C-Section Deliveries Influencing Late Preterm Births & The Sequelae of Late Preterm Deliveries Heather Brumberg, MD, MPH, FAAP Medical Director, LHVPN.

C-Section Deliveries C-Section Deliveries Influencing Late Influencing Late

Preterm Births & The Preterm Births & The Sequelae of Late Sequelae of Late

Preterm DeliveriesPreterm Deliveries

Heather Brumberg, MD, MPH, FAAPHeather Brumberg, MD, MPH, FAAPMedical Director, LHVPNMedical Director, LHVPN

Assistant Professor of Pediatrics and Clinical Public Assistant Professor of Pediatrics and Clinical Public Health, NYMCHealth, NYMC

Director of Regional Neonatal Public Health Director of Regional Neonatal Public Health Programs, Maria Fareri Children’s Hospital, Valhalla, Programs, Maria Fareri Children’s Hospital, Valhalla,

NYNYJanuary 22, 2008January 22, 2008

Shift in gestational distribution:Shift in gestational distribution:May be in part due to change in May be in part due to change in

practice to deliver earlier to avoid practice to deliver earlier to avoid post-term birthspost-term births

19922003

Davidoff, MJ et al. Semin Perinatol 30(1):8-15, 2006

34-36 wks32-33 wks<32 wks

Over 70% of All Preterm Over 70% of All Preterm Births Are Late PretermBirths Are Late Preterm (34-36 weeks gestation) (34-36 weeks gestation)

http://www.marchofdimes.com/files/MP_Late_Preterm_Birth-Every_Week_Matters_3-24-06.pdf

Late Preterms Increasing Late Preterms Increasing Over TimeOver Time

Late Preterms Increasing Late Preterms Increasing by Race/Ethnicity Over by Race/Ethnicity Over

TimeTime

Late Preterm Birth Rates Late Preterm Birth Rates and Economic Burden and Economic Burden

1 out of 11 births is a late preterm 1 out of 11 births is a late preterm infantinfant

In 2005, prematurity cost the United In 2005, prematurity cost the United States $26.2 billion dollarsStates $26.2 billion dollars

In California,1996- preventing non-In California,1996- preventing non-medically indicated births between medically indicated births between 34-37 weeks could have saved 49.9 34-37 weeks could have saved 49.9 million dollarsmillion dollars

Raju, T. Clin Perinatol 33: 751-763, 2006

Why are Late Preterm Births Why are Late Preterm Births on the Rise?on the Rise?

C-section rate is increasing in the late C-section rate is increasing in the late preterm populationpreterm population

Extremes in maternal age (<16, >35) Extremes in maternal age (<16, >35) linked to premature birthlinked to premature birth

Assisted reproductionAssisted reproduction Obesity/fetal macrosomiaObesity/fetal macrosomia Other maternal medical issues (i.e. Other maternal medical issues (i.e.

preeclampsia)preeclampsia) Reduction in late preterm stillbirths Reduction in late preterm stillbirths

(Hankins and Longo, 2006; Raju, 2006)

C-Sections Increase Over C-Sections Increase Over Time by Gestational AgeTime by Gestational Age

Elective DeliveryElective Delivery ACOG recommends elective delivery should ACOG recommends elective delivery should

not be preformed prior to 39 wksnot be preformed prior to 39 wks However, inaccuracies in dating can occurHowever, inaccuracies in dating can occur

Early u/s standard, last menstrual period less Early u/s standard, last menstrual period less accurateaccurate May not always utilized depending on timing of prenatal May not always utilized depending on timing of prenatal

carecare Has also been implicated in increased preterm birthHas also been implicated in increased preterm birth

Fetal lung maturity is suggested if dating is Fetal lung maturity is suggested if dating is unclearunclear However, not always done due to perception of However, not always done due to perception of

risks due to amniocentesisrisks due to amniocentesis Little data, Little data, directlydirectly link c/s at maternal request (4- link c/s at maternal request (4-

18% of all c-sections) to late preterm birth, although 18% of all c-sections) to late preterm birth, although both rates have risen concurrentlyboth rates have risen concurrently(Raju, 2006; Jain and Dudell, 2006; Fuchs and Wapner 2006)

Complications of Pregnancy Complications of Pregnancy as Potential Causesas Potential Causes

Preterm labor on the rise in late pretermsPreterm labor on the rise in late preterms Premature rupture of membranes also on the Premature rupture of membranes also on the

riserise Expeditious delivery after 34 wks recommendedExpeditious delivery after 34 wks recommended

