Distinguishing Among Causes of Death for Patients with Kidney Failure on Hemodialysis.

KEY POINTS: We found poor ability to distinguish among different causes of death using clinical information in the 30 days before death for patients on hemodialysis. We found that models of different causes of death identified similar associated clinical factors. Given the lack of clear phenotypic differences, this study questions the usefulness of cause of death in research in dialysis. BACKGROUND: Patients treated with maintenance hemodialysis are at high risk of death from a variety of causes. METHODS: To identify markers (i.e., risk phenotypes) that distinguish among causes of death, we used dialysis electronic health record data for a cohort of adults treated with maintenance in-center hemodialysis who died between 2003 and 2016 (n=19,793). Patients were linked to the United States Renal Data System (USRDS) Files. We classified USRDS-reported causes of death into five categories: sudden cardiac death, nonsudden cardiac death cardiovascular death, infection, others, and unknown. A subcohort was linked to the National Death Index with similar categories defined. We used ensemble classification trees to discriminate among causes using demographics, vital signs, laboratory measures, health service utilization, and comorbidity claims from 30 days before death. We then created nested case-control populations for each cause of death and used ridge logistic regression to evaluate clinical risk markers that associate with distinct causes. RESULTS: The area under the receiver operating characteristic curves from ensemble classification trees were all between 0.59 and 0.70, suggesting minimal ability to distinguish among causes using clinical risk markers. Model coefficients were similar and highly correlated across different cause of death models (i.e., 0.87–0.94). This suggests that most clinical risk markers are shared across causes without distinct risk phenotypes. CONCLUSIONS: We conclude that different causes of death may share similar clinical risk markers in the setting of kidney failure or that the causes of death attributed on USRDS or National Death Index forms are not precise.

Duke Scholars

Author Julia Jarrard Scialla Medicine, Nephrology

Author Jonathan Wilson  

Author Benjamin Alan Goldstein Biostatistics & Bioinformatics, Division of Translational Bi ...