protriptyline hydrochloride TCA 7816 protriptyline hydrochloride TCA 7755 protriptyline hydrochloride TCA 25085 trimipramine TCA 25045 trimipramine TCA 2533 trimipramine TCA 8928 trimipramine maleate TCA 42228 trimipramine maleate TCA 53808 trimipramine maleate TCA 45226 trimipramine maleate TCA 27568 trimipramine maleate TCA 2531 trimipramine maleate TCA 2532 trimipramine maleate TCA 2039 trimipramine maleate TCA 57978 trimipramine maleate TCA 4310 trimipramine maleate TCA 3196 trimipramine maleate TCA 12111 viloxazine hydrochloride TCA 12309 viloxazine hydrochloride TCA 40494 agomelatine Other antidepressant 40295 agomelatine Other antidepressant 6895 duloxetine hydrochloride Other antidepressant 13151 duloxetine hydrochloride Other antidepressant 51383 duloxetine hydrochloride Other antidepressant 14849 duloxetine hydrochloride Other antidepressant 7122 duloxetine hydrochloride Other antidepressant 6846 mirtazapine Other antidepressant 43242 mirtazapine Other antidepressant 47945 mirtazapine Other antidepressant 53648 mirtazapine Other antidepressant 54792 mirtazapine Other antidepressant 47966 mirtazapine Other antidepressant 43237 mirtazapine Other antidepressant 54012 mirtazapine Other antidepressant 6488 mirtazapine Other antidepressant 48698 mirtazapine Other antidepressant 43248 mirtazapine Other antidepressant 43250 mirtazapine Other antidepressant 43247 mirtazapine Other antidepressant 59694 mirtazapine Other antidepressant 6421 mirtazapine Other antidepressant 15268 mirtazapine Other antidepressant 50892 mirtazapine Other antidepressant 742 mirtazapine Other antidepressant 53699 mirtazapine Other antidepressant 54644 mirtazapine Other antidepressant 6481 mirtazapine Other antidepressant 56209 mirtazapine Other antidepressant 53321 mirtazapine Other antidepressant 43241 mirtazapine Other antidepressant 43256 mirtazapine Other antidepressant 55482 mirtazapine Other antidepressant 43239 mirtazapine Other antidepressant 33337 mirtazapine Other antidepressant
225
60538 mirtazapine Other antidepressant 58625 mirtazapine Other antidepressant 10083 mirtazapine Other antidepressant 40160 mirtazapine Other antidepressant 59954 mirtazapine Other antidepressant 43253 mirtazapine Other antidepressant 43257 mirtazapine Other antidepressant 43235 mirtazapine Other antidepressant 43236 mirtazapine Other antidepressant 46668 mirtazapine Other antidepressant 31168 mirtazapine Other antidepressant 4726 mirtazapine Other antidepressant 43246 mirtazapine Other antidepressant 53543 mirtazapine Other antidepressant 60370 mirtazapine Other antidepressant 16154 mirtazapine Other antidepressant 58291 mirtazapine Other antidepressant 59953 mirtazapine Other antidepressant 48185 mirtazapine Other antidepressant 49820 mirtazapine Other antidepressant 6854 mirtazapine Other antidepressant 54342 mirtazapine Other antidepressant 43234 mirtazapine Other antidepressant 6795 mirtazapine Other antidepressant 9534 nefazodone hydrochloride Other antidepressant 4554 nefazodone hydrochloride Other antidepressant 4297 nefazodone hydrochloride Other antidepressant 4011 nefazodone hydrochloride Other antidepressant 3391 nefazodone hydrochloride Other antidepressant 15163 reboxetine mesilate Other antidepressant 2356 reboxetine mesilate Other antidepressant 41609 trazodone hydrochloride Other antidepressant 34421 trazodone hydrochloride Other antidepressant 57226 trazodone hydrochloride Other antidepressant 34003 trazodone hydrochloride Other antidepressant 55138 trazodone hydrochloride Other antidepressant 29857 trazodone hydrochloride Other antidepressant 29339 trazodone hydrochloride Other antidepressant 34580 trazodone hydrochloride Other antidepressant 12710 trazodone hydrochloride Other antidepressant 6442 trazodone hydrochloride Other antidepressant 3355 trazodone hydrochloride Other antidepressant 8174 trazodone hydrochloride Other antidepressant 4194 trazodone hydrochloride Other antidepressant 59931 trazodone hydrochloride Other antidepressant 19181 trazodone hydrochloride Other antidepressant 41710 trazodone hydrochloride Other antidepressant 34470 trazodone hydrochloride Other antidepressant 4003 trazodone hydrochloride Other antidepressant 4874 trazodone hydrochloride Other antidepressant 1730 trazodone hydrochloride Other antidepressant 55137 trazodone hydrochloride Other antidepressant 13621 trazodone hydrochloride Other antidepressant 30983 trazodone hydrochloride Other antidepressant 4020 trazodone hydrochloride Other antidepressant 41709 trazodone hydrochloride Other antidepressant 54747 tryptophan Other antidepressant 54686 tryptophan Other antidepressant 4422 tryptophan Other antidepressant 20504 tryptophan Other antidepressant 5611 tryptophan Other antidepressant 12221 tryptophan Other antidepressant 8844 tryptophan/ascorbic acid/pyridoxine Other antidepressant 58681 venlafaxine Other antidepressant 51699 venlafaxine Other antidepressant 58837 venlafaxine Other antidepressant 40517 venlafaxine hydrochloride Other antidepressant 51361 venlafaxine hydrochloride Other antidepressant 39360 venlafaxine hydrochloride Other antidepressant 45818 venlafaxine hydrochloride Other antidepressant 45806 venlafaxine hydrochloride Other antidepressant 59035 venlafaxine hydrochloride Other antidepressant 52516 venlafaxine hydrochloride Other antidepressant 42600 venlafaxine hydrochloride Other antidepressant 41299 venlafaxine hydrochloride Other antidepressant 44936 venlafaxine hydrochloride Other antidepressant 40048 venlafaxine hydrochloride Other antidepressant 623 venlafaxine hydrochloride Other antidepressant 57751 venlafaxine hydrochloride Other antidepressant 59923 venlafaxine hydrochloride Other antidepressant 9182 venlafaxine hydrochloride Other antidepressant 40062 venlafaxine hydrochloride Other antidepressant
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41314 venlafaxine hydrochloride Other antidepressant 58726 venlafaxine hydrochloride Other antidepressant 40764 venlafaxine hydrochloride Other antidepressant 40049 venlafaxine hydrochloride Other antidepressant 40815 venlafaxine hydrochloride Other antidepressant 40059 venlafaxine hydrochloride Other antidepressant 59753 venlafaxine hydrochloride Other antidepressant 52716 venlafaxine hydrochloride Other antidepressant 55501 venlafaxine hydrochloride Other antidepressant 60549 venlafaxine hydrochloride Other antidepressant 59563 venlafaxine hydrochloride Other antidepressant 1474 venlafaxine hydrochloride Other antidepressant 44937 venlafaxine hydrochloride Other antidepressant 6274 venlafaxine hydrochloride Other antidepressant 470 venlafaxine hydrochloride Other antidepressant 40407 venlafaxine hydrochloride Other antidepressant 45959 venlafaxine hydrochloride Other antidepressant 51280 venlafaxine hydrochloride Other antidepressant 60449 venlafaxine hydrochloride Other antidepressant 53326 venlafaxine hydrochloride Other antidepressant 43968 venlafaxine hydrochloride Other antidepressant 55424 venlafaxine hydrochloride Other antidepressant 49511 venlafaxine hydrochloride Other antidepressant 56457 venlafaxine hydrochloride Other antidepressant 43334 venlafaxine hydrochloride Other antidepressant 43673 venlafaxine hydrochloride Other antidepressant 40514 venlafaxine hydrochloride Other antidepressant 50934 venlafaxine hydrochloride Other antidepressant 40917 venlafaxine hydrochloride Other antidepressant 50081 venlafaxine hydrochloride Other antidepressant 40277 venlafaxine hydrochloride Other antidepressant 56662 venlafaxine hydrochloride Other antidepressant 39359 venlafaxine hydrochloride Other antidepressant 2654 venlafaxine hydrochloride Other antidepressant 2617 venlafaxine hydrochloride Other antidepressant 40817 venlafaxine hydrochloride Other antidepressant 40092 venlafaxine hydrochloride Other antidepressant 43203 venlafaxine hydrochloride Other antidepressant 39770 venlafaxine hydrochloride Other antidepressant 13237 venlafaxine hydrochloride Other antidepressant 48199 venlafaxine hydrochloride Other antidepressant 1222 venlafaxine hydrochloride Other antidepressant 39809 venlafaxine hydrochloride Other antidepressant 5710 venlafaxine hydrochloride Other antidepressant 52074 venlafaxine hydrochloride Other antidepressant 40515 venlafaxine hydrochloride Other antidepressant 301 venlafaxine hydrochloride Other antidepressant 40054 venlafaxine hydrochloride Other antidepressant 45664 venlafaxine hydrochloride Other antidepressant 41033 venlafaxine hydrochloride Other antidepressant 25945 iproniazide MAOI 12503 isocarboxazid MAOI 41731 isocarboxazid MAOI 12207 isocarboxazid MAOI 5187 moclobemide MAOI 2883 moclobemide MAOI 9206 moclobemide MAOI 41747 moclobemide MAOI 5832 moclobemide MAOI 4321 phenelzine sulfate MAOI 3349 phenelzine sulfate MAOI 41654 tranylcypromine sulfate MAOI 3783 tranylcypromine sulfate MAOI 10787 tranylcypromine sulfate MAOI 3356 tranylcypromine sulphate & trifluoperazine MAOI 24890 tranylcypromine sulphate & trifluoperazine MAOI 3955 tranylcypromine sulphate & trifluoperazine MAOI
Anxiolytics/hypnotics
Product code
Drug substance Drug class
9696 alprazolam benzodiazepines 11486 alprazolam benzodiazepines 12598 alprazolam benzodiazepines 10802 alprazolam benzodiazepines 11958 bromazepam benzodiazepines 19941 bromazepam benzodiazepines 55774 bromazepam benzodiazepines 9721 bromazepam benzodiazepines 22424 bromazepam benzodiazepines 6025 chlordiazepoxide hydrochloride benzodiazepines 6516 chlordiazepoxide hydrochloride benzodiazepines
227
34928 chlordiazepoxide hydrochloride benzodiazepines 28879 chlordiazepoxide hydrochloride benzodiazepines 41583 chlordiazepoxide hydrochloride benzodiazepines 41606 chlordiazepoxide hydrochloride benzodiazepines 41988 chlordiazepoxide hydrochloride benzodiazepines 35936 chlordiazepoxide hydrochloride benzodiazepines 41582 chlordiazepoxide hydrochloride benzodiazepines 9048 chlordiazepoxide hydrochloride benzodiazepines 24599 chlordiazepoxide hydrochloride benzodiazepines 32231 chlordiazepoxide hydrochloride benzodiazepines 43438 chlordiazepoxide hydrochloride benzodiazepines 27880 chlordiazepoxide hydrochloride benzodiazepines 8550 chlordiazepoxide hydrochloride benzodiazepines 17294 chlordiazepoxide hydrochloride benzodiazepines 45241 chlordiazepoxide hydrochloride benzodiazepines 44302 chlordiazepoxide hydrochloride benzodiazepines 4543 chlordiazepoxide hydrochloride benzodiazepines 41581 chlordiazepoxide hydrochloride benzodiazepines 2122 chlordiazepoxide hydrochloride benzodiazepines 1463 chlordiazepoxide hydrochloride benzodiazepines 5294 chlordiazepoxide hydrochloride benzodiazepines 18125 chlordiazepoxide hydrochloride benzodiazepines 40386 chlordiazepoxide hydrochloride benzodiazepines 3147 chlordiazepoxide hydrochloride benzodiazepines 41574 chlordiazepoxide hydrochloride benzodiazepines 8913 chlordiazepoxide hydrochloride benzodiazepines 41629 chlordiazepoxide hydrochloride benzodiazepines 12477 chlordiazepoxide hydrochloride benzodiazepines 30273 chlordiazepoxide hydrochloride benzodiazepines 55481 clobazam benzodiazepines 54934 clobazam benzodiazepines 3110 clobazam benzodiazepines 8487 clobazam benzodiazepines 54759 clobazam benzodiazepines 56781 clobazam benzodiazepines 53311 clonazepam benzodiazepines 57664 clonazepam benzodiazepines 14743 clonazepam benzodiazepines 58460 clonazepam benzodiazepines 34491 clonazepam benzodiazepines 45077 clonazepam benzodiazepines 53739 clonazepam benzodiazepines 2073 clonazepam benzodiazepines 50108 clonazepam benzodiazepines 13200 clonazepam benzodiazepines 48544 clonazepam benzodiazepines 47066 clonazepam benzodiazepines 17637 clonazepam benzodiazepines 4483 clonazepam benzodiazepines 59396 clonazepam benzodiazepines 32500 clonazepam benzodiazepines 1559 clonazepam benzodiazepines 58482 clonazepam benzodiazepines 5842 diazepam benzodiazepines 57749 diazepam benzodiazepines 28347 diazepam benzodiazepines 56236 diazepam benzodiazepines 58959 diazepam benzodiazepines 32296 diazepam benzodiazepines 10909 diazepam benzodiazepines 36581 diazepam benzodiazepines 20514 diazepam benzodiazepines 34338 diazepam benzodiazepines 46966 diazepam benzodiazepines 8344 diazepam benzodiazepines 2401 diazepam benzodiazepines 34524 diazepam benzodiazepines 34293 diazepam benzodiazepines 3973 diazepam benzodiazepines 23820 diazepam benzodiazepines 57838 diazepam benzodiazepines 9065 diazepam benzodiazepines 1400 diazepam benzodiazepines 53566 diazepam benzodiazepines 45313 diazepam benzodiazepines 46 diazepam benzodiazepines 34876 diazepam benzodiazepines 32853 diazepam benzodiazepines 34635 diazepam benzodiazepines 41607 diazepam benzodiazepines 4176 diazepam benzodiazepines 34614 diazepam benzodiazepines
228
34615 diazepam benzodiazepines 20164 diazepam benzodiazepines 34033 diazepam benzodiazepines 34677 diazepam benzodiazepines 34561 diazepam benzodiazepines 54695 diazepam benzodiazepines 4395 diazepam benzodiazepines 16734 diazepam benzodiazepines 34681 diazepam benzodiazepines 42503 diazepam benzodiazepines 34807 diazepam benzodiazepines 28698 diazepam benzodiazepines 12849 diazepam benzodiazepines 3205 diazepam benzodiazepines 3870 diazepam benzodiazepines 4338 diazepam benzodiazepines 34892 diazepam benzodiazepines 45218 diazepam benzodiazepines 2078 diazepam benzodiazepines 10274 diazepam benzodiazepines 20968 diazepam benzodiazepines 51985 diazepam benzodiazepines 45244 diazepam benzodiazepines 4587 diazepam benzodiazepines 33672 diazepam benzodiazepines 9045 diazepam benzodiazepines 38410 diazepam benzodiazepines 9111 diazepam benzodiazepines 29945 diazepam benzodiazepines 10402 diazepam benzodiazepines 53461 diazepam benzodiazepines 41632 diazepam benzodiazepines 8842 diazepam benzodiazepines 2352 diazepam benzodiazepines 46913 diazepam benzodiazepines 28703 diazepam benzodiazepines 59122 diazepam benzodiazepines 59407 diazepam benzodiazepines 45135 diazepam benzodiazepines 6747 diazepam benzodiazepines 34045 diazepam benzodiazepines 47 diazepam benzodiazepines 34340 diazepam benzodiazepines 8345 diazepam benzodiazepines 51335 diazepam benzodiazepines 19299 diazepam benzodiazepines 30321 diazepam benzodiazepines 2083 diazepam benzodiazepines 41689 diazepam benzodiazepines 33070 diazepam benzodiazepines 18488 diazepam benzodiazepines 34335 diazepam benzodiazepines 8334 diazepam benzodiazepines 34482 diazepam benzodiazepines 5793 diazepam benzodiazepines 9430 diazepam benzodiazepines 14480 flunitrazepam benzodiazepines 24422 flurazepam benzodiazepines 12278 flurazepam benzodiazepines 18928 flurazepam benzodiazepines 24321 flurazepam hydrochloride benzodiazepines 3956 flurazepam hydrochloride benzodiazepines 3950 flurazepam hydrochloride benzodiazepines 7566 flurazepam hydrochloride benzodiazepines 3105 flurazepam hydrochloride benzodiazepines 28360 ketazolam benzodiazepines 23796 ketazolam benzodiazepines 12452 ketazolam benzodiazepines 12130 ketazolam benzodiazepines 5150 loprazolam mesilate benzodiazepines 23205 loprazolam mesilate benzodiazepines 41596 loprazolam mesilate benzodiazepines 46896 lorazepam benzodiazepines 33086 lorazepam benzodiazepines 37566 lorazepam benzodiazepines 10409 lorazepam benzodiazepines 2091 lorazepam benzodiazepines 36200 lorazepam benzodiazepines 13279 lorazepam benzodiazepines 56551 lorazepam benzodiazepines 35932 lorazepam benzodiazepines 10954 lorazepam benzodiazepines
229
