Faktor Risiko Dan Hasil Luaran Early Dan Late

8/12/2019 Faktor Risiko Dan Hasil Luaran Early Dan Late

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OBSTETRICS

Incidence of preeclampsia: risk factors and outcomesassociated with early- versus late-onset diseaseSarka Lisonkova, MD, PhD; K. S. Joseph, MD, PhD

OBJECTIVE: The population-based incidence of early-onset (


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therefore carried out a population-basedstudy to describe the gestational age-

specic incidence of preeclampsia onset

among women with singleton pregnan-cies and to examine risk factors and birth

outcomes associated with early-onset

and late-onset disease.

MA T E R I A L S A N D METHODS

We included all singleton deliveries in

Washington State during the period from

2003 to 2008, utilizing information from2 large population databases: (1) the

Comprehensive Discharge Abstract Da-

tabase (CHARS) which included allhospitalizations in Washington State, and

(2) the Birth Events Record Database(BERD), which included birth records of

all live born infants and fetal deaths.Women with a diagnosis of preeclampsiaor eclampsia (henceforth referred to as

preeclampsia), including preeclampsia

superimposed on chronic hypertensionwere identied from the CHARS data-

base (International Classication of Dis-eases, ninth revision [ICD-9] diagnostic

codes 642.4, 642.5, 642.6, and 642.7).

Hospitalization records with a diag-nosis of preeclampsia were linkedto birth

records to obtain information about

gestational age at delivery, maternalcharacteristics, clinical risk factors, and

birth outcomes. The number of weeksbetween the hospitalization when the

preeclampsia diagnosis was made and

birthhospitalizationwas calculated basedon theCHARS and BERD record linkage.

Preeclampsia occurring at less than

34 weeks of gestation was identied asearly-onset disease, whereas preeclamp-

sia that occurred at 34 weeks or later waslabeled late-onset disease, irrespective of

the gestational week at delivery. Infantbirth records were also linked to CHARS(infant) hospitalization records to iden-

tify cases of severe neonatal morbidity

(see the following text).There were 484,111 women who were

residents of Washington State and whodelivered a singleton stillbirth or live

birth in a Washington State hospital be-

tween 2003 and 2008. Women with amissing estimate of gestation or gesta-

tional age at delivery less than 20 weeks

and women without a linkage betweenthe birth/fetal death certicate (BERD

database) and maternal hospitalizationdata (CHARS database) were excluded

(5.7%, n 27,443).

Maternal characteristics and clinicalrisk factors examined for potential as-

sociation with preeclampsia included

maternal age (younger than 20 and35 years old or older vs 20-34 years);

parity (number of previous live births,none vs 1 or more); marital status (single/

widowed/separated vs married/common

law); education (less than high schoolvs high school education or greater);

race (non-Hispanic white vs Hispanic,

African-American, Native-American, andother); smoking during pregnancy (yes/

no); infertility treatment (yes/no); dia-betes mellitus (yes/no); chronic hyper-

tension prior to pregnancy (yes/no);infants sex (male/female); and congenitalanomalies (yes/no).

Fetal death was dened as in utero or

intrapartum death of a fetus delivered at20 weeks gestation or later, neonatal

death was dened as a death of an infantwithin 28 days after birth, and perinatal

death included fetal or neonatal death.

Using birth hospitalization data for in-fants (obtained from the linked infants

birth and hospitalization records), the

following adverse birth outcomes wereidentied based on ICD-9 codes: bron-

chopulmonary dysplasia (BPD; code770.7), intraventricular hemorrhage

(IVH) grade III and IV (codes 772.13

and 772.14), periventricular leukomala-cia (PVL; code 779.7), retinopathy of

prematurity (ROP; code 362.2), necro-

tizing enterocolitis (NEC; code 777.5),and neonatal sepsis (code 771.81). Other

neonatal outcomes were identied frombirth records, namely, neonatal seizures,

Apgar score at 5 minutes, and neonatalintensive care unit (NICU) admission.Severe neonatal morbidity included

any of the following: a 5-minute Apgar

score of 3 or less, neonatal seizures, BPD,IVH grade III or IV, PVL, ROP, NEC, and

neonatal sepsis. The composite out-come of neonatal mortality/morbidity

included both neonatal death and severe

neonatal morbidity, whereas perinatalmortality/morbidity included perinatal

death and severe neonatal morbidity.

