Detection of Pathological Tachycardia by Analysis of Electrogram Morphology

Abstract

Pacemaker recognition of pathological tachycardia relies on heart rate analysis. This can lead to misdiagnosis when sinus tachycardia exceeds the preset tachycardia response trigger rate. We have explored a method for automatic tachycardia diagnosis by analysis of bipolar endocardial electrogram morphology. Electrograms were recorded from 11 patients (pts) during sinus rhythm and during a total of 20 abnormal rhythms: retrograde atrial depolarization from ventricular pacing in six patients; atrioventricular reentry tachycardia in five patients with intermittent left bundle branch block in one of those; AV nodal reentry tachycardia in five patients and ventricular tachycardia in three patients. Posture and respiration were varied during all rhythms except ventricular tachycardia. The electrograms were then digitized and converted to a form in which the amplitudes were proportional to the rates of change of the original electrogram (equivalent to a first time derivative); the derived signal was then analyzed by a new gradient pattern detection (GPD) program. Analysis of the processed atrial signals by GPD resulted in automatic recognition of abnormal rhythms from sinus rhythm in all cases except for one patient's retrograde atrial depolarization. At the ventricular level, GPD successfully distinguished all abnormal rhythms from sinus rhythm including recognition of left bundle branch block and varying degrees of preexcitation. Respiratory and postural variation did not affect the recognition process. We conclude that electrogram GPD has successfully and automatically detected a variety of arrhythmias which can be treated by implantable pulse generators and may, therefore, be a useful adjunct to heart rate analysis in future generations of such antitachycardia pacemakers.