45829 lorazepam benzodiazepines 37745 lorazepam benzodiazepines 57268 lorazepam benzodiazepines 23002 lorazepam benzodiazepines 39284 lorazepam benzodiazepines 14417 lorazepam benzodiazepines 41391 lorazepam benzodiazepines 42814 lorazepam benzodiazepines 1088 lorazepam benzodiazepines 17830 lorazepam benzodiazepines 34516 lormetazepam benzodiazepines 34292 lormetazepam benzodiazepines 34361 lormetazepam benzodiazepines 3687 lormetazepam benzodiazepines 21437 lormetazepam benzodiazepines 3357 lormetazepam benzodiazepines 34692 lormetazepam benzodiazepines 48517 lormetazepam benzodiazepines 34534 lormetazepam benzodiazepines 3354 lormetazepam benzodiazepines 34642 lormetazepam benzodiazepines 18291 lormetazepam benzodiazepines 10789 medazepam benzodiazepines 10790 medazepam benzodiazepines 21464 medazepam benzodiazepines 10791 medazepam benzodiazepines 43450 midazolam benzodiazepines 49595 midazolam benzodiazepines 52954 midazolam benzodiazepines 48807 midazolam benzodiazepines 49095 midazolam benzodiazepines 45695 midazolam benzodiazepines 55931 midazolam benzodiazepines 48817 midazolam hydrochloride benzodiazepines 7301 midazolam hydrochloride benzodiazepines 48715 midazolam hydrochloride benzodiazepines 10278 midazolam hydrochloride benzodiazepines 50618 midazolam hydrochloride benzodiazepines 44764 midazolam maleate benzodiazepines 52845 midazolam maleate benzodiazepines 58685 midazolam maleate benzodiazepines 2407 nitrazepam benzodiazepines 7924 nitrazepam benzodiazepines 3524 nitrazepam benzodiazepines 27847 nitrazepam benzodiazepines 41385 nitrazepam benzodiazepines 46953 nitrazepam benzodiazepines 35 nitrazepam benzodiazepines 34770 nitrazepam benzodiazepines 34686 nitrazepam benzodiazepines 19450 nitrazepam benzodiazepines 34408 nitrazepam benzodiazepines 7786 nitrazepam benzodiazepines 9814 nitrazepam benzodiazepines 37325 nitrazepam benzodiazepines 23874 nitrazepam benzodiazepines 15492 nitrazepam benzodiazepines 34555 nitrazepam benzodiazepines 34964 nitrazepam benzodiazepines 34806 nitrazepam benzodiazepines 3686 nitrazepam benzodiazepines 4141 oxazepam benzodiazepines 41601 oxazepam benzodiazepines 41542 oxazepam benzodiazepines 4566 oxazepam benzodiazepines 41602 oxazepam benzodiazepines 41553 oxazepam benzodiazepines 36604 oxazepam benzodiazepines 7652 oxazepam benzodiazepines 25273 oxazepam benzodiazepines 41531 oxazepam benzodiazepines 46946 oxazepam benzodiazepines 8721 oxazepam benzodiazepines 41411 oxazepam benzodiazepines 4140 oxazepam benzodiazepines 25893 prazepam benzodiazepines 56927 temazepam benzodiazepines 34002 temazepam benzodiazepines 32847 temazepam benzodiazepines 49589 temazepam benzodiazepines 12462 temazepam benzodiazepines 41562 temazepam benzodiazepines
230
13612 temazepam benzodiazepines 33648 temazepam benzodiazepines 30985 temazepam benzodiazepines 21454 temazepam benzodiazepines 46078 temazepam benzodiazepines 28058 temazepam benzodiazepines 36611 temazepam benzodiazepines 55836 temazepam benzodiazepines 23493 temazepam benzodiazepines 45283 temazepam benzodiazepines 36602 temazepam benzodiazepines 34406 temazepam benzodiazepines 41653 temazepam benzodiazepines 41516 temazepam benzodiazepines 1729 temazepam benzodiazepines 31163 temazepam benzodiazepines 20245 temazepam benzodiazepines 46964 temazepam benzodiazepines 41718 temazepam benzodiazepines 34331 temazepam benzodiazepines 56811 temazepam benzodiazepines 38418 temazepam benzodiazepines 15110 temazepam benzodiazepines 46939 temazepam benzodiazepines 8798 temazepam benzodiazepines 23120 temazepam benzodiazepines 20 temazepam benzodiazepines 10430 temazepam benzodiazepines 12293 temazepam benzodiazepines 27367 temazepam benzodiazepines 41717 temazepam benzodiazepines 921 temazepam benzodiazepines 780 temazepam benzodiazepines 45254 temazepam benzodiazepines 2403 temazepam benzodiazepines 29441 temazepam benzodiazepines 34508 temazepam benzodiazepines 20801 temazepam benzodiazepines 7569 temazepam benzodiazepines 32320 temazepam benzodiazepines 30779 temazepam benzodiazepines 38424 temazepam benzodiazepines 34572 temazepam benzodiazepines 7567 temazepam benzodiazepines 7571 triazolam benzodiazepines 55303 triazolam benzodiazepines 46909 triazolam benzodiazepines 2404 triazolam benzodiazepines 41822 triazolam benzodiazepines 55892 chloral hydrate chloral hydrate/cloral betaine 30249 chloral hydrate chloral hydrate/cloral betaine 4632 chloral hydrate chloral hydrate/cloral betaine 60204 chloral hydrate chloral hydrate/cloral betaine 60006 chloral hydrate chloral hydrate/cloral betaine 1784 chloral hydrate chloral hydrate/cloral betaine 3580 chloral hydrate chloral hydrate/cloral betaine 3928 chloral hydrate chloral hydrate/cloral betaine 9063 chloral hydrate chloral hydrate/cloral betaine 58185 chloral hydrate chloral hydrate/cloral betaine 51578 chloral hydrate chloral hydrate/cloral betaine 13473 chloral hydrate chloral hydrate/cloral betaine 20679 chloral hydrate chloral hydrate/cloral betaine 4018 chloral hydrate chloral hydrate/cloral betaine 45225 chloral hydrate chloral hydrate/cloral betaine 20800 chloral hydrate chloral hydrate/cloral betaine 4017 chloral hydrate chloral hydrate/cloral betaine 2950 chloral hydrate chloral hydrate/cloral betaine 12898 chloral hydrate/syrup chloral hydrate/cloral betaine 19073 chloral hydrate/syrup chloral hydrate/cloral betaine 1134 cloral betaine chloral hydrate/cloral betaine 18859 cloral betaine chloral hydrate/cloral betaine 2300 cloral betaine chloral hydrate/cloral betaine 32796 potassium bromide/chloral hydrate chloral hydrate/cloral betaine 12443 potassium bromide/chloral hydrate chloral hydrate/cloral betaine 55191 melatonin melatonin 50115 melatonin melatonin 45783 melatonin melatonin 55100 melatonin melatonin 52289 melatonin melatonin 58566 melatonin melatonin 49196 melatonin melatonin 38208 melatonin melatonin
231
38265 melatonin melatonin 55860 melatonin melatonin 52487 melatonin melatonin 53064 melatonin melatonin 58692 melatonin melatonin 45367 melatonin melatonin 45230 melatonin melatonin 52303 melatonin melatonin 57406 melatonin melatonin 49576 melatonin melatonin 17663 melatonin melatonin 7099 melatonin melatonin 10068 melatonin melatonin 16993 melatonin melatonin 26391 melatonin melatonin 52683 melatonin melatonin 50258 melatonin melatonin 41961 melatonin melatonin 56393 melatonin melatonin 14221 melatonin melatonin 54717 melatonin melatonin 35142 melatonin melatonin 48436 melatonin melatonin 14250 melatonin melatonin 13023 melatonin melatonin 14210 melatonin melatonin 52079 melatonin melatonin 45975 melatonin melatonin 35224 melatonin melatonin 14145 melatonin melatonin 9598 zaleplon z drugs 5916 zaleplon z drugs 5306 zaleplon z drugs 5352 zaleplon z drugs 2017 zolpidem tartrate z drugs 29869 zolpidem tartrate z drugs 31710 zolpidem tartrate z drugs 3741 zolpidem tartrate z drugs 41696 zolpidem tartrate z drugs 41539 zolpidem tartrate z drugs 3126 zolpidem tartrate z drugs 30981 zolpidem tartrate z drugs 43560 zolpidem tartrate z drugs 33841 zolpidem tartrate z drugs 42089 zolpidem tartrate z drugs 5459 zolpidem tartrate z drugs 41697 zolpidem tartrate z drugs 33663 zopiclone z drugs 34897 zopiclone z drugs 59640 zopiclone z drugs 3320 zopiclone z drugs 14365 zopiclone z drugs 34823 zopiclone z drugs 45353 zopiclone z drugs 15852 zopiclone z drugs 34612 zopiclone z drugs 24135 zopiclone z drugs 66 zopiclone z drugs 4187 zopiclone z drugs 34777 zopiclone z drugs 30056 zopiclone z drugs 5058 zopiclone z drugs 57937 zopiclone z drugs 721 zopiclone z drugs 29219 zopiclone z drugs 30377 zopiclone z drugs 43445 zopiclone z drugs 34874 zopiclone z drugs 46799 zopiclone z drugs 52022 zopiclone z drugs 34372 zopiclone z drugs 33045 zopiclone z drugs 12038 chlormezanone other anxiolytic/hypnotic 1909 chlormezanone other anxiolytic/hypnotic 7748 dichloralphenazone other anxiolytic/hypnotic 8758 dichloralphenazone other anxiolytic/hypnotic 18976 methyprylone other anxiolytic/hypnotic 18925 methyprylone other anxiolytic/hypnotic 32538 potassium bromide other anxiolytic/hypnotic 58922 sodium hydroxybutyrate other anxiolytic/hypnotic 10513 triclofos sodium other anxiolytic/hypnotic 31951 triclofos sodium other anxiolytic/hypnotic
232
17102 amobarbital sodium other anxiolytic/hypnotic 14415 amobarbital sodium other anxiolytic/hypnotic 27481 amobarbital sodium other anxiolytic/hypnotic 28146 amobarbital sodium other anxiolytic/hypnotic 12010 amobarbital sodium other anxiolytic/hypnotic 15614 amobarbital sodium other anxiolytic/hypnotic 14416 amobarbital sodium other anxiolytic/hypnotic 14414 amobarbital sodium other anxiolytic/hypnotic 13470 amobarbital sodium other anxiolytic/hypnotic 13411 amobarbital sodium other anxiolytic/hypnotic 13471 amobarbital sodium other anxiolytic/hypnotic 8548 amobarbital sodium other anxiolytic/hypnotic 15615 amobarbital sodium other anxiolytic/hypnotic 8713 amobarbital sodium other anxiolytic/hypnotic 4134 amobarbital sodium other anxiolytic/hypnotic 21460 amobarbital sodium/secobarbital sodium other anxiolytic/hypnotic 221 amobarbital sodium/secobarbital sodium other anxiolytic/hypnotic 8624 butobarbital other anxiolytic/hypnotic 13447 butobarbital other anxiolytic/hypnotic 50442 phenobarbital other anxiolytic/hypnotic 59917 phenobarbital other anxiolytic/hypnotic 29306 phenobarbital other anxiolytic/hypnotic 24138 phenobarbital other anxiolytic/hypnotic 58846 phenobarbital other anxiolytic/hypnotic 59013 phenobarbital other anxiolytic/hypnotic 55019 phenobarbital other anxiolytic/hypnotic 1576 phenobarbital other anxiolytic/hypnotic 58905 phenobarbital other anxiolytic/hypnotic 59715 phenobarbital other anxiolytic/hypnotic 202 phenobarbital other anxiolytic/hypnotic 59795 phenobarbital other anxiolytic/hypnotic 60059 phenobarbital other anxiolytic/hypnotic 45370 phenobarbital other anxiolytic/hypnotic 59574 phenobarbital other anxiolytic/hypnotic 41973 phenobarbital other anxiolytic/hypnotic 25543 phenobarbital other anxiolytic/hypnotic 4496 phenobarbital other anxiolytic/hypnotic 57247 phenobarbital other anxiolytic/hypnotic 55502 phenobarbital other anxiolytic/hypnotic 58891 phenobarbital other anxiolytic/hypnotic 34275 phenobarbital other anxiolytic/hypnotic 60212 phenobarbital other anxiolytic/hypnotic 58532 phenobarbital other anxiolytic/hypnotic 51326 phenobarbital other anxiolytic/hypnotic 39618 phenobarbital other anxiolytic/hypnotic 19907 phenobarbital other anxiolytic/hypnotic 1399 phenobarbital other anxiolytic/hypnotic 47812 phenobarbital other anxiolytic/hypnotic 28945 phenobarbital other anxiolytic/hypnotic 27895 phenobarbital other anxiolytic/hypnotic 59868 phenobarbital other anxiolytic/hypnotic 10273 phenobarbital other anxiolytic/hypnotic 59065 phenobarbital other anxiolytic/hypnotic 3225 phenobarbital other anxiolytic/hypnotic 56880 phenobarbital other anxiolytic/hypnotic 60598 phenobarbital other anxiolytic/hypnotic 5439 phenobarbital other anxiolytic/hypnotic 33372 phenobarbital other anxiolytic/hypnotic 59232 phenobarbital other anxiolytic/hypnotic 35164 phenobarbital other anxiolytic/hypnotic 33323 phenobarbital other anxiolytic/hypnotic 57722 phenobarbital other anxiolytic/hypnotic 59136 phenobarbital other anxiolytic/hypnotic 60648 phenobarbital other anxiolytic/hypnotic 23768 phenobarbital sodium other anxiolytic/hypnotic 55796 phenobarbital sodium other anxiolytic/hypnotic 15022 phenobarbital sodium other anxiolytic/hypnotic 23767 phenobarbital sodium other anxiolytic/hypnotic 12539 secobarbital sodium other anxiolytic/hypnotic 26775 secobarbital sodium other anxiolytic/hypnotic 14613 secobarbital sodium other anxiolytic/hypnotic 12264 secobarbital sodium other anxiolytic/hypnotic 49504 buspirone hydrochloride other anxiolytic/hypnotic 5385 buspirone hydrochloride other anxiolytic/hypnotic 59095 buspirone hydrochloride other anxiolytic/hypnotic 3574 buspirone hydrochloride other anxiolytic/hypnotic 28880 buspirone hydrochloride other anxiolytic/hypnotic 2394 buspirone hydrochloride other anxiolytic/hypnotic 43240 buspirone hydrochloride other anxiolytic/hypnotic 46847 buspirone hydrochloride other anxiolytic/hypnotic 45275 buspirone hydrochloride other anxiolytic/hypnotic 40153 buspirone hydrochloride other anxiolytic/hypnotic
233
9008 buspirone hydrochloride other anxiolytic/hypnotic 59170 clomethiazole other anxiolytic/hypnotic 3491 clomethiazole other anxiolytic/hypnotic 563 clomethiazole other anxiolytic/hypnotic 2535 clomethiazole edisilate other anxiolytic/hypnotic 58361 clomethiazole edisilate other anxiolytic/hypnotic 11326 aspirin/ethoheptazine citrate/meprobamate other anxiolytic/hypnotic 8464 meprobamate other anxiolytic/hypnotic 10676 meprobamate other anxiolytic/hypnotic 24642 meprobamate other anxiolytic/hypnotic 2828 meprobamate other anxiolytic/hypnotic 12484 meprobamate other anxiolytic/hypnotic 12512 meprobamate other anxiolytic/hypnotic 3639 meprobamate other anxiolytic/hypnotic 8303 meprobamate other anxiolytic/hypnotic 36312 sodium oxybate other anxiolytic/hypnotic 35810 sodium oxybate other anxiolytic/hypnotic
234
Appendix 6: Read and ICD-10 codes used in the identification of fracture
Medical code
Read code Read term Fracture type
57190 S022700 closed fracture of mandible, alveolar border of body Skull/facial 54553 S023x00 open fracture of mandible, multiple sites Skull/facial 25631 S02z.00 fracture of facial bone nos Skull/facial
106283 S023700 open fracture of mandible, alveolar border of body Skull/facial 89688 S030z00 Closed #skull NOS no intracranial inj + concussion unspec Skull/facial 33692 S0z..00 fracture of skull nos Skull/facial 24132 S837311 broken teeth injury with complication Skull/facial 33459 S027.00 open orbital blow-out fracture Skull/facial 50687 S041300 Closed #skull/face, mult + intracranial inj, 1-24hrs LOC Skull/facial 5280 S028000 fracture of nasal bones Skull/facial
93438 S000600 Closed #skull vlt no intracranial inj, LOC unspec duration Skull/facial 14878 S024.00 fracture of malar or maxillary bones, closed Skull/facial 44343 S02A.00 le fort i fracture maxilla Skull/facial 12462 S025100 open fracture zygoma Skull/facial 17958 S001000 Closed #skull vlt + intracranial injury, unspec state consc Skull/facial 73441 S003100 Open #skull vlt + intracranial injury, no loss of consc Skull/facial 20515 S028100 fracture of orbital floor Skull/facial 64167 S003000 Open #skull vlt + intracranial injury, unspec state of consc Skull/facial 2461 S01..00 fracture of base of skull Skull/facial
45365 S837300 broken tooth injury with complication Skull/facial 49644 S024z00 fracture of malar or maxillary bones, closed, nos Skull/facial 37904 S022x00 closed fracture of mandible, multiple sites Skull/facial 36268 S022z00 fracture of mandible, closed, nos Skull/facial 70282 S025.11 fracture of upper jaw, open Skull/facial 47842 S000.00 closed fracture vault of skull without intracranial injury Skull/facial 59341 S022300 closed fracture of mandible, coronoid process Skull/facial 96406 S010z00 Closed #skull bse no intracranial injury + concussion unspec Skull/facial 27657 S001.00 closed fracture vault of skull with intracranial injury Skull/facial 20195 S00z.00 fracture of vault of skull nos Skull/facial 4225 S024000 closed fracture maxilla Skull/facial
11161 S028300 fracture of mandible Skull/facial 57246 S002.00 open fracture vault of skull without intracranial injury Skull/facial 67641 SC00.00 late effect of fracture of skull and face bones Skull/facial 41675 S01..13 frontal sinus fracture Skull/facial 57328 S03z.00 skull fracture nos Skull/facial 31797 S04..11 multiple face fractures Skull/facial 50247 S04z.00 multiple fractures involving skull/face with other bones nos Skull/facial 45956 S011600 Closed #skull bse + intracranial injury, LOC unspec duration Skull/facial 71583 S022600 closed fracture of mandible, symphysis of body Skull/facial 33515 S044.00 multiple fractures involving skull and facial bones Skull/facial 70673 S023000 open fracture mandible (site unspecified) Skull/facial 9736 S01..15 occiput bone fracture Skull/facial
