[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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A new software package has been developed which implements wavelet analysis (WA) of signal averaged electrocardiograms (SAECG). Wavelet analysis is a new time-frequency technique which is able to detect small transient disturbances even if they are hidden within the high gain QRS complex. In 3 substudies, this new approach was tested and compared with the standard time-domain indices of SAECG : The first substudy utilised the case-control population of patients with and without sustained ventricular tachycardia (VT) after myocardial infarction (MI). 53 patients with post infarction VT were age, sex, and infarct site matched with 53 patients without a history of arrhythmic complications after infarction. The power of wavelet analysis and time-domain analysis (TD) was compared in distinguishing patients with and without sustained VT after myocardial infarction. The second substudy assessed short-term reproducibility of the numerical indices of WA and TD. The third substudy applied WA of SAECG to prospective risk stratification of MI survivors. Study population consisted of 551 post infarction patients from whom during a 2-year of follow-up 32 suffered from cardiac death (CM), 21 potentially arrhythmic death, 19 sudden cardiac death (SCD), 19 developed non-fatal sustained VT, and 5 patients were resuscitated from documented ventricular fibrillation. The positive predictive characteristics (dependency of positive predictive accuracy on sensitivity) were evaluated for predicting different follow-up events. Both modes of analysis were compared at selected levels of sensitivity.
These studies show that : (1) the distinction between patients with and without VT after myocardial infarction is similarly powerful by both wavelet and time-domain analysis, (2) WA is similarly powerful in identifying VT patients with anterior and inferior infarction (p=1.4x10-9,n=30, and p=2.0x10-5,n=23, respectively), (3) the reproducibility of WA is higher than that of TD, (4) for all events, WA gave higher positive predictive accuracy than TD analysis in risk prediction.

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