Suppr超能文献

握力、行走速度与心血管疾病风险预测:来自 406834 名英国生物库参与者的研究

Grip Strength and Walking Pace and Cardiovascular Disease Risk Prediction in 406,834 UK Biobank Participants.

机构信息

Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK.

Institute of Health and Wellbeing, University of Glasgow, UK.

出版信息

Mayo Clin Proc. 2020 May;95(5):879-888. doi: 10.1016/j.mayocp.2019.12.032. Epub 2020 Apr 13.

Abstract

OBJECTIVE

To investigate whether the addition of grip strength and/or self-reported walking pace to established cardiovascular disease (CVD) risk scores improves their predictive abilities.

PATIENTS AND METHODS

A total of 406,834 participants from the UK Biobank, with baseline measurements between March 13, 2006, and October 1, 2010, without CVD at baseline were included in this study. Associations of grip strength and walking pace with CVD outcomes were investigated using Cox models adjusting for classical risk factors (as included in established risk scores), and predictive utility was determined by changes in C-index and categorical net reclassification index.

RESULTS

Over a median of 8.87 years of follow-up (interquartile range 3, 8.25-9.47 years), there were 7274 composite fatal/nonfatal events (on the basis of the American College of Cardiology/American Heart Association [ACC/AHA] outcome) and 1955 fatal events (on the basis of the Systematic Coronary Risk Evaluation [SCORE] risk score). Both grip strength and walking pace were inversely associated with CVD outcomes after adjusting for classical risk factors. Addition of grip strength (change in C-index: ACC/AHA, +0.0017; SCORE, +0.0047), usual walking pace (ACC/AHA, +0.0031; SCORE, +0.0130), and both combined (ACC/AHA, +0.0041; SCORE, +0.0148) improved the C-index and also improved the net reclassification index (grip, +0.55%; walking pace, +0.53%; combined, 1.12%).

CONCLUSION

The present study has found that the addition of grip strength or usual walking pace to existing risk scores results in improved CVD risk prediction, with an additive effect when both are added. As both these measures are cheap and easy to administer, these tools could provide an important addition to CVD risk screening, although further external validation is required.

摘要

目的

探究在已建立的心血管疾病(CVD)风险评分中加入握力和/或自我报告的步行速度是否能提高其预测能力。

方法

本研究共纳入了 406834 名来自英国生物库的参与者,这些参与者在 2006 年 3 月 13 日至 2010 年 10 月 1 日期间基线测量时没有 CVD。使用 Cox 模型研究握力和步行速度与 CVD 结局的关系,调整了经典风险因素(包含在已建立的风险评分中),并通过 C 指数和分类净重新分类指数的变化来确定预测效用。

结果

在中位 8.87 年的随访期间(四分位距 3,8.25-9.47 年),有 7274 例复合性致命/非致命事件(基于美国心脏病学会/美国心脏协会 [ACC/AHA] 结局)和 1955 例致命事件(基于系统性冠状动脉风险评估 [SCORE] 风险评分)。在调整了经典风险因素后,握力和步行速度均与 CVD 结局呈负相关。加入握力(ACC/AHA,C 指数变化+0.0017;SCORE,C 指数变化+0.0047)、通常的步行速度(ACC/AHA,C 指数变化+0.0031;SCORE,C 指数变化+0.0130)以及两者的组合(ACC/AHA,C 指数变化+0.0041;SCORE,C 指数变化+0.0148)均能提高 C 指数,并提高净重新分类指数(握力,+0.55%;步行速度,+0.53%;两者的组合,+1.12%)。

结论

本研究发现,在现有的风险评分中加入握力或通常的步行速度可以提高 CVD 风险预测,并且当两者都加入时会产生附加效应。由于这两种方法都很便宜且易于实施,因此这些工具可能为 CVD 风险筛查提供重要补充,尽管还需要进一步的外部验证。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验