67890 S031200 Closed #skull NOS + intracranial inj, <1hr loss of consc Skull/facial 26408 S02xz00 fracture of other facial bones, closed, nos Skull/facial 2642 S022.00 fracture of mandible, closed Skull/facial
44949 S02B.00 le fort ii fracture maxilla Skull/facial 36448 S024.11 fracture of upper jaw, closed Skull/facial 9771 S020.11 closed fracture nasal bone Skull/facial
60633 S023100 open fracture of mandible, condylar process Skull/facial 65724 S000000 Closed #skull vlt no intracranial injury, unspec state consc Skull/facial 30028 S028200 fracture of malar and maxillary bones Skull/facial 61388 S03..00 other and unqualified skull fractures Skull/facial 97064 S013.00 open fracture base of skull with intracranial injury Skull/facial 62977 S010.00 closed fracture base of skull without intracranial injury Skull/facial 29091 S022000 closed fracture mandible (site unspecified) Skull/facial 10168 S836311 broken teeth injury without complication Skull/facial 37192 S021.11 open fracture nasal bone Skull/facial 32011 S025000 open fracture maxilla Skull/facial 66312 S002100 Open #skull vlt no intracranial injury, no loss of consc Skull/facial 39859 S04..12 multiple skull fractures Skull/facial 94411 S032.00 Open #skull NOS without mention of intracranial injury Skull/facial 35312 S02yz00 fracture of other facial bones,open, nos Skull/facial 73206 S041.00 Mult #skull/face+other bones, closed + intracranial injury Skull/facial 16890 S022.12 fracture of lower jaw, closed Skull/facial 50524 S000200 Closed #skull vlt no intracranial injury, <1hr loss of consc Skull/facial 68981 S02C.00 le fort iii fracture maxilla Skull/facial 69737 S012.00 open fracture base skull without mention intracranial injury Skull/facial 61357 S003600 Open #skull vlt + intracranial injury, LOC unspec duration Skull/facial 66114 S002000 Open #skull vlt no intracranial injury, unspec state consc Skull/facial 12109 S836300 broken tooth injury Skull/facial 55955 S023500 open fracture of mandible, angle of jaw Skull/facial 71030 SC00.11 late effect of face fracture Skull/facial 65532 S032z00 Open #skull NOS no intracranial inj + concussion unspec Skull/facial 62955 S000100 Closed #skull vlt no intracranial injury, no loss of consc Skull/facial 66763 S030100 Closed #skull NOS no intracranial inj, no loss of consc Skull/facial 71866 S041z00 Closed #skull/face,mult + intracran inj, concussion unspec Skull/facial
417 S020.00 closed fracture nose Skull/facial
235
68660 S023400 open fracture of mandible, ramus, unspecified Skull/facial 17455 S02z.11 jaw fracture nos Skull/facial 72412 S001400 Closed #skull vlt + intracranial injury, >24hr LOC+recovery Skull/facial 67603 S033.00 open fracture of skull nos with intracranial injury Skull/facial 9103 S02..00 fracture of face bones Skull/facial
59233 S02y.00 open fracture other facial bone Skull/facial 58957 S010100 Closed #skull bse no intracranial injury, no loss of consc Skull/facial 72710 S043400 Open #skull/face, mult + intracran inj, >24hr LOC + recovery Skull/facial 27492 S031.00 closed fracture of skull nos with intracranial injury Skull/facial 35456 S6...00 intracranial injury excluding those with skull fracture Skull/facial 60239 S023z00 fracture of mandible, open, nos Skull/facial 3408 S021.00 open fracture nose Skull/facial
15184 S00..00 fracture of vault of skull Skull/facial 92354 S040.00 Mult #skull/face+other bones, closed, no intracranial injury Skull/facial 63679 S011.00 closed fracture base of skull with intracranial injury Skull/facial 73411 S042.00 Mult #skull/face + other bones, open, no intracranial injury Skull/facial 72400 S040200 Closed #skull/face, mult, no intracranial inj, <1hr LOC Skull/facial
104931 S023600 open fracture of mandible, symphysis of body Skull/facial 62841 S001600 Closed #skull vlt + intracranial injury, LOC unspec duration Skull/facial 52871 S000500 Closed #skull vlt no intracranial inj,>24hr LOC not restored Skull/facial 59006 S022800 closed fracture of mandible, body, other and unspecified Skull/facial 12179 S022100 closed fracture of mandible, condylar process Skull/facial 4978 S02x100 fracture of orbit nos, closed Skull/facial
73430 S000z00 Closed #skull vlt no intracranial injury + concussion unspec Skull/facial 99549 S023200 open fracture of mandible, subcondylar Skull/facial 59959 S001z00 Closed #skull vlt with intracranial injury+concussion unspec Skull/facial 24790 S026.00 closed orbital blow-out fracture Skull/facial 62743 S003z00 Open #skull vlt with intracranial injury + concussion unspec Skull/facial 62716 S022.11 fracture of inferior maxilla, closed Skull/facial 31153 S02y100 fracture of orbit nos, open Skull/facial 33593 S01z.00 fracture of base of skull nos Skull/facial 28913 S022400 closed fracture of mandible, ramus, unspecified Skull/facial 60260 S023800 open fracture of mandible, body, other and unspecified Skull/facial 58688 S010000 Closed #skull bse no intracranial injury, unspec state consc Skull/facial 30707 S01..12 ethmoid sinus fracture Skull/facial 62835 S043000 Open #skull/face, mult + intracranial inj, unspec consc Skull/facial 37609 S01..16 orbital roof fracture Skull/facial 73451 S013400 Open #skull bse + intracranial injury, >24hr LOC + recovery Skull/facial 46142 S04..00 multiple fractures involving skull or face with other bones Skull/facial 68940 S025z00 fracture of malar or maxillary bones, open, nos Skull/facial 23780 S03z.11 depressed skull fracture nos Skull/facial 93851 S001300 Closed #skull vlt + intracranial injury, 1-24hr loss consc Skull/facial 60402 SC00.12 late effect of skull fracture Skull/facial 94692 Syu0400 [x]fracture of skull and facial bones, part unspecified Skull/facial 51299 S003.00 open fracture vault of skull with intracranial injury Skull/facial
721 S0...00 fracture of skull Skull/facial 66765 S000300 Closed #skull vlt no intracranial injury, 1-24hr loss consc Skull/facial 32298 S6z..00 intracranial injury, excluding those with skull fracture nos Skull/facial 2251 S024100 closed fracture zygoma Skull/facial 4088 SC20.00 late effect of intracranial injury without skull fracture Skull/facial
69491 S031300 Closed #skull NOS + intracranial inj, 1-24hrs loss of consc Skull/facial 93804 S041000 Closed #skull/face, mult + intracranial inj, unspec consc Skull/facial 38050 S023.00 fracture of mandible, open Skull/facial 41730 S022200 closed fracture of mandible, subcondylar Skull/facial 96681 S041600 Closed #skull/face,mult + intracran inj, LOC unspec duration Skull/facial 48636 S025.00 fracture of malar or maxillary bones, open Skull/facial 64550 S031600 Closed #skull NOS + intracranial inj, LOC unspec duration Skull/facial 41707 S022500 closed fracture of mandible, angle of jaw Skull/facial 57644 S030.00 closed fracture of skull nos without intracranial injury Skull/facial 36772 S023.11 fracture of lower jaw, open Skull/facial 94450 S010200 Closed #skull bse no intracranial injury, <1hr loss of consc Skull/facial 29119 S02x.00 closed fracture other facial bone Skull/facial 30203 S028.00 fracture of skull and facial bones Skull/facial 71725 S011400 Closed #skull bse + intracranial injury, >24hr LOC+recovery Skull/facial 11296 S100.00 closed fracture of cervical spine Neck 55627 S101.00 open fracture of cervical spine Neck 99936 Syu1600 [x]fracture of other parts of neck Neck 95006 S100E00 closed fracture axis, posterior arch Neck 64297 S100L00 closed fracture cervical vertebra, transverse process Neck 53337 S100H00 closed fracture cervical vertebra, wedge Neck 42149 S100C00 closed fracture axis, spinous process Neck 98393 S100800 closed fracture atlas, isolated arch or articular process Neck 73416 S110z00 closed fracture of cervical spine with cord lesion nos Neck 41930 S100z00 closed fracture of cervical spine not otherwise specified Neck 94638 Syu1500 [x]fracture of other specified cervical vertebra Neck 27654 S100600 closed fracture of sixth cervical vertebra Neck 51741 SC01000 late effect of fracture of cervical vertebra Neck 62337 S110000 cls spinal fracture with unspec cervical cord lesion, c1-4 Neck 39887 S100A00 closed fracture axis, odontoid process Neck
101574 S101000 open fracture of unspecified cervical vertebra Neck 34403 S10A100 fracture of second cervical vertebra Neck 24672 S100700 closed fracture of seventh cervical vertebra Neck
236
65300 S101600 open fracture of sixth cervical vertebra Neck 72617 S101x00 multiple open fractures of cervical vertebrae Neck 69645 S101100 open fracture atlas Neck 10252 S1...00 fracture of neck and trunk Neck 73786 SR10000 closed fractures involving head with neck Neck 60593 S100300 closed fracture of third cervical vertebra Neck 53976 S101200 open fracture axis Neck 69432 S111.00 open fracture of cervical spine with spinal cord lesion Neck 55346 S100x00 multiple closed fractures of cervical vertebrae Neck 25284 S1z..00 fracture of neck and trunk nos Neck 52300 S110.00 closed fracture of cervical spine with cord lesion Neck 3288 S10A.00 fracture of neck Neck
16277 S100200 closed fracture axis Neck 54299 S100K00 closed fracture cervical vertebra, spinous process Neck 32009 SR10.00 fractures involving head with neck Neck 67973 S100G00 closed fracture cervical vertebra, burst Neck 41548 S100400 closed fracture of fourth cervical vertebra Neck 27575 S100500 closed fracture of fifth cervical vertebra Neck 15613 S100000 closed fracture of unspecified cervical vertebra Neck 69974 S100900 closed fracture atlas, comminuted Neck 24671 S101500 open fracture of fifth cervical vertebra Neck 19189 S10A200 multiple fractures of cervical spine Neck 94292 S100D00 closed fracture axis, transverse process Neck 5445 S100100 closed fracture atlas Neck
95513 S100M00 closed fracture cervical vertebra, posterior arch Neck 72711 S110600 cls spinal fracture with unspec cervical cord lesion, c5-7 Neck 94844 S101A00 open fracture axis, odontoid process Neck 28133 S10A000 fracture of first cervical vertebra Neck 43091 S112600 cls spinal fracture with unspec thoracic cord lesion, t7-12 Rib/sternum/thoracic 11378 S12z.11 rib fracture nos Rib/sternum/thoracic 55424 S120500 closed fracture of five ribs Rib/sternum/thoracic 9688 S127.00 fracture of rib Rib/sternum/thoracic
101299 S113000 opn spinal fracture with unspec thoracic cord lesion, t1-6 Rib/sternum/thoracic 73613 S121000 open fracture of rib, unspecified Rib/sternum/thoracic 17107 S29..12 multiple rib fractures Rib/sternum/thoracic 68899 S29..13 multiple fractures of sternum Rib/sternum/thoracic 39816 S102000 closed fracture thoracic vertebra, burst Rib/sternum/thoracic 62631 S4J2000 closed fracture-subluxation of sternum Rib/sternum/thoracic 3983 S122.00 closed fracture sternum Rib/sternum/thoracic
35849 S112.00 closed fracture of thoracic spine with spinal cord lesion Rib/sternum/thoracic 58190 S12X000 closed fracture of bony thorax part unspecified Rib/sternum/thoracic 56961 S12..00 fracture of rib(s), sternum, larynx and trachea Rib/sternum/thoracic
101560 S121z00 open fracture of rib(s) nos Rib/sternum/thoracic 65155 S4J0000 closed fracture-dislocation of sternum Rib/sternum/thoracic
280 S120.00 closed fracture rib Rib/sternum/thoracic 71452 S121900 open fracture multiple ribs Rib/sternum/thoracic 73611 S112z00 closed fracture of thoracic spine with cord lesion nos Rib/sternum/thoracic 66322 S150100 open multiple fracture of thoracic spine Rib/sternum/thoracic 5381 S15..00 fracture of thoracic vertebra Rib/sternum/thoracic
99516 S102500 closed fracture thoracic vertebra, posterior arch Rib/sternum/thoracic 16494 S120100 closed fracture of one rib Rib/sternum/thoracic 7831 S120000 closed fracture of rib, unspecified Rib/sternum/thoracic
48224 S121.00 open fracture rib Rib/sternum/thoracic 48886 S102400 closed fracture thoracic vertebra, transverse process Rib/sternum/thoracic 65484 S120600 closed fracture of six ribs Rib/sternum/thoracic 34197 S120400 closed fracture of four ribs Rib/sternum/thoracic 65151 S124000 closed flail chest Rib/sternum/thoracic 28524 S102100 closed fracture thoracic vertebra, wedge Rib/sternum/thoracic
101973 8752 plugging of flail chest Rib/sternum/thoracic 10696 S127000 multiple fractures of ribs Rib/sternum/thoracic 68652 S120800 closed fracture of eight or more ribs Rib/sternum/thoracic 95839 S12y000 closed fracture of other parts of bony thorax Rib/sternum/thoracic 41138 S102z00 closed fracture thoracic vertebra not otherwise specified Rib/sternum/thoracic 11770 S102y00 other specified closed fracture thoracic vertebra Rib/sternum/thoracic 94593 S4J3000 open fracture-subluxation of sternum Rib/sternum/thoracic 28244 S120z00 closed fracture of rib(s) nos Rib/sternum/thoracic 54353 S12X.00 fracture of bony thorax, part unspecified Rib/sternum/thoracic 56248 SC01100 late effect of fracture of thoracic vertebra Rib/sternum/thoracic 44826 S121200 open fracture of two ribs Rib/sternum/thoracic 73956 S121700 open fracture of seven ribs Rib/sternum/thoracic
101318 S103500 open fracture thoracic vertebra, posterior arch Rib/sternum/thoracic 11277 S150.00 multiple fractures of thoracic spine Rib/sternum/thoracic 35260 S150000 closed multiple fractures of thoracic spine Rib/sternum/thoracic 60615 S113.00 open fracture of thoracic spine with spinal cord lesion Rib/sternum/thoracic 94236 S4J1000 open fracture-dislocation of sternum Rib/sternum/thoracic 11004 S120900 closed fracture multiple ribs Rib/sternum/thoracic 27818 S12z.12 sternum fracture nos Rib/sternum/thoracic 11969 S128.00 fracture of sternum Rib/sternum/thoracic 56384 S120300 closed fracture of three ribs Rib/sternum/thoracic 45723 S12z.00 fracture of rib(s), sternum, larynx or trachea nos Rib/sternum/thoracic 27404 S102.00 closed fracture thoracic vertebra Rib/sternum/thoracic 36249 S124.00 flail chest Rib/sternum/thoracic
237
63253 S103.00 open fracture thoracic vertebra Rib/sternum/thoracic 48958 S112100 cls spinal fracture wth complete thoracic cord lesion,t1-6 Rib/sternum/thoracic 40533 S120200 closed fracture of two ribs Rib/sternum/thoracic 64872 S102300 closed fracture thoracic vertebra, spinous process Rib/sternum/thoracic 62047 S103100 open fracture thoracic vertebra, wedge Rib/sternum/thoracic 99895 S12y.00 fracture of other parts of bony thorax Rib/sternum/thoracic 63982 S123.00 open fracture sternum Rib/sternum/thoracic 90494 S120700 closed fracture of seven ribs Rib/sternum/thoracic 73601 S105000 open fracture lumbar vertebra, burst Lumbar spine/pelvis 72600 S106100 closed vertical fracture of sacrum Lumbar spine/pelvis 45011 S4J1100 open fracture-dislocation of pelvis Lumbar spine/pelvis 99203 S135y00 other open fracture of pelvis Lumbar spine/pelvis 35018 S135z00 other/multiple open fracture of pelvis nos Lumbar spine/pelvis 59904 S130y00 other specified closed fracture acetabulum Lumbar spine/pelvis 9072 S10B400 fracture of acetabulum Lumbar spine/pelvis
55280 S109.00 open fracture pelvis, coccyx Lumbar spine/pelvis 738 S13..00 fracture or disruption of pelvis Lumbar spine/pelvis
41698 S134300 closed fracture pelvis, ischial tuberosity Lumbar spine/pelvis 3888 S104.00 closed fracture lumbar vertebra Lumbar spine/pelvis
35096 S104300 closed fracture lumbar vertebra, spinous process Lumbar spine/pelvis 96984 S135000 open fracture of ilium, unspecified Lumbar spine/pelvis 29089 S104400 closed fracture lumbar vertebra, transverse process Lumbar spine/pelvis 28375 S13y.00 closed fracture of pelvis nos Lumbar spine/pelvis 42968 S104000 closed fracture lumbar vertebra, burst Lumbar spine/pelvis 95585 S104600 closed fracture lumbar vertebra, tricolumnar Lumbar spine/pelvis 57923 S130300 closed fracture acetabulum, posterior column Lumbar spine/pelvis 70674 S133z00 open fracture of pubis nos Lumbar spine/pelvis 7004 S132000 closed fracture pelvis, single pubic ramus Lumbar spine/pelvis