Standard OB management of these: tocolysis Standard OB management of these: tocolysis and glucocorticoids up to 34 wksand glucocorticoids up to 34 wks

Similarly expert opinion recommends Similarly expert opinion recommends intervention for mild preeclampsia at 37 wks intervention for mild preeclampsia at 37 wks and severe as early as 34 weeksand severe as early as 34 weeks

Beyond 34 wks, aggressive efforts to prevent Beyond 34 wks, aggressive efforts to prevent delivery are not attempteddelivery are not attempted

(Dobak and Gardner, 2006; Fuchs and Wapner, 2006)

Diabetes and Pregnancy Diabetes and Pregnancy Weight Gain (Risks for C-Weight Gain (Risks for C-

Sections and Preeclampsia) Sections and Preeclampsia) Increased Over TimeIncreased Over Time

Maternal Age (Risk for Maternal Age (Risk for Preeclampsia) Increased Preeclampsia) Increased

Over TimeOver Time

Multiple Gestation Rates Stable, Multiple Gestation Rates Stable, BUT High Proportion are BUT High Proportion are Increasingly Late PretermsIncreasingly Late Preterms (6x More Likely to be (6x More Likely to be Premature)Premature)May be due to medical May be due to medical intervention for maternal intervention for maternal (preeclampsia) or fetal reasons(preeclampsia) or fetal reasons

PreeclampsiaPreeclampsia Preeclampsia on the rise (6-10% of all Preeclampsia on the rise (6-10% of all

pregnancies), likely due to change in pregnancies), likely due to change in demographic of pregnant women demographic of pregnant women Increased nulliparity, maternal age, obesity, and Increased nulliparity, maternal age, obesity, and

multiple gestationsmultiple gestations However, better management has led to reduced However, better management has led to reduced

maternal and perinatal complicationsmaternal and perinatal complications Studies did not delineate if delivery of Studies did not delineate if delivery of

mothers with preeclampsia was for fetal mothers with preeclampsia was for fetal indication, preterm labor or rupture of indication, preterm labor or rupture of membranes, or preeclampsiamembranes, or preeclampsia

Interestingly, despite ACOG guidelines, Interestingly, despite ACOG guidelines, 15% of mild preeclampsia are delivered at 15% of mild preeclampsia are delivered at 34-36 wks34-36 wks (Sibai,

2006)

ObjectiveObjective

To identify maternal risk factors To identify maternal risk factors associatedassociated

with delivery of late preterm with delivery of late preterm infants (34 - 36 weeks infants (34 - 36 weeks gestation)gestation)

Jessica L. Kalia, DO, Paul Jessica L. Kalia, DO, Paul Visintainer, PhD, Jordan Kase, Visintainer, PhD, Jordan Kase, MD, Heather L. Brumberg, MD, MD, Heather L. Brumberg, MD, MPH E-PAS2007:61:8075.6MPH E-PAS2007:61:8075.6

MethodsMethods Birth certificate data from NY State Department Birth certificate data from NY State Department

of Health Vital Statistics of Health Vital Statistics Study subjectsStudy subjects

Term (37-42 weeks gestation) infantsTerm (37-42 weeks gestation) infants Late preterm (34-36 weeks gestation) infantsLate preterm (34-36 weeks gestation) infants Born in Westchester County, New YorkBorn in Westchester County, New York 2004-20052004-2005

Data analysisData analysis Compared late preterm to term infants for delivery Compared late preterm to term infants for delivery

characteristics, receipt of prenatal care, and maternal characteristics, receipt of prenatal care, and maternal demographicsdemographics

Statistical AnalysisStatistical Analysis Chi square was used to compare frequenciesChi square was used to compare frequencies Poisson regression was used for analysis of relative Poisson regression was used for analysis of relative

risksrisks Statistical significance set at p < 0.05Statistical significance set at p < 0.05

Results: Westchester County Live Results: Westchester County Live Births by Weeks GestationBirths by Weeks Gestation

2004

(n=12,306)

2005

(n=12,860)

Late Preterms (8%)Late Preterms (8%)

Increased C-sections in Late Increased C-sections in Late Preterm InfantsPreterm Infants

* p< 0.05

0%

20%

40%

60%

80%

C-Section Vaginal delivery

34-36 wks

37-42 wks

% L

ive

Birt

hs

* *

Total: 25,166 live births

More C-Sections in Late Preterm More C-Sections in Late Preterm Infants for Maternal Conditions Infants for Maternal Conditions

