First Trimester Ultrasound Biomarkers for Predicting Preeclampsia: A Prospective Cohort Study in Surabaya, Indonesia

Abstract

Introduction: Preeclampsia (PE) remains a leading cause of maternal and perinatal morbidity and mortality worldwide, particularly in developing countries like Indonesia. Early identification of high-risk women is crucial for timely intervention. This study aimed to evaluate the predictive performance of first-trimester ultrasound biomarkers, specifically uterine artery pulsatility index (UtA-PI) and mean arterial pressure (MAP), combined with maternal characteristics, for predicting PE in a cohort of pregnant women in Surabaya, Indonesia.

Methods: This prospective cohort study enrolled pregnant women attending their first-trimester antenatal care visit at Private Hospital, Surabaya, between January 2022 and December 2023. Inclusion criteria were singleton pregnancies, gestational age between 11 and 13 weeks 6 days, and availability of complete follow-up data until delivery. Maternal characteristics (age, body mass index, parity, smoking history, family history of PE) were recorded. UtA-PI was measured using transabdominal Doppler ultrasound, and MAP was calculated from blood pressure measurements. The primary outcome was the development of PE, defined according to the International Society for the Study of Hypertension in Pregnancy (ISSHP) criteria. Logistic regression analysis was used to develop a prediction model, and its performance was assessed using receiver operating characteristic (ROC) curves and area under the curve (AUC).

Results: A total of 850 pregnant women were included in the final analysis. The incidence of PE was 8.2% (n=70). The prediction model incorporating maternal age, BMI, prior history of PE, UtA-PI, and MAP demonstrated good predictive performance for overall PE (AUC = 0.85; 95% CI, 0.81-0.89). For early-onset PE (delivery <34 weeks), the AUC was 0.92 (95% CI, 0.87-0.97), and for late-onset PE (delivery ≥34 weeks), the AUC was 0.78 (95% CI, 0.73-0.83). UtA-PI and MAP were significant independent predictors of PE (p<0.001). A risk score was developed, with a cut-off value showing a sensitivity of 80% and specificity of 75% for overall PE.

Conclusion: The combination of maternal characteristics, UtA-PI, and MAP in the first trimester provides a valuable tool for predicting PE in an Indonesian population. This model demonstrates particularly strong performance for predicting early-onset PE, which is associated with greater maternal and fetal morbidity. Early identification of high-risk women allows for targeted surveillance and potential preventative strategies.