53566 S131.00 open fracture acetabulum Lumbar spine/pelvis 67669 S135600 open fracture pelvis, iliac wing Lumbar spine/pelvis 42780 S105.00 open fracture lumbar vertebra Lumbar spine/pelvis 94584 S117300 open fracture of sacrum with other spinal cord injury Lumbar spine/pelvis 64777 S131z00 open fracture acetabulum nos Lumbar spine/pelvis 51038 S133100 open fracture pelvis, multiple pubic rami - stable Lumbar spine/pelvis 34212 S4J2100 closed fracture-subluxation of pelvis Lumbar spine/pelvis 40643 S134000 closed fracture of ilium, unspecified Lumbar spine/pelvis 94649 S130100 closed fracture acetabulum, posterior lip alone Lumbar spine/pelvis 99376 S116z00 closed fracture of sacrum with spinal cord lesion nos Lumbar spine/pelvis 6667 S132100 closed fracture pelvis, multiple pubic rami - stable Lumbar spine/pelvis
40587 S134500 closed fracture pelvis, anterior inferior iliac spine Lumbar spine/pelvis 34708 S134100 closed fracture pelvis, ischium Lumbar spine/pelvis 65297 S4J3100 open fracture-subluxation of pelvis Lumbar spine/pelvis 43448 S135400 open fracture pelvis, anterior superior iliac spine Lumbar spine/pelvis 27922 S10B300 fracture of ilium Lumbar spine/pelvis 28155 SC01200 late effect of fracture of lumbar vertebra Lumbar spine/pelvis 49567 S114000 closed spinal fracture with unspecified lumbar cord lesion Lumbar spine/pelvis
105695 S105400 open fracture lumbar vertebra, transverse process Lumbar spine/pelvis 34910 S4J0100 closed fracture-dislocation of pelvis Lumbar spine/pelvis 94127 S133y00 other specified open fracture of pubis Lumbar spine/pelvis 10990 S10B000 fracture of lumbar vertebra Lumbar spine/pelvis 8266 S104100 closed fracture lumbar vertebra, wedge Lumbar spine/pelvis 3675 S10B100 fracture of sacrum Lumbar spine/pelvis
57444 S116.00 closed fracture of sacrum with spinal cord lesion Lumbar spine/pelvis 101517 S118z00 closed fracture of coccyx with spinal cord lesion nos Lumbar spine/pelvis
8613 S10B600 multiple fractures of lumbar spine and pelvis Lumbar spine/pelvis 108000 S135100 open fracture pelvis, ischium Lumbar spine/pelvis 69418 S130400 closed fracture acetabulum, floor Lumbar spine/pelvis
101447 S133200 open fracture pelvis, multiple pubic rami - unstable Lumbar spine/pelvis 64139 S13z.00 open fracture of pelvis nos Lumbar spine/pelvis 96473 S117.00 open fracture of sacrum with spinal cord lesion Lumbar spine/pelvis 5302 S132.00 closed fracture pubis Lumbar spine/pelvis
44059 S114.00 closed fracture of lumbar spine with spinal cord lesion Lumbar spine/pelvis 72525 S130000 closed fracture acetabulum, anterior lip alone Lumbar spine/pelvis 94189 S115.00 open fracture of lumbar spine with spinal cord lesion Lumbar spine/pelvis 51018 S118.00 closed fracture of coccyx with spinal cord lesion Lumbar spine/pelvis 14834 S108.00 closed fracture pelvis, coccyx Lumbar spine/pelvis 33961 S134.00 other or multiple closed fracture of pelvis Lumbar spine/pelvis 12406 S10B.00 fracture of lumbar spine and pelvis Lumbar spine/pelvis 50749 S133.00 open fracture of pubis Lumbar spine/pelvis 28702 S132z00 closed fracture pubis nos Lumbar spine/pelvis 2328 S10B500 fracture of pubis Lumbar spine/pelvis
53802 Syu3400 [x]fract of other and unspec parts of lumbar spine & pelvis Lumbar spine/pelvis 27854 S134600 closed fracture pelvis, iliac wing Lumbar spine/pelvis 11639 S134z00 other or multiple closed fracture of pelvis nos Lumbar spine/pelvis 73479 S130200 closed fracture acetabulum, anterior column Lumbar spine/pelvis 95842 S104500 closed fracture lumbar vertebra, posterior arch Lumbar spine/pelvis 62562 S131y00 other specified open fracture acetabulum Lumbar spine/pelvis 46592 S132200 closed fracture pelvis, multiple pubic rami - unstable Lumbar spine/pelvis 34685 S133000 open fracture pelvis, single pubic ramus Lumbar spine/pelvis
835 S10B200 fracture of coccyx Lumbar spine/pelvis 95529 S114100 closed spinal fracture with complete lumbar cord lesion Lumbar spine/pelvis 66434 S107.00 open fracture sacrum Lumbar spine/pelvis
238
65302 S105100 open fracture lumbar vertebra, wedge Lumbar spine/pelvis 52470 S134700 closed vertical fracture of ilium Lumbar spine/pelvis
105935 S107000 open compression fracture sacrum Lumbar spine/pelvis 68763 S135300 open fracture pelvis, ischial tuberosity Lumbar spine/pelvis 72404 S106000 closed compression fracture sacrum Lumbar spine/pelvis 45527 S130z00 closed fracture acetabulum nos Lumbar spine/pelvis 97354 S107100 open vertical fracture of sacrum Lumbar spine/pelvis 38895 S132y00 other specified closed fracture pubis Lumbar spine/pelvis 65084 S135.00 other or multiple open fracture of pelvis Lumbar spine/pelvis 28234 S134400 closed fracture pelvis, anterior superior iliac spine Lumbar spine/pelvis 98267 S130600 closed fracture acetabulum, double column unspecified Lumbar spine/pelvis 15877 S106.00 closed fracture sacrum Lumbar spine/pelvis 1591 S130.00 closed fracture acetabulum Lumbar spine/pelvis
28110 SR16.00 fract invol thorax with lower back and pelvis with limb(s) Lumbar spine/pelvis 33918 SC0X.00 sequelae of other fracture of thorax and pelvis Lumbar spine/pelvis 57223 SR16000 closed fracture inv thorax wth low back and pelvis and limbs Lumbar spine/pelvis 45934 SR11.00 fractures involving thorax with lower back and pelvis Lumbar spine/pelvis 36332 S210600 closed fracture scapula, neck Shoulder/upper arm 44715 S200000 closed fracture of clavicle, unspecified part Shoulder/upper arm 33489 S220200 closed fracture of proximal humerus, anatomical neck Shoulder/upper arm 10382 S22z.00 fracture of humerus nos Shoulder/upper arm 99325 S225x00 open fracture of distal humerus, multiple Shoulder/upper arm 73109 S211400 open fracture scapula, blade Shoulder/upper arm 8661 S224600 closed fracture distal humerus, lateral epicondyle Shoulder/upper arm
61378 S222z00 closed fracture of humerus, shaft or unspecified part nos Shoulder/upper arm 94460 S201z00 open fracture of clavicle nos Shoulder/upper arm 4211 S20..11 collar bone fracture Shoulder/upper arm
11313 S220100 closed fracture proximal humerus, neck Shoulder/upper arm 33870 S21z.00 fracture of scapula nos Shoulder/upper arm 73768 S211000 open fracture of scapula, unspecified part Shoulder/upper arm 28739 S220400 closed fracture proximal humerus, head Shoulder/upper arm 11044 S220300 closed fracture proximal humerus, greater tuberosity Shoulder/upper arm 1548 S228.00 fracture of lower end of humerus Shoulder/upper arm
10622 S221.11 shoulder fracture - open Shoulder/upper arm 30659 S227.00 fracture of shaft of humerus Shoulder/upper arm 70653 S221700 open fracture proximal humerus, four part Shoulder/upper arm 28393 S224800 closed fracture distal humerus, capitellum Shoulder/upper arm 10735 S21..11 shoulder blade fracture Shoulder/upper arm 48217 S225600 open fracture distal humerus, lateral epicondyle Shoulder/upper arm 4029 S210300 closed fracture scapula, glenoid Shoulder/upper arm
57592 S210z00 closed fracture of scapula nos Shoulder/upper arm 61812 S201.00 open fracture of clavicle Shoulder/upper arm 28724 S224700 closed fracture distal humerus, medial epicondyle Shoulder/upper arm 66237 S292100 open multiple fractures of clavicle, scapula and humerus Shoulder/upper arm 6893 S224100 closed fracture distal humerus, supracondylar Shoulder/upper arm
86803 S225400 open fracture of distal humerus, condyle(s) unspecified Shoulder/upper arm 32348 S224400 closed fracture of distal humerus, condyle(s) unspecified Shoulder/upper arm
517 S22..00 fracture of humerus Shoulder/upper arm 68556 S201300 open fracture clavicle, lateral end Shoulder/upper arm 64229 S4A1.00 open fracture-dislocation shoulder Shoulder/upper arm 48961 S223000 open fracture of humerus nos Shoulder/upper arm 53866 Syu4400 [x]fracture of shoulder and upper arm, unspecified Shoulder/upper arm 44721 S220000 closed fracture of proximal humerus, unspecified part Shoulder/upper arm 70604 S221600 open fracture proximal humerus, three part Shoulder/upper arm 16389 S210100 closed fracture scapula, acromion Shoulder/upper arm 52083 S224500 closed fracture of distal humerus, trochlea Shoulder/upper arm 19186 S222000 closed fracture of humerus nos Shoulder/upper arm 62833 S224x00 closed fracture of distal humerus, multiple Shoulder/upper arm 73426 S223z00 open fracture of humerus, shaft or unspecified part nos Shoulder/upper arm 70486 S221400 open fracture proximal humerus, head Shoulder/upper arm 60580 S4A2000 closed fracture-subluxation shoulder joint Shoulder/upper arm 48859 S210500 closed fracture scapula, spine Shoulder/upper arm 8348 S4A0.00 closed fracture-dislocation shoulder Shoulder/upper arm
53688 S221000 open fracture of proximal humerus, unspecified part Shoulder/upper arm 38028 S210000 closed fracture of scapula, unspecified part Shoulder/upper arm 35789 S4A2.00 closed fracture-subluxation shoulder Shoulder/upper arm 97352 Syu4200 [x]multiple fractures of clavicle, scapula and humerus Shoulder/upper arm 29137 S220700 closed fracture proximal humerus, four part Shoulder/upper arm 38353 S220z00 closed fracture of proximal humerus not otherwise specified Shoulder/upper arm 47839 S225z00 open fracture of distal humerus, not otherwise specified Shoulder/upper arm 36464 S222.00 closed fracture of humerus, shaft or unspecified part Shoulder/upper arm 45275 S221z00 open fracture of proximal humerus not otherwise specified Shoulder/upper arm 5345 S4A..00 fracture-dislocation or subluxation shoulder Shoulder/upper arm 9420 S221.00 open fracture of the proximal humerus Shoulder/upper arm
63899 S225500 open fracture of distal humerus, trochlea Shoulder/upper arm 70864 S201000 open fracture of clavicle, unspecified part Shoulder/upper arm 33680 S223.00 open fracture of humerus, shaft or unspecified part Shoulder/upper arm 71207 S221200 open fracture of proximal humerus, anatomical neck Shoulder/upper arm 60163 S225200 open fracture distal humerus, lateral condyle Shoulder/upper arm 34172 S225.00 open fracture of the distal humerus Shoulder/upper arm 18394 S224200 closed fracture distal humerus, lateral condyle Shoulder/upper arm
483 S20..00 fracture of clavicle Shoulder/upper arm
239
28307 S200200 closed fracture clavicle, shaft Shoulder/upper arm 40330 S220600 closed fracture proximal humerus, three part Shoulder/upper arm 35386 S211.00 open fracture of scapula Shoulder/upper arm 1177 S21..00 fracture of scapula Shoulder/upper arm
31760 S225100 open fracture distal humerus, supracondylar Shoulder/upper arm 33540 S224z00 closed fracture of distal humerus, not otherwise specified Shoulder/upper arm 33704 S4A0000 closed fracture-dislocation shoulder joint Shoulder/upper arm 97820 S225900 open fracture distal humerus, bicondylar (t-y fracture) Shoulder/upper arm 29899 S200300 closed fracture clavicle, lateral end Shoulder/upper arm 27620 S210.00 closed fracture of scapula Shoulder/upper arm 40367 S224300 closed fracture distal humerus, medial condyle Shoulder/upper arm 69312 S225300 open fracture distal humerus, medial condyle Shoulder/upper arm 48239 S221300 open fracture proximal humerus, greater tuberosity Shoulder/upper arm 53622 S221100 open fracture proximal humerus, neck Shoulder/upper arm 33749 S200.00 closed fracture of clavicle Shoulder/upper arm 16866 S225700 open fracture distal humerus, medial epicondyle Shoulder/upper arm 17956 S201200 open fracture clavicle, shaft Shoulder/upper arm 2101 S226.00 fracture of upper end of humerus Shoulder/upper arm
102965 S4A1000 open fracture-dislocation shoulder joint Shoulder/upper arm 32646 S225800 open fracture distal humerus, capitellum Shoulder/upper arm 64021 S211200 open fracture scapula, coracoid Shoulder/upper arm 15376 S224.00 closed fracture of the distal humerus Shoulder/upper arm 16944 S292.00 multiple fractures of clavicle, scapula and humerus Shoulder/upper arm 94435 S211z00 open fracture of scapula nos Shoulder/upper arm 52406 S220500 closed fracture of humerus, upper epiphysis Shoulder/upper arm 40976 S292000 closed multiple fractures of clavicle, scapula and humerus Shoulder/upper arm 27886 S222100 closed fracture of humerus, shaft Shoulder/upper arm 5344 S210400 closed fracture scapula, blade Shoulder/upper arm
55687 S211100 open fracture scapula, acromion Shoulder/upper arm 60108 S211300 open fracture scapula, glenoid Shoulder/upper arm 44711 S200100 closed fracture clavicle, medial end Shoulder/upper arm 28066 S20z.00 fracture of clavicle nos Shoulder/upper arm 11222 S220.00 closed fracture of the proximal humerus Shoulder/upper arm 59943 S221500 open fracture of humerus, upper epiphysis Shoulder/upper arm 71953 S211600 open fracture scapula, neck Shoulder/upper arm 34907 S210200 closed fracture scapula, coracoid Shoulder/upper arm 28179 S200z00 closed fracture of clavicle nos Shoulder/upper arm 52457 Syu4300 [x]fracture of other parts of shoulder and upper arm Shoulder/upper arm 40358 S223100 open fracture of humerus, shaft Shoulder/upper arm
100040 S201100 open fracture clavicle, medial end Shoulder/upper arm 53677 S224900 closed fracture distal humerus, bicondylar (t-y fracture) Shoulder/upper arm 70503 S233200 open fracture of the ulnar shaft Forearm 11262 S235300 open fracture of ulna, styloid process Forearm 7988 S239.00 fracture of shaft of radius Forearm
104070 S235C00 open fracture distal radius, intra-articular, die-punch Forearm 4359 S23x300 closed fracture of the radius and ulna Forearm
33404 S236.00 fracture of upper end of ulna Forearm 58752 S4B2.00 closed fracture-subluxation elbow Forearm 10246 S231300 open monteggia's fracture Forearm 18389 S234000 closed fracture of forearm, lower end, unspecified Forearm 2662 S230300 closed monteggia's fracture Forearm
12063 S230B00 closed fracture olecranon, intra-articular Forearm 30418 S235800 open galeazzi fracture Forearm 26324 S232.00 closed fracture of radius and ulna, shaft Forearm 9165 S234300 closed fracture of ulna, styloid process Forearm
42957 S230z00 closed fracture of proximal forearm not otherwise specified Forearm 19058 S234D00 closed fracture distal radius, extra-articular, other type Forearm 17822 S230200 closed fracture of ulna, coronoid Forearm 43972 S4B1.00 open fracture-dislocation elbow Forearm 52977 Syu5400 [x]fracture of forearm, unspecified Forearm 33883 S230900 closed fracture of the proximal radius Forearm 18299 S234.00 closed fracture of radius and ulna, lower end Forearm 44924 S235200 open fracture of the distal radius, unspecified Forearm 27784 S233z00 open fracture of radius and ulna, shaft, nos Forearm 65301 S23yz00 open fracture of radius and ulna, nos Forearm 15764 S23x.00 closed fracture of radius and ulna, unspecified part Forearm 24621 S23x200 closed fracture of ulna (alone), unspecified Forearm 53698 S235D00 open fracture distal radius, extra-articular other type Forearm 40268 S234800 closed galeazzi fracture Forearm 62960 S4B0100 closed fracture-dislocation superior radio-ulnar joint Forearm 70590 S23y000 open fracture of forearm, unspecified Forearm 2303 S237.00 fracture of upper end of radius Forearm
34371 S230400 closed fracture of proximal ulna, comminuted Forearm 27590 S235.00 open fracture of radius and ulna, lower end Forearm 66774 S235z00 open fracture of forearm, lower end, nos Forearm 7009 S230600 closed fracture radius, head Forearm 6380 S235B00 open fracture radial styloid Forearm 137 S23x111 fracture of radius nos Forearm
34426 S230500 closed fracture of the proximal ulna Forearm 60630 S235000 open fracture of forearm, lower end, unspecified Forearm 23987 S234211 dupuytren's fracture, radius - closed Forearm
105278 S235211 dupuytren's fracture, radius - open Forearm
240
