First‐trimester screening with specific algorithms for early‐ and late‐onset fetal growth restriction

Objective To develop optimal first‐trimester algorithms for the prediction of early and late fetal growth restriction ( FGR ). Methods This was a prospective cohort study of singleton pregnancies undergoing first‐trimester screening. FGR was defined as an ultrasound estimated fetal weight < 10 th percentile plus Doppler abnormalities or a birth weight < 3 rd percentile. Logistic regression‐based predictive models were developed for predicting early and late FGR (cut‐off: delivery at 34 weeks). The model included the a‐priori risk (maternal characteristics), mean arterial pressure ( MAP ), uterine artery pulsatility index ( UtA‐PI ), placental growth factor ( PlGF ) and soluble fms‐like tyrosine kinase‐1 (sFlt‐1). Results Of the 9150 pregnancies included, 462 (5%) fetuses were growth restricted: 59 (0.6%) early and 403 (4.4%) late. Significant contributions to the prediction of early FGR were provided by black ethnicity, chronic hypertension, previous FGR , MAP , UtA‐PI , PlGF and sFlt‐1. The model achieved an overall detection rate ( DR ) of 86.4% for a 10% false‐positive rate (area under the receiver–operating characteristics curve (AUC): 0.93 (95% CI , 0.87–0.98)). The DR was 94.7% for FGR with pre‐eclampsia ( PE ) (64% of cases) and 71.4% for FGR without PE (36% of cases). For late FGR , significant contributions were provided by chronic hypertension, autoimmune disease, previous FGR , smoking status, nulliparity, MAP , UtA‐PI , PlGF and sFlt‐1. The model achieved a DR of 65.8% for a 10% false‐positive rate (AUC: 0.76 (95% CI , 0.73–0.80)). The DR was 70.2% for FGR with PE (12% of cases) and 63.5% for FGR without PE (88% of cases). Conclusions The optimal screening algorithm was different for early vs late FGR , supporting the concept that screening for FGR is better performed separately for the two clinical forms. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.