Abstract

Introduction: Risk models are greatly needed to target appropriate patients for implantable cardioverter defibrillators (ICDs) in clinical practice for primary prevention of sudden death. Hypothesis: We hypothesized that the Seattle Heart Failure Model (SHFM) for overall survival and the Seattle Proportional Risk Model (SPRM) for proportional risk of arrhythmic death (AD) would identify National Cardiovascular Data Registry (NCDR) ICD Registry patients most likely to have improved survival with versus without an ICD. Methods: SHFM and SPRM scores were determined for patients with and without ICDs (ICD Registry versus a control group derived from the University of Washington Registry, Italian Heart Failure Registry, Swedish Heart Failure Registry, COMET, Val-HeFT, and PRAISE trials). Multivariable Cox proportional hazards regression was used to evaluate adjusted associations of SPRM and SHFM with survival over 5 years from the Social Security Death Index. Results: Among 98,846 patients (87,914 with ICDs and 10,932 without ICDs), increasing SFHM risk was strongly associated with decreased survival (P<0.0001). Compared with patients having a lower SPRM-predicted proportional risk of AD, patients with a higher predicted proportional AD risk had approximately twice the ICD survival benefit (HR 0.602 [95% CI 0.537-0.675] for SPRM quintile 5 versus HR 0.793 [0.736-0.855] for SPRM quintile 1). The ICD-SPRM interaction was highly significant (Figure). The ICD did not improve adjusted survival versus controls in the 25% of patients with higher predicted survival (SHFM < mean) but a lower proportional AD risk (SPRM < mean) (HR 0.921, 95% CI 0.787-1.08, P=0.31); however, survival in patients with opposite findings (SHFM > mean, SPRM > mean) was greatly improved versus controls (HR 0.599, 95% CI 0.530-0.677, P<0.0001). Conclusions: The SHFM and SPRM scores together identify real-world patients most likely to benefit from primary prevention ICD implantation.

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