Development and Internal Validation of a Model Predicting Premature Cardiovascular Disease Among Women With Hypertensive Disorders of Pregnancy: A Population‐Based Study in Quebec, Canada

Abstract

Background Hypertensive disorders of pregnancy (HDP) are associated with an increased risk of premature cardiovascular disease (CVD), but existing cardiovascular prediction models do not adequately capture risks in young women. We developed a model to predict the 10‐year risk of premature CVD and mortality among women who have HDP. Methods and Results Using a population‐based cohort of women with HDP who delivered between April 1989 and March 2017 in Quebec, Canada, we developed a 10‐year CVD risk model using Cox proportional hazards regression. Women aged 18 to 45 years were followed from their first HDP‐complicated delivery until March 2018. We assessed performance of the model based on discrimination, calibration, and risk stratification ability. Internal validity was assessed using the bootstrap method. The cohort included 95 537 women who contributed 1 401 084 person‐years follow‐up. In total, 4024 (4.2%) of women were hospitalized for CVD, of which 1585 events (1.6%) occurred within 10 years of follow‐up. The final model had modest discriminatory performance (area under the receiver operating characteristic curve, 0.66; 95% CI, 0.65–0.67) and good calibration with slope of 0.95 and intercept of −0.19. There was moderate classification accuracy (likelihood ratio+: 5.90; 95% CI, 5.01–6.95) in the highest‐risk group upon risk stratification. Conclusions Overall, our model had modest performance in predicting the 10‐year risk of premature CVD for women with HDP. We recommend the addition of clinical variables, and external validation, before consideration for clinical use.

Keywords

• cardiovascular
• prediction modeling
• preeclampsia
• pregnancy hypertension
• prognosis