基于多变量趋势分析的心肌梗死风险评估

Risk Evaluation of Myocardial Infarction Based on Multivariate Trend Analysis

基于心血管疾病患者的心率变异性(HRV)、心率减速力(DC)以及脉搏波传导速度(PWV)等多变量的测量与分析,研究心肌梗死风险早期评估的可行性。随机选择35名心血管疾病患者(11例心肌梗死、8例冠心病、6例动脉硬化和10例高血压)和31名健康常对照,采用自主研制的心肌梗死风险评估平台,采集15min的心电数据和1min的脉搏波数据,进行HRV、DC和PWV分析,并与对照组结果进行比较;实验结果表明心血管疾病组与对照组的HRV、DC和PWV分析结果具有明显的差异性,而其中DC和HRV时域分析方法中的NN50、PNN50及TINN还能有效反映出相关病理的渐变过程。综合HRV、DC和PWV等参变量的趋势分析能够为心肌梗死早期风险评估、临床筛查和预警提供参考。

This paper is aimed to study the feasibility of myocardial infarction risk assessment by noninvasive multiva riable trend analysis, including heart rate variability （HRV）, deceleration capacity （13（2） of heart rate and pulse wave velocity （PWV）. Thirty five patients with cardiovascular diseases （11 Myocardial infarction（MI）, 8 coronary artery disease（CAD）, 6 artery atherosclerosis（AA） and 10 hypertension）, and 31 healthy subjects were randomly selected into a control group for this research as comparison. 15min ECG and lmin pulse wave data were collected based on the analysis workbench developed by our Lab. HRV, DC and PWV between the cardiovascular group and the control group were analyzed and compared. The results showed that the HRV indices, DC and PWV were significantly high er than those in the control group. The DC and the HRV indices including NN50, PNNS0 and TINN especially pres ented a decline trend that was consistent with the regularity of cardiovascular development process. This noninvasive multivariable trend analysis of HRV, DC and PWV can be a reference for the earlier risk prediction of MI.