BACKGROUND: Monitoring arrhythmic risk may improve management of patients with implantable cardioverter-defibrillators (ICD) and prevent ICD shocks. Changes in repolarization duration between subsequent beats quantified as short-term variability (STV) is associated with ventricular arrhythmias in several animal models. OBJECTIVE: We evaluated STV of QT from right ventricular intracardiac ICD electrograms in patients with structural heart disease and compared its predictive value with the QT variability index (QTVI). METHODS: In 233 patients, STV over 60 beats for QT and RR intervals and their ratio was calculated (STV(QT), STV(RR), STV(Ratio), respectively). QTVI was derived from mean and SD of QT and heart rate. Follow-up duration was 26 ± 15 months. Predictive value was determined for sudden arrhythmic death (SAD) defined as sudden cardiac death or fast ventricular tachycardia/fibrillation [CL < 240 ms]. RESULTS: In univariate analysis, STV(Ratio), but not STV(QT) or STV(RR), was predictive of SAD. Hazard ratios for highest quartile STV(Ratio) and QTVI were comparable (STV(Ratio): 1.9, 95% confidence interval [CI] 1.1 to 3.3, P = .038, QTVI: 2.2, 95% CI 1.2 to 3.8, P = .010). In a multivariate model, highest quartile STV(Ratio) was predictive of SAD after adjustment for New York Heart Association class, history of ischemia, ICD indication, and use of class I antiarrhythmics (hazard ratio 1.8, 95% CI 1.0 to 3.4, P < .050). A combined criterion of highest quartile for both STV(Ratio) and QTVI identified patients at highest risk (hazard ratio 2.4, 95% CI 1.3 to 4.3, P = .005, positive predictive value 38%, negative predictive value 82%). CONCLUSION: STV(Ratio) from ICD electrograms is predictive of SAD. Predictive value is similar for order-based STV(Ratio) and distribution-based QTVI, but the combination of both parameters can further improve results.
BACKGROUND: Monitoring arrhythmic risk may improve management of patients with implantable cardioverter-defibrillators (ICD) and prevent ICD shocks. Changes in repolarization duration between subsequent beats quantified as short-term variability (STV) is associated with ventricular arrhythmias in several animal models. OBJECTIVE: We evaluated STV of QT from right ventricular intracardiac ICD electrograms in patients with structural heart disease and compared its predictive value with the QT variability index (QTVI). METHODS: In 233 patients, STV over 60 beats for QT and RR intervals and their ratio was calculated (STV(QT), STV(RR), STV(Ratio), respectively). QTVI was derived from mean and SD of QT and heart rate. Follow-up duration was 26 ± 15 months. Predictive value was determined for sudden arrhythmic death (SAD) defined as sudden cardiac death or fast ventricular tachycardia/fibrillation [CL < 240 ms]. RESULTS: In univariate analysis, STV(Ratio), but not STV(QT) or STV(RR), was predictive of SAD. Hazard ratios for highest quartile STV(Ratio) and QTVI were comparable (STV(Ratio): 1.9, 95% confidence interval [CI] 1.1 to 3.3, P = .038, QTVI: 2.2, 95% CI 1.2 to 3.8, P = .010). In a multivariate model, highest quartile STV(Ratio) was predictive of SAD after adjustment for New York Heart Association class, history of ischemia, ICD indication, and use of class I antiarrhythmics (hazard ratio 1.8, 95% CI 1.0 to 3.4, P < .050). A combined criterion of highest quartile for both STV(Ratio) and QTVI identified patients at highest risk (hazard ratio 2.4, 95% CI 1.3 to 4.3, P = .005, positive predictive value 38%, negative predictive value 82%). CONCLUSION:STV(Ratio) from ICD electrograms is predictive of SAD. Predictive value is similar for order-based STV(Ratio) and distribution-based QTVI, but the combination of both parameters can further improve results.
Authors: Larisa G Tereshchenko; Iwona Cygankiewicz; Scott McNitt; Rafael Vazquez; Antoni Bayes-Genis; Lichy Han; Sanjoli Sur; Jean-Philippe Couderc; Ronald D Berger; Antoni Bayes de Luna; Wojciech Zareba Journal: Circ Arrhythm Electrophysiol Date: 2012-06-23
Authors: Mathias Baumert; Alberto Porta; Marc A Vos; Marek Malik; Jean-Philippe Couderc; Pablo Laguna; Gianfranco Piccirillo; Godfrey L Smith; Larisa G Tereshchenko; Paul G A Volders Journal: Europace Date: 2016-01-27 Impact factor: 5.214
Authors: Jonathan W Waks; Elsayed Z Soliman; Charles A Henrikson; Nona Sotoodehnia; Lichy Han; Sunil K Agarwal; Dan E Arking; David S Siscovick; Scott D Solomon; Wendy S Post; Mark E Josephson; Josef Coresh; Larisa G Tereshchenko Journal: J Am Heart Assoc Date: 2015-01-19 Impact factor: 5.501
Authors: Andrea Orosz; Éva Csajbók; Csilla Czékus; Henriette Gavallér; Sándor Magony; Zsuzsanna Valkusz; Tamás T Várkonyi; Attila Nemes; István Baczkó; Tamás Forster; Tibor Wittmann; Julius Gy Papp; András Varró; Csaba Lengyel Journal: PLoS One Date: 2015-04-27 Impact factor: 3.240