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Clinical Experience with a New Detection Algorithm for Differentiation of Supraventricular from Ventricular Tachycardia in a Dual‐Chamber Defibrillator
Author(s) -
SINHA ANILMARTIN,
STELLBRINK CHRISTOPH,
SCHUCHERT ANDREAS,
MÖX BERNHARD,
JORDAENS LUC,
LAMAISON DOMINIQUE,
GILL JASWINDER,
KAPLAN ANDREW,
MERKELY BELA
Publication year - 2004
Publication title -
journal of cardiovascular electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.193
H-Index - 138
eISSN - 1540-8167
pISSN - 1045-3873
DOI - 10.1046/j.1540-8167.2004.03290.x
Subject(s) - medicine , supraventricular tachycardia , cardiology , ventricular tachycardia , dual (grammatical number) , implantable cardioverter defibrillator , supraventricular arrhythmia , algorithm , tachycardia , atrial fibrillation , computer science , art , literature
Inadequate therapy for supraventricular tachyarrhythmias (SVT) is a frequent problem of implantable cardioverter defibrillators (ICD). Dual‐chamber ICDs have been developed to improve discrimination of SVT from ventricular tachycardia (VT). We investigated the positive predictivity, sensitivity, and specificity of a new algorithm, the SMART detection™ algorithm, incorporated in the Phylax AV (Biotronik) dual‐chamber ICD. Methods and Results: Two hundred nine patients (185 men, age 64 ± 11 years) received a Phylax AV ICD with SMART detection™ activated. In 138 of these patients, 1,245 sustained tachycardia episodes with a detailed electrogram were stored in the device during a follow‐up period of 10 ± 6 months. Episodes were correctly classified as ventricular fibrillation (VF, n = 178) in 52 patients, VT (n = 641) in 98 patients, and SVT (n = 385) in 48 patients by the algorithm. Forty‐one true SVT episodes (3.3%) were misclassified as VT: atrial fibrillation (n = 7) and flutter (n = 1), sinus tachycardia (n = 12), and other SVT (n = 21). The positive predictivity for VF/VT was 94.5% (95% CI 92.7–95.8) uncorrected and 94.5% (95% CI 92.9–95.8%) corrected with the generalized equation estimation (GEE) method. The positive predictivity for SVT was 100%. The specificity was 88.9% (95% CI 85.6–91.6%) uncorrected and 89.0% (95% CI 85.6–91.6%) corrected with the GEE method with a sensitivity of 100%. Conclusion: The SMART detection™ algorithm was safe and reliable for the detection of all ventricular tachycardias. Although its specificity was high, it should be improved with regard to SVT to avoid inappropriate ICD therapies. (J Cardiovasc Electrophysiol, Vol. 15, pp. 1‐7, June 2004)