Resting Heart Rate Trajectory Pattern Predicts Arterial Stiffness in a Community-Based Chinese Cohort.
Resting Heart Rate Trajectory Pattern Predicts Arterial Stiffness in a Community-Based Chinese Cohort.
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静息心率轨迹模式可以预测基于社区的中国队列中的动脉僵硬。
DOI：
10.1161/atvbaha.116.308674
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发表时间：
2017-02
期刊：
影响因子：
--
通讯作者：
Gao X
中科院分区：
文献类型：
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作者：
Chen S;Li W;Jin C;Vaidya A;Gao J;Yang H;Wu S;Gao X
研究长期静息心率（RHR）模式是否可以预测大型队列中动脉僵硬的风险。这个以社区为基础的队列包括12，554名参与凯伦研究的参与者，他们没有心肌梗死，中风，心律失常和癌症。我们使用潜在的混合物模型来识别2006年，2008年和2010年的RHR轨迹。我们使用多变量线性回归模型来检查RHR轨迹模式与动脉僵硬风险之间的相关性，该风险通过2010-2016年的臂踝脉搏波速度（baPWV）进行评估。我们调整了可能的混杂因素，包括社会经济状况、生活方式因素、药物使用、合并症、血脂、血糖和高敏C反应蛋白的血清浓度。我们根据2006年的状态和2006-2010年期间的变化模式确定了五种不同的RHR轨迹模式（低稳定、中等稳定、中等增加、升高-下降和升高-稳定）。结果发现，高稳定型RHR轨迹型的bpPWV值最高，低稳定型RHR轨迹型的bpPWV值最低（校正均数差= 157 cm/s，P<0.001）。相对于这两个极端类别，动脉僵硬（bpPWV≥1400 cm/s）风险的校正比值比为4.14（95%置信区间：2.61-6.57）。一致地，较高的平均RHR、较高的年RHR增加率和较高的RHR变异性都与较高的动脉僵硬风险相关。长期RHR模式是动脉僵硬的强有力预测因素。
To examined whether the long-term resting heart rate (RHR) pattern can predict the risk of having arterial stiffness in a large ongoing cohort. This community-based cohort included 12,554 participants in the Kailun study, free of myocardial infraction, stroke, arrhythmia, and cancer. We used latent mixture modeling to identify RHR trajectories in 2006, 2008 and 2010. We used multivariate linear regression model to examine the association between RHR trajectory patterns and the risk of having arterial stiffness, which was assessed by brachial-ankle pulse wave velocity (baPWV) in 2010–2016. We adjusted for possible confounding factors, including social economic status, lifestyle factors, use of medications, co-morbidities, serum concentrations of lipids, glucose and high-sensitive C-reactive proteins. We identified five distinct RHR trajectory patterns based on their 2006 status and pattern of change during 2006–2010 (low-stable, moderate-stable, moderate-increasing, elevated-decreasing, and elevated-stable). We found that individuals with elevated-stable RHR trajectory pattern had the highest bpPWV value and individuals with the low-stable RHR trajectory pattern had the lowest value (adjusted mean difference = 157 cm/s, P<0.001). Adjusted odds ratio for risk of having arterial stiffness (bpPWV≥1400 cm/s) was 4.14 (95% confidence interval: 2.61–6.57) relative to these two extreme categories. Consistently, a higher average RHR, a higher annual RHR increase rate and a higher RHR variability were all associated with a higher risk of having arterial stiffness. Long-term RHR pattern is a strong predictor of having arterial stiffness.