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American Heart Association, Circulation: Arrhythmia and Electrophysiology, 12(11), 2018

DOI: 10.1161/circep.118.006730

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Predictive Score for Identifying Survival and Recurrence Risk Profiles in Patients Undergoing Ventricular Tachycardia Ablation

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Background: Several distinct risk factors for arrhythmia recurrence and mortality following ventricular tachycardia (VT) ablation have been described. The effect of concurrent risk factors has not been assessed so far; thus, it is not yet possible to estimate these risks for a patient with several comorbidities. The aim of the study was to identify specific risk groups for mortality and VT recurrence using the Survival Tree (ST) analysis method. Methods: In 1251 patients 16 demographic, clinical and procedure-related variables were evaluated as potential prognostic factors using ST analysis using a recursive partitioning algorithm that searches for relationships among variables. Survival time and time to VT recurrence in groups derived from ST analysis were compared by a log-rank test. A random forest analysis was then run to extract a variable importance index and internally validate the ST models. Results: Left ventricular ejection fraction, implantable cardioverter defibrillator/cardiac resynchronization device, previous ablation were, in hierarchical order, identified by ST analysis as best predictors of VT recurrence, while left ventricular ejection fraction, previous ablation, Electrical storm were identified as best predictors of mortality. Three groups with significantly different survival rates were identified. Among the high-risk group, 65.0% patients were survived and 52.1% patients were free from VT recurrence; within the medium- and low-risk groups, 84.0% and 97.2% patients survived, 72.4% and 88.4% were free from VT recurrence, respectively. Conclusions: Our study is the first to derive and validate a decisional model that provides estimates of VT recurrence and mortality with an effective classification tree. Preprocedure risk stratification could help optimize periprocedural and postprocedural care.