An integrated model with classification criteria to predict small-for-gestational-age fetuses at risk of adverse perinatal outcome
Por:
Figueras F, Savchev S, Triunfo S, Crovetto F and Gratacós E
Publicada:
1 mar 2015
Ahead of Print:
27 ene 2015
Resumen:
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. Copyright (C) 2014 ISUOG. Published by John Wiley & Sons Ltd.
Filiaciones:
Figueras F:
University of Barcelona, Barcelona, Spain
BCNatal, Barcelona Center for Maternal, Fetal and Neonatal Medicine, Hospital Clínic and Hospital Sant Joan de Déu, University of Barcelona, Barcelona, Spain
Fetal and Perinatal Research Centre, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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