A decision tree-based survival analysis of patients with a history of inappropriate implantable cardioverter-defibrillator therapy

Masaru Yamamoto, Katsunori Okajima, Akira Shimane, Tomoya Ozawa, Itsuro Morishima, Toru Asai, Masahiko Takagi, Atsunobu Kasai, Eitaro Fujii, Ken Kiyono, Eiichi Watanabe, Yukio Ozaki

Research output: Contribution to journalArticle

Abstract

Summary 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.

Original languageEnglish
Pages (from-to)318-326
Number of pages9
JournalInternational heart journal
Volume60
Issue number2
DOIs
Publication statusPublished - 01-01-2019

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Decision Trees
Implantable Defibrillators
Survival Analysis
Decision Support Techniques
Therapeutics
Mortality
Brain Natriuretic Peptide
Proportional Hazards Models
Sinus Tachycardia
Electric Countershock
Atrial Flutter
Supraventricular Tachycardia
Sudden Death
Atrial Fibrillation
Cardiac Arrhythmias
Cause of Death
Regression Analysis

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine

Cite this

Yamamoto, Masaru ; Okajima, Katsunori ; Shimane, Akira ; Ozawa, Tomoya ; Morishima, Itsuro ; Asai, Toru ; Takagi, Masahiko ; Kasai, Atsunobu ; Fujii, Eitaro ; Kiyono, Ken ; Watanabe, Eiichi ; Ozaki, Yukio. / A decision tree-based survival analysis of patients with a history of inappropriate implantable cardioverter-defibrillator therapy. In: International heart journal. 2019 ; Vol. 60, No. 2. pp. 318-326.
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Yamamoto, M, Okajima, K, Shimane, A, Ozawa, T, Morishima, I, Asai, T, Takagi, M, Kasai, A, Fujii, E, Kiyono, K, Watanabe, E & Ozaki, Y 2019, 'A decision tree-based survival analysis of patients with a history of inappropriate implantable cardioverter-defibrillator therapy', International heart journal, vol. 60, no. 2, pp. 318-326. https://doi.org/10.1536/ihj.18-288

A decision tree-based survival analysis of patients with a history of inappropriate implantable cardioverter-defibrillator therapy. / Yamamoto, Masaru; Okajima, Katsunori; Shimane, Akira; Ozawa, Tomoya; Morishima, Itsuro; Asai, Toru; Takagi, Masahiko; Kasai, Atsunobu; Fujii, Eitaro; Kiyono, Ken; Watanabe, Eiichi; Ozaki, Yukio.

In: International heart journal, Vol. 60, No. 2, 01.01.2019, p. 318-326.

Research output: Contribution to journalArticle

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T1 - A decision tree-based survival analysis of patients with a history of inappropriate implantable cardioverter-defibrillator therapy

AU - Yamamoto, Masaru

AU - Okajima, Katsunori

AU - Shimane, Akira

AU - Ozawa, Tomoya

AU - Morishima, Itsuro

AU - Asai, Toru

AU - Takagi, Masahiko

AU - Kasai, Atsunobu

AU - Fujii, Eitaro

AU - Kiyono, Ken

AU - Watanabe, Eiichi

AU - Ozaki, Yukio

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Summary 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.

AB - Summary 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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