Prediction models for appropriate ICD shock and mortality achieved external validation C-statistics of 0.60 and 0.74, respectively, but failed to identify a large group with insufficient ICD benefit.
Cohort (n=2,891)
Can prediction models accurately predict appropriate ICD shock and all-cause mortality to identify patients with insufficient benefit from primary prevention ICD implantation?
Prediction models for primary prevention ICD efficacy showed moderate discrimination for mortality but poor discrimination for appropriate shocks, highlighting the ongoing challenge of risk stratification.
Effect estimate: C-statistic 0.60-0.74
AIMS: This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. METHODS AND RESULTS: We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. CONCLUSION: Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed.
Verstraelen et al. (Fri,) conducted a cohort in Primary prevention of sudden cardiac death (n=2,891). Prediction models for appropriate ICD shock and mortality was evaluated on Appropriate ICD shock and all-cause mortality (C-statistic 0.60-0.74). Prediction models for appropriate ICD shock and mortality achieved external validation C-statistics of 0.60 and 0.74, respectively, but failed to identify a large group with insufficient ICD benefit.
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