title: Antenatal prediction of neonatal mortality in very premature infants.
abstract: OBJECTIVE
  To develop a prognostic model for antenatal prediction of neonatal mortality in infants threatening to be born very preterm (<32 weeks).
  
  
  METHODS
  Nationwide cohort study in The Netherlands between 1999 and 2007. We studied 8500 singletons born between 25(+0) and 31(+6) weeks of gestation where fetus was alive at birth without congenital anomalies. We developed a multiple logistic regression model to estimate the risk of neonatal mortality within 28 days after birth, based on characteristics that are known before birth. We used bootstrapping techniques for internal validation. Discrimination (AUC), accuracy (Brier score) and calibration (graph, c-statistics) were used to assess the model's predictive performance.
  
  
  RESULTS
  Neonatal mortality occurred in 766 (90 per 1000) live births. The final model consisted of seven variables. Predictors were low gestational age, no antental corticosteroids, male gender, maternal age ≥35 years, Caucasian ethnicity, non-cephalic presentation and non-3rd level of hospital. The predicted probabilities ranged from 0.003 to 0.697 (IQR 0.02-0.11). The model had an AUC of 0.83, the Brier score was 0.065. The calibration graph showed good calibration, and the test for the Hosmer Lemeshow c-statistic showed no lack of fit (p=0.43).
  
  
  CONCLUSIONS
  Neonatal mortality can be predicted for very preterm births based on the antenatal factors gestational age, antental corticosteroids, fetal gender, maternal age, ethnicity, presentation and level of hospital. This model can be helpful in antenatal counseling.
authors.affiliation: Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands. Electronic address: a.c.ravelli@amc.uva.nl.
authors.forename: Anita C J
authors.initials: AC
authors.lastname: Ravelli
authors.affiliation: Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands; Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Jelle M
authors.initials: JM
authors.lastname: Schaaf
authors.affiliation: Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Ben Willem J
authors.initials: BW
authors.lastname: Mol
authors.affiliation: Department of Neonatology, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Pieter
authors.initials: P
authors.lastname: Tamminga
authors.affiliation: Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Martine
authors.initials: M
authors.lastname: Eskes
authors.affiliation: Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Joris A M
authors.initials: JA
authors.lastname: van der Post
authors.affiliation: Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Ameen
authors.initials: A
authors.lastname: Abu-Hanna
mesh_terms: D000328:Adult; D005260:Female; D005865:Gestational Age; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D062071:Infant, Extremely Premature; D007231:Infant, Newborn; D008297:Male; D008423:Maternal Age; D009426:Netherlands / Q000453:epidemiology; D011247:Pregnancy; D047928:Premature Birth; D018570:Risk Assessment; D044465:White People
keywords: Antepartum risk assessment; Ethnicity; Level of hospital; Neonatal mortality; Prediction model; Very preterm birth