Time-domain and frequency-domain analyses of the signal-averaged ECG in patients with ventricular tachycardia and ischemic versus nonischemic dilated cardiomyopathy Academic Article Article uri icon

Overview

MeSH Major

  • Cardiac Pacing, Artificial
  • Tachycardia, Ventricular

abstract

  • The value of time-domain and frequency-domain (spectral turbulence) analyses of the signal-averaged electrocardiogram was investigated to predict induced sustained monomorphic ventricular tachycardia (VT). Two groups of patients with spontaneous nonsustained VT and left ventricular ejection fraction less than 50% were enrolled: 70 patients with idiopathic dilated cardiomyopathy (group 1) and 70 patients with ischemic heart disease (group 2). Sustained VT was induced in 9 cases (13%) in group 1 and 16 (23%) in group 2. The prevalence of abnormal time-domain and spectral turbulence analysis was 16 and 37%, respectively, in group 1 and 27 and 51%, respectively, in group 2 (NS). In group 1, the predictive accuracy of time-domain and spectral turbulence analysis for induced VT was 86 and 67%, respectively (P < .01). In group 2, the predictive accuracy of the two techniques for induced VT was, respectively, 79 and 66% (NS). In both groups, the predictive accuracy of time-domain analysis was higher than that of spectral turbulence analysis in patients with intraventricular conduction defect (IVCD): 65 versus 25%, respectively, in group 1 (P < .01), and 81 versus 44%, respectively, in group 2 (P < .05). However, the predictive accuracy of time-domain and spectral analyses was similar in patients without IVCD: 94 versus 84%, respectively, in group 1, and 77 versus 74%, respectively, in group 2. Thus, in patients with dilated cardiomyopathy, (1) the etiology does not affect the predictive accuracy of time and frequency domain and frequency-domain analyses have high predictive accuracy in patients without IVCD; and (3) spectral turbulence analysis does not improve VT prediction in patients with IVCD.

publication date

  • January 1994

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1016/S0022-0736(94)80094-4

PubMed ID

  • 7884364

Additional Document Info

start page

  • 213

end page

  • 8

volume

  • 27

number

  • SUPPL. 1