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A New Single Chamber Implantable Defibrillator with Atrial Sensing: A Practical Demonstration of Sensing and Ease of Implantation
Published on: February 28, 2012
A Decision Tree-Based Survival Analysis of Patients with a History of Inappropriate Implantable
Masaru Yamamoto1, Katsunori Okajima2, Akira Shimane2
1Department of Laboratory Medicine, Fujita Health University Hospital.
Abstract:
Implantable cardioverter-defibrillators (ICDs) improve survival in patients who are at risk of sudden death. However, inappropriate therapy is commonly given to ICD recipients, and this situation may be associated with an increased risk of death. This study aimed to construct a risk stratification scheme by using decision tree analysis in patients who received inappropriate ICD therapy.Mortality was calculated from a retrospective data analysis of a multicenter cohort involving 417 ICD recipients. Inappropriate therapy was defined as therapy for nonventricular arrhythmias, including sinus tachycardia, supraventricular tachycardia, atrial fibrillation/flutter, oversensing, and lead failure. Inappropriate therapy included antitachycardia pacing, cardioversion, and defibrillation. The prognostic factors were identified by a Cox proportional hazards regression analysis, and we constructed a decision tree.During an average follow-up of 5.2 years, 48 patients (12%) had all-cause death. A multivariate Cox hazard model revealed that the age (hazard ratio [HR] 1.06, P < 0.001), ln B-type natriuretic peptide (BNP) (HR 1.47, P = 0.02), nonsinus rhythm at implantation (HR 2.70, P < 0.05), and inappropriate therapy occurring during sedentary/awake conditions (HR 3.51, P = 0.001) correlated with an increased risk of mortality. An inappropriate therapy due to abnormal sensing (HR 0.16, P = 0.04) decreased the risk of mortality. Furthermore, a decision tree analysis stratified the patients well by using 4 covariates: BNP, activity at the time of inappropriate therapy, mechanism of inappropriate therapy, and baseline rhythm at ICD implantation (log-rank test, P < 0.0001).We identified the predictors of mortality in inappropriate ICD therapy recipients and constructed a risk stratification scheme by using decision tree analysis.
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