The SPRINT Protocol for Tight Glycaemic Control Geoffrey M Shaw, J. Geoffrey Chase, Xing-Wei Wong, Thomas Lotz, Jessica Lin, Aaron LeCompte, Timothy Lonergan,

The SPRINT Protocol for Tight Glycaemic

Control Geoffrey M Shaw, J. Geoffrey Chase, Xing-Wei Wong, Thomas

Lotz, Jessica Lin, Aaron LeCompte, Timothy Lonergan, Michael

Willacy and Christopher E. HannDept of Intensive Care Christchurch Hospital and Dept of Medicine CSM&HS University of Otago, NZDept of Mechanical Engineering, Centre for Bio-Engineering, Universiity of Canterbury, NZ

Tight glucose control

Hyperglycaemia is prevalent in critical care

Impaired endogenous insulin production

Increased effective insulin resistance

Average blood glucose values > 10mmol/L not uncommon in some critical care units (over length of stay)

Stress of condition induces hyperglycaemia

Tight control better outcomes:

Reduced mortality

Reduced length of stay and length of mechanical ventilation

8.46 to 7.26 mmol /L

11.1mmol/L

et al

All patients

LOS >3days

Oxidative stress

Vanhorebeek I. De Vos R, Mesotten D, Wouters P, De Wolf-Peeters C, Van den Berghe G, Protection of hepatocyte mitochondrial ultrastructure and function by strict blood glucose control with insulin in critically ill patients. Lancet 2005;365:53-59

Post-mortem liver biopsies from 20 patientsIntensive insulin (11) vs Conventional treatment (9)

Hypertrophic mitochondria with an increased number of abnormal and irregular cristae and reduced matrix electron density were observed in 7 of 9 conventionally treated patients. Only 1 of 11 patients given intensive insulin treatment had these morphological abnormalities (p=0·005).

Liver: poor glycaemic control

Liver: tight glycaemic control

Skeletal Muscle

Skeletal Muscle

AIC1 AIC4: Prior Art

u(t)

Gmeasured

Gmodelled

+

-Update parameterspG and SI

pG

SI

t

• 4 years prior trials and research• Models mature• Adaptive Control• Short specific trials

Overall AIC control system concept is well established

)(1

tPQ

QGGSGpG

GeIG

V

tuIInI b

)(

)(1

tPQ

QGGSGpG

GeIG

The only ways to reduce glucose levels are:

increase insulin (Q) which saturates decrease feed (P)

Glucose = GInsulin = QFeed = P

Insulin-only (AIC3) control of a patient

Dextrose feed and Insulin input

Time (minutes)

Tight control target = 4-6 mmol/l

Insulin bolusesFeed rate

Glucose level mmol/l

Insulin-feed (AIC4) control of a patient

Time (minutes)

Dextrose feed and Insulin input

Tight control target = 4-6 mmol/l

Glucose level mmol/l

Feed rate Insulin boluses

Patient 5 = textbook case

Wong, XW, Chase, JG, Shaw, GM, Hann, CE, Lotz, T, Lin, J, Singh-Levett, I, Hollingsworth, L, Wong, OS and Andreassen, S (2006). “Model Predictive Glycaemic Regulation in Critical Illness using Insulin and Nutrition Input: a Pilot Study,” Medical Engineering and Physics, In Press

SPRINT Specialised Relative Insulin and Nutrition Table

Optimises both insulin and nutrition rates to control glycaemic levels

Developed through extensive computer simulationEnsures safe protocol before clinical implementation

Simple interface for ease of use by nursing staff

Combines the very tight control of computerised simulations with minimal implementation cost (no bedside computer required…)

SPRINT Step 1 = Feed Rate Table

Requires current glucose measurement and last hour change in glucose

SPRINT Step 2 = Insulin Table

If feed rate = 0 use only insulin wheel

Requires current glucose measurement, last hour change and last hours insulin bolus

Patient 5008

• Time = 163 hours• Mean = 5.4 mmol/L• 4-6.1 = 85%• 4-7.75 = 97%• Avg Feed = 85%• Avg Insulin = 3.4 U/hr

Lonergan, T, LeCompte, A, Willacy, M, Chase, JG, Shaw, GM, Wong, XW, Lotz, T, Lin, J, and Hann, CE (2006). “A Simple Insulin-Nutrition Protocol for Tight Glycemic Control in Critical Illness: Development and Protocol Comparison,” Diabetes Technology & Therapeutics (DT&T), In Press

0

5

10

15

Ease of Use Quality Suitability

Num

ber

of r

espo

nden

ts

Very Good

Good

Satisfactory

Poor

Nursing survey: SPRINT

Results

0

1000

2000

<4 4 to 6 6 to 8 8 to 10 10 to 12 12 to 15 15 to 20 20 plus

Blood glucose [mmol/L]

Num

ber

of

mea

sure

men

ts

2005

0

500

1000

1500

<4 4 to 6 6 to 8 8 to 10 10 to 12 12 to 15 15 to 20 20 plus

Blood glucose [mmol/L]

Num

ber

of

mea

sure

men

ts

2003

16,063 hours of control on SPRINT; 11,249 measurements

118 admissions

Average APAPCHE II score = 21 (41% risk of death)

Too low (hypoglycaemia)Too low (hypoglycaemia)

Too high(hyperglycaemia)Too high(hyperglycaemia)

