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An integrated model with classification criteria to predict small‐for‐gestational‐age fetuses at risk of adverse perinatal outcome
Author(s) -
Figueras F.,
Savchev S.,
Triunfo S.,
Crovetto F.,
Gratacos E.
Publication year - 2015
Publication title -
ultrasound in obstetrics and gynecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.202
H-Index - 141
eISSN - 1469-0705
pISSN - 0960-7692
DOI - 10.1002/uog.14714
Subject(s) - medicine , umbilical artery , small for gestational age , obstetrics , fetus , gestational age , pregnancy , birth weight , body mass index , biophysical profile , cohort , uterine artery , gestation , genetics , biology
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 < 10 th centile, a mean UtA‐PI > 95 th centile or an EFW < 3 rd 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 © 2014 ISUOG. Published by John Wiley & Sons Ltd.