title: An integrated model with classification criteria to predict small-for-gestational-age fetuses at risk of adverse perinatal outcome.
abstract: OBJECTIVE
  To develop an integrated model with the best performing criteria for predicting adverse outcome in small-for-gestational-age (SGA) pregnancies.
  
  
  METHODS
  A cohort of 509 pregnancies with a suspected SGA fetus, eligible for trial of labor, was recruited prospectively and data on perinatal outcome were recorded. A predictive model for emergency Cesarean delivery because of non-reassuring fetal status or neonatal acidosis was constructed using a decision tree analysis algorithm, with predictors: maternal age, body mass index, smoking, nulliparity, gestational age at delivery, onset of labor (induced vs spontaneous), estimated fetal weight (EFW), umbilical artery pulsatility index (PI), mean uterine artery (UtA) PI, fetal middle cerebral artery PI and cerebroplacental ratio (CPR).
  
  
  RESULTS
  An adverse outcome occurred in 134 (26.3%) cases. The best performing predictors for defining a high risk for adverse outcome in SGA fetuses was the presence of a CPR < 10th centile, a mean UtA-PI > 95th centile or an EFW < 3rd centile. The algorithm showed a sensitivity, specificity and positive and negative predictive values for adverse outcome of 82.8% (95% CI, 75.1-88.6%), 47.7% (95% CI, 42.6-52.9%), 36.2% (95% CI, 30.8-41.8%) and 88.6% (95% CI, 83.2-92.5%), respectively. Positive and negative likelihood ratios were 1.58 and 0.36.
  
  
  CONCLUSIONS
  Our model could be used as a diagnostic tool for discriminating SGA pregnancies at risk of adverse perinatal outcome.
authors.affiliation: Fetal and Perinatal Research Centre, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; BCNatal, Barcelona Center for Maternal, Fetal and Neonatal Medicine, Hospital Clínic and Hospital Sant Joan de Déu, University of Barcelona, Barcelona, Spain; University of Barcelona, Barcelona, Spain.
authors.forename: F
authors.initials: F
authors.lastname: Figueras
authors.forename: S
authors.initials: S
authors.lastname: Savchev
authors.forename: S
authors.initials: S
authors.lastname: Triunfo
authors.forename: F
authors.initials: F
authors.lastname: Crovetto
authors.forename: E
authors.initials: E
authors.lastname: Gratacos
mesh_terms: D000328:Adult; D000465:Algorithms; D002585:Cesarean Section / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D005260:Female; D005317:Fetal Growth Retardation / Q000000981:diagnostic imaging; D006801:Humans; D007231:Infant, Newborn; D007236:Infant, Small for Gestational Age; D007751:Labor, Induced / Q000706:statistics & numerical data; D008423:Maternal Age; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging* / Q000196:embryology / Q000503:physiopathology; D011237:Predictive Value of Tests; D011247:Pregnancy; D011256:Pregnancy Outcome; D011263:Pregnancy Trimester, Third; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology; D018608:Ultrasonography, Doppler; D016216:Ultrasonography, Prenatal / Q000379:methods; D055988:Uterine Artery / Q000000981:diagnostic imaging* / Q000196:embryology / Q000503:physiopathology
keywords: Doppler; fetal growth restriction; management; perinatal complications; small-for-gestational age