BACKGROUND AND OBJECTIVES: There are few data on risk factors for sudden cardiac death (SCD) in patients undergoing hemodialysis (HD). The study objective was to identify predictors associated with various causes of death in the Hemodialysis (HEMO) Study and to develop a prediction model for SCD using a competing risk approach. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In this analysis of 1745 HEMO participants, all-cause mortality was classified as SCD, non-SCD, and noncardiac death. Predictors for each cause of death were evaluated using cause-specific Cox proportional hazards models, and a competing risk approach was used to calculate absolute risk predictions for SCD. RESULTS: During a median follow-up of 2.5 years, 808 patients died. Rates of SCD, non-SCD, and noncardiac death were 22%, 17%, and 61%, respectively. Predictors of various causes of death differ somewhat in HD patients. Age, diabetes, peripheral vascular disease, ischemic heart disease, serum creatinine, and alkaline phosphatase were independent predictors of SCD. The 3-year C-statistic for SCD was 0.75 (95% confidence interval, 0.70-0.79), and calibration was good (χ(2)=1.1; P=0.89). At years 3 and 5 of follow-up, the standard Cox model overestimated the risk for SCD as compared with the competing risk approach on the relative scale by 25% and 46%, respectively, and on the absolute scale by 2% and 6%, respectively. CONCLUSIONS: Predictors of various causes of death differ in HD patients. The proposed prediction model for SCD accounts for competing causes of death. External validation of this model is required.
BACKGROUND AND OBJECTIVES: There are few data on risk factors for sudden cardiac death (SCD) in patients undergoing hemodialysis (HD). The study objective was to identify predictors associated with various causes of death in the Hemodialysis (HEMO) Study and to develop a prediction model for SCD using a competing risk approach. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In this analysis of 1745 HEMO participants, all-cause mortality was classified as SCD, non-SCD, and noncardiac death. Predictors for each cause of death were evaluated using cause-specific Cox proportional hazards models, and a competing risk approach was used to calculate absolute risk predictions for SCD. RESULTS: During a median follow-up of 2.5 years, 808 patients died. Rates of SCD, non-SCD, and noncardiac death were 22%, 17%, and 61%, respectively. Predictors of various causes of death differ somewhat in HDpatients. Age, diabetes, peripheral vascular disease, ischemic heart disease, serum creatinine, and alkaline phosphatase were independent predictors of SCD. The 3-year C-statistic for SCD was 0.75 (95% confidence interval, 0.70-0.79), and calibration was good (χ(2)=1.1; P=0.89). At years 3 and 5 of follow-up, the standard Cox model overestimated the risk for SCD as compared with the competing risk approach on the relative scale by 25% and 46%, respectively, and on the absolute scale by 2% and 6%, respectively. CONCLUSIONS: Predictors of various causes of death differ in HDpatients. The proposed prediction model for SCD accounts for competing causes of death. External validation of this model is required.
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