Related to PregnancyRelated to Pregnancy

0%

2%

4%

6%

8%

10%

12%

Elective Fetal risk Maternal- pregrelated

Maternal- notpreg related

34-36 wk

37-42 wk

0%

2%

4%

6%

8%

10%

12%

Elective Fetal risk Maternal- pregrelated

Maternal- notpreg related

34-36 wk

37-42 wk

*

* p< 0.05

% L

ive

Birt

hs

Total: 25,166 live births

No Difference in No Difference in Commencement of Prenatal Commencement of Prenatal

CareCare

0%

20%

40%

60%

80%

1st Trimester 3rd Trimesteror No PNC

34-36 weeks

37-42 weeks

0%

20%

40%

60%

80%

1st Trimester 3rd Trimesteror No PNC

34-36 weeks

37-42 weeks

Per

cen

t L

ive

Bir

ths

Total: 25,166 live births

Extremes of Maternal Age Extremes of Maternal Age Have Higher Rates of Late Have Higher Rates of Late

Preterm Infants Preterm Infants

22%

24%

26%

28%

30%

≥ 35 years old

* p < 0.05

0.0%

0.2%

0.4%

0.6%

0.8%

< 17 yrs old

34-36 wk

37-42 wk

*% Live Births % Live

Births *

Total: 25,166 live births

No Difference in No Difference in Medicaid UseMedicaid Use

20%

30%

40%

medicaid primary

34-36 weeks

37- 42 weeks

Summary of Relative Risks for Late Preterm Summary of Relative Risks for Late Preterm InfantsInfants

Relative Risk

ConclusionsConclusions Late preterm delivery more likely at extremes Late preterm delivery more likely at extremes

of maternal age of maternal age Maternal conditions related to pregnancy Maternal conditions related to pregnancy

more likely to result in c-section delivery of more likely to result in c-section delivery of late preterm infantlate preterm infant

C-section delivery more likely in late preterms C-section delivery more likely in late preterms Elective c-section rates are Elective c-section rates are not significantly not significantly

differentdifferent between term and late preterms between term and late preterms No difference in commencement of prenatal No difference in commencement of prenatal

care between term and late pretermscare between term and late preterms No socioeconomic difference in late preterm No socioeconomic difference in late preterm

and term mothers as measured by primary and term mothers as measured by primary medicaid usemedicaid use

Wang M et al Pediatrics 114: 372-376, 2004Neu J, Semin Perinatol. 30: 77-80, 2006Raju, T et al. Pediatrics 118: 1207-21, 2006Kramer, MS et al, JAMA 284: 843-849, 2000

Morbidity & Mortality

Total Total MortalityMortality

Singleton Live Singleton Live BirthsBirths

RR (95% CI)RR (95% CI)

United StatesUnited States 2.9 2.9 (2.8-3.0)(2.8-3.0)

CanadaCanada 4.5 4.5 (4.0-5.0)(4.0-5.0)

0% 10% 20% 30% 40% 50% 60%

Jaundice

RDS

IV Fluid

Hypoglycemia

Temp Instability

Term

Late Preterm

Morbidities

Infant MortalityInfant Mortality Late preterms 3 times more likely to die Late preterms 3 times more likely to die

than term infants in their first year of lifethan term infants in their first year of life Late preterms 6 times as likely to die Late preterms 6 times as likely to die

than term babies in their first week of than term babies in their first week of life (early neonatal period)life (early neonatal period)

Late preterms 3 times as likely to die Late preterms 3 times as likely to die than term babies after their first week to than term babies after their first week to 27 days (late neonatal period)27 days (late neonatal period)

Leading cause is congential anomaliesLeading cause is congential anomalies

(Tomashek et al. 2007)

Other OutcomesOther Outcomes Increased risk of rehospitalization, most Increased risk of rehospitalization, most

commonly due to jaundice (63%) and commonly due to jaundice (63%) and infection (13%; Shapiro-Mendoza et al. infection (13%; Shapiro-Mendoza et al. 2006) 2006)

Increased risk of SIDS 1.37 per 1,000 Increased risk of SIDS 1.37 per 1,000 live births (33-36 wks) vs. 0.69 per 1,000 live births (33-36 wks) vs. 0.69 per 1,000 live births (term) as well as increased live births (term) as well as increased risk of apnea and apparent life risk of apnea and apparent life threatening events (Clapp 2006)threatening events (Clapp 2006)

Suck-swallow immaturity and slow Suck-swallow immaturity and slow motility/gastric emptying also leads to motility/gastric emptying also leads to prolonged hospitalization and prolonged hospitalization and readmission (Neu 2006)readmission (Neu 2006)

Kinney HC. Seminars in Perinatology 30: 81-88, 2006.