34367 S23y100 open fracture of radius (alone), unspecified Forearm 909 S23z.00 fracture of radius and ulna, nos Forearm
49796 S235500 open fracture distal ulna - other Forearm 7636 S231600 open fracture radial head Forearm 3748 S233.00 open fracture of radius and ulna, shaft Forearm
40476 S234500 closed fracture distal ulna, unspecified Forearm 10228 S4B..00 fracture-dislocation or subluxation elbow Forearm 28293 S234E00 closed fracture distal radius, intra-articular, other type Forearm 8704 S23y300 open fracture of the radius and ulna Forearm 7754 S225.11 elbow fracture - open Forearm
10149 S23A.00 fracture of shafts of both ulna and radius Forearm 28708 S234600 closed fracture radius and ulna, distal Forearm
104355 S4B1100 open fracture-dislocation superior radio-ulnar joint Forearm 60343 S4C3000 open fracture-subluxation, distal radio-ulnar joint Forearm
343 S234100 closed colles' fracture Forearm 29152 S231100 open fracture olecranon, extra-articular Forearm 44538 S230A00 closed fracture radius and ulna, proximal Forearm
199 S23B.00 fracture of lower end of radius Forearm 102302 S234G00 greenstick fracture of distal radius Forearm 42864 S232100 closed fracture of the radial shaft Forearm 33687 S4B0.00 closed fracture-dislocation elbow Forearm 35031 S232300 closed fracture radius and ulna, middle Forearm 48245 S233300 open fracture radius and ulna, middle Forearm 54780 S23y.00 open fracture of radius and ulna, unspecified part Forearm 67036 S4B2000 closed fracture-subluxation elbow joint Forearm 66233 S233100 open fracture of the radial shaft Forearm 51364 S232000 closed fracture of radius, shaft, unspecified Forearm 50654 S23x000 closed fracture of forearm, unspecified Forearm 85491 S4B3.00 open fracture-subluxation elbow Forearm 38398 S235600 open fracture radius and ulna, distal Forearm 9538 S230100 closed fracture olecranon, extra-articular Forearm
54149 S4B1000 open fracture-dislocation elbow joint Forearm 34737 S231700 open fracture radial neck Forearm 37875 S231A00 open fracture radius and ulna, proximal Forearm 45695 S231.00 open fracture of proximal radius and ulna Forearm 17952 S23x100 closed fracture of radius (alone), unspecified Forearm 36328 S23xz00 closed fracture of radius and ulna, nos Forearm 61374 S231500 open fracture of the proximal ulna Forearm 6213 S23C.00 fracture of lower end of both ulna and radius Forearm
10640 S23..11 forearm fracture Forearm 9261 S4C1000 open fracture-dislocation, distal radio-ulnar joint Forearm 8410 S231B00 open fracture olecranon, intra-articular Forearm 1742 S234200 closed fracture of the distal radius, unspecified Forearm
96691 S235400 open fracture of ulna, lower epiphysis Forearm 27591 S234z00 closed fracture of forearm, lower end, nos Forearm 33933 S230000 closed fracture of proximal forearm, unspecified part Forearm
104356 S4B2100 closed fracture-subluxation superior radio-ulnar joint Forearm 102916 Syu5300 [x]fracture of other parts of forearm Forearm 72408 S231800 open fracture proximal radius, comminuted Forearm 63948 S231900 open fracture of the proximal radius Forearm 8915 S293.00 multiple fractures of forearm Forearm
33808 S232z00 closed fracture of radius and ulna, shaft, nos Forearm 44652 S4C2000 closed fracture-subluxation, distal radio-ulnar jt Forearm 6915 S234B00 closed fracture radial styloid Forearm 6825 S23..00 fracture of radius and ulna Forearm
55201 S231z00 open fracture of forearm, upper end, nos Forearm 42076 S234400 closed fracture of ulna, lower epiphysis Forearm 17922 S4C0000 closed fracture-dislocation distal radio-ulnar joint Forearm 43570 S230.00 closed fracture of proximal radius and ulna Forearm 28741 S23y200 open fracture of ulna (alone), unspecified Forearm 52614 S231200 open fracture of ulna, coronoid Forearm 34286 S230711 Closed # radius neck Forearm 8382 S238.00 fracture of shaft of ulna Forearm 9468 S4B0000 closed fracture-dislocation elbow joint Forearm
50223 S231000 open fracture of proximal forearm, unspecified Forearm 6074 S235100 open colles' fracture Forearm
33720 S224000 closed fracture of elbow, unspecified part Forearm 1073 S23x211 fracture of ulna nos Forearm
63588 S235E00 open fracture distal radius, intra-articular other type Forearm 1250 S224.11 elbow fracture - closed Forearm 7660 S230700 closed fracture radius, neck Forearm
34370 S230800 closed fracture proximal radius, comminuted Forearm 60518 S233000 open fracture of radius, shaft, unspecified Forearm 44142 S225000 open fracture of elbow, unspecified part Forearm 44844 S234C00 closed fracture distal radius, intra-articular, die-punch Forearm 44790 S232200 closed fracture of the ulnar shaft Forearm 27881 S250600 closed fracture finger metacarpal Wrist/hand 45094 S260W00 closed fracture finger distal phalanx, multiple Wrist/hand 28197 S261R00 open fracture finger distal phalanx Wrist/hand 24598 S250500 closed fracture finger metacarpal head Wrist/hand 52588 S251400 open fracture finger metacarpal neck Wrist/hand 25519 S250300 closed fracture finger metacarpal shaft Wrist/hand
241
67097 S260Q00 closed fracture finger middle phalanx, multiple Wrist/hand 27783 S4C0300 closed fracture-dislocation, carpometacarpal joint Wrist/hand 53650 S250C00 closed fracture thumb metacarpal head Wrist/hand 29117 S260R00 closed fracture finger distal phalanx Wrist/hand 47837 S240C00 closed fracture scaphoid, waist, oblique Wrist/hand 33908 S27..00 multiple fractures of hand bones Wrist/hand 40304 S261K00 open fracture finger middle phalanx Wrist/hand 68262 S4C3600 open fracture-subluxation peri-lunate trans-scaphoid Wrist/hand 63961 S261100 Opn # mid/prox phalanx or phalanges, unspecified part Wrist/hand
100350 S4C2y00 closed fracture-subluxation other carpal Wrist/hand 18336 S261.00 open fracture of one or more phalanges of hand Wrist/hand 53593 S261B00 open fracture thumb distal phalanx, tuft Wrist/hand 17921 S4C2.00 closed fracture-subluxation of the wrist Wrist/hand
102013 S241z00 open fracture of carpal bone nos Wrist/hand 40361 S251600 open fracture finger metacarpal Wrist/hand 27643 S260S00 closed fracture finger distal phalanx, base Wrist/hand 24516 S260D00 closed fracture finger proximal phalanx Wrist/hand 17286 S241100 open fracture of the scaphoid Wrist/hand 10462 S4D0500 closed fracture-dislocation, interphalangeal joint thumb Wrist/hand 33866 S261M00 open fracture finger middle phalanx, shaft Wrist/hand 34356 S260N00 closed fracture finger middle phalanx, neck Wrist/hand 43681 S260500 closed fracture thumb proximal phalanx, shaft Wrist/hand 61181 S260C00 closed fracture thumb distal phalanx, mallet Wrist/hand 12546 S250400 closed fracture finger metacarpal neck Wrist/hand 34058 S260000 closed fracture of phalanx or phalanges, unspecified Wrist/hand 67584 S4C0200 closed fracture-dislocation mid carpal Wrist/hand 52067 S253.00 open fracture sesamoid bone of hand Wrist/hand 22375 S24..00 fracture of carpal bone Wrist/hand 7564 S242100 fracture of first metacarpal bone Wrist/hand
23983 S251100 Opn # thumb metacarpal base, intra-articular, Bennett Wrist/hand 53068 Syu6500 [x]fracture of other & unspecified parts of wrist and hand Wrist/hand 4582 S26z.00 fracture of one or more phalanges of hand nos Wrist/hand
28249 S260800 closed fracture thumb distal phalanx Wrist/hand 43792 S24z.00 fracture of carpal bone nos Wrist/hand 56906 S251900 Opn # thumb metacarpal base, intra-articular, Rolando Wrist/hand 69729 S261J00 open fracture finger proximal phalanx, multiple Wrist/hand 65715 S261A00 open fracture thumb distal phalanx, shaft Wrist/hand 94416 S261500 open fracture thumb proximal phalanx, shaft Wrist/hand 69363 S261N00 open fracture finger middle phalanx, neck Wrist/hand 19403 S240B00 closed fracture scaphoid, waist, transverse Wrist/hand 38408 S4C0100 closed fracture-dislocation radiocarpal joint Wrist/hand 64113 S261G00 open fracture finger proximal phalanx, neck Wrist/hand 15666 S240.00 closed fracture of carpal bone Wrist/hand
103416 S261C00 open fracture thumb distal phalanx, mallet Wrist/hand 46798 S4C3100 open fracture-subluxation radiocarpal joint Wrist/hand 18338 S260F00 closed fracture finger proximal phalanx, shaft Wrist/hand 12516 S2B..00 fracture of bone of hand Wrist/hand 2643 S25..11 hand fracture - metacarpal bone Wrist/hand
67718 S261L00 open fracture finger middle phalanx, base Wrist/hand 67011 S261x00 open fracture of phalanx or phalanges, multiple sites Wrist/hand 54123 S261W00 open fracture finger distal phalanx, multiple Wrist/hand 16985 S240A00 closed fracture scaphoid, proximal pole Wrist/hand 62853 S251000 open fracture of metacarpal bone(s), site unspecified Wrist/hand 73165 S240F00 closed fracture carpal bones, multiple Wrist/hand 6168 S240100 closed fracture of the scaphoid Wrist/hand
34931 S260100 Clsd # mid/prox phalanx/phalanges, unspecified part Wrist/hand 33905 S250200 closed fracture finger metacarpal base Wrist/hand 61279 S261300 open fracture thumb proximal phalanx Wrist/hand 50781 S261z00 open fracture of one or more phalanges of hand nos Wrist/hand 63292 S4C1600 open fracture-dislocation peri-lunate trans-scaphoid Wrist/hand 44943 S260H00 closed fracture finger proximal phalanx, head Wrist/hand 33616 S260K00 closed fracture finger middle phalanx Wrist/hand 34099 S261200 Opn # distal phalanx or phalanges, unspecified part Wrist/hand
102046 S261V00 open fracture finger distal phalanx, mallet Wrist/hand 64027 S260600 closed fracture thumb proximal phalanx, neck Wrist/hand 94031 S261400 open fracture thumb proximal phalanx, base Wrist/hand 34429 S4C0.00 closed fracture dislocation of wrist Wrist/hand 45374 S260x00 closed fractures of phalanx or phalanges, multiple sites Wrist/hand 42844 S4C1.00 open fracture dislocation wrist Wrist/hand 25620 S260200 Cls # distal phalanx or phalanges, unspecified part Wrist/hand 51700 S261U00 open fracture finger distal phalanx, tuft Wrist/hand 6455 SC3C000 sequelae of fracture at wrist and hand level Wrist/hand 8302 S260.00 closed fracture of one or more phalanges of hand Wrist/hand
33684 S261D00 open fracture finger proximal phalanx Wrist/hand 97476 S4C1300 open fracture-dislocation carpometacarpal joint Wrist/hand 5260 S26..11 finger fracture Wrist/hand
49598 S250B00 closed fracture thumb metacarpal neck Wrist/hand 68595 S4C2300 closed fracture-subluxation, carpometacarpal joint Wrist/hand
101316 S261700 open fracture thumb proximal phalanx, head Wrist/hand 33929 S240z00 closed fracture of carpal bone nos Wrist/hand 34307 S260P00 closed fracture finger middle phalanx, head Wrist/hand 63712 S4C2600 closed fracture-subluxation peri-lunate trans-scaphoid Wrist/hand
242
42139 S260B00 closed fracture thumb distal phalanx, tuft Wrist/hand 28425 S240E00 closed fracture scaphoid, tuberosity Wrist/hand 52895 S250700 closed fracture finger metacarpal, multiple Wrist/hand 34054 S250900 Cls # thumb metacarpal base, intra-articular, Rolando Wrist/hand 63071 S4D2500 closed fracture-subluxation, interphalangeal joint thumb Wrist/hand 44712 S240D00 closed fracture scaphoid, waist, comminuted Wrist/hand
553 S242000 fracture of scaphoid Wrist/hand 48837 S261S00 open fracture finger distal phalanx, base Wrist/hand 44431 S270.00 closed multiple fractures of hand bones Wrist/hand
441 S26..00 fracture of one or more phalanges of hand Wrist/hand 37986 S261800 open fracture thumb distal phalanx Wrist/hand 33678 S260400 closed fracture thumb proximal phalanx, base Wrist/hand 98867 S251A00 open fracture thumb metacarpal shaft Wrist/hand 4725 S242300 multiple fractures of metacarpal bones Wrist/hand 203 S234.11 wrist fracture - closed Wrist/hand
44737 S260J00 closed fracture finger proximal phalanx, multiple Wrist/hand 45690 S4D1500 open fracture-dislocation, interphalangeal joint thumb Wrist/hand 62334 S261F00 open fracture finger proximal phalanx, shaft Wrist/hand 64575 S241D00 open fracture scaphoid, waist, comminuted Wrist/hand 68085 S241000 open fracture of carpal bone, unspecified Wrist/hand 2888 S25..00 fracture of metacarpal bone Wrist/hand
27699 S260E00 closed fracture finger proximal phalanx, base Wrist/hand 59985 S241C00 open fracture scaphoid, waist, oblique Wrist/hand 44700 S261E00 open fracture finger proximal phalanx, base Wrist/hand 6299 S263.00 fracture of other finger Wrist/hand
10250 S4D..00 fracture-dislocation/subluxation finger/thumb Wrist/hand 49256 S4C1100 open fracture-dislocation radiocarpal joint Wrist/hand 52333 S261T00 open fracture finger distal phalanx, shaft Wrist/hand
482 S26..12 thumb fracture excluding base Wrist/hand 72407 S251700 open fracture finger metacarpal, multiple Wrist/hand 60765 S251800 open fracture of thumb metacarpal Wrist/hand 99397 S261600 open fracture thumb proximal phalanx, neck Wrist/hand
993 S242200 fracture of other metacarpal bone Wrist/hand 56886 S240y00 closed fracture of other carpal bone Wrist/hand 65731 S261900 open fracture thumb distal phalanx, base Wrist/hand 25811 S250800 closed fracture of thumb metacarpal Wrist/hand 33582 S260300 closed fracture thumb proximal phalanx Wrist/hand 33598 S260L00 closed fracture finger middle phalanx, base Wrist/hand 8199 S264.00 multiple fractures of fingers Wrist/hand
53923 S27z.00 multiple fractures of hand bones nos Wrist/hand 36556 S261000 open fracture of phalanx or phalanges, unspecified Wrist/hand 61529 S261H00 open fracture finger proximal phalanx, head Wrist/hand 49588 S241E00 open fracture scaphoid, tuberosity Wrist/hand 73824 S241B00 open fracture scaphoid, waist, transverse Wrist/hand 73150 S251200 open fracture finger metacarpal base Wrist/hand 52305 S251300 open fracture finger metacarpal shaft Wrist/hand 33757 S260M00 closed fracture finger middle phalanx, shaft Wrist/hand 62808 S260A00 closed fracture thumb distal phalanx, shaft Wrist/hand 33990 S271.00 open multiple fractures of hand bones Wrist/hand 40535 S260z00 closed fracture of one or more phalanges of hand nos Wrist/hand 52398 S260V00 closed fracture finger distal phalanx, mallet Wrist/hand 59219 S4C3.00 open fracture-subluxation of the wrist Wrist/hand 71739 Syu6400 [x]fracture of other metacarpal bone Wrist/hand 94661 S4C3300 open fracture-subluxation, carpometacarpal joint Wrist/hand 8056 S242.00 fracture at wrist and hand level Wrist/hand
103524 S4C2200 closed fracture-subluxation mid carpal Wrist/hand 10428 S250100 Cls # thumb metacarpal base, intra-articular, Bennett Wrist/hand
102225 S251C00 open fracture thumb metacarpal head Wrist/hand 102155 Syu6300 [x]fracture of other carpal bone(s) Wrist/hand 29111 S251.00 open fracture of metacarpal bone(s) Wrist/hand 31525 S250000 closed fracture of metacarpal bone (s), site unspecified Wrist/hand 33651 S260700 closed fracture thumb proximal phalanx, head Wrist/hand 34080 S260900 closed fracture thumb distal phalanx, base Wrist/hand 50634 S250A00 closed fracture thumb metacarpal shaft Wrist/hand 92349 S4D3500 open fracture-subluxation, interphalangeal joint thumb Wrist/hand 33695 S260T00 closed fracture finger distal phalanx, shaft Wrist/hand 99459 S261P00 open fracture finger middle phalanx, head Wrist/hand 57979 S240000 closed fracture of carpal bone, unspecified Wrist/hand 10167 S24..11 hand fracture - carpal bone Wrist/hand 6881 S250z00 closed fracture of metacarpal bone(s) nos Wrist/hand
33679 S260G00 closed fracture finger proximal phalanx, neck Wrist/hand 53693 S251500 open fracture finger metacarpal head Wrist/hand 50148 S4C2100 closed fracture-subluxation radiocarpal joint Wrist/hand 10022 S235.11 wrist fracture - open Wrist/hand 55814 S241A00 open fracture scaphoid, proximal pole Wrist/hand 55212 S4C0600 closed fracture-dislocation peri-lunate trans-scaphoid Wrist/hand 65141 S241.00 open fracture of carpal bone Wrist/hand 18614 S4C..00 fracture-dislocation or subluxation of wrist Wrist/hand 7500 S262.00 fracture of thumb Wrist/hand
