Intraventricular Electrogram Analysis for Ventricular Tachycardia Detection: Statistical Validation


  • This work was supported by NSF grant No. EET-8351215, and a Rackham Predoctoral Fellowship, University of Michigan.

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THRONE, R.D., ET AL.: Intraventricular Electrogram Analysis for Ventricular Tachycardia Detection: Statistical Validation. Time-domain analysis of intraventricular electrogram morphology during ventricular tachycardia (VT) and sinus rhythm or atrial fibrillation (SR/AF) has been proposed as a method for increasing the specificity of pathological tachycardia detection by antitachycardia devices. However, few studies have validated the use of such analysis with statistical methods. When statistical methods have been utilized, it has been assumed that the distribution of the values derived from analysis of the intracardiac electrograms have had a normal (gaussian) distribution. In this study, we sought to determine whether: (1) the distribution of values derived from analysis of intracardiac electrogram during SR/AF and VT is gaussian or nongaussian; and (2) the discrimination of monomorphic VT from SR/AF using SR/AF templates can be validated statistically. Two previously proposed time-domain methods—correlation waveform analysis (CWA) and area of difference (AD)—were selected for evaluation of 29 patients with 33 distinct, sustained monomorphic VTs. An initial SR/AF template was used to analyze subsequent SR/AF and VT passages with a minimum of 50 consecutive depolarizations using a “best-fit” alignment. The values derived from each analysis were examined subsequently for skewness (asymmetry) and kurtosis (shape) using two-tailed tests (p < 0.02). For passages of SR/AF, a normal (gaussian) distribution was present in only 24% (CWA), and 45% (AD); for passages of VT, normal distribution was present in only 58% for both CWA and AD. Using appropriate statistical testing with nonparametric tolerance intervals, CWA and AD discriminated VT from SR/AF in 29 out of 33 (88%), and 30 out of 33 (91%) instances, respectively, with 95% confidence. Thus, the assumption of a gaussian distribution for values derived from time-domain analysis of intraventricular electrograms for VT detection is not uniformly valid. Both CWA, which is independent of both baseline and amplitude fluctuations, and AD, which is not independent of these fluctuations, have similar performance when validated with appropriate statistical methods.