The predictive value of early pregnancy markers for the risk of preeclampsia in women with twin pregnancies

Background Predicting pre-eclampsia (PE) risk in twin pregnancies enables timely intervention and disease management. We developed a predictive model integrating baseline characteristics, uterine artery pulsatility index (UtA-PI), and serum biomarkers (uE3, AFP, inhibin A) to identify high-risk patients for early intervention. Methods This prospective cohort study enrolled 339 twin pregnancies receiving antenatal care at a tertiary hospital (January 2019–March 2024). Serum AFP, uE3, inhibin-A levels, and bilateral UtA-PI were measured at 11–16 weeks’ gestation. A nomogram prediction model for PE risk was constructed. Results PE was diagnosed in 43 of 339 women (incidence: 12.68%; 95% CI: 9.12–16.25%). Six variables met inclusion criteria (P < 0.10 in univariate/multivariate analyses): IVF conception, pre-pregnancy BMI, right UtA-PI, serum inhibin A, serum uE3, and chorionicity. The model identified lower pre-pregnancy BMI, elevated right UtA-PI, and dysregulated serum biomarkers (uE3, inhibin A) as key predictors of PE. The nomogram demonstrated moderate discriminative ability (C-index: 0.74; 95% CI: 0.67–0.81). Calibration curves indicated excellent agreement between predicted and observed risk, while decision and clinical impact curves confirmed clinical utility. Conclusions Integrating IVF status, chorionicity, early-pregnancy serum biomarkers (inhibin A, uE3), and right UtA-PI effectively predicts PE risk in twin pregnancies.