33845 S260U00 closed fracture finger distal phalanx, tuft Wrist/hand 6392 S250.00 closed fracture of metacarpal bone(s) Wrist/hand 7531 S252.00 closed fracture sesamoid bone of hand Wrist/hand
243
47847 S251z00 open fracture of metacarpal bone(s) nos Wrist/hand 30076 S2z..00 fracture of upper limb nos Upper limb (unspec) 5929 S2...11 arm fracture Upper limb (unspec) 6195 S2...00 fracture of upper limb Upper limb (unspec)
48142 S313200 open fracture of femur, lower epiphysis Femur 55327 S312x00 closed fracture distal femur, comminuted/intra-articular Femur 8040 S31..00 other fracture of femur Femur 520 S31z.00 fracture of femur, nos Femur
67633 S303000 Open # of proximal femur, trochanteric section, unspecified Femur 38489 S300.00 closed fracture proximal femur, transcervical Femur 61802 S312z00 closed fracture of distal femur not otherwise specified Femur 27989 SC3D400 sequelae of fracture of femur Femur 5332 S312300 closed fracture distal femur, supracondylar Femur
24587 S4E..00 fracture-dislocation or subluxation hip Femur 39396 S303400 open fracture of femur, intertrochanteric Femur 51861 S300311 closed fracture, base of neck of femur Femur 21773 S3x2.00 multiple fractures of femur Femur 42805 S313300 open fracture distal femur, supracondylar Femur 47917 SC03.00 late effect of fracture neck of femur Femur 36599 S300800 closed fracture proximal femur, subcapital, garden grade iii Femur 60885 S301600 open fracture proximal femur,subcapital, garden grade i Femur 33957 S300700 closed fracture proximal femur, subcapital, garden grade ii Femur 52194 S300300 closed fracture proximal femur, basicervical Femur 34106 S311000 open fracture of femur, unspecified part Femur 73981 S301.00 open fracture proximal femur, transcervical Femur 8589 S315.00 fracture of lower end of femur Femur
45562 S312400 closed fracture distal femur, medial condyle Femur 34351 S300600 closed fracture proximal femur, subcapital, garden grade i Femur 50727 S301000 Opn # proximal femur, intracapsular section, unspecified Femur 22329 S312.11 closed fracture of femur, distal end Femur 38054 S30z.00 open fracture of neck of femur nos Femur 96644 S303011 open fracture of femur, greater trochanter Femur 6868 S310.00 closed fracture of femur, shaft or unspecified part Femur
100771 S301311 open fracture base of neck of femur Femur 73113 Syu7200 [x]fractures of other parts of femur Femur 5301 S302.00 closed fracture of proximal femur, pertrochanteric Femur
61733 S303.00 open fracture of proximal femur, pertrochanteric Femur 72138 S301100 open fracture proximal femur, transepiphyseal Femur
101567 S303100 open fracture proximal femur, intertrochanteric, two part Femur 54242 S312600 closed fracture distal femur, bicondylar (t-y fracture) Femur 37662 S310000 closed fracture of femur, unspecified part Femur 17936 14G7.00 h/o: hip fracture Femur 94360 S311z00 open fracture of femur, shaft or unspecified part, nos Femur 67394 S301700 open fracture proximal femur,subcapital, garden grade ii Femur 48337 S302012 closed fracture of femur, lesser trochanter Femur 34078 S300900 closed fracture proximal femur, subcapital, garden grade iv Femur 73234 S301y11 open fracture of femur, subcapital Femur 45779 S300A00 closed fracture of femur, upper epiphysis Femur 2225 S30..00 fracture of neck of femur Femur
19387 S302011 closed fracture of femur, greater trochanter Femur 18273 S30y.00 closed fracture of neck of femur nos Femur 88737 S313z00 open fracture of distal femur not otherwise specified Femur 42972 S311.00 open fracture of femur, shaft or unspecified part Femur 71282 S303200 open fracture proximal femur, subtrochanteric Femur 70479 S303z00 open fracture of proximal femur, pertrochanteric, nos Femur 28954 S312.00 closed fracture distal femur Femur 32866 S313.11 open fracture of femur, distal end Femur 67294 S313400 open fracture distal femur, medial condyle Femur 58642 S30x.00 open fracture of unspecified proximal femur Femur 8646 S314.00 fracture of shaft of femur Femur
17019 S300500 Cls # prox femur, subcapital, Garden grade unspec. Femur 29145 S302200 closed fracture proximal femur, subtrochanteric Femur 51170 S313.00 open fracture distal femur Femur 19117 S302000 Cls # proximal femur, trochanteric section, unspecified Femur 53279 S312000 closed fracture of distal femur, unspecified Femur 45141 S302100 closed fracture proximal femur, intertrochanteric, two part Femur 73210 S301400 open fracture head, femur Femur 96518 S301A00 open fracture of femur, upper epiphysis Femur 58720 S4E1.00 open fracture-dislocation, hip joint Femur 97971 S303300 open fracture proximal femur, intertrochanteric, comminuted Femur 36391 S300400 closed fracture head of femur Femur 34738 S313500 open fracture distal femur, lateral condyle Femur 10570 S30y.11 hip fracture nos Femur 73208 S313x00 open fracture distal femur, comminuted/intra-articular Femur 69919 S300100 closed fracture proximal femur, transepiphyseal Femur 93374 S4E2.00 closed fracture-subluxation, hip joint Femur 40267 S4E0.00 closed fracture-dislocation, hip joint Femur 45529 S313000 open fracture distal femur, unspecified Femur 24674 S310100 closed fracture shaft of femur Femur 38878 S301500 open fracture proximal femur,subcapital, garden grade unspec Femur 8243 S305.00 subtrochanteric fracture Femur
68229 S300y11 closed fracture of femur, subcapital Femur
244
24276 S30w.00 closed fracture of unspecified proximal femur Femur 51999 S301900 open fracture proximal femur,subcapital, garden grade iv Femur 39984 S300000 Cls # prox femur, intracapsular section, unspecified Femur 1994 S30..11 hip fracture Femur
65690 S300200 closed fracture proximal femur, midcervical section Femur 38355 S312500 closed fracture distal femur, lateral condyle Femur 49209 S300y00 closed fracture proximal femur, other transcervical Femur 10095 S311100 open fracture shaft of femur Femur 68668 S301y00 open fracture proximal femur, other transcervical Femur 62966 S300z00 closed fracture proximal femur, transcervical, nos Femur 21922 S312200 closed fracture of femur, lower epiphysis Femur 23803 S301800 open fracture proximal femur,subcapital, garden grade iii Femur 51216 S302300 Cls # proximal femur, intertrochanteric, comminuted Femur 8648 S302400 closed fracture of femur, intertrochanteric Femur
44735 S302z00 Cls # of proximal femur, pertrochanteric section, NOS Femur 28426 S332100 closed fracture shaft of fibula Lower leg/ankle 51938 S333100 open fracture shaft of fibula Lower leg/ankle 33457 S331100 open fracture proximal fibula Lower leg/ankle 35011 S32z.00 fracture of patella, nos Lower leg/ankle 54280 S330200 closed fracture of tibia and fibula, proximal Lower leg/ankle 28352 S33y100 open fracture of fibula, unspecified part, nos Lower leg/ankle 42969 S344000 closed fracture ankle, bimalleolar, low fibular fracture Lower leg/ankle 34021 S332000 closed fracture shaft of tibia Lower leg/ankle 40653 S4F0.00 closed fracture-dislocation, knee joint Lower leg/ankle 29109 S33x.00 closed fracture of tibia and fibula, unspecified part, nos Lower leg/ankle 27721 S335000 open fracture distal tibia, extra-articular Lower leg/ankle 52322 S330900 closed fracture fibula, neck Lower leg/ankle 47828 S347000 open fracture ankle, trimalleolar, low fibular fracture Lower leg/ankle 50549 S320100 closed fracture patella, proximal pole Lower leg/ankle 44786 S331400 open fracture proximal tibia, lateral condyle (plateau) Lower leg/ankle 33768 S330600 closed fracture spine, tibia Lower leg/ankle 38733 S330700 closed fracture tubercle, tibia Lower leg/ankle 4572 S33x200 closed fracture of tibia and fibula, unspecified part Lower leg/ankle
28118 S333000 open fracture shaft of tibia Lower leg/ankle 28070 S4G3.00 open fracture-subluxation, ankle joint Lower leg/ankle 29121 S332.00 closed fracture of tibia/fibula, shaft Lower leg/ankle 33666 S4F2.00 closed fracture-subluxation, knee joint Lower leg/ankle 52346 S346100 closed fracture ankle, trimalleolar, high fibular fracture Lower leg/ankle 14826 S344.11 dupuytren's fracture, fibula Lower leg/ankle 9917 S347.00 open fracture ankle, trimalleolar Lower leg/ankle
33706 S331000 open fracture of the proximal tibia Lower leg/ankle 2630 S33..00 fracture of tibia and fibula Lower leg/ankle
10007 S338.00 fracture of lower end of tibia Lower leg/ankle 62787 S33yz00 open fracture of tibia and fibula, unspecified part, nos Lower leg/ankle 65228 S335100 open fracture distal tibia, intra-articular Lower leg/ankle 10009 S346.00 closed fracture ankle, trimalleolar Lower leg/ankle 7340 S342.00 closed fracture ankle, lateral malleolus Lower leg/ankle
99027 S331800 open fracture fibula, head Lower leg/ankle 73105 S343100 open fracture ankle, lateral malleolus, high Lower leg/ankle 52499 S330800 closed fracture fibula, head Lower leg/ankle
101840 S331A00 open fracture tibial plateau Lower leg/ankle 25485 S33z.00 fracture of tibia and fibula, nos Lower leg/ankle 33656 S330100 closed fracture proximal fibula Lower leg/ankle 18584 S345.00 open fracture ankle, bimalleolar Lower leg/ankle 22370 S330400 closed fracture proximal tibia, lateral condyle (plateau) Lower leg/ankle 56525 S346000 closed fracture ankle, trimalleolar, low fibular fracture Lower leg/ankle 18388 S343.00 open fracture ankle, lateral malleolus Lower leg/ankle 99161 S331900 open fracture fibula, neck Lower leg/ankle 63633 S331600 open fracture spine, tibia Lower leg/ankle 55464 S332z00 closed fracture of tibia and fibula, shaft, nos Lower leg/ankle 40069 S331.00 open fracture of tibia and fibula, proximal Lower leg/ankle 2250 S344.12 pott's fracture - ankle Lower leg/ankle
33393 S320.00 closed fracture of the patella Lower leg/ankle 41287 S320400 closed fracture patella, comminuted (stellate) Lower leg/ankle
971 S33x000 closed fracture of tibia, unspecified part, nos Lower leg/ankle 29911 S4F..00 fracture-dislocation or subluxation knee Lower leg/ankle 27719 S334.00 closed fracture distal tibia Lower leg/ankle 28198 S333z00 open fracture of tibia and fibula, shaft, nos Lower leg/ankle 49798 S331700 open fracture tubercle, tibia Lower leg/ankle 7723 S337.00 fracture of shaft of tibia Lower leg/ankle
105819 S347100 open fracture ankle, trimalleolar, high fibular fracture Lower leg/ankle 44329 S320200 closed fracture patella, distal pole Lower leg/ankle 4304 S33x100 closed fracture of fibula, unspecified part, nos Lower leg/ankle
40164 S330500 closed fracture proximal tibia, bicondylar Lower leg/ankle 52371 S344100 closed fracture ankle, bimalleolar, high fibular fracture Lower leg/ankle 44276 S331300 open fracture proximal tibia, medial condyle (plateau) Lower leg/ankle 29164 S33y000 open fracture of tibia, unspecified part, nos Lower leg/ankle 34302 S4G0.00 closed fracture-dislocation, ankle joint Lower leg/ankle 33520 S332200 closed fracture of tibia and fibula, shaft Lower leg/ankle
100159 S321100 open fracture patella, proximal pole Lower leg/ankle 7317 S344.00 closed fracture ankle, bimalleolar Lower leg/ankle 6917 S336.00 fracture of upper end of tibia Lower leg/ankle
245
50227 S321000 open fracture patella, transverse Lower leg/ankle 22761 S330012 closed fracture of tibial tuberosity Lower leg/ankle 54660 S320300 closed fracture patella, vertical Lower leg/ankle 33475 S321200 open fracture patella, distal pole Lower leg/ankle 57196 S4F3.00 open fracture-subluxation, knee joint Lower leg/ankle 59411 S4G2.00 closed fracture-subluxation, ankle joint Lower leg/ankle 41971 S33xz00 closed fracture of tibia and fibula, unspecified part, nos Lower leg/ankle 8465 S334100 closed fracture distal tibia, intra-articular Lower leg/ankle
35620 S342100 closed fracture ankle, lateral malleolus, high Lower leg/ankle 7135 S342000 closed fracture ankle, lateral malleolus, low Lower leg/ankle
34151 S334000 closed fracture distal tibia, extra-articular Lower leg/ankle 28233 S33y.00 open fracture of tibia and fibula, unspecified part, nos Lower leg/ankle 28068 S333.00 open fracture of tibia/fibula, shaft Lower leg/ankle 78444 S33A.00 fracture of tibia Lower leg/ankle
235 S32..00 fracture of patella Lower leg/ankle 66808 S345000 open fracture ankle, bimalleolar, low fibular fracture Lower leg/ankle 6839 S339000 closed fracture of distal fibula Lower leg/ankle
49801 S331012 open fracture of tibial tuberosity Lower leg/ankle 42978 S330z00 closed fracture of tibia and fibula, proximal nos Lower leg/ankle 33974 S341.00 open fracture ankle, medial malleolus Lower leg/ankle 20678 S333200 open fracture of tibia and fibula, shaft Lower leg/ankle 93029 S331011 open fracture of tibial condyles Lower leg/ankle 27992 S335.00 open fracture distal tibia Lower leg/ankle 28273 S321.00 open fracture of the patella Lower leg/ankle 44830 S330.00 closed fracture of tibia and fibula, proximal Lower leg/ankle 43566 S343000 open fracture ankle, lateral malleolus, low Lower leg/ankle 56927 S4G1.00 open fracture-dislocation, ankle joint Lower leg/ankle 4737 S34x.00 closed fracture ankle, unspecified Lower leg/ankle
28550 S330000 closed fracture of the proximal tibia Lower leg/ankle 6286 S340.00 closed fracture ankle, medial malleolus Lower leg/ankle
28731 S4F1.00 open fracture-dislocation, knee joint Lower leg/ankle 53951 S330011 closed fracture of tibial condyles Lower leg/ankle 6731 S349.00 fracture of lateral malleolus Lower leg/ankle 9212 S34z.00 fracture of ankle, nos Lower leg/ankle
100640 S33B.00 open fracture of distal tibia and fibula Lower leg/ankle 57439 S331z00 open fracture of tibia and fibula, proximal nos Lower leg/ankle 49526 S320000 closed fracture patella, transverse Lower leg/ankle 12369 S339100 open fracture of distal fibula Lower leg/ankle 29084 S33y200 open fracture of tibia and fibula, unspecified part Lower leg/ankle
105816 S345100 open fracture ankle, bimalleolar, high fibular fracture Lower leg/ankle 38765 S34y.00 open fracture ankle, unspecified Lower leg/ankle 54145 S331200 open fracture of tibia and fibula, proximal Lower leg/ankle
100202 S33C.00 closed fracture of distal tibia and fibula Lower leg/ankle 325 S34..00 fracture of ankle Lower leg/ankle
5009 S348.00 fracture of medial malleolus Lower leg/ankle 806 S339.00 fracture of fibula alone Lower leg/ankle
50254 S321400 open fracture patella, comminuted (stellate) Lower leg/ankle 15491 S4G..00 fracture-dislocation or subluxation ankle Lower leg/ankle 46955 S352900 closed fracture talus, neck Foot 30611 S352111 closed fracture of astragalus Foot 97380 Syu9400 [x]fracture of other tarsal bones Foot 70226 S351100 open fractures calcaneus, intra-articular Foot 49821 S353300 open fracture cuboid Foot 52340 S4H1.00 open fracture-dislocation, foot Foot 34424 S36z.00 fracture of one or more phalanges of foot nos Foot 67007 S353.00 open fracture of other tarsal and metatarsal bones Foot 45664 S352A00 closed fracture talus, body Foot 93650 S4H3.00 open fracture-subluxation, foot Foot 39733 S35z.00 fracture of tarsal and metatarsal bones nos Foot
100196 S353000 open fracture of tarsal bone, unspecified Foot 37450 S352800 closed fracture talus, head Foot 29748 S352D00 closed fracture metatarsal neck Foot
106875 S4H1600 open fracture-dislocation, ipj, multiple toes Foot 51213 S361200 open fracture distal phalanx, toe Foot 48925 S353z00 open fracture of tarsal and metatarsal bones nos Foot 53905 S360300 closed fracture multiple phalanges, toe Foot 28371 S352F00 closed fracture metatarsal, multiple Foot
105612 S353E00 open fracture metatarsal head Foot 68514 S4H3400 open fracture-subluxation, ipj, single toe Foot 71132 S4H0100 closed fracture-dislocation, midtarsal joint Foot 43153 S352z00 closed fracture of one or more tarsal + metatarsal bones nos Foot 2672 S36..00 fracture of one or more phalanges of foot Foot 1873 S36..11 toe fracture Foot