Small-for-gestational-age (SGA) infantswere dened as those weighing less than

the 10th percentile of the sex- and gesta-tional ageespecic birthweight reference

for the United States,26 whereas large-for-

gestational age infants were those weigh-ing over the 90th percentile. We used the

clinical estimate of gestation provided in

the data source because this is more ac-curate than gestational age estimated by

the last menstrual period.27,28

Gestational ageespecic rates of pre-

eclampsia were calculated using ongoing

pregnancies as the denominator. c2 tests

were used to assess the differences be-

tween rates of early-onset and late-onset

preeclampsia across maternal and clin-ical characteristics. The Cox regressionmodel, with preeclampsia onset as the

outcome and gestational age as the time

axis, was usedto estimate adjusted hazardratios (AHRs) and 95% condence in-tervals (CIs). This enabled us to create the

appropriate risk sets, with censoring of

subjects who developed preeclampsia orwho delivered at any particular gestation.

When the proportional hazards as-

sumption was not satised, we examined

the interaction term between the risk

factor and gestational age at diagnosiscategorized as less than 34 weeks and 34

weeks or longer and obtained AHRs for

both early-onset and late-onset pre-eclampsia separately. The Wald statisticwas used to assess statistical signicance

of the interaction terms. Shoenfeld re-

siduals were used to evaluate the pro-

portional hazards assumption of thenal model.29

Birth outcomes including fetal death,

perinatal death, and severe neonatal

morbidity were analyzed using thefetuses-at-risk approach. Under this

formulation, all fetuses at a specic

gestation were considered at risk foradverse outcomes at that gestation.

Thus, for example, all fetuses at 28 weekswith early-onset preeclampsia were

considered to be at risk of live birth,

stillbirth, neonatal death, or severeneonatal morbidity at 28 weeks, irre-

spective of whether they actually deliv-ered at 28 weeks or at a subsequent

gestational week.30,31 Two fetuses-at-riskebased logistic regression models

were used to estimate causal associations

between early-onset and late-onset pre-eclampsia and birth outcomes.

www.AJOG.org Obstetrics Research

DECEMBER 2013 American Journal of Obstetrics &Gynecology 544.e2
http://www.ajog.org/http://www.ajog.org/


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TABLE 1

Maternal characteristics and clinical factors associated with early- and late-onset preeclampsia, singletondeliveries, Washington State, 2003-2008

Maternal

characteristics/clinicalfactors

Ongoingpregnanciesat 20 weeks Early-onset preeclampsia

Ongoingpregnanciesat 34 weeksa Late-onset preeclampsia

(n[ 456,668) (n[ 1752) Rate per 1000 (n[ 447,822) (n[ 12,449) Rate per 1000

Age, y


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These models were constructed using

ongoing pregnancies(ie,fetuses at risk)as the denominator32,33; all ongoing

pregnancies at 20 weeks gestation were

included in models examining birthoutcomes following early-onset pre-

eclampsia, whereas all ongoing preg-

nancies at 340 weeksgestation (amongwomen without early-onset preeclamp-

sia) were included in the denominatorfor birth outcomes following late-onset

preeclampsia.

In addition, we compared neonatal

outcomes between infants born tomothers with and without early-onset or

late-onset preeclampsia, adjusting forgestational age at delivery (traditional

analysis). This analysis used live birthsat a particular gestational age as the

denominator and provided a predictive

(noncausal) model comparing the oddsof adverse neonatal outcomes amongmothers with and without preeclampsia,

conditional on delivery of a live-born

infant at a specic gestational age.32,33

We further compared birth outcomes

between mothers with early-onset pre-eclampsia who delivered at 34 weeks or

longer, and mothers with late-onsetpreeclampsia (who, by denition, all

delivered at 34 weeks).

We performed sensitivity analyses

examining theeffect of obesity on theriskof early-onset and late-onset pre-

eclampsia and its association with birthoutcomes. Obesity was dened as a body

mass index (BMI) greater than 30 kg/m2.

Missing values for BMI (27.7%, 14.6%,

and 13.9% in the early-onset, late-onset,

and no preeclampsia groups, respec-tively) were imputed using multipleimputation procedures (proc MI, SAS

software, version 9.2; SAS Institute Inc,

Cary, NC). In addition, we adjusted fortime period (year of delivery) to address

the potential effects of changes in ob-stetric and neonatal practices.

