PREDICTIVE MODEL FOR HYPERTENSIVE DISORDERS IN PREGNANCY: A CROSS-SECTIONAL STUDY FROM A MATERNAL HOSPITAL, TASHKENT

Abstract

Background: Hypertensive disorders of pregnancy (HDP) account for significant maternal and neonatal morbidity and mortality, particularly in the low-resource setting. Detection of high-risk pregnancies early on is very important. Objective: To identify independent clinical predictors and develop a predictive model for hypertensive disorders of pregnancy. Methods: Cross-sectional study was done among 58 pregnant women at Maternity Hospital No. 3, Tashkent. Thirty participants were with HDP. Collected data included BMI, family history of hypertension, chronic hypertension, history of preeclampsia, anemia, diabetes mellitus, and maternal age. Bivariate and multivariate logistic regression analyses were used. Results: Obesity (BMI ≥30), history of familial hypertension, chronic hypertension, preeclampsia history, and diabetes mellitus were independent predictors of HDP. The good discriminatory capacity of the final model was 81% (accuracy) and 0.81 (AUC). The age of the mother was not an independent predictor due to the quite young population involved in the study. Conclusion: Five clinical predictors are capable of distinguishing women at risk for HDP: BMI, chronic hypertension, family history, diabetes, and prior preeclampsia. The model can help clinicians by utilizing early screening and prophylactic treatment.