Development of a Triage Tool for Stratification and Referral of Women at Risk of Preeclampsia in Low‐Resource Antenatal Settings: A Prospective Cohort Study

ABSTRACT Background and Aims Preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality globally, with high incidence and case fatality rates in low‐ and middle‐income countries (LMICs). Early identification of at‐risk women is critical, yet many predictive models require laboratory or imaging resources that are unavailable in resource‐limited settings. This study aimed to develop a points‐based clinical triage tool for preeclampsia risk stratification using routinely collected antenatal care (ANC) data. Methods A prospective cohort study of 703 pregnant women attending ANC was conducted, with retrospective extraction of baseline clinical data. Maternal sociodemographic characteristics, obstetric history, blood pressure (BP) measurements, and proteinuria screening results were analysed. Multivariable logistic regression was used to identify independent predictors of preeclampsia, and model performance was evaluated using discrimination, calibration, and internal bootstrapping. A weighted scoring system was derived from regression coefficients, and receiver operating characteristic (ROC) analysis was used to determine optimal cut‐off values for risk stratification. Results A five‐component clinical triage tool for risk stratification of preeclampsia was developed. The tool incorporates maternal age (≥ 35 years), nulliparity, elevated blood pressure (≥ 140/90 mmHg), family history of preeclampsia, and dipstick proteinuria (≥ + 1), generating a total risk score ranging from 0 to 18. Based on the risk score, women were categorised into low risk (0–10 points), moderate risk (11–15 points), and high risk (≥ 16 points) groups. The incidence of preeclampsia increased across these categories, from 5.1% in the low‐risk group to 30.2% among women classified as high risk. At the high‐risk threshold (≥ 16 points), the tool demonstrated good discriminatory performance (AUC = 0.83), with a sensitivity of 78.3% and a specificity of 83.3% for identifying women who subsequently developed preeclampsia. Conclusion This study demonstrates that a simple, points‐based clinical triage tool using routinely collected antenatal data has potential for stratifying preeclampsia risk.