All analyses were performed on pub-

licly accessible de-identied data. Anexemption from ethics approval was

granted by the Department of Social and

Health Services, State of Washington.Analyses were carried out using SAS

software, version 9.2 (SAS Institute Inc.,Cary, NC). A 2-tailed P < .05 was

considered signicant.

RESULTS

The study included 456,668 women who

delivered a singleton live birth or still-

birth between 2003 and 2008. The rate ofpreeclampsia was 3.11 per 100 singleton

deliveries (14,201 of 456,668), and the

rate of eclampsia was 4.12 per 10,000singleton deliveries (188 of 456,668).

The frequency of early-onset pre-eclampsia was 0.38 per 100 deliveries,

and the frequency of late-onset pre-

eclampsia was 2.72 per 100 deliveries(Table 1). The gestational ageespecic

incidence of preeclampsia increased withpregnancy duration, from 0.01 per 1000

ongoing pregnancies at 20 weeksgesta-

tion to 9.62 per 1000 ongoing pregnan-cies at 40 weeksgestation (Figure).

Women who were at the extremes ofmaternal age(younger than 20 or 35 years

TABLE 1

Maternal characteristics and clinical factors associated with early- and late-onset preeclampsia, singletondeliveries, Washington State, 2003-2008 (continued)

Maternal

characteristics/clinicalfactors

Ongoingpregnanciesat 20 weeks Early-onset preeclampsia

Ongoingpregnanciesat 34 weeksa Late-onset preeclampsia

(n[ 456,668) (n[ 1752) Rate per 1000 (n[ 447,822) (n[ 12,449) Rate per 1000

Congenital anomalies

Yes 2249 23 10.2 1949 66 33.9

No 454,419 1729 3.8 445,873 12,383 27.8

The number of pregnancies does not add up to the total in some categories because of missing values (missing values exceeding 3% were 4.1% for education, 3.6% for smoking, and 6.6% fornumber of prior live births in the early-onset preeclampsia group).

a Ongoing pregnancies without early-onset preeclampsia.

Lisonkova. Early- vs late-onset preeclampsia. Am J Obstet Gynecol 2013.

FIGURE

Gestational ageespecific incidence of preeclampsia, singletondeliveries, Washington State, 2003-2008

Lisonkova. Early- vs late-onset preeclampsia. Am J Obstet Gynecol 2013 .




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old or older), African-American, un-married, and nulliparous had higher rates

of early-onset preeclampsia (Table 1).

Similarly, women who had diabetesmellitus or chronic hypertension, used

infertility treatment to conceive, and hadan infant with a congenital anomaly also

had higher rates of early-onset pre-

eclampsia. Women who were very young(younger than 20 years of age), unmar-

ried, nulliparous, had diabetes mellitusor chronic hypertension, used infertility

treatment to conceive, and were pregnant

with a male fetus also had higher rates oflate-onset preeclampsia. On the other

hand women who smoked or belongedto the other race category (ie, other

than non-Hispanic white, Hispanic,African-American and Native-American;

Table 2) had lower rates of late-onset

disease.Several risk factors were associated with

preeclampsia, without a signicant dif-

ference in adjusted hazard ratios for early-and late-onset disease (Table 2). These

included smoking during pregnancy(AHR, 0.87; 95% CI, 0.82e0.93 for both

early- and late-onset disease), unmarried

status (AHR, 1.14; 95% CI, 1.10e1.19),older maternal age (AHR, 1.15; 95% CI,

1.10e1.21), and infants sex (AHR for

male sex, 1.10; 95% CI, 1.06e1.14).

In contrast, several risk factors dif-fered signicantly in their association

with early- vs late-onset preeclampsia.

African-American race, chronic hyper-tension, and congenital anomalies were

more stronglyassociated with early-onsetdisease, whereas young maternal age(younger than 20 vs 20-35 years), other

race (not including African-American,

Hispanic or Native-American vs non-Hispanic white), nulliparity, and dia-

betes mellitus were more stronglyassociated with late-onset disease. Other

race had a protective effect on late-onset

disease compared with non-Hispanicwhite race (AHR, 0.68; 95% CI,

0.63e0.73).

