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基于体力活动队列预测心血管或脑血管疾病风险:亚太地区(APAC)研究结果

Predicting risk on cardiovascular or cerebrovascular disease based on a physical activity cohort: Results from APAC study.

作者信息

Zhao Juan, Yu Ye, Zhu Xiaolan, Xie Yuling, Ai Songwei, Lehmann H Immo, Deng Xuan, Hu Feifei, Li Guoping, Zhou Yong, Xiao Junjie

机构信息

Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Medicine Shanghai University Nantong China.

Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Life Science Shanghai University Shanghai China.

出版信息

MedComm (2020). 2023 Mar 10;4(2):e220. doi: 10.1002/mco2.220. eCollection 2023 Apr.

Abstract

Commonly used prediction models have been primarily constructed without taking physical activity into account. Using the Kailuan physical activity cohorts from Asymptomatic Polyvascular Abnormalities in Community (APAC) study, we developed a 9-year cardiovascular or cerebrovascular disease (CVD) risk prediction equation. Participants in this study were included from APAC cohort, which included 5440 participants from the Kailuan cohort in China. Cox proportional hazard regression model was applied to construct sex-specific risk prediction equations for the physical activity cohort (PA equation). Proposed equations were compared with the 10-year risk prediction model, which is developed for atherosclerotic cardiovascular disease risk in Chinese cohorts (China-PAR equation). statistics of PA equations were 0.755 (95% confidence interval, 0.750-0.758) for men and 0.801 (95% confidence interval, 0.790-0.813) for women. The estimated area under the receiver operating characteristic curves in the validation set shows that the PA equations perform as good as the China-PAR. From calibration among four categories of predicted risks, the predicted risk rates by PA equations were almost identical to the Kaplan-Meier observed rates. Therefore, our developed sex-specific PA equations have effective performance for predicting CVD for physically active cohorts in the physical activity cohort in Kailuan.

摘要

常用的预测模型主要是在未考虑身体活动的情况下构建的。利用社区无症状多血管异常(APAC)研究中的开滦身体活动队列,我们开发了一个9年心血管或脑血管疾病(CVD)风险预测方程。本研究的参与者来自APAC队列,该队列包括来自中国开滦队列的5440名参与者。应用Cox比例风险回归模型为身体活动队列构建性别特异性风险预测方程(PA方程)。将提出的方程与为中国队列中的动脉粥样硬化性心血管疾病风险开发的10年风险预测模型(China-PAR方程)进行比较。PA方程的统计数据男性为0.755(95%置信区间,0.750 - 0.758),女性为0.801(95%置信区间,0.790 - 0.813)。验证集中受试者工作特征曲线下的估计面积表明,PA方程的表现与China-PAR相当。从四类预测风险的校准来看,PA方程的预测风险率与Kaplan-Meier观察率几乎相同。因此,我们开发的性别特异性PA方程在预测开滦身体活动队列中身体活跃人群的CVD方面具有有效性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5d8/9999708/4d9d9eea2122/MCO2-4-e220-g002.jpg

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