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May 24, 2004Journal of Cardiovascular Electrophysiology62 citationsOpen Access

Clinical Experience with a New Detection Algorithm for Differentiation of Supraventricular from Ventricular Tachycardia in a Dual‐Chamber Defibrillator

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ASAnil‐Martin SinhaCSChristoph StellbrinkASAndreas Schuchert

Structured PICO

Does the SMART detection algorithm accurately differentiate SVT from VT in patients with a dual-chamber ICD?

P
Population
209 patients (185 men, age 64 +/- 11 years) who received a Phylax AV dual-chamber ICD with SMART detection algorithm activated.
I
Intervention
SMART detection algorithm incorporated in the Phylax AV (Biotronik) dual-chamber ICD
O
Outcome
Positive predictivity, sensitivity, and specificity of the SMART detection algorithm for differentiating SVT from VTsurrogate

The SMART detection algorithm in dual-chamber ICDs demonstrated 100% sensitivity for ventricular tachycardias, though specificity for SVT was 88.9%, indicating room for improvement to avoid inappropriate therapies.

Abstract

INTRODUCTION: 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 trade mark 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 trade mark 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 trade mark 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.

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Cite This Study

Sinha et al. (2004) studied this question.

synapsesocial.com/papers/6a7e7289e26c9db0b64d9485https://doi.org/10.1046/j.1540-8167.2004.03290.x
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