Women with chronic hypertensionhad the highest risk for preeclampsia,

TABLE 2

Crude and adjusted hazard ratios for early- and late-onset preeclampsia, singleton deliveries, Washington State,2003-2008

Demographic/clinical factors

Preeclampsia, unadjusted analysis Preeclampsia, adjusted analysis

Early onset Late onset Early onset Late onset

HR 95% CI HR 95% CI AHR 95% CI AHR 95% CI

Age, y


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with more than a 10-fold higher rateof early-onset disease (AHR, 11.7; 95%

CI, 10.1e13.6) and an approximately

5-fold higher rate of late-onset disease(AHR, 5.8; 95% CI, 5.4e6.3) as

compared with women without chronichypertension.

The rates of all adverse birth

outcomes, except for large for gesta-tional age (LGA), were signicantly

higher among women with early-onsetpreeclampsia compared with women

without early-onset disease (Table 3).Among women with early-onset pre-

eclampsia, approximately 12%, deliv-

ered at 34 weeksgestation or later, andalmost one half of births (49.5%) were

very low birthweight (


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The adjusted rates of adverse birth

outcomes were also higher amongmothers with late-onset disease as

compared with mothers without pre-

eclampsia, although the differences inrates were substantially less and some

were not statistically signicant (Table 4).

The rates of fetal, neonatal, and perinatal

death, for example, were not signi

-cantly higher among women with late-onset preeclampsia (AOR, 1.29; 95%

CI, 0.81e1.96; AOR, 1.09; 95% CI,

0.61e1.96, and AOR, 1.19; 95% CI,0.83e1.69, respectively). Rates of SGA,

in contrast, were signicantly elevated

among mothers with late-onset disease(AOR, 2.68; 95% CI, 2.54e2.82).

From the prognostic perspective, live-born infants of mothers with early-onset

preeclampsia were less likely to die in the

neonatal period (AOR, 0.51; 95% CI,0.36e0.74) compared with those born at

the same gestation to mothers without

preeclampsia (Appendix;SupplementaryTable 1). However, these infants had

higher odds of severe neonatal morbidity(AOR, 1.35; 95% CI, 1.16e1.57), NICU

admission (AOR, 2.44; 95% CI,

2.13e2.80), and SGA (AOR, 2.78; 95%CI, 2.46e3.13). The unadjusted odds of

LGA were lower among infants of

mothers with late-onset disease (odds

ratio, 0.78; 95%CI, 0.73e

0.83), althoughadjustment for gestational age and other

covariates increased the relative odds

(AOR, 1.09; 95% CI, 1.02e1.16).Birth outcomes among women with

early-onset preeclampsia who deliveredat a gestation of 34 weeks or longer and

women with late-onset preeclampsia

were similar in terms of fetal andneonatal death (Table 5). However, the

rates of the most common outcomes,such as NICU admission and SGA, weresignicantly elevated among the early-

onset group (AOR, 2.22; 95% CI,1.60e3.07; and AOR, 1.66; 95% CI,

1.24e2.23, respectively).

Sensitivity analyses showed that highBMI was a stronger risk factor for early-

onset than for late-onset disease (AHR,

2.10; 95% CI, 1.91e2.32; and AHR, 1.71;95% CI, 1.65e1.77, respectively), similar

to the association between chronic hy-

pertension and the preeclampsia sub-types. The AHR for chronic hypertension

decreased after additional adjustment forobesity (AHR, 9.4; 95% CI, 8.2e10.9; and

AHR, 2.24; 95% CI, 2.11e2.38, for early-

and late-onset preeclampsia, respec-tively). The associations between early-

and late-onset preeclampsia and birthoutcomes were not appreciably affected

by additional adjustment for BMI except

for LGA, which was no longer signi-cantly elevated among live-born infants

of mothers with late-onset preeclampsia(AOR, 1.03; 95% CI, 0.97e1.10).

Additional adjustment for time period(year of birth) did not change the results.

Women excluded from the study weredifferent from the study population

with regard to several risk factors for

preeclampsia. Some risk factors (suchas African-American race, no prior

live births, chronic hypertension, and

congenital anomalies) were overrep-resented among the excluded women,

whereas other risk factors (such as oldermaternal age, Hispanic and Native-

American race, single parent status, and

diabetes mellitus) were less frequent thanexpected (Appendix; Supplementary

Table 2).