Neurodevelopmental Neurodevelopmental OutcomesOutcomes

More likely to have developmental delay by 3 More likely to have developmental delay by 3 y/o RR (95%CI)= 1.46 (1.42-1.50)y/o RR (95%CI)= 1.46 (1.42-1.50)

More likely to be referred for special needs, More likely to be referred for special needs, special education, and have problems with special education, and have problems with school readiness than term counterpartsschool readiness than term counterparts

Small studies also suggest higher risk of Small studies also suggest higher risk of cerebral palsy, speech disorders, behavioral cerebral palsy, speech disorders, behavioral abnormalitiesabnormalities

Increased risk of hyberbilirubinemia Increased risk of hyberbilirubinemia (jaundice) and kernicterus(jaundice) and kernicterus Abnormal movements, hearing impairment, Abnormal movements, hearing impairment,

spasticity, abnormal movement of eyesspasticity, abnormal movement of eyes(Engle, 2007; Adams-Chapman, 2006)

ObjectiveObjective

Compare the enrollment in EI and Compare the enrollment in EI and the utilization of therapeutic the utilization of therapeutic services between services between moderately moderately pretermpreterm (32-36 weeks gestation) and (32-36 weeks gestation) and very pretermvery preterm (<32 weeks gestation) (<32 weeks gestation) infants at 12 months infants at 12 months ± 2 months± 2 months corrected agecorrected age

Jessica L. Kalia DO, Paul Visintainer Jessica L. Kalia DO, Paul Visintainer PhD, Heather L. Brumberg MD, PhD, Heather L. Brumberg MD, MPH, Maria Pici MD, Jordan Kase MPH, Maria Pici MD, Jordan Kase MD MD E-PAS2007:61:6280.25 E-PAS2007:61:6280.25

Why Early Intervention?Why Early Intervention?

Used as a surrogate to assess Used as a surrogate to assess neurodevelopmentneurodevelopment

Objective measurementObjective measurement 33% delay in at least 1 area of 33% delay in at least 1 area of

developmentdevelopment Must be receiving services, not just Must be receiving services, not just

referred for EI evaluationreferred for EI evaluation

MethodsMethods

Preterm infants followed at the Regional Preterm infants followed at the Regional Neonatal Follow-up Clinic in White Plains, Neonatal Follow-up Clinic in White Plains, NY from Jan 2005 through Oct 2006NY from Jan 2005 through Oct 2006

Included all patients <37 weeks gestation Included all patients <37 weeks gestation who had an evaluation at 12 months who had an evaluation at 12 months ± 2 ± 2 months corrected age (CA)months corrected age (CA)

Stratified into moderately preterm (32-36 Stratified into moderately preterm (32-36 weeks gestation) and very preterm (<32 weeks gestation) and very preterm (<32 weeks gestation) groupsweeks gestation) groups

Antenatal, maternal, and neonatal variables Antenatal, maternal, and neonatal variables obtained by NICU discharge summaries obtained by NICU discharge summaries and parental reportand parental report

Logistic regression, Chi square, and Logistic regression, Chi square, and Fisher’s exact tests used for analysisFisher’s exact tests used for analysis

ResultsResults

497 preterms(<37 wks)

n = 169 Evaluated

at 12 mo ± 2 mo CA

n = 77 VP (<32 wks)

n = 92MP (32-36 wks)

n = 328 Not evaluated

at 12 mo ± 2 mo CA

n = 208Not 12 mo ± 2 mo CA

at time of study

n = 101Lost to follow up

n = 19 Not assessed at

12 mo ± 2 mo CA

Patient CharacteristicsPatient CharacteristicsModerateModerate

lylyPreterm Preterm

Very Very Preterm Preterm

p p valuevalue

Gestational age (weeks) Gestational age (weeks) ## 34 ± 134 ± 1 28 ± 228 ± 2 <0.001<0.001

Birth wt (grams) Birth wt (grams) ## 2124 ± 2124 ±

493 493 1114 ± 1114 ±

374 374 <0.001<0.001

Length of stay (weeks) Length of stay (weeks) ## 2.3 ± 2.02.3 ± 2.0 8.9 ± 5.48.9 ± 5.4 <0.001<0.001

