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A Study Of Clinical Usefulness Of Heart Rate Variability And Poincare Plot For Diagnosing Heart Diseases

Posted on:2003-09-18Degree:MasterType:Thesis
Country:ChinaCandidate:W X HanFull Text:PDF
GTID:2144360092970051Subject:Epidemiology and Health Statistics
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AIM: To investigate the normal range of 24-hour Heart Rate Variability(HRV) andPoincare plot, and to evaluate their clinical useful value of diagnosing heart diseases.METHODS: 5l8 normal control persons and 227 cases with heart disease wereundergone by 24h Dynamic ElectrocardiograPh Monitoring(DCG).We a-nalyzed aIl oftheir data and 24h HRV variances including Time domain method and Non-linearanalysis by the computer.RESUTS: (l) The great majority of 24h HRV variances were non-normal distribution,then using percentile to identify the normal range of HRV was reasonable and accordingto clinical conditions to define the normal rage of HRV using Percentile. (2) All of HRVvariances were influenced by age and decreased along with growing up. A part of HRVvariances were related with sex and the variances of male were higher then fema1e. (3)The HRV variances were significantly lower in the heaft disease groups than in thenormal control ones. It was most clear in MyocardiaI Infarction (MI) and DilatedCardiomyopathy(DCM) groups with serious myocardial damage. (4) It was markedpositive correlation between the Non-linear variances (VLI,VAI,DI) and the Timedomain analysis ones. (5) Poincare plot shaPed as Comet form is more than 90% in thenormal controls and as Non-Comet form about 80.6 I 2.6% in the heart disease cases. (6)'I'he change of Poincare plot shaPe was related with age but not with sex. The ration ofNon-Comet form increased with age. (7) Compdring with SDNN, Poincare plot showedsimilar Specificity, False positive and Positive predictive value. But it has statisticalsignifican higher Sensitivity Negative predictive value and Youden's index, and IowerFalse negative than SDNN.CONCLUSION: 24h HRV is able to reflect the abnormal function of autonomic nerver system, then it can be use to judge someone with or without heart disease and the degrees of the disease. The characteristics of Poincare plot are audio-visual, sensitive, specificity, accuracy, convenient, and not influenced by sex, so it is better than SDNN for clinical usefulness.
Keywords/Search Tags:Heart Rate Variability(HRV), Non-linear analysis( Chaos analysis), Poincare plot ( Lorenz plot), Dynamic Electrocardiograph Monitoring( DCG )
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