An integrated model with classification criteria to predict small-for-gestational-age fetuses at risk of adverse perinatal outcome.

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.