Key result
ICD shock and mortality prediction models fail to identify patients with insufficient device benefit.
Why the study?
Can prediction models accurately predict appropriate ICD shock and all-cause mortality to identify patients with insufficient benefit from primary prevention ICD implantation?
Population
1441 development and 1450 validation patients with reduced left ventricular function scheduled for primary prevention ICD
Design
Cohort study for prediction model development and external validation
Follow-up
Median 2.4 years (development) and 2.7 years (validation)
Authors
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Current models insufficient for routine ICD risk stratification; leaves open need for superior predictors in primary prevention.
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?
Effect estimate: C-statistic 0.60-0.74
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.
Verstraelen et al. (2021) 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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