Chen Shiyuan, Yuan Xiaoxia, Zhu Wei
Naval Medical Center, Naval Medical University, No. 880 Xiangyin Road, Yangpu District, Shanghai, 200433, China.
Acta Diabetol. 2025 Mar;62(3):405-421. doi: 10.1007/s00592-024-02369-z. Epub 2024 Nov 7.
Given the notable rise in the prevalence of metabolic syndrome (MS) in China, it is urgent to identify early screening indicators. Extensive dose-response meta-analyses have been conducted to investigate the association between resting heart rate (RHR) and MS, and additional relevant studies have been updated in the last five years. Therefore, this paper aims to update the results of previous meta-analyses.
PubMed, Cochrane Library, Web of Science, and Embase databases were searched from the inception to 25th May 2023. Additional relevant references were manually screened. Quality assessment was performed independently by authors using the Newcastle-Ottawa Scale. Stata 15.0 software was applied for data analysis. A random-effects model was adopted to pool the effect size of hazard ratio (HR) and 95% confidence interval (CI). A restricted cubic spline function was utilized to assess dose-response relationships. The protocol was prospectively registered in PROSPERO (number CRD42023458979). 35 studies from 21 reports were included, with 433,365 adults and 84,354 events of MS and/or diabetes mellitus. The highest RHR tertile was positively associated with the risk of MS [HR = 1.80, 95% CI (1.60, 2.04)]. Dose-response analysis suggested a non-linear correlation between RHR and MS, with a 3.5% increase in risk per unit increase in RHR, at a RHR of 42.5.
Both high RHR and its increasing rate are significantly associated with the risk of MS. Therefore, RHR might be a non-invasive and convenient community-based screening tool for the management and monitoring of MS.
鉴于中国代谢综合征(MS)患病率显著上升,识别早期筛查指标迫在眉睫。已开展大量剂量反应荟萃分析来研究静息心率(RHR)与MS之间的关联,且过去五年有更多相关研究更新。因此,本文旨在更新先前荟萃分析的结果。
检索了PubMed、Cochrane图书馆、Web of Science和Embase数据库,时间跨度从建库至2023年5月25日。人工筛选了其他相关参考文献。作者使用纽卡斯尔-渥太华量表独立进行质量评估。应用Stata 15.0软件进行数据分析。采用随机效应模型汇总风险比(HR)的效应量和95%置信区间(CI)。利用受限立方样条函数评估剂量反应关系。该方案已在PROSPERO(注册号CRD42023458979)进行前瞻性注册。纳入了来自21篇报告的35项研究,涉及433365名成年人以及84354例MS和/或糖尿病事件。RHR最高三分位数与MS风险呈正相关[HR = 1.80,95%CI(1.60,2.04)]。剂量反应分析表明RHR与MS之间存在非线性相关性,在RHR为42.5时,RHR每增加一个单位,风险增加3.5%。
高RHR及其上升速率均与MS风险显著相关。因此,RHR可能是一种用于MS管理和监测的非侵入性且便捷的基于社区的筛查工具。