| アブストラクト | BACKGROUND: Currently available risk scores for cardiovascular disease (CVD) were developed in older populations and do not incorporate sex-specific factors, which limits their ability to provide accurate estimates in younger women. OBJECTIVES: The objective of the study was to develop and validate a prognostic model, including female-specific risk factors, that can identify women at high risk. METHODS: We created a cohort of 262,891 women aged 15 to 45 years with 1 randomly selected delivery from 1999 to 2017 in the Clinical Practice Research Datalink database to develop models for screening women within the first-year postpartum. The primary outcome was incident CVD. The least absolute shrinkage and selection operator method and an accelerated failure time Weibull model were used to determine the inclusion of predictors and to estimate the final model. Internal validation via bootstrapping was used to estimate the optimism-corrected measures of model performance. RESULTS: A total of 943 women (0.81 per 1,000 person-years) experienced a cardiovascular event over a median follow-up of 3.8 years (Q1-Q3 1.5-7.9). Predictors in the final model included traditional CVD risk factors, along with social deprivation, polycystic ovary syndrome, prior use of oral contraceptives, depression, thyroid disorders, hypertensive disorders of pregnancy, gestational diabetes, preterm birth, small-for-gestational-age birthweight, parity, and history of pregnancy complications. Optimism-corrected performance median (Q1-Q3) measures showed modest discrimination (C-statistic: 0.637 [0.623-0.650]) and good calibration (slope: 0.919 [0.905-0.930]). CONCLUSIONS: Although the model showed modest predictive accuracy and performance, the findings highlight the importance of sex-specific risk factors for identifying women at high risk of CVD in the postpartum period. |
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| 組織名 | Child Health Evaluative Sciences Program, The Hospital for Sick Children,;Toronto, Ontario, Canada; Division of Epidemiology, Dalla Lana School of Public;Health, University of Toronto, Toronto, Ontario, Canada. Electronic address:;sonia.grandi@sickkids.ca.;Department of Epidemiology, Biostatistics, and Occupational Health, McGill;University, Montreal, Quebec, Canada; Centre for Clinical Epidemiology, Lady;Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada; Department of;Medicine, McGill University, Montreal, Quebec, Canada.;Department of Obstetrics and Gynaecology, Faculty of Medicine, University of;British Columbia, British Columbia, Canada.;Department of Obstetrics and Gynaecology, School of Medicine, Queen's University,;Kingston, Ontario, Canada.;Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada; McGill;University Health Center Research Institute, Montreal, Quebec, Canada; Department;of Pediatrics, McGill University, Montreal, Quebec, Canada. |
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