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Home Blood Pressure Variability Risk Prediction Score for Cardiovascular Disease Using Data From the J-HOP Study

医学 血压 内科学 弗雷明翰风险评分 体质指数 早晨 比例危险模型 冲程(发动机) 糖尿病 心脏病学 傍晚 疾病 内分泌学 机械工程 物理 天文 工程类
作者
Kazuomi Kario,Hiroshi Kanegae,Yukie Okawara,Naoko Tomitani,Satoshi Hoshide
出处
期刊:Hypertension [Ovid Technologies (Wolters Kluwer)]
被引量:3
标识
DOI:10.1161/hypertensionaha.124.23397
摘要

BACKGROUND: Home blood pressure (BP) is more closely associated with cardiovascular event risk than office BP, but cardiovascular risk prediction based on home BP variability is lacking. This study developed a simple cardiovascular event prediction score, including home BP variability data, from the J-HOP study (Japan Morning Surge-Home Blood Pressure). METHODS: The J-HOP study extended follow-up from December 2017 to May 2018 generated the study data set (4231 patients). Cardiovascular events included fatal/nonfatal stroke (n=94), coronary heart disease (n=124), heart failure (n=42), and aortic dissection (n=8). Cox proportional hazards models were used to predict overall cardiovascular risk. Potential covariates included age, sex, body mass index, smoking, history of diabetes, statin use, history of cardiovascular disease, total cholesterol:high-density lipoprotein cholesterol ratio, office systolic BP (SBP), mean of morning-evening average (MEave), home SBP, and average real variability of MEave home SBP. A risk score and models were constructed, and model performance was assessed. RESULTS: Model performance was best when average real variability of MEave SBP was included (C statistic, 0.760). The risk score assigns points for age (5-year bands), sex, cardiovascular disease history, high-density lipoprotein cholesterol, mean MEave home SBP, and average real variability of MEave home SBP. Estimated 10-year cardiovascular risk ranged from ≤0.6% (score ≤0) to >32% (score ≥26). Calibration 2 statistics values for the model (2.66) and risk score (5.29) indicated excellent goodness of fit. CONCLUSIONS: This simple cardiovascular disease prediction algorithm, including day-by-day home BP variability, could be used as part of a home BP–centered approach to hypertension management in clinical practice.

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