BACKGROUND: An increasing number of patients starting renal replacement therapy are older and have complex comorbidity. In keeping with these demographics, an increased number of older patients undergo transplantation each year. To date, no study has reported baseline comorbidity characteristics of those who underwent transplantation, validated the use of comorbidity indices, or asked whether comorbidity predicts patient outcome after kidney transplantation. Our objective is to report baseline comorbidity and compare the use of different indices for recipients of kidneys from both deceased and living donors. METHODS: Using data from the Canadian Organ Replacement Registry, we tested the ability of 4 comorbidity indices to predict patient survival by using a Cox regression model. Model covariates included donor source, age, race, sex, treatment period, primary renal disease cause, months on dialysis therapy, and comorbidities. RESULTS: A total of 6,324 patients were included; 22% had > or =1 comorbid condition at baseline. After adjustment for age, sex, and cause of renal disease, increased comorbidity was associated strongly with reduced patient survival. Of all comorbidity indices examined, the model containing the Charlson Comorbidity Index (CCI) offered the best fit. The model containing log--CCI had an index of concordance of 74%. CONCLUSION: The CCI is a suitable tool for the measurement of comorbidity in renal transplant recipients.
BACKGROUND: An increasing number of patients starting renal replacement therapy are older and have complex comorbidity. In keeping with these demographics, an increased number of older patients undergo transplantation each year. To date, no study has reported baseline comorbidity characteristics of those who underwent transplantation, validated the use of comorbidity indices, or asked whether comorbidity predicts patient outcome after kidney transplantation. Our objective is to report baseline comorbidity and compare the use of different indices for recipients of kidneys from both deceased and living donors. METHODS: Using data from the Canadian Organ Replacement Registry, we tested the ability of 4 comorbidity indices to predict patient survival by using a Cox regression model. Model covariates included donor source, age, race, sex, treatment period, primary renal disease cause, months on dialysis therapy, and comorbidities. RESULTS: A total of 6,324 patients were included; 22% had > or =1 comorbid condition at baseline. After adjustment for age, sex, and cause of renal disease, increased comorbidity was associated strongly with reduced patient survival. Of all comorbidity indices examined, the model containing the Charlson Comorbidity Index (CCI) offered the best fit. The model containing log--CCI had an index of concordance of 74%. CONCLUSION: The CCI is a suitable tool for the measurement of comorbidity in renal transplant recipients.
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