COMMENT

Our population-based study showed

that the gestational ageespecic inci-

dence of preeclampsia among womenwith singleton pregnancies increased

sharply with gestational age. The rate ofearly-onset disease (


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maternal age were associated with ahigher risk of late-onset preeclampsia.

Early-onset preeclampsia conferred a

substantially higher risk for adverse birthoutcomes than late-onset preeclampsia.

In contrast, the prognosis for neonataldeath among infants born to women

with early-onset preeclampsia was better

than the prognosis for infants born at thesame gestation because of other causes.

The lower risk of neonatal death amonginfants born to mothers with pre-

eclampsia at preterm gestation has been

reported previously.2,16,17 This differ-

ence in prognosis, however, was condi-

tional on a live birth and not evidentin the causal fetuses-at-risk analysis

(Table 4). Furthermore, the rates ofNICU admission and SGA were signi-

cantly higher among infants born to

mothers with early-onset preeclampsia.Approximately 12% of the women with

early-onset preeclampsia delivered at agestation of 34 weeks or longer.

Our population-based study exam-

ined gestational ageespecic rates ofpreeclampsia in a large cohort of sin-

gletons. Overall rates of preeclampsiawere consistent with previous estimates

from industrialized countries, which

have reported preeclampsia rates be-tween 3 and 5 per 100 deliveries2,3 and

eclampsia rates between 2.7 and 8.2 per10,000 deliveries.2,7

Although the causes of preeclampsiaarenot known, placental dysfunction has

been implicated in its origins,18,20,34 and

placental morphology studies suggestthat preeclampsia is a heterogeneous

entity.34-36 Our results show that effect of

risk factors such as race/ethnicity, nulli-parity, chronic hypertension, and dia-

betes vary according to the subtype ofpreeclampsia. For example, congenital

anomalies were more strongly associated

with early-onset disease, suggesting thepresence of associated placental abnor-

malities that affect perfusion and result

in early-onset disease. In contrast, astronger positive association between

diabetes mellitus and late-onset pre-eclampsia suggests that relative placental

insuf

ciency is more likely to occur indiabetic pregnancies with a larger fetus.We also observed a stronger association

between early-onset disease and SGA (as

compared with late-onset disease andSGA), likely because of the profound

effects of poor placental perfusion earlyin gestation and differences in disease

severity.20,37

Our study has a few limitations.

Gestational age at the onset of pre-

eclampsia was estimated based on the

time between hospital admission forpreeclampsia and hospital admission fordelivery. We were not able to capture

women with preeclampsia who were not

hospitalized andthose who did notdeliverin the hospital. However, such missed

cases of preeclampsia were likely milder

cases that did not result in serious com-plications requiring hospitalization. In

some cases, theonset of preeclampsia mayhave occurred a few days before the

admission to the hospital. The delay be-

tween the onset of preeclampsia andadmission to the hospital may have

resulted in some misclassication of early-

onset disease as late-onset preeclampsia.As with any administrative database,

the accuracy of diagnoses was contingenton documentation and abstraction from

medical records. However, it has been

shown that linkage between hospitali-zation data and birth/infant death cer-

ticates increases data accuracy and that

the accuracy of major obstetric diagnoses

and procedures is relatively high inWashington States linked data le.38

TABLE 5

Crude and adjusted odd ratios for birth outcomes contrastingearly-onset vs late-onset preeclampsia, singleton deliveriesat gestation of 34 weeks, Washington State, 2003-2008

Birth outcomes

Early-onset preeclampsiawith delivery at gestation34 weeks (n[ 213)

Late-onsetpreeclampsia(n[ 12,449) Pvaluea

Gestational age at delivery, wks

34-36 128 (60.1) 2911 (23.4) < .01

37-43 85 (39.9) 9538 (76.6)

Birthweight, g


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Other potential weaknesses of thestudy include limited information about

risk factors, such as BMI. Sensitivity

analyses showed that high BMI had astronger association with early- vs late-

onset preeclampsia (similar to chronic

hypertension), suggesting that metabolicsyndrome (associated with high BMI)

may play a stronger role in early-onset vslate-onset disease.

