A prediction model for stillbirth based on first trimester pre‐eclampsia combined screening

Abstract

AbstractObjectiveTo evaluate the accuracy of combined models of maternal biophysical factors, ultrasound, and biochemical markers for predicting stillbirths.MethodsA retrospective cohort study of pregnant women undergoing first‐trimester pre‐eclampsia screening at 11–13 gestational weeks was conducted. Maternal characteristics and history, mean arterial pressure (MAP) measurement, uterine artery pulsatility index (UtA‐PI) ultrasound, maternal ophthalmic peak ratio Doppler, and placental growth factor (PlGF) serum were collected during the visit. Stillbirth was classified as placental dysfunction‐related when it occurred with pre‐eclampsia or birth weight <10th percentile. Combined prediction models were developed from significant variables in stillbirths, placental dysfunction‐related, and controls. We used the area under the receiver‐operating‐characteristics curve (AUC), sensitivity, and specificity based on a specific cutoff to evaluate the model's predictive performance by measuring the capacity to distinguish between stillbirths and live births.ResultsThere were 13 (0.79%) cases of stillbirth in 1643 women included in the analysis. The combination of maternal factors, MAP, UtA‐PI, and PlGF, significantly contributed to the prediction of stillbirth. This model was a good predictor for all (including controls) types of stillbirth (AUC 0.879, 95% CI: 0.799–0.959, sensitivity of 99.3%, specificity of 38.5%), and an excellent predictor for placental dysfunction‐related stillbirth (AUC 0.984, 95% CI: 0.960–1.000, sensitivity of 98.5, specificity of 85.7).ConclusionScreening at 11–13 weeks' gestation by combining maternal factors, MAP, UtA‐PI, and PlGF, can predict a high proportion of stillbirths. Our model has good accuracy for predicting stillbirths, predominantly placental dysfunction‐related stillbirths.