5 min Apgar5 min Apgar ^ ^ 9 (6,9)9 (6,9) 7 (1,9)7 (1,9) <0.001<0.001

Sex, n (%)Sex, n (%) NSNS

MaleMale 55 (60)55 (60) 37 (48)37 (48)

FemaleFemale 37 (40)37 (40) 40 (52)40 (52)

Delivery type, n (%)Delivery type, n (%) NSNS

NSVDNSVD 27 (32)27 (32) 20 (26)20 (26)

C/SC/S 40 (48)40 (48) 39 (51)39 (51)

Stat C/SStat C/S 17 (20)17 (20) 18 (23)18 (23)## mean ± SD , ^̂median (min,max), NS = not significant

Patient DemographicsPatient DemographicsModeratelModeratel

y y PreterPreter

m m

VeryVeryPreterPreter

m m p p

valuevalue

Multiple gestation, n (%)Multiple gestation, n (%) 0.020.02

SingletonSingleton 62 (67)62 (67) 60 (78)60 (78)

TwinsTwins 21 (22)21 (22) 17 (22)17 (22)

TripletsTriplets 9 (10)9 (10) 0 (0)0 (0)

Medicaid, n (%)Medicaid, n (%) 80 (87)80 (87) 71(92)71(92) NSNS

Maternal age (years) Maternal age (years) # 31 ± 7 31 ± 7 29 ± 7 29 ± 7 NSNS

Maternal race, n (%)Maternal race, n (%) 0.010.01

CaucasianCaucasian 34 (38)34 (38) 14 (18)14 (18)

African AmericanAfrican American 20 (22)20 (22) 21 (28)21 (28)

HispanicHispanic 30 (33)30 (33) 26 (34)26 (34)

OtherOther 6 (7)6 (7) 15 (20)15 (20)

Maternal substance abuse, n Maternal substance abuse, n (%)(%) 8 (9)8 (9) 7 (9)7 (9) NSNS

# mean ± SD , NS = not significant

Rate of Therapy UseRate of Therapy Use

0%

10%

20%

30%

40%

50%

60%

70%

80%

EI PT OT Speech SpecialEd

MP

VP

*

* *

*

* p= <0.05

*

Very Preterm vs. Moderately Very Preterm vs. Moderately Preterm Odds RatiosPreterm Odds Ratios

1

EI

0 10

PT

OT

Speech

Special Ed

*

Very Preterm vs. Moderately Very Preterm vs. Moderately PretermPreterm

Adjusted Odds RatiosAdjusted Odds Ratios

10 10

EI

PT

OT

Speech

Special

Ed

Adjusted for:

5 minute Apgar score

Caffeine

BPD

RDS

Length of stay

SummarySummary

Over 1/3 of moderately preterm Over 1/3 of moderately preterm infants were enrolled in EI and 28% infants were enrolled in EI and 28% received physical therapyreceived physical therapy

When adjusting the odds ratios for When adjusting the odds ratios for neonatal factors, there was no neonatal factors, there was no difference in the odds of utilizing difference in the odds of utilizing therapies between the two therapies between the two gestational age groupsgestational age groups

ConclusionConclusion

Moderately preterm babies are Moderately preterm babies are at at riskrisk and must be and must be screenedscreened and and referred for interventional therapiesreferred for interventional therapies

They should not be considered They should not be considered “small” full term infants“small” full term infants

ImplicationsImplications

If our results could be extrapolated to If our results could be extrapolated to the general population, there would the general population, there would be 150,000 moderately preterm and be 150,000 moderately preterm and 75,000 very preterm infants enrolled 75,000 very preterm infants enrolled in EI per yearin EI per year

AcknowlegementsAcknowlegements

Westchester Medical Westchester Medical CenterCenterJordan Kase MDJordan Kase MD

Jessica Kalia, DOJessica Kalia, DO

Sergio Golombek MD, Sergio Golombek MD, MPHMPH

Dept of Epidemiology, Dept of Epidemiology, NY Medical CollegeNY Medical CollegePaul Visintainer PhDPaul Visintainer PhD

Children’s Children’s Rehabilitation CenterRehabilitation Center

Maria Pici MDMaria Pici MD

NY State Department of NY State Department of Vital StatisticsVital Statistics

-Larry Schoen, Director -Larry Schoen, Director of the Statistical of the Statistical Analysis and Program Analysis and Program Support Unit in the Support Unit in the Bureau of Biometrics Bureau of Biometrics and Health Statisticsand Health Statistics

-Daljit Singh, -Daljit Singh, BiostatisticianBiostatistician

Still awake? Thank You!Still awake? Thank You!