Early Pregnancy Blood Pressure Trajectories Predict Preeclampsia and Gestational Hypertension Among Low Risk Pregnancies

Abstract

Develop and validate a prediction model for risk of preeclampsia (PE) and gestational hypertension (GH) using early pregnancy blood pressure (BP) patterns plus risk factors (RF) routinely available in clinical settings among low and moderate risk pregnancies. Retrospective cohort of 249,892 low or moderate risk singleton pregnancies delivered at Kaiser Permanente Northern California hospitals in 2009-2019. Electronic health records excluded prior hypertension, heart, kidney or liver disease and history of PE. All BPs were < 140/90 at < 20 weeks gestation. Data were randomly divided into a training dataset (N=174,925;70%) for model development and a validation dataset (n=74,967;30%). We used group-based trajectory modeling of longitudinal clinical systolic BPs to identify early pregnancy BP trajectory (BPT) groups < 20 weeks. We fit multinomial logistic regression models to predict early PE (< 34 weeks), late PE (≥34 weeks) and GH including BPT alone or with multiple RF (BMI, parity, age, race/ethnicity, diabetes) vs. an initial BP alone or with other RF. C-statistics generated from the validation dataset evaluated model predictive performance. The sample of 249,892 low to moderate risk individuals had mean (SD) maternal age of 30.9 y (5.3), BMI of 26.0 kg/m2 (5.8), 57% were nulliparous, and 63% were from Black, Hispanic, or Asian groups, and 100% had all normal BPs < 20 weeks. Overall, 992 (0.4%) developed early PE, 10,612 (4.3%) late PE, and 10,854 (4.3%) GH. BPT group models performed much better (C-statistic:0.664-0.732) than models with initial BP only (0.630-0.700), multiple RF alone, or in combination (Table 1). The best model performance (0.729-0.768) to predict early PE, late PE and GH included BPT groups plus BMI, parity, age, race/ethnicity, and diabetes. Six BP patterns plus RF available in routine clinical care improved prediction of early and late PE, and GH in lower risk pregnancies. Our findings show promise to guide surveillance and strategies to distinguish risk among ostensibly low risk groups.