Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA.
Eur Heart J. 2019 Apr 7;40(14):1113-1120. doi: 10.1093/eurheartj/ehy863.
To evaluate whether history of pregnancy complications [pre-eclampsia, gestational hypertension, preterm delivery, or small for gestational age (SGA)] improves risk prediction for cardiovascular disease (CVD).
This population-based, prospective cohort study linked data from the HUNT Study, Medical Birth Registry of Norway, validated hospital records, and Norwegian Cause of Death Registry. Using an established CVD risk prediction model (NORRISK 2), we predicted 10-year risk of CVD (non-fatal myocardial infarction, fatal coronary heart disease, and non-fatal or fatal stroke) based on established risk factors (age, systolic blood pressure, total and HDL-cholesterol, smoking, anti-hypertensives, and family history of myocardial infarction). We evaluated whether adding pregnancy complication history improved model fit, calibration, discrimination, and reclassification. Among 18 231 women who were parous, ≥40 years of age, and CVD-free at start of follow-up, 39% had any pregnancy complication history and 5% experienced a CVD event during a median follow-up of 8.2 years. While pre-eclampsia and SGA were associated with CVD in unadjusted models (HR 1.96, 95% CI 1.44-2.65 for pre-eclampsia and HR 1.46, 95% CI 1.18-1.81 for SGA), only pre-eclampsia remained associated with CVD after adjusting for established risk factors (HR 1.60, 95% CI 1.16-2.17). Adding pregnancy complication history to the established prediction model led to small improvements in discrimination (C-index difference 0.004, 95% CI 0.002-0.006) and reclassification (net reclassification improvement 0.02, 95% CI 0.002-0.05).
Pre-eclampsia independently predicted CVD after controlling for established risk factors; however, adding pre-eclampsia, gestational hypertension, preterm delivery, and SGA made only small improvements to CVD prediction among this representative sample of parous Norwegian women.
评估妊娠并发症史（子痫前期、妊娠期高血压、早产或胎儿生长受限（SGA））是否能提高心血管疾病（CVD）的风险预测能力。
本研究基于人群的前瞻性队列研究，将来自 HUNT 研究、挪威医学出生登记处、经过验证的医院记录和挪威死因登记处的数据进行了关联。使用已建立的 CVD 风险预测模型（NORRISK 2），我们根据既定的风险因素（年龄、收缩压、总胆固醇和高密度脂蛋白胆固醇、吸烟、抗高血压药物和心肌梗死家族史），预测 10 年 CVD（非致命性心肌梗死、致命性冠心病和非致命性或致命性中风）的风险。我们评估了添加妊娠并发症史是否能改善模型拟合度、校准度、区分度和再分类能力。在 18231 名≥40 岁、初诊时无 CVD 的经产妇中，39%有妊娠并发症史，5%在中位随访 8.2 年后发生 CVD 事件。虽然在未校正模型中，子痫前期和 SGA 与 CVD 相关（子痫前期的 HR 为 1.96，95%CI 为 1.44-2.65，SGA 的 HR 为 1.46，95%CI 为 1.18-1.81），但在校正了既定风险因素后，只有子痫前期与 CVD 相关（HR 为 1.60，95%CI 为 1.16-2.17）。将妊娠并发症史添加到既定预测模型中，仅能略微提高区分度（C 指数差异 0.004，95%CI 0.002-0.006）和再分类（净再分类改善 0.02，95%CI 0.002-0.05）。
在校正既定风险因素后，子痫前期独立预测 CVD；然而，在这个有代表性的挪威经产妇样本中，添加子痫前期、妊娠期高血压、早产和 SGA 仅能对 CVD 预测有微小的改善。
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