2003 Retrospective Data (Doran, 2004)Mean Glucose = 8.1Lognormal = outliers to high side

2003 Retrospective Data (Doran, 2004)Mean Glucose = 8.1Lognormal = outliers to high side

SPRINTSPRINT

0

1000

2000

3000

<3 3 to4

4 to5

5 to6

6 to7

7 to8

8 to9

9 to10

10 to11

11 to12

12 to13

13 to15

15 to17

18 to20

20plus

Num

ber

of

mea

sure

men

ts

Reduction in incidence of high blood glucoseReduction in incidence of high blood glucose

Results

Mean

Mean

Normal distribution -- 90% in desired bandNormal distribution -- 90% in desired band

Tight control:

Areas under all fitted curves are equal

Tight control within target bands

Tight control:

Poor control:

BG less than 2.5mmol/L = harmful!!

3.5% of simulated van den Berghe measurements less than 2.5mmol/L

Poor control:

10% of SPRINT ICU measurements > 7.75 mmol/L

70% of simulated Krinsley measurements > 7.75 mmol/L

38% of simulated sliding scale measurements > 7.75 mmol/L

Cumulative distribution function for all blood glucose measurements

Glucose mmol/ L

Cu

mu

lati

ve p

rob

abil

ity

Percentiles for ICU data- SPRINT

2.5mmol/L = 4.1x 10-5

3.0mmol/L = 0.001

4.0mmol/L = 0.041

6.1mmol/L = 0.59

7.0mmol/L = 0.81

7.75mmol/L =0.91

SPRINT ICU raw data- 26-04-06

ICU data- SPRINT (lognormal) 26-04-06

Model simulation- SPRINT (lognormal)

Model simulation- van den Berghe (lognormal)

Model simulation- Krinsley

Tight control 2003 retrospective data 2005-06 SPRINT

0.0 5.0 10.0 15.0 20.0

2.50

5.00

7.50

10.00

12.50

15.00Avg BGRangeRetroavgRetrorange

R Sq Linear = 0.283R Sq Linear = 0.36

Blood Glucose Range (mmol/l)

Blood Glucose

Average

(mmol/l)

5.0 10.0 15.0 20.0

2.50

5.00

7.50

10.00

12.50

15.00 Avg BG Max Retroavg Retromax

R Sq Linear = 0.459

R Sq Linear = 0.652

Peak Blood Glucose (mmol/l)

Blood Glucose

Average

(mmol/l)

Flatter is betterTighter is better

Flatter is betterTighter is better

P < 0.05 P < 0.05

SPRINT is flatter and tighter in both cases (P < 0.05)SPRINT is flatter and tighter in both cases (P < 0.05)

0%

5%

10%

15%

20%

25%

30%

2004-05 SPRINT

Mo

rta

lity

%

.

SPRINT has decreased mortality by 32%

44 deaths in 169 patients

23 deaths in 118 patients

All performance indicators agree with simulation and tight control!

Protocol is safe – no clinically significant hypoglycaemia

Effective use of insulin and nutrition

Tightness of glucose control: the first 118 admissions

Improved patient outcome: LOS >3 days

Outcomes:

Average BG 5.9 mmol/L

Average time in 4 -6.1 60%

Average time in 4 -7 82%

Average time in 4 -7.75 90%

Percentage of all measurements less than 4 2.7%

Percentage of all measurements less than 2.5 0.1%

Average insulin bolus 2.7 U

Average percentage of goal feed 66%

Average feed rate 51 ml/hr

(assuming 1.06 cal/ml for feed) 1293 cal/day

P=0.04

Tightness of glucose control*

Outcomes:

SPRINT Mortality grouped by APACHE II 2004-05APACHE II Number Mortality Number Mortality0-14 20 5% 104 1.9%15-24 44 20% 200 15.5%25-34 23 26% 48 45.8%35+ 6 67% 7 71.4%

SPRINT Sepsis data 2004-05 (% change)Total sepsis patients 21 49%Total sepsis LOS<3 3 13%Total sepsis LOS≥3 18 25%Mortality sepsis all 4 19% 35.0% -46%Mortality sepsis LOS<3 1 33% 37.0% -10%Mortality sepsis LOS≥ 3 3 17% 34.0% -51%

*

*

* Incomplete data

Average APACHE II = 21 Average APACHE II =18.3

http:/www.geocities.com/active_insulin_control

This is just the beginning…

Aim:

Tight Glycaemic control for everyone with minimal clinical effort……..

………from babies to adults…..

Acknowledgements

Intensive Care Nursing Staff, Christchurch Hospital

Maths and Stats Gurus

Dr Dom LeeDr Dom LeeDr Bob Dr Bob BroughtonBroughton Dr Chris HannDr Chris Hann

Prof Prof Graeme WakeGraeme WakeThomas LotzThomas Lotz

Jessica Lin & AIC3Jessica Lin & AIC3AIC2AIC2 Jason Wong & AIC4Jason Wong & AIC4AIC1AIC1

The Danes

Prof Steen Prof Steen AndreassenAndreassen

Dunedin

Dr Kirsten Dr Kirsten McAuleyMcAuley Prof Jim MannProf Jim Mann

Assoc. Prof. Geoff Chase

AIC5: Mike, Aaron and TimAIC5: Mike, Aaron and Tim

Acknowledgements