Predictive value of wavelet decomposition of the signal-averaged electrocardiogram in idiopathic dilated cardiomyopathy

Background Wavelet decomposition of the signal-averaged electrocardiogram h as been proposed as a method of detecting small and transient irregularitie s hidden within the QRS complex and of overcoming some of the limitations o f time domain analysis of the signal-averaged electrocardiogram. Aim This study evaluated the potential utility of wavelet decomposition ana lysis in the risk stratification of patients with idiopathic dilated cardio myopathy. Methods and Results Both wavelet decomposition and time domain analysis wer e applied to the signal-averaged electrocardiogram recordings of 82 patient s with idiopathic dilated cardiomyopathy (mean age 43 +/- 14 years, 60 men) and 72 normal controls (mean age 44 +/- 15 years, 48 men). Three conventio nal time domain indices and four wavelet decomposition analysis parameters (QRS length, maximum count, surface area, and relative length) were derived from each recording using a Del Mar CEWS system and an in-house software p ackage, respectively. The results showed that (1) more patients with idiopa thic dilated cardiomyopathy than without had late potentials, and that the filtered QRS duration was significantly longer in patients than in controls (P<0.001). Similarly, abnormal wavelet decomposition analysis was more com mon in patients and wavelet decomposition measurements were significantly d ifferent between patients and controls (P<0.01); (2) conventional time doma in analysis did not distinguish between clinically stable patients and pati ents who developed progressive heart failure, or between patients with and without arrhythmic events; (3) wavelet decomposition analysis identified in patients who went on to develop progressive heart failure but failed to di stinguish patients with arrhythmic events from those without; (4) survival analyses of a mean follow-up of 23 months showed that patients with late po tentials tended to develop progressive heart failure more frequently than o thers (P=0.06). Patients with an abnormal wavelet decomposition result more frequently developed progressive heart failure than those with a normal wa velet decomposition result (P=0.027); (5) in a univariate analysis (Cox mod el), wavelet decomposition measurements but not time domain indices signifi cantly correlated with the development of progressive heart failure (P=0.01 ). Multivariate analysis showed that only left ventricular end-diastolic di mension and peak oxygen consumption during exercise remained significant pr edictors of progressive heart failure. Conclusion Wavelet decomposition analysis of the signal-averaged electrocar diogram is superior to conventional time domain analysis for identifying pa tients with idiopathic dilated cardiomyopathy at increased risk of clinical deterioration. Wavelet decomposition analysis, however, is unlikely to pro spectively distinguish patients at a high risk of arrhythmic events in idio pathic dilated cardiomyopathy in its present form. (Eur Heart J 2000; 21: 1 015-1022) (C) 2000 The European Society of Cardiology.