INTRODUCTION: Electrogram morphology analysis improves discrimination of supraventricular tachycardias (SVTs) from ventricular tachycardias (VTs) in implantable cardioverter defibrillators (ICDs), but electrogram morphology may change with lead maturation, drugs, or disease progression. We report the clinical performance of an automatic algorithm that creates and updates templates from non-paced, slow rhythm and continuously checks the quality of the template used for arrhythmia discrimination. METHODS AND RESULTS: We studied this algorithm in 193 patients with single-chamber ICDs (Marquis VR, Medtronic Inc., Minneapolis, MN, USA). Of the 112 patients who completed 6-month follow-up, 99.1% of the patients had > or =1 automatic template created. Match scores between template and ongoing rhythm are computed using Haar Wavelets. Of the 435 automatic templates evaluated at follow-up, 423 (97.2%) had a median match score > or =70%. Intrinsic rhythm at 1 month had significantly higher match scores (P < 0.001) with automatic templates (90.3 +/- 7.0%) than with manual templates (85.7 +/- 10.9%) generated at pre-hospital discharge (PHD). The percentage of appropriately rejected SVTs was slightly higher with the automatic template (280/339 episodes) than with the manual template at PHD (272/339 episodes) while the Wavelet detection of VT was the same (218/220 episodes). CONCLUSIONS: In patients receiving ICDs, the automatic templates were successfully created during a 6-month follow-up period, and consistently matched the patients' intrinsic rhythm at the nominal match threshold. Both early (<1 month postimplant) and late (1- to 3-month follow-up period) changes in electrogram morphology were identified, confirming the need for automatic template updating.
INTRODUCTION: Electrogram morphology analysis improves discrimination of supraventricular tachycardias (SVTs) from ventricular tachycardias (VTs) in implantable cardioverter defibrillators (ICDs), but electrogram morphology may change with lead maturation, drugs, or disease progression. We report the clinical performance of an automatic algorithm that creates and updates templates from non-paced, slow rhythm and continuously checks the quality of the template used for arrhythmia discrimination. METHODS AND RESULTS: We studied this algorithm in 193 patients with single-chamber ICDs (Marquis VR, Medtronic Inc., Minneapolis, MN, USA). Of the 112 patients who completed 6-month follow-up, 99.1% of the patients had > or =1 automatic template created. Match scores between template and ongoing rhythm are computed using Haar Wavelets. Of the 435 automatic templates evaluated at follow-up, 423 (97.2%) had a median match score > or =70%. Intrinsic rhythm at 1 month had significantly higher match scores (P < 0.001) with automatic templates (90.3 +/- 7.0%) than with manual templates (85.7 +/- 10.9%) generated at pre-hospital discharge (PHD). The percentage of appropriately rejected SVTs was slightly higher with the automatic template (280/339 episodes) than with the manual template at PHD (272/339 episodes) while the Wavelet detection of VT was the same (218/220 episodes). CONCLUSIONS: In patients receiving ICDs, the automatic templates were successfully created during a 6-month follow-up period, and consistently matched the patients' intrinsic rhythm at the nominal match threshold. Both early (<1 month postimplant) and late (1- to 3-month follow-up period) changes in electrogram morphology were identified, confirming the need for automatic template updating.