We did not have detailed information

about antenatal screening, and obstetricand neonatal care practices in the

different hospitals in Washington state

including use of aspirin among womenat high risk for preeclampsia. Potential

inaccuracies in diagnosis and differencesin intervention between physicians and

hospitals may have resulted in somenondifferential misclassication of riskfactors and outcomes and led to some

dilution in observed associations.

Finally, subjects excluded from thestudy because of missing information or

unlinked records were signicantlydifferent from those included in the

study, with respect to some maternal

characteristics, although the fractionexcluded was small (5.7%).

The strengths of our study include a

large study population and gestationalageespecic incidence rates dened us-

ing the onset of disease. The populationperspective obtained by using statewide

information minimized potential selec-

tion bias that may be present in hospital-based studies, especially those that

include selected hospital patients.30-33

The large study size offered statistical

power for analysis of rare adverse birthoutcomes. Finally, the use of the fetuses-

at-risk approach in addition to tradi-

tional perinatal modeling provides thecausal and prognostic perspectives on

the relation between preeclampsia andbirth outcomes.

In summary, population-based data

on singleton deliveries in WashingtonState between 2003 and 2008 showed

that the incidence of preeclampsiaincreased sharply with gestational age.

Even though some risk factors were

common to both early- and late-onsetdisease, several risk factors had quanti-

tatively different associations with the 2subtypes of preeclampsia. Early-onset

preeclampsia had far greater adverse ef-

fects on the fetus and infant comparedwith late-onset disease. Our study thus

conrms the heterogeneity of pre-

eclampsia and shows that the timing ofdisease onset is one important indicator

of disease severity and possibly of diseaseetiology. Research studies should treatthe 2 preeclampsia subtypes as distinct

entities from an etiological and prog-nostic standpoint. -

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AP P E N D I X

SUPPLEMENTARY TABLE 1

Crude and AORs for neonatal outcomes among livenewborns, following early- and late-onset preeclampsia,singleton deliveries, Washington State, 2003-2008a

Neonatal outcomes

Early-onset preeclampsia Late-onset preeclampsia

OR 95% CI AORa 95% CI OR 95% CI AORa 95% CI

SGA (90th percentile) 0.27 0.14e0.52 0.46 0.29e0.74 0.78 0.73e0.83 1.09 1.02e1.16

Apgar score at 5 min 3 0.46 0.36e0.59 0.84 0.64e1.10 2.62 2.14e3.22 1.98 1.59e2.46

NICU admission 1.90 1.66e2.17 2.44 2.13e2.80 3.82 3.62e4.03 1.65 1.55e1.76

Severe neonatal morbidityb 0.82 0.72e0.94 1.35 1.16e1.57 2.59 2.29e2.93 1.57 1.37e1.79

Neonatal death 0.29 0.22e0.39 0.51 0.36e0.74 1.31 0.78e2.19 0.71 0.39e1.28

Neonatal death/severe morbidity 0.75 0.66e0.85 1.18 1.01e1.37 2.50 2.21e2.82 1.51 1.32e1.72

Regression models adjusted for gestational age, race, parity, maternal age, maternal education, infants sex, marital status, infertility treatment, chronic hypertension, diabetes, and congenital

anomalies.

AOR, adjusted odds ratio; CI, confidence interval; LGA, large for gestational age; NICU, neonatal intensive care unit; OR, odds ratio; SGA, small for gestational age.

a Prognostic model comparing neonatal outcomes conditional on live birth, adjusted for gestational age at delivery. Fetal death was not included in the prognostic model because such deaths occurbefore birth; b Includes any of the following: a 5 minute Apgar score of 3 or less, bronchopulmonary dysplasia, necrotizing enterocolitis, neonatal seizures, neonatal sepsis, intraventricularhemorrhage grades 3 and 4, periventricular leukomalacia, and retinopathy of prematurity.

Lisonkova. Early- vs late-onset preeclampsia. Am J Obstet Gynecol 2013.

Research Obstetrics www.AJOG.org

544.e11 American Journal of Obstetrics &Gynecology DECEMBER 2013


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SUPPLEMENTARY TABLE 2

Demographic and clinical characteristics, singleton deliveries with andwithout inclusion criteria, Washington State, 2003-2008a

Demographic/clinical risk factors

Included Excluded

Pvaluebn[ 456,668 (%) n[27,443 (%)a

Age, y

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Faktor Risiko Dan Hasil Luaran Early Dan Late

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