Improving SVT discrimination in single-chamber ICDs: A new electrogram morphology-based algorithm

Introduction: Wide-spread adoption of ICD therapy has focused efforts on improving the quality of life for patients by reducing "inappropriate" shock therapies. To this end, distinguishing supraventricular tachycardia from ventricular tachycardia remains a major challenge for ICDs. More sophisticated discrimination algorithms based on ventricular electrogram morphology have been made practicable by the increased computational ability of modern ICDs. Methods and Results: We report results from a large prospective study (1,122 pts) of a new ventricular electrogram morphology tachycardia discrimination algorithm (Wavelet™ Dynamic Discrimination, Medtronic, Minneapolis, MN, USA) operating at minimal algorithm setting (RV coil-can electrogram, match threshold of 70%). This is a nonrandomized cohort study of ICD patients using the morphology discrimination of the Wavelet algorithm to distinguish SVT and VT/VF. The Wavelet criterion was required ON in all patients and all other supraventricular tachycardia discriminators were required to be OFF. Spontaneous episodes (N = 2,235) eligible for ICD therapy were adjudicated for detection algorithm performance. The generalized estimating equations method was used to remove bias introduced when an individual patient contributes multiple episodes. Inappropriate therapies for supraventricular tachycardia were reduced by 78% (90% CI: 72.8-82.9%) for episodes within the range of rates where Wavelet was programmed to discriminate. Sensitivity for sustained ventricular tachycardia was 98.6% (90% CI: 97-99.3%) without the use of high-rate time out. Conclusions: Results from this prospective study of the Wavelet electrogram morphology discrimination algorithm operating as the sole discriminator in the ON mode demonstrate that inappropriate therapy for supraventricular tachycardia in a single-chamber ICD can be dramatically reduced compared to rate detection alone.