Key result
Using a cutoff value of 50% change from normal sinus rhythm, the ratio of first-order to zero-order QR coefficient completely separated ventricular tachycardia from supraventricular tachycardia (P=0.03).
Why the study?
Does polynomial modeling of ventricular shock electrograms reliably discriminate between SVT and VT in patients with implantable defibrillators?
Observational (n=7)
Does polynomial modeling of ventricular shock electrograms reliably discriminate between SVT and VT in patients with implantable defibrillators?
Simple polynomial equations modeling ventricular shock electrograms can reliably discriminate between SVT and VT, providing a potential algorithm for low computational power implantable devices.
Answers are grounded in this paper and cite their sources.
Polynomial EGM modeling reliably discriminates SVT from VT; leaves open whether it reduces inappropriate ICD shocks in prospective trials.
BACKGROUND: Inappropriate shocks continue to be a problem for patients with implantable defibrillators (ICD). We evaluated the performance of polynomial-modeled ventricular electrograms (EGM) to discriminate between supraventricular tachycardia (SVT) and ventricular tachycardia (VT). METHODS: Seven sets of EGM from patients having both SVT and VT documented during a single ICD interrogation were included. The cardiac cycle was analyzed off-line in two parts, QR and RQ segments, which were modeled separately using third-order and sixth-order polynomial equations, respectively. These segments were then analyzed to determine which polynomial coefficients were most significant for rhythm discrimination. RESULTS: When analyzing the QR segment during arrhythmia, there were statistically significant (P<0.05) correlations in 4 of 4 (100%) of the QR coefficients when comparing normal sinus rhythm (NSR) to SVT and 2 of 4 (50%) when comparing NSR to VT or SVT to VT. When analyzing the RQ segment during arrhythmia, there were statistically significant (P<0.05) correlations in 4 of 7 (57%) of the RQ coefficients when comparing NSR to SVT, 5 of 7 (71%) when comparing NSR to VT, and 3 of 7 (43%) when comparing SVT to VT. Using a cutoff value of 50% change from NSR, the ratio of first-order to zero-order QR coefficient was able to completely separate VT from SVT (P=0.03) in this series of patients. CONCLUSION: Our data demonstrate the feasibility of simple polynomial equations that reproduce the depolarization and repolarization phases of human ventricular shock EGM. The ratio of first-order to zero-order QR coefficient was able to reliably discriminate between SVT and VT while reducing the polynomial model to a first-order system. The results of this pilot trial may serve as the basis for a larger prospective trial implementing a discrimination algorithm for use in low computational power implantable devices.
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Williams et al. (2006) conducted an observational in Implantable defibrillator patients with SVT and VT (n=7). Polynomial-modeled ventricular electrograms was evaluated on Discrimination between supraventricular tachycardia (SVT) and ventricular tachycardia (VT) (p=0.03). Using a cutoff value of 50% change from normal sinus rhythm, the ratio of first-order to zero-order QR coefficient completely separated ventricular tachycardia from supraventricular tachycardia (P=0.03).
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