Abstract
Tachycardia detection by implantable antitachycardia devices using rate alone has major limitations. Several alternative methods have been proposed to distinguish ventricular tachycardia or ventricular fibrillation from normal sinus rhythm using intracardiac electrograms. These methods have not been tested, however, for recognition of ventricular tachycardia in patients with abnormal surface QRS conduction during sinus rhythm or with antiarrhythmic drug therapy. In this study, three techniques for the identification of ventricular tachycardia from intracavitary bipolar ventricular electrograms were examined and compared: correlation waveform analysis, amplitude distribution analysis, and spectral analysis using Fast Fourier transformation. Thirty episodes of induced monomorphic ventricular tachycardia were analyzed and compared sinus rhythm in four groups of patients with: I. Normal surface QRS conduction during sinus rhythm without antiarrhythmic drug therapy (five episodes); II. Intraventricular conduction delay or bundle branch block during sinus rhythm without antiarrhythmic drug therapy (nine episodes); III. Normal surface QRS conduction during sinus rhythm with antiarrhythmic therapy (six episodes); and IV. Intraventricular conduction delay or bundle branch block during sinus rhythm with antiarrhythmic drug therapy (ten episodes). Correlation waveform analysis had 100% sensitivity and specificity in distinguishing ventricular tachycardia from sinus rhythm, even in the presence of an intraventricular conduction delay, bundle branch block, and antiarrhythmic drug therapy. In contrast, amplitude distribution analysis differentiated 15/30 episodes (50.0%) of ventricular tachycardia from sinus rhythm, and a maximum of 18/30 episodes (60.0%) of ventricular tachycardia were identified by special analysis using Fast Fourier transformation. Correlation waveform analysis appears to be a reliable technique to discriminate ventricular tachycardia from sinus rhythm using intracavitary ventricular electrograms. Its computational demands are modest, making it suitable for consideration in an implantable antitachycardia device.
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