Mortality after cardioverter-defibrillator replacement: Results of the DECODE survival score index

Published:November 26, 2020DOI:


      Device replacement is the ideal time to reassess health care goals regarding continuing implantable cardioverter-defibrillator (ICD) therapy. Only few data are available on the decision making at this time.


      The goals of this study were to identify factors associated with poor prognosis at the time of ICD replacement and to develop a prognostic index able to stratify those patients at risk of dying early.


      DEtect long-term COmplications after implantable cardioverter-DEfibrillator replacement (DECODE) was a prospective, single-arm, multicenter cohort study aimed at estimating long-term complications in a large population of patients who underwent ICD/cardiac resynchronization therapy – defibrillator replacement. Potential predictors of death were investigated, and all these factors were gathered into a survival score index (SUSCI).


      We included 983 consecutive patients (median age 71 years (63-78)); 750 (76%) were men, 537 (55%) had ischemic cardiomyopathy; 460 (47%) were implanted with cardiac resynchronization therapy – defibrillator. During a median follow-up period of 761 days (interquartile range 628–904 days), 114 patients (12%) died. In multivariate Cox regression analysis, New York Heart Association class III/IV, ischemic cardiomyopathy, body mass index < 26 kg/m2, insulin administration, age ≥ 75 years, history of atrial fibrillation, and hospitalization within 30 days before ICD replacement remained associated with death. The survival score index showed a good discriminatory power with a hazard ratio of 2.6 (95% confidence interval 2.2–3.1; P < .0001). The risk of death increased according to the severity of the risk profile ranging from 0% (low risk) to 47% (high risk).


      A simple score that includes a limited set of variables appears to be predictive of total mortality in an unselected real-world population undergoing ICD replacement. Evaluation of the patient’s profile may assist in predicting vulnerability and should prompt individualized options, especially for high-risk patients.


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