28800 S4H0400 closed fracture-dislocation, ipj, single toe Foot 25073 S360000 closed fracture proximal phalanx, toe Foot 4310 S352300 closed fracture cuboid Foot
27567 S352C00 closed fracture metatarsal shaft Foot 42902 S4H1400 open fracture-dislocation, ipj, single toe Foot 97386 S353A00 open fracture talus, body Foot 67239 S353J00 open fracture of base of fifth metatarsal Foot
169 S35..11 metatarsal bone fracture Foot 40992 S353200 open fracture navicular Foot
246
72586 S353B00 open fracture metatarsal base Foot 95728 S4H2400 closed fracture-subluxation, ipj, single toe Foot 8263 S350.11 heel bone fracture Foot
37865 S361.00 open fracture of one or more phalanges of foot Foot 2176 S362.00 fracture of great toe Foot
31847 S362100 open fracture of great toe Foot 73703 S4H2200 closed fracture-subluxation, tarsometatarsal joint Foot 2442 S355.00 fracture of talus Foot
34723 S350100 closed fracture calcaneus, intra-articular Foot 72822 S4H2600 closed fracture-subluxation, ipj, multiple toes Foot 7159 S363.00 fracture of other toe Foot
15079 S352100 closed fracture of talus Foot 67849 S4H0200 closed fracture-dislocation, tarsometatarsal joint Foot 50517 S361000 open fracture proximal phalanx, toe Foot 15166 S350.12 os calcis fracture Foot 8276 S350.00 closed fracture of calcaneus Foot
97803 S353D00 open fracture metatarsal neck Foot 92268 S4H0600 closed fracture-dislocation, ipj, multiple toes Foot 55939 S353700 open fracture metatarsal Foot
845 S35..00 fracture of one or more tarsal and metatarsal bones Foot 92043 S4H1200 open fracture-dislocation, tarsometatarsal joint Foot 11635 S352200 closed fracture navicular Foot 64378 S352G00 closed tarsal fractures, multiple Foot 93536 S353900 open fracture talus, neck Foot 1857 S354.00 fracture of calcaneus Foot
44673 S4H2.00 closed fracture-subluxation, foot Foot 65028 S4H2100 closed fracture-subluxation, midtarsal joint Foot 29804 S360100 closed fracture middle phalanx, toe Foot 28604 S362000 closed fracture of great toe Foot 24620 S352B00 closed fracture metatarsal base Foot 17249 S4H..00 fracture-dislocation or subluxation foot Foot 61556 S361300 open fracture multiple phalanges, toe Foot 3937 S352700 closed fracture metatarsal Foot
35077 S352E00 closed fracture metatarsal head Foot 15927 S352.00 closed fracture of other tarsal and metatarsal bones Foot 39758 S353100 open fracture of talus Foot 28251 S360200 closed fracture distal phalanx, toe Foot 69728 S361100 open fracture middle phalanx, toe Foot 2710 S35..12 tarsal bone fracture Foot 9174 S3x4.00 multiple fractures of foot Foot
64545 S353C00 open fracture metatarsal shaft Foot 6062 S356.00 fracture of metatarsal bone Foot
44628 S4H0.00 closed fracture-dislocation foot Foot 66099 S353F00 open fracture metatarsal, multiple Foot 28875 S352J00 closed fracture of base of fifth metatarsal Foot 43378 S351.00 open fracture of calcaneus Foot 57924 S350000 closed fracture calcaneus, extra-articular Foot 20253 S352000 closed fracture of tarsal bone, unspecified Foot 4306 S360.00 closed fracture of one or more phalanges of foot Foot 8891 S3...00 fracture of lower limb Lower limb (unspec)
33903 S37..00 fracture of lower limb, level unspecified Lower limb (unspec) 20893 S310012 upper leg fracture nos Lower limb (unspec) 2603 S3...11 leg fracture Lower limb (unspec)
35253 S33x.11 lower leg fracture nos Lower limb (unspec) 38741 7K1D200 prim open reduct fract long bone & fixation flexible nail Other fracture or related follow-up 59716 7K1HE00 revision to open reduction of fracture and external fixation Other fracture or related follow-up 24611 7K6F200 primary open reduction of fracture dislocation of joint nec Other fracture or related follow-up 7034 7K1LE00 closed reduction of fracture of elbow Other fracture or related follow-up
17036 8HB9.00 fracture therapy follow-up Other fracture or related follow-up 103307 7K6GK00 prim closed reduc fract dislocat joint and internal fixation Other fracture or related follow-up 63452 7J42300 spinal extension traction for fracture of spine Other fracture or related follow-up 22393 7K1JH00 primary wire fixation of fracture Other fracture or related follow-up 30377 Z6G1900 fracture - traction Other fracture or related follow-up 43730 7J03300 reduction of closed fracture of orbit bone Other fracture or related follow-up 12823 7K1J300 closed reduction fracture small bone & fixation using screw Other fracture or related follow-up 4350 7J13400 reduction of le fort 1 fracture of maxilla Other fracture or related follow-up
29858 7K1D300 prim open reduction fract small bone & fixation using screw Other fracture or related follow-up 8513 ZV57700 [v]rehabilitation following fracture Other fracture or related follow-up
99994 7K1K900 other primary external immobilisation of fracture Other fracture or related follow-up 107358 7K1Y000 remanip intracap fract neck fem and fix using nail or screw Other fracture or related follow-up 45410 7J41z00 decompression of fracture of spine nos Other fracture or related follow-up 34850 7J43100 fixation of fracture of spine using harrington rod Other fracture or related follow-up 51392 7J13100 open reduction of fracture of maxilla nec Other fracture or related follow-up 48159 7J42.11 other reduction of fracture of spine and stabilisation Other fracture or related follow-up 24809 7K1La00 revision to skin traction of fracture Other fracture or related follow-up 58589 7J42D00 revision to collar stabilisation of spinal fracture Other fracture or related follow-up 17443 7J12.11 reduction of fracture of jaw nec Other fracture or related follow-up
103434 7J43E00 removal of fracture fixation device from spine Other fracture or related follow-up 35866 7K6H400 revision to closed reduction of fracture dislocation alone Other fracture or related follow-up 12165 7K1KB00 revision to external fixation of fracture Other fracture or related follow-up 36893 7K1LW00 primary closed reduction of fracture and skin traction Other fracture or related follow-up 51521 7J42600 primary bedrest stabilisation of spinal fracture Other fracture or related follow-up
247
31933 7J41.00 decompression of fracture of spine Other fracture or related follow-up 97111 7K1F400 prim extraarticular reduction intraartic fracture bone nec Other fracture or related follow-up 97838 7K1Kz11 closed reduction bone fract & fix with gissane spike fixator Other fracture or related follow-up 5886 7K1L700 closed reduction of fracture of tibia and or fibula Other fracture or related follow-up
69319 7J13z00 reduction of fracture of maxilla nos Other fracture or related follow-up 4528 7K1G.00 other primary open reduction of fracture of bone Other fracture or related follow-up
38433 7K1L900 closed reduction of fracture of metatarsus Other fracture or related follow-up 28926 7J12100 open reduction of fracture of mandible nec Other fracture or related follow-up 36449 7K1Ez00 prim open reduction fracture bone & extramedull fixation nos Other fracture or related follow-up 63980 7J43200 fixation of fracture of spine and skull traction hfq Other fracture or related follow-up 60254 7J12000 reduction of fracture of alveolus of mandible Other fracture or related follow-up 53348 7K1Fy00 primary open reduction of intraarticular fracture bone os Other fracture or related follow-up 30213 7K1L300 remanipulation of fracture of bone nec Other fracture or related follow-up 49529 7J42200 manipulative reduction of fracture of spine Other fracture or related follow-up
108001 7K1HD00 revision to open reduction of fracture and skeletal traction Other fracture or related follow-up 73344 7J43y00 other specified fixation of fracture of spine Other fracture or related follow-up 50907 7K1EB00 prim open reduct fract ankle & complex extramedull fixat nec Other fracture or related follow-up 53670 7K1J011 cl red intracaps frac neck femur fix-garden cannulated screw Other fracture or related follow-up 33602 7K1G400 primary open reduction of fracture and cast immobilisation Other fracture or related follow-up 17138 7J17700 traction for fracture of jaw Other fracture or related follow-up 65606 7J41y00 other specified decompression of fracture of spine Other fracture or related follow-up 18962 7K1L500 closed reduction of fracture of femur Other fracture or related follow-up 61653 7K6GX00 primary closed reduction of fracture dislocation alone Other fracture or related follow-up 37297 7J12z00 reduction of fracture of mandible nos Other fracture or related follow-up 6248 7K1J.00 closed (or no) reduction of fracture and internal fixation Other fracture or related follow-up
91658 7J41400 posterior decompression of fracture of spine nec Other fracture or related follow-up 8594 ZV67400 [v]fracture follow-up Other fracture or related follow-up
15952 7K1J100 closed reduction fract long bone & rigid internal fixatn nec Other fracture or related follow-up 20744 7J42.00 other reduction of fracture of spine Other fracture or related follow-up 60121 7K1E012 prim open reduct fract long bone & fix using ellis plate Other fracture or related follow-up 3095 7J03100 reduction of fracture of nasal bones nec Other fracture or related follow-up 4849 N338000 malunion of fracture Other fracture or related follow-up
10736 7206100 open reduction of fracture of orbit Other fracture or related follow-up 99527 7K1J200 closed reduction fract long bone & flexible intern fixat hfq Other fracture or related follow-up 98016 7J41200 posterior decompression of fracture of spine Other fracture or related follow-up 55308 7K1L011 manipulation of fracture and skeletal traction nec Other fracture or related follow-up 11453 7K1LB00 closed reduction of fracture of hallux Other fracture or related follow-up 61389 7J42M00 primary cls reduc spinal fracture+skull traction stabilisatn Other fracture or related follow-up 92356 7J42z00 other reduction of fracture of spine nos Other fracture or related follow-up 47709 7K1F200 prim fixat fragment chondral cartilage intraartic fract bone Other fracture or related follow-up 42186 7K1Jy00 closed reduction of bone fracture and internal fixation os Other fracture or related follow-up 62029 7K1Hz00 secondary open reduction of fracture of bone nos Other fracture or related follow-up
104338 7K1Yz00 second closed reduc fract of bone and internal fixation nos Other fracture or related follow-up 8885 7K1LJ00 closed reduction of fracture of thumb Other fracture or related follow-up
57893 7K1LT00 primary closed reduction of fracture and cast immobilisation Other fracture or related follow-up 35052 7K1LX00 revision to closed reduction of fracture alone Other fracture or related follow-up 88784 7J13y00 other specified reduction of fracture of maxilla Other fracture or related follow-up 40999 7K1J012 cl red intracaps fract neck femur fix - smith-petersen nail Other fracture or related follow-up 27361 7J12y00 other specified reduction of fracture of mandible Other fracture or related follow-up 94374 7J42G00 revision to external fixation stabilisation spinal fracture Other fracture or related follow-up 49870 7K1G000 prmy open reduction of fracture and skeletal traction Other fracture or related follow-up 25173 7J03000 reduction of fracture of nasoethmoid complex of bones Other fracture or related follow-up 36872 7K1E011 prim open reduct fract long bone & fix using eggers plate Other fracture or related follow-up 10008 N338.00 malunion and nonunion of fracture Other fracture or related follow-up
104067 7K1L211 remanipulation of fracture and skeletal traction nec Other fracture or related follow-up 35530 7K1LK00 closed reduction of fracture of metacarpus Other fracture or related follow-up 69702 7K1K700 primary functional bracing of fracture Other fracture or related follow-up 39071 7206700 packing of maxilla to correct blow-out fracture of orbit Other fracture or related follow-up 10737 82...11 closed reduction of fracture Other fracture or related follow-up 64222 7K1Kz00 closed reduction of bone fracture and external fixation nos Other fracture or related follow-up 25312 7J13300 reduction of blowout fracture of orbital floor Other fracture or related follow-up 26130 7K1LD00 closed reduction of fracture of nasal bone Other fracture or related follow-up 28081 7K1Hy00 other specified secondary open reduction of fracture of bone Other fracture or related follow-up 36698 7K1Dz00 prim open reduction fracture bone & intramedull fixation nos Other fracture or related follow-up 30748 7K1JJ00 revision to wire fixation of fracture Other fracture or related follow-up 36497 7K1Jz00 closed reduction of bone fracture and internal fixation nos Other fracture or related follow-up 7930 7K1F500 primary open reduction fracture patella fixat tension band Other fracture or related follow-up
15800 7J03.00 reduction of fracture of facial bone Other fracture or related follow-up 104066 7K1Y100 remanip fracture long bone and rigid internal fixation nec Other fracture or related follow-up 32723 7K1EA00 prim open reduct fract ankle & extramedull fixat nec Other fracture or related follow-up 59570 7K1K100 closed reduct fract bone and fixat functional bracing system Other fracture or related follow-up 20598 7J43.00 fixation of fracture of spine Other fracture or related follow-up 63954 7J43211 barr skull traction for fracture of spine Other fracture or related follow-up 89101 7206800 internal fixation of fracture of orbit Other fracture or related follow-up
105803 7K1DE00 prim op red frac neck fem op fix us prox fem nail antirotatn Other fracture or related follow-up 15622 7J42500 spinal traction for fracture of spine nec Other fracture or related follow-up
104803 7J42L00 primary cls reduction spinal fracture+bedrest stabilisation Other fracture or related follow-up 70919 7K1Ly00 other specified other closed reduction of fracture of bone Other fracture or related follow-up 54198 7K6H200 secondary open reduction fracture dislocation of joint nec Other fracture or related follow-up
106504 7J41000 complex decompression of fracture of spine Other fracture or related follow-up 64388 7J43300 primary open reduc spinal fracture+internal fix+wire Other fracture or related follow-up 34277 7K1Dy00 prim open reduction fracture bone & intramedullary fixatn os Other fracture or related follow-up
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90472 7J41500 balloon kyphoplasty of fracture of spine Other fracture or related follow-up 101031 S336000 fracture tibial plateau Other fracture or related follow-up
6660 7K1L400 closed reduction of fracture of hip Other fracture or related follow-up 89434 7P20100 delivery of rehabilitation for hip fracture Other fracture or related follow-up 60352 7J43z00 fixation of fracture of spine nos Other fracture or related follow-up 38472 7K1Ld00 primary arthroscopic reduction of fracture Other fracture or related follow-up 34743 7K1Lg00 revision to arthroscopic reduction and fixation of fracture Other fracture or related follow-up 46862 7K1Lc00 revision to cast immobilisation of fracture Other fracture or related follow-up 44899 7K1JL00 revision to closed reduction of fracture and wire fixation Other fracture or related follow-up 51147 7J13500 reduction of le fort 2 fracture of maxilla Other fracture or related follow-up 2887 7K1L100 manipulation of fracture of bone nec Other fracture or related follow-up
67910 7J43900 rvsn open reduc spinal fracture+internal fix+plate Other fracture or related follow-up 45394 7K1F300 primary intraarticular fixation intraartic fracture bone nec Other fracture or related follow-up 43600 7J42400 halo skull traction for fracture of spine Other fracture or related follow-up 6224 9N0X.00 seen in fracture clinic Other fracture or related follow-up
