Predictive value of fetal Doppler velocimetry, fetal growth trajectory and maternal serum biomarkers for short-term adverse perinatal outcome: secondary analysis of DRIGITAT study.

OBJECTIVES

To evaluate the predictive value of markers of placental insufficiency and fetal growth restriction for a composite adverse perinatal outcome (CAPO) in a small-for-gestational-age (SGA) population. We also aimed to identify profiles that discriminate fetuses as low or high risk for CAPO, and to evaluate the association of onset of labor and mode of birth with CAPO.

METHODS

This was a preplanned post-hoc analysis of the DRIGITAT study, a Dutch multicenter cohort study of management strategy in 690 singleton SGA pregnancies at 32.0-36.9 weeks' gestation, between 2018 and 2022. We used data from 440 participants with available biomarker measurements, who were not randomized for immediate birth before 36 weeks' gestation on the basis of recurrent abnormal Doppler velocimetry. We defined CAPO as fetal death, adverse condition at birth, major neonatal morbidity and/or neonatal mortality. We analyzed the predictive value for CAPO of maternal body mass index (BMI), gestational age, estimated fetal weight (EFW) and soluble fms-like tyrosine kinase-1 to placental growth factor ratio (sFlt-1/PlGF ratio) at inclusion, development of pre-eclampsia, highest value of the umbilicocerebral ratio (UCR) and fetal growth velocity. We also used these variables to develop a prediction model for CAPO using forward stepwise logistic regression to emulate real-world clinical evaluation.

RESULTS

In this population of 440 singleton SGA pregnancies, maternal BMI at inclusion (P = 0.02), gestational age at inclusion (P ≤ 0.001), EFW at inclusion (P ≤ 0.001), sFlt-1/PlGF ratio at inclusion (P ≤ 0.001), development of pre-eclampsia (P ≤ 0.001), highest value of the UCR measured at any time during pregnancy (P ≤ 0.001) and fetal growth velocity (P ≤ 0.001) were all associated significantly with CAPO. When combined into a prediction model using logistic regression analysis, maternal BMI at inclusion, gestational age at inclusion, development of pre-eclampsia and fetal growth velocity did not add to the predictive value of the model, because of their correlation with other variables. The area under the receiver-operating-characteristics curve of the final prediction model, comprising EFW at inclusion, sFlt-1/PlGF ratio at inclusion and the highest UCR value at any time, was 0.75 (95% CI, 0.70-0.81). At false-positive rates of 5%, 10% and 25%, the sensitivities of the prediction model for CAPO were 35.6%, 44.2% and 63.5%, respectively. The median gestational age at birth and birth weight were lower in neonates that experienced CAPO compared with those that did not (37.0 weeks vs 38.3 weeks and 1.993 kg vs 2.518 kg, respectively). Vaginal birth occurred in 69.3% of our population. In the group that experienced CAPO, a higher number of (emergency) Cesarean sections were performed.

CONCLUSIONS

In a SGA population, maternal BMI, gestational age, EFW and sFlt-1/PlGF ratio at inclusion, highest UCR at any time, development of pre-eclampsia and fetal growth velocity were associated with CAPO. A model incorporating EFW at inclusion, sFlt-1/PlGF ratio at inclusion and highest UCR was most effective for the prediction of CAPO. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.