Spectral turbulence analysis of the signal-averaged electrocardiogram and its predictive accuracy for inducible sustained monomorphic ventricular tachycardia.
This study was designed to assess the accuracy of a new noninvasive frequency analysis method for predicting patients with inducible sustained monomorphic ventricular tachycardia (VT) at electrophysiologic study and hence the risk of spontaneous ventricular tachyarrhythmias. Signal-averaged electrocardiograms from 3 orthogonal bipolar surface leads were evaluated using a microcomputer-based frequency analysis system that performs analysis of conventional time-domain late potentials as well as incorporating a new technique for spectral analysis of relatively short, overlapping signal segments spanning the whole QRS complex. The spectral analysis technique measured abnormalities anywhere in the entire QRS complex and did so without dependence on any arbitrarily defined frequency, duration or amplitude cutoffs. The hallmark of arrhythmogenic abnormality was hypothesized to be frequent and abrupt changes in the frequency signature of the QRS wave front velocity as it propagates throughout the ventricle around areas of abnormal conduction, resulting in a high degree of spectral turbulence. One-hundred forty-two subjects were studied, including 71 totally normal control subjects ("true negatives"), 33 with both late potentials by time-domain analysis and inducible sustained monomorphic VT ("true positives"), 28 with late potentials but no evidence of spontaneous or inducible sustained monomorphic VT ("false positives") and 10 with inducible sustained monomorphic VT but absence of time-domain late potentials ("false negatives"). The frequency analysis technique correctly classified 100% of the true negatives, 97% of the true positives, 86% of the late potentials false positives and 60% of the late potentials false negatives. The total predictive accuracy of frequency analysis for all groups was 94%, compared with 73% for time-domain late potential analysis. The results suggest that a high degree of spectral turbulence of the overall QRS signal during sinus rhythm may provide a more accurate marker for the anatomic-electrophysiologic substrate of reentrant tachyarrhythmias than detection of late potentials in the terminal QRS region by either time- or frequency-domain analysis. Spectral turbulence analysis is applicable to patients irrespective of the QRS duration and the presence or absence of bundle branch block.