34396 7K1G100 prmy open reduction of fracture and external fixation Other fracture or related follow-up 7428 7K1LG00 closed reduction of fracture of shoulder Other fracture or related follow-up
46171 7J42700 primary collar stabilisation of spinal fracture Other fracture or related follow-up 91649 7J43700 primary open reduc spinal fracture+other internal fix Other fracture or related follow-up 48219 7K1LZ00 primary skin traction of fracture Other fracture or related follow-up 29103 7K1KE00 primary closed reduction of fracture and external fixation Other fracture or related follow-up 20445 7206400 open reduction of fracture of orbit and internal fixation Other fracture or related follow-up 34634 7J42100 open reduction of fracture of spine nec Other fracture or related follow-up 10102 7K1Ky00 closed reduction of bone fracture and external fixation os Other fracture or related follow-up 15085 7K1Lz00 other closed reduction of fracture of bone nos Other fracture or related follow-up 6379 7K1LF00 closed reduction of fracture of humerus Other fracture or related follow-up
32012 7K1Le00 primary arthroscopic reduction and fixation of fracture Other fracture or related follow-up 64862 7K1K000 closed reduction fracture bone and fixation to skeleton hfq Other fracture or related follow-up 30288 7J13000 reduction of fracture of alveolus of maxilla Other fracture or related follow-up 55447 7K1H200 secondary open reduction of intraarticular fracture of bone Other fracture or related follow-up 63085 7K1G500 primary open reduction of fracture and functional bracing Other fracture or related follow-up 4465 7J03200 reduction of fracture of zygomatic bones Other fracture or related follow-up
107718 7K1Yy00 os second closed reduct fracture bone and internal fixation Other fracture or related follow-up 22780 7J13.00 reduction of fracture of maxilla Other fracture or related follow-up 60412 7J13600 reduction of le fort 3 fracture of maxilla Other fracture or related follow-up 41760 7K1Lb00 primary cast immobilisation of fracture Other fracture or related follow-up 36783 7K6H700 secondary open reduction fracture disloc joint & fixation Other fracture or related follow-up 28621 7J03z00 reduction of fracture of facial bone nos Other fracture or related follow-up 28966 7J43000 primary open reduc spinal fracture+internal fix+plate Other fracture or related follow-up 54959 7K1H.11 revision to open reduction of fracture of bone Other fracture or related follow-up 35742 7K1Lf00 revision to arthroscopic reduction of fracture Other fracture or related follow-up 6994 7J12.00 reduction of fracture of mandible Other fracture or related follow-up 5951 7K1LM00 closed reduction of fracture of wrist Other fracture or related follow-up
30429 7K1F.00 primary open reduction of intraarticular fracture of bone Other fracture or related follow-up 4115 7K1D100 prim open reduct fract long bone & fixation rigid nail nec Other fracture or related follow-up
35889 7J13200 closed reduction of fracture of maxilla nec Other fracture or related follow-up 9727 7K1H.00 secondary open reduction of fracture of bone Other fracture or related follow-up 4641 7K1T100 debridement of open fracture Other fracture or related follow-up
29778 7K1E400 prim open reduct fract ankle & complex extramedull fixat nec Other fracture or related follow-up 69362 7K6H411 remanipulation of fracture dislocation alone Other fracture or related follow-up 8800 7K1L600 closed reduction of fracture of knee Other fracture or related follow-up
49564 7J42000 open reduction of fracture of spine & excis facet of spine Other fracture or related follow-up 54327 7K1E200 prim open reduct fract long bone & extramedull fixatn suture Other fracture or related follow-up 63064 7J03y00 other specified reduction of fracture of facial bone Other fracture or related follow-up 23966 7K6G200 primary manipulative closed reduct fract dislocat joint nec Other fracture or related follow-up 42223 7K1F000 primary reduction intraarticular fract bone using arthrotomy Other fracture or related follow-up 41888 7K1G200 primary open reduction+external fixation of femoral fracture Other fracture or related follow-up 57626 7K1H900 revision to open reduction of fracture alone Other fracture or related follow-up 55077 7K1LC00 closed reduction of fracture of lower limb Other fracture or related follow-up 7339 7K1LA00 closed reduction of fracture of toe Other fracture or related follow-up
38131 7K1LN00 closed reduction of fracture of upper limb Other fracture or related follow-up 102254 7K1Y.00 second closed reduction fracture bone and internal fixation Other fracture or related follow-up
8630 7K1E.00 primary open reduction fract bone & extramedullary fixation Other fracture or related follow-up 29582 7K1D511 k wiring of fracture Other fracture or related follow-up 4629 7K1L.00 other closed reduction of fracture of bone Other fracture or related follow-up
11342 7J12200 closed reduction of fracture of mandible nec Other fracture or related follow-up 6942 7K1LL00 closed reduction of fracture of radius and or ulna Other fracture or related follow-up
73812 7K1N900 primary skeletal traction of fracture Other fracture or related follow-up 6069 7K1LH00 closed reduction of fracture of finger Other fracture or related follow-up
98165 7J42B00 primary other external stabilisation of spinal fracture Other fracture or related follow-up 24715 7K1K.00 closed (or no) reduction of fracture and external fixation Other fracture or related follow-up 6106 7K1L800 closed reduction of fracture of ankle Other fracture or related follow-up
100161 7J42C00 revision to bedrest stabilisation of spinal fracture Other fracture or related follow-up 57558 7K1E013 prim open reduct fract long bone & fix using hicks plate Other fracture or related follow-up 34355 7K1JK00 primary closed reduction of fracture and wire fixation Other fracture or related follow-up 55930 7K6FE00 primary open reduction of fracture dislocation alone Other fracture or related follow-up 62489 7J43.11 internal fixation of fracture of spine Other fracture or related follow-up 88269 7J41300 vertebroplasty of fracture of spine Other fracture or related follow-up 53575 7J02300 repair of fracture of cranium nec Other fracture or related follow-up 16141 7K1Gz00 other primary open reduction of fracture of bone nos Other fracture or related follow-up 55286 7K1E300 prim open reduc fract long bone & cmplx extramedul fixat nec Other fracture or related follow-up 28533 7K1H000 second open reduct fract bone & intramedullary fixation hfq Other fracture or related follow-up
249
21942 7K1Gy11 primary open reduction of bone fracture & external fixation Other fracture or related follow-up 93752 7J42y00 other specified other reduction of fracture of spine Other fracture or related follow-up 11872 7K1LV00 primary closed reduction of fracture alone Other fracture or related follow-up 68811 7J41100 anterior decompression of fracture of spine Other fracture or related follow-up 40321 7K1G300 primary open reduction of fracture alone Other fracture or related follow-up 38868 7K1K200 remanipulation of fracture of bone and external fixation hfq Other fracture or related follow-up 96903 7K1KA00 revision to functional bracing of fracture Other fracture or related follow-up 98056 7J43A00 rvsn open reduc spinal fracture+internal fix+rod system Other fracture or related follow-up 50460 7K1Fz00 primary open reduction of intraarticular fracture bone nos Other fracture or related follow-up 71006 7J42900 primary cast stabilisation of spinal fracture Other fracture or related follow-up 22144 7K6GN00 closed reduction fracture disloc joint & internal fixation Other fracture or related follow-up 11333 7K1K800 primary external fixation of fracture Other fracture or related follow-up 18840 S330300 closed fracture proximal tibia, medial condyle (plateau) Other fracture or related follow-up 91919 7K1G600 primary open reduction of fracture and skin traction Other fracture or related follow-up 99297 7K6HX00 revision to open reduction fracture dislocation alone Other fracture or related follow-up 50279 N338z00 fracture malunion or nonunion nos Other fracture or related follow-up 56080 7K1H100 second open reduct fract bone & extramedullary fixation hfq Other fracture or related follow-up 63218 7J43C00 rvsn open reduc spinal fracture+internal fix+internl fixator Other fracture or related follow-up 61491 7J43400 primary open reduc spinal fracture+internal fix+rod system Other fracture or related follow-up 85656 7K6Hh00 sec open red fracture dislocat joint and intern fixation nec Other fracture or related follow-up 68992 7K1H400 secondary open reduct fracture bone & external fixation hfq Other fracture or related follow-up 5972 7206200 removal of fixation from fracture of orbit Other fracture or related follow-up
95879 8HTo.00 referral to fracture clinic Other fracture or related follow-up 7672 7K1D.00 primary open reduction fracture bone & intramedull fixation Other fracture or related follow-up
53007 Zw01.00 [q] fractures involving the epiphyseal plate Other fracture or related follow-up 455 S3z0000 greenstick fracture Other fracture or related follow-up
29162 S3zz.00 fracture of bones nos Other fracture or related follow-up 37310 S3z0.00 closed fracture of bones, unspecified Other fracture or related follow-up
358 S3z..11 fracture nos Other fracture or related follow-up 2470 S3z..00 fracture of unspecified bones Other fracture or related follow-up
250
ICD-10 code ICD-10 term Fracture type S02.0 Fracture of vault of skull Skull/facial S02.1 Fracture of base of skull Skull/facial S02.2 Fracture of nasal bones Skull/facial S02.3 Fracture of orbital floor Skull/facial S02.4 Fracture of malar and maxillary bones Skull/facial S02.5 Fracture of tooth Skull/facial S02.6 Fracture of mandible Skull/facial S02.7 Multiple fractures involving skull and facial bones Skull/facial S02.8 Fractures of other skull and facial bones Skull/facial S02.9 Fracture of skull and facial bones, part unspecified Skull/facial S12.0 Fracture of first cervical vertebra Neck S12.1 Fracture of second cervical vertebra Neck S12.2 Fracture of other specified cervical vertebra Neck S12.7 Multiple fractures of cervical spine Neck S12.8 Fracture of other parts of neck Neck S12.9 Fracture of neck, part unspecified Neck T02.0 Fractures involving head with neck Head/neck (unspec) S22.0 Fracture of thoracic vertebra Rib/sternum/thoracic S22.1 Multiple fractures of thoracic spine Rib/sternum/thoracic S22.2 Fracture of sternum Rib/sternum/thoracic S22.3 Fracture of rib Rib/sternum/thoracic S22.4 Multiple fractures of ribs Rib/sternum/thoracic S22.5 Flail chest Rib/sternum/thoracic S22.8 Fracture of other parts of bony thorax Rib/sternum/thoracic S22.9 Fracture of bony thorax, part unspecified Rib/sternum/thoracic S32.0 Fracture of lumbar vertebra Lumbar spine/pelvis S32.1 Fracture of sacrum Lumbar spine/pelvis S32.2 Fracture of coccyx Lumbar spine/pelvis S32.3 Fracture of ilium Lumbar spine/pelvis S32.4 Fracture of acetabulum Lumbar spine/pelvis S32.5 Fracture of pubis Lumbar spine/pelvis S32.7 Multiple fractures of lumbar spine and pelvis Lumbar spine/pelvis S32.8 Fracture of other and unspecified parts of lumbar spine and pelvis Lumbar spine/pelvis T08.0 Closed fracture of spine, level unspecified Spine (unspec) T08.1 Open fracture of spine, level unspecified Spine (unspec) T91.1 Sequelae of fracture of spine Spine (unspec) T02.1 Fractures involving thorax with lower back and pelvis Lumbar spine/pelvis S42.0 Fracture of clavicle Shoulder/upper arm S42.1 Fracture of scapula Shoulder/upper arm S42.2 Fracture of upper end of humerus Shoulder/upper arm S42.3 Fracture of shaft of humerus Shoulder/upper arm S42.4 Fracture of lower end of humerus Shoulder/upper arm S42.7 Multiple fractures of clavicle, scapula and humerus Shoulder/upper arm S42.8 Fracture of other parts of shoulder and upper arm Shoulder/upper arm S42.9 Fracture of shoulder girdle, part unspecified Shoulder/upper arm S52.0 Fracture of upper end of ulna Forearm S52.1 Fracture of upper end of radius Forearm S52.2 Fracture of shaft of ulna Forearm S52.3 Fracture of shaft of radius Forearm S52.4 Fracture of shafts of both ulna and radius Forearm S52.5 Fracture of lower end of radius Forearm S52.6 Fracture of lower end of both ulna and radius Forearm S52.7 Multiple fractures of forearm Forearm S52.8 Fracture of other parts of forearm Forearm S52.9 Fracture of forearm, part unspecified Forearm S62.0 Fracture of navicular [scaphoid] bone of hand Wrist/hand S62.1 Fracture of other carpal bone(s) Wrist/hand S62.2 Fracture of first metacarpal bone Wrist/hand S62.3 Fracture of other metacarpal bone Wrist/hand S62.4 Multiple fractures of metacarpal bones Wrist/hand S62.5 Fracture of thumb Wrist/hand S62.6 Fracture of other finger Wrist/hand S62.7 Multiple fractures of fingers Wrist/hand S62.8 Fracture of other and unspecified parts of wrist and hand Wrist/hand T02.2 Fractures involving multiple regions of one upper limb Upper limb (unspec) T02.4 Fractures involving multiple regions of both upper limbs Upper limb (unspec) T10.0 Closed fracture of upper limb, level unspecified Upper limb (unspec) T10.1 Open fracture of upper limb, level unspecified Upper limb (unspec) S72.0 Fracture of neck of femur Femur S72.1 Pertrochanteric fracture Femur S72.2 Subtrochanteric fracture Femur S72.3 Fracture of shaft of femur Femur S72.4 Fracture of lower end of femur Femur S72.7 Multiple fractures of femur Femur S72.8 Fractures of other parts of femur Femur S72.9 Fracture of femur, part unspecified Femur S82.0 Fracture of patella Lower leg/ankle S82.1 Fracture of upper end of tibia Lower leg/ankle S82.2 Fracture of shaft of tibia Lower leg/ankle S82.3 Fracture of lower end of tibia Lower leg/ankle
251
S82.4 Fracture of fibula alone Lower leg/ankle S82.5 Fracture of medial malleolus Lower leg/ankle S82.6 Fracture of lateral malleolus Lower leg/ankle S82.7 Multiple fractures of lower leg Lower leg/ankle S82.8 Fractures of other parts of lower leg Lower leg/ankle S82.9 Fracture of lower leg, part unspecified Lower leg/ankle S92.0 Fracture of calcaneus Foot S92.1 Fracture of talus Foot S92.2 Fracture of other tarsal bone(s) Foot S92.3 Fracture of metatarsal bone Foot S92.4 Fracture of great toe Foot S92.5 Fracture of other toe Foot S92.7 Multiple fractures of foot Foot S92.9 Fracture of foot, unspecified Foot T02.3 Fractures involving multiple regions of one lower limb Lower limb (unspec) T02.5 Fractures involving multiple regions of both lower limbs Lower limb (unspec) T12.0 Closed fracture of lower limb, level unspecified Lower limb (unspec) T12.1 Open fracture of lower limb, level unspecified Lower limb (unspec) T02.6 Fractures involving multiple regions of upper limb(s)/lower limb(s) Other fracture or related follow-up T02.7 Fractures involving thorax with lower back/pelvis with limb(s) Other fracture or related follow-up T02.8 Fractures involving other combinations of body regions Other fracture or related follow-up T02.9 Multiple fractures, unspecified Other fracture or related follow-up T14.2 Fracture of unspecified body region Other fracture or related follow-up X59.0 Exposure to unspecified factor causing fracture Other fracture or related follow-up Z09.4 Follow-up examination after treatment of fracture Other fracture or related follow-up Z47.0 Follow-up inv removal of fracture plate/other internal fixation device Other fracture or related follow-up Z54.4 Convalescence following treatment of fracture Other fracture or related follow-up
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