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Clinical Evaluation of Morphology Discrimination: An Algorithm for Rhythm Discrimination in Cardioverter Defibrillators

BORIANI, G., et al.: Clinical Evaluation of Morphology Discrimination: An Algorithm for Rhythm Discrimination in Cardioverter Defibrillators. The aim of this study was to test the new morphology discrimination diagnostic algorithm for ICDs that differentiates supraventricular tachycardias (SVTs) fro...

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Published in:Pacing and clinical electrophysiology 2001-06, Vol.24 (6), p.994-1001
Main Authors: BORIANI, GIUSEPPE, BIFFI, MAURO, FRABETTI, LORENZO, LATTUCA, J. JOHN, BRANZI, ANGELO
Format: Article
Language:English
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Summary:BORIANI, G., et al.: Clinical Evaluation of Morphology Discrimination: An Algorithm for Rhythm Discrimination in Cardioverter Defibrillators. The aim of this study was to test the new morphology discrimination diagnostic algorithm for ICDs that differentiates supraventricular tachycardias (SVTs) from VTs by analysis of ventricular depolarization complexes morphology. Twenty‐five patients implanted with a St. Jude Ventritex single chamber ICD were studied during electrophysiological evaluation at pre‐discharge and were followed for 7 ± 4 months. Sensitivity and specificity for VT detection and overall diagnostic accuracy of the morphology discrimination algorithm were calculated on 326 detected events. At electrophysiological evaluation, the algorithm was tested during 67 episodes of right atrial pacing, during 119 episodes of RV pacing (at basal interventricular septum and RV apex) and during 27 episodes of sustained AF: specificity was 98%, sensitivity was 66%, and diagnostic accuracy was 80%. All episodes of AF were correctly diagnosed as SVT. Exclusion of detections related to pacing at the basal interventricular septum, resulted in a specificity of 98%, a sensitivity of 85%, and a diagnostic accuracy of 93%. During follow‐up, evaluation of the morphology discrimination algorithm on 113 spontaneous episodes (31 VTs, 31 AF, 7 SVTs, and 44 sinus tachycardias) exhibited a specificity of 89%, a sensitivity of 100%, and a diagnostic accuracy of 92%. In conclusion, the morphology discrimination algorithm exhibits a high specificity in discriminating VTs from SVTs, although with a corresponding reduction in sensitivity. The preliminary experience on spontaneous episodes is promising. To correct for the reduction in sensitivity, it is advisable to use this algorithm in parallel with other algorithms for rhythm discrimination (sudden onset, stability) coupled with extended high rate.
ISSN:0147-8389
1540-8159
DOI:10.1046/j.1460-9592.2001.00994.x