Comparison of time domain and spectral turbulence analysis of the signal-averaged electrocardiogram for the prediction of prognosis in idiopathic dilated cardiomyopathy.

Abstract

Despite significant advances in the treatment of heart failure, the prognosis of patients with idiopathic dilated cardiomyopathy remains poor. Although several of prognostic variables have been shown to be useful in risk stratification of patients with idiopathic dilated cardiomyopathy, their predictive accuracy is low and clinical usefulness uncertain. This study was undertaken to assess the signal-averaged electrocardiogram (SAECG) in patients with idiopathic dilated cardiomyopathy and to compare the ability of time domain and spectral turbulence analytic techniques to predict clinical outcome. SAECG analysis was performed in 80 patients with idiopathic dilated cardiomyopathy. Nineteen patients had left bundle-branch block and eight were taking low-dose amiodarone for life-threatening arrhythmias. Conventional time domain and spectral turbulence analyses of the SAECG were performed using Del Mar 183 software. During a follow-up of 27 +/- 19 months, 24 patients developed progressive heart failure, while the others remained clinically stable. Late potentials were detected in 28% of patients and were equally frequent in patients with and without progressive heart failure (38 vs. 23%, p = 0.20). Spectral turbulence analysis was abnormal in 34% of patients, and patients with abnormal results developed progressive heart failure more frequently than those with normal results (50 vs. 17%, p = 0.01). All spectral turbulence analysis parameters were significantly different in patients with progressive heart failure compared with those who remained clinically stable (p < or = 0.01). Furthermore, progressive heart failure-free survival at 2 years was significantly lower in patients with abnormal compared with normal results (63 vs. 87%; p < 0.05), but was similar in patients with and without late potentials (72 vs. 83%; p = 0.30). The relative risk for developing progressive heart failure using spectral turbulence analysis was 3.4 (95% confidence interval 1.2-9.7) and 2.8 (95% confidence interval 1.1-8.7) using time domain analysis. The sensitivity, specificity, and the positive and negative predictive accuracy for identifying patients who developed progressive heart failure were 50, 83, 50, and 83%, respectively, (p = 0.01) for spectral turbulence analysis, and 36, 85, 45 and 80%, respectively, (p = 0.09) for time domain analysis. Abnormalities in the SAECG of patients with idiopathic dilated cardiomyopathy are common and appear to provide a noninvasive marker for development of progressive heart failure.