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基于自我报告的体力活动水平评估美国心脏协会/美国心脏病学会合并队列方程对动脉粥样硬化性心血管疾病风险的表现。

Performance of the American Heart Association/American College of Cardiology Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Self-reported Physical Activity Levels.

机构信息

Division of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas.

Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.

出版信息

JAMA Cardiol. 2021 Jun 1;6(6):690-696. doi: 10.1001/jamacardio.2021.0948.

Abstract

IMPORTANCE

The American Heart Association/American College of Cardiology pooled cohort equations (PCEs) are used for predicting 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Pooled cohort equation risk prediction capabilities across self-reported leisure-time physical activity (LTPA) levels and the change in model performance with addition of LTPA to the PCE are unclear.

OBJECTIVE

To evaluate PCE risk prediction performance across self-reported LTPA levels and the change in model performance by adding LTPA to the existing PCE model.

DESIGN, SETTING, AND PARTICIPANTS: Individual-level pooling of data from 3 longitudinal cohort studies-Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Cardiovascular Health Study-was performed. A total of 18 824 participants were stratified into 4 groups based on self-reported LTPA levels: inactive (0 metabolic equivalent of task [MET]-min/wk), less than guideline-recommended (<500 MET-min/wk), guideline-recommended (500-1000 MET-min/week), and greater than guideline-recommended (>1000 MET-min/wk). Pooled cohort equation risk discrimination was studied using the C statistic and reclassification capabilities were studied using the Greenwood Nam-D'Agostino χ2 goodness-of-fit test. Change in risk discrimination and reclassification on adding LTPA to PCEs was evaluated using change in C statistic, integrated discrimination index, and categorical net reclassification index.

MAIN OUTCOMES AND MEASURES

Adjudicated ASCVD events during 10-year follow-up.

RESULTS

Among 18 824 participants studied, 10 302 were women (54.7%); mean (SD) age was 57.6 (8.2) years. A total of 5868 participants (31.2%) were inactive, 3849 (20.4%) had less than guideline-recommended LTPA, 3372 (17.9%) had guideline-recommended LTPA, and 5735 (30.5%) had greater than guideline-recommended LTPA level. Higher LTPA levels were associated with a lower risk of ASCVD after adjustment for risk factors (hazard ratio [HR] per 1-SD higher LTPA, 0.91; 95% CI, 0.86-0.96). Across LTPA groups, PCE risk discrimination (C statistic, 0.76-0.78) and risk calibration (all χ2 P > .10) was similar. Addition of LTPA to the PCE model resulted in no significant change in the C statistic (0.0005; 95% CI, -0.0004 to 0.0015; P = .28) and categorical net reclassification index (-0.003; 95% CI, -0.010 to 0.010; P = .95), but a minimal improvement in the integrated discrimination index (0.0008; 95% CI, 0.0002-0.0013; P = .005) was observed. Similar results were noted when cohort-specific coefficients were used for creating the baseline model.

CONCLUSIONS AND RELEVANCE

Higher self-reported LTPA levels appear to be associated with lower ASCVD risk and increasing LTPA promotes cardiovascular wellness. These findings suggest the American Heart Association/American College of Cardiology PCEs are accurate at estimating the probability of 10-year ASCVD risk regardless of LTPA level. The addition of self-reported LTPA to PCEs does not appear to be associated with improvement in risk prediction model performance.

摘要

重要性

美国心脏协会/美国心脏病学会的汇总队列方程(PCE)用于预测 10 年动脉粥样硬化性心血管疾病(ASCVD)风险。目前尚不清楚 PCE 风险预测能力在自我报告的闲暇时间体力活动(LTPA)水平上的差异,以及在 PCE 中加入 LTPA 后模型性能的变化。

目的

评估 PCE 风险预测性能在自我报告的 LTPA 水平上的差异,以及通过将 LTPA 添加到现有 PCE 模型中对模型性能的变化。

设计、地点和参与者:对来自 3 项纵向队列研究(社区动脉粥样硬化风险研究、多民族动脉粥样硬化研究和心血管健康研究)的数据进行个体水平汇总。共有 18824 名参与者根据自我报告的 LTPA 水平分为 4 组:不活动(0 代谢当量任务[MET]-min/wk)、低于指南推荐量(<500 MET-min/wk)、指南推荐量(500-1000 MET-min/week)和高于指南推荐量(>1000 MET-min/wk)。使用 C 统计量研究 PCE 风险区分能力,使用 Greenwood-Nam-D'Agostino χ2 拟合优度检验研究再分类能力。通过 C 统计量、综合鉴别指数和分类净再分类指数的变化评估在 PCE 中添加 LTPA 对风险区分和再分类的变化。

主要结局和测量

10 年随访期间的 ASCVD 事件。

结果

在 18824 名参与者中,有 10302 名女性(54.7%);平均(SD)年龄为 57.6(8.2)岁。共有 5868 名参与者(31.2%)不活动,3849 名(20.4%)的 LTPA 低于指南推荐量,3372 名(17.9%)的 LTPA 符合指南推荐量,5735 名(30.5%)的 LTPA 超过了指南推荐量。在调整了危险因素后,较高的 LTPA 水平与 ASCVD 风险降低相关(每 1-SD 更高 LTPA 的 HR,0.91;95%CI,0.86-0.96)。在 LTPA 组中,PCE 风险区分(C 统计量,0.76-0.78)和风险校准(所有 χ2 P 值均>0.10)相似。在 PCE 模型中加入 LTPA 后,C 统计量没有显著变化(0.0005;95%CI,-0.0004 至 0.0015;P=0.28)和分类净再分类指数(-0.003;95%CI,-0.010 至 0.010;P=0.95),但综合鉴别指数略有改善(0.0008;95%CI,0.0002-0.0013;P=0.005)。当使用队列特定系数为基线模型创建时,也观察到了类似的结果。

结论和相关性

较高的自我报告的 LTPA 水平似乎与较低的 ASCVD 风险相关,而增加 LTPA 则促进心血管健康。这些发现表明,美国心脏协会/美国心脏病学会的 PCE 能够准确估计 10 年 ASCVD 风险的概率,无论 LTPA 水平如何。在 PCE 中加入自我报告的 LTPA 似乎不会改善风险预测模型的性能。

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