摘要
目的通过分析冠心病合并慢性心力衰竭患者脉图时域特征参数,探讨心功能不全状态与脉图特征的相关性,挖掘脉诊的临床诊断价值。方法采用ZBOX—I型脉象数字化采集分析仪采集脉象样本,将其按照心功能不全状态进行分组,并运用非参数检验的方法比较与分析心功能不全不同分组脉图时域特征参数的组间差异;基于脉图特征参数,运用随机森林模式识别方法建立冠心病合并慢性心力衰竭患者心功能不全状态评估模型。结果与心功能不全轻度组比较,心功能不全中、重度组h4/h1、t1/T、t1/t4(P<0.05)显著增大;t4(P<0.01),t3、t5、T、h5/h1(P<0.05)显著减小;本实验基于193例样本的脉图时域特征建立了心功能不全状态评估识别模型,其平均识别率为70.93%。结论冠心病合并慢性心力衰竭患者的脉图时域特征参数组间比较存在显著差异,其参数变化可以反映患者的心功能不全状态,有助心功能不全状态的诊断。
Objectives To explore the value of pulse diagnosis as a tool of clinical diagnosis by analyzing the parameters in time-domain of pulse recorded under different state of cardiac insufficiency in patients with coronary heart disease(CHD)complicated with chronic heart failure(CHF),.Methods The ZBOX-I type pulse digital acquisition analyzer was used to collect pulse samples,and grouped them according to different state of cardiac insufficiency.The nonparametric test was used to compare and analyze the differences of parameters in time-domain of the recorded pulses between different groups of cardiac insufficiency.Based on the time-domain parameters,a Random Forest(RF)pattern recognition method was used to establish an assessment model of cardiac insufficiency for patients with CHD complicated with CHF.Results Compared with the mild group of cardiac insufficiency,the h4/h1,t1/T,t1/t4(P<0.05)of pulse parameters in moderate to severe group of cardiac insufficiency increased significantly;t4(P<0.01),t3,t5,T,h5/h1(P<0.05)of those parameters reduced significantly.Furthermore,in this experiment,an assessment model for cardiac insufficient was established based on the time-domain characteristics of 193 pulse samples with an average recognition rate of 70.93%.Conclusion There were significant differences in the time-domain characteristics of pulse recordings between different groups of cardiac insufficiency in patients with CHD and CHF,which showed that changes to pulse parameters can reflect the different state of cardiac insufficiency and help to diagnose the state of cardiac insufficiency.
作者
刘璐
张春柯
陈瑞
王忆勤
燕海霞
郭睿
Liu Lu;Zhang Chunke;Chen Rui;Wang Yiqin;Yan Haixia;Guo Rui(School of Basic Medical Sciences,Shanghai University of Traditional Chinese Medicine,Key Laboratory of Health Identification and Assessment of Shanghai,Shanghai 201203,China;People's Hospital of Ganzhou District,Gansu 734000,China)
出处
《世界科学技术-中医药现代化》
CSCD
北大核心
2020年第9期3301-3305,共5页
Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology
基金
上海科学技术委员会生物医药领域项目(19441901100):基于人工智能的新型中医脉诊仪的研制,负责人:郭睿
国家自然科学基金委员会青年项目(81302913):基于心血管系统电网络模型的冠心病不同证型脉象仿真及形成机理的研究,负责人:郭睿
国家自然科学基金委员会面上项目(81673880):基于中医四诊大数据的冠心病风险评估与预测模型研究,负责人:王忆勤。
关键词
冠心病
心力衰竭
脉图
时域参数
模式识别
Coronary heart disease
Chronic heart failure
TCM pulse
Time-domain parameter of pulse recording
Pattern recognition
