[Association between resting heart rate trajectory pattern and risk of cardiovascular and cerebrovascular diseases].

Objective: To examine whether the long-term resting heart rate (RHR) pattern can predict the risk of cardiovascular and cerebrovascular diseases (CVDs). Methods: This prospective cohort study included 63 040 participants who took part in the health examination in 2006 and one of the health examinations on 2008 or 2010 and were free of myocardial infarction, stroke, arrhythmia, cancer and not treated with β-recepter blocker. The outcomes were the first occurrence of myocardial infarction and stroke during the follow up ended on December 31, 2015. RHRs were measured in 2006, 2008, and 2010. We used latent mixture modeling SAS Proc procedure to identify RHR trajectories. We identified 4 distinct RHR trajectory patterns based on the data derived from 2006 and on the pattern change during 2006 to 2010 (low-stable, moderate-stable, moderate-increasing, elevated-decreasing). Collected the general clinical data of the patients. Cox regression model was used to determine the association between RHR trajectory patterns and the risk of CVDs during follow up. Hazard ratio (HR) with 95% confidence intervals (CI) were calculated using Cox regression modeling. Results: There were statistical significance among the 4 distinct RHR trajectory patterns on the following variables: age, gender, smoking status, drinking status, physical activity, education status, history of use antihypertensive drugs, history of hypertension,history of diabetes, body mass index, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, fasting blood glucose, and the level of high-sensitivity C-reactive protein (all P<0.01). The moderate-increasing pattern experienced the highest risk of developing stroke and CVDs among all 4 patterns. The cumulative incidence of cerebral infarction, cerebral hemorrhage and CVDs in the order of low-stable trajectory, moderate-stable trajectory and moderate-increasing trajectory. The cumulative incidences of cerebral infarction, cerebral hemorrhage and CVDs in elevated-decreasing trajectory group were significantly lower than those in moderate-increasing trajectory group, but higher than those in moderate-stable trajectory group. Compared to the low-stable pattern, adjusted HR was 1.3 (95%CI 1.0-1.6) for the moderate-increasing pattern after adjustment for potential confounders. Conclusion: Our study finds that individuals with moderate-increasing RHR trajectory pattern are associated with higher risk of cardiovascular and CVDs.目的：探讨静息心率轨迹对心脑血管事件的影响。 方法：该研究为前瞻性队列研究。选择参加了2006年度开滦集团公司职工健康体检且至少参加了2008、2010年度任一健康体检者作为研究对象，排除有心律失常、心肌梗死、卒中、肿瘤以及服用β受体阻滞剂者，最终纳入统计分析的对象共63 040名，研究随访至2015年12月31日，以心肌梗死、卒中为终点事件。依据2006、2008、2010年度健康体检期间静息心率数据，使用SAS Proc Traj程序确定了4种不同的静息心率轨迹组，分别为低-稳定轨迹组、中-稳定轨迹组、中-高轨迹组和高-低轨迹组。收集入选者的一般临床资料。采用Cox比例风险模型进一步分析不同静息心率轨迹组发生心脑血管事件的风险差异。 结果：4种静息心率轨迹组人群年龄、性别、吸烟史、饮酒史、体育锻炼、教育程度、服用降压药物史、高血压病史、糖尿病病史、体重指数（BMI）、甘油三酯（TG）、低密度脂蛋白胆固醇（LDL-C）、高密度脂蛋白胆固醇（HDL-C）、空腹血糖（FBG）、高敏C反应蛋白（hsCRP）差异均有统计学意义（P均<0.01）。低-稳定轨迹组、中-稳定轨迹组和中-高轨迹组人群脑梗死、脑出血以及心脑血管事件的累积发病率均依次升高，高-低轨迹组人群的脑梗死、脑出血以及心脑血管事件的累积发病率低于中-高轨迹组，但高于中-稳定轨迹组，差异均有统计学差异（P均<0.05）。校正了年龄、性别、吸烟史、饮酒史、体育锻炼、服用降压药物史、高血压病史、糖尿病病史、BMI、TG、LDL-C、HDL-C、FBG、hsCRP等混杂因素后，中-高轨迹组人群发生心脑血管事件的风险是低-稳定轨迹组的1.3倍（HR=1.3，95%CI 1.0~1.6，P<0.05）。 结论：开滦研究人群中存在着不同的静息心率轨迹，高水平的静息心率轨迹心脑血管事件发生风险高。.