BACKGROUND: To reduce inappropriate therapy from implantable cardioverter-defibrillators (ICDs), electrogram morphology discrimination has been developed to improve arrhythmia discrimination without compromising device safety. OBJECTIVES: The purpose of this study was to determine the accuracy of the morphology discrimination algorithm for detecting ventricular tachycardia (VT). METHODS: Stored electrograms of 795 tachyarrhythmias from 106 patients with a St. Jude Medical ICD (51 single-chamber and 55 dual-chamber) were analyzed by the investigators. The data were analyzed for morphology discrimination alone, sudden onset and stability, and morphology discrimination in combination with sudden onset and stability. Data were corrected for multiple episodes within a patient with the generalized estimating equation method. RESULTS: Using the nominal template match of 60%, morphology discrimination alone provided sensitivity and specificity of 78% and 95% for single-chamber ICDs and 63% and 92% for dual-chamber ICDs, respectively. Based on the receiver operator characteristic curve, the optimal-match percent threshold was 80% to 85% but at the expense of specificity. Morphology discrimination combined with sudden onset and stability increased sensitivity to 98% with specificity of 86% in single-chamber devices. In dual-chamber devices, the loss in sensitivity is compensated by rate branch analysis, yielding a sensitivity of 98%. CONCLUSION: Arrhythmia discrimination based on electrogram morphology has the potential to reject atrial tachyarrhythmias. However, there is a risk for underdetection of ventricular tachyarrhythmias if arrhythmia discrimination is primarily based on morphology. To guarantee patient safety in single-chamber devices, the morphology discrimination algorithm must be programmed in combination with established detection algorithms. In dual-chamber devices, loss of sensitivity is compensated by the V > A rate branch.
BACKGROUND: To reduce inappropriate therapy from implantable cardioverter-defibrillators (ICDs), electrogram morphology discrimination has been developed to improve arrhythmia discrimination without compromising device safety. OBJECTIVES: The purpose of this study was to determine the accuracy of the morphology discrimination algorithm for detecting ventricular tachycardia (VT). METHODS: Stored electrograms of 795 tachyarrhythmias from 106 patients with a St. Jude Medical ICD (51 single-chamber and 55 dual-chamber) were analyzed by the investigators. The data were analyzed for morphology discrimination alone, sudden onset and stability, and morphology discrimination in combination with sudden onset and stability. Data were corrected for multiple episodes within a patient with the generalized estimating equation method. RESULTS: Using the nominal template match of 60%, morphology discrimination alone provided sensitivity and specificity of 78% and 95% for single-chamber ICDs and 63% and 92% for dual-chamber ICDs, respectively. Based on the receiver operator characteristic curve, the optimal-match percent threshold was 80% to 85% but at the expense of specificity. Morphology discrimination combined with sudden onset and stability increased sensitivity to 98% with specificity of 86% in single-chamber devices. In dual-chamber devices, the loss in sensitivity is compensated by rate branch analysis, yielding a sensitivity of 98%. CONCLUSION:Arrhythmia discrimination based on electrogram morphology has the potential to reject atrial tachyarrhythmias. However, there is a risk for underdetection of ventricular tachyarrhythmias if arrhythmia discrimination is primarily based on morphology. To guarantee patient safety in single-chamber devices, the morphology discrimination algorithm must be programmed in combination with established detection algorithms. In dual-chamber devices, loss of sensitivity is compensated by the V > A rate branch.
Authors: Bruce L Wilkoff; Laurent Fauchier; Martin K Stiles; Carlos A Morillo; Sana M Al-Khatib; Jesœs Almendral; Luis Aguinaga; Ronald D Berger; Alejandro Cuesta; James P Daubert; Sergio Dubner; Kenneth A Ellenbogen; N A Mark Estes; Guilherme Fenelon; Fermin C Garcia; Maurizio Gasparini; David E Haines; Jeff S Healey; Jodie L Hurtwitz; Roberto Keegan; Christof Kolb; Karl-Heinz Kuck; Germanas Marinskis; Martino Martinelli; Mark McGuire; Luis G Molina; Ken Okumura; Alessandro Proclemer; Andrea M Russo; Jagmeet P Singh; Charles D Swerdlow; Wee Siong Teo; William Uribe; Sami Viskin; Chun-Chieh Wang; Shu Zhang Journal: J Arrhythm Date: 2016-02-01