Terry King-Wing Ma1, Kai Ming Chow1, Bonnie Ching-Ha Kwan1, Jack Kit-Chung Ng1, Wing-Fai Pang1, Chi Bon Leung1, Philip Kam-To Li1, Cheuk Chun Szeto2. 1. Carol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. 2. Carol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. ccszeto@cuhk.edu.hk.
Abstract
BACKGROUND: Several comorbidity scoring systems have been developed and validated, mostly in western hemodialysis patients with a high risk of cardiovascular disease. The performance of comorbidity scoring, however, depends on the patient population. In this study, we determine the optimal comorbidity scoring system for predicting survival of incident Chinese PD patients. METHODS: We studied 461 incident PD patients. The performance of Charlson Comorbidity Index (CCI), Hemmelgarn score, and Liu score as the survival predictor was compared. RESULTS: The mean age was 57.7 ± 13.7 years. The median CCI, Hemmelgarn, and Liu scores were 4 [inter-quartile range (IQR) 2-5], 1 (IQR 0-2), and 4 (IQR 2-5), respectively. Patients were followed for 45.5 ± 33.0 months. All 3 comorbidity scores were predictors of patient survival by univariate analysis. After adjusting for confounding factors, CCI was the best predictor of patient survival among the 3 indices, with each point increase in CCI conferring 31% excess in mortality risk [95% confidence interval (CI) 21-41%, p < 0.001]. In contrast, each point increase in Liu score confers 20% excess in mortality risk (95% CI 13-27%, p < 0.001). Although the Hemmelgarn score is an independent predictor of patient survival, over 70% of patients score 0 or 1 by this system, limiting its role as a prognostic marker. CONCLUSION: CCI should be the preferred method for quantifying comorbidity load in incident Chinese PD patients, and it is a good predictor of survival in this group of patients.
BACKGROUND: Several comorbidity scoring systems have been developed and validated, mostly in western hemodialysis patients with a high risk of cardiovascular disease. The performance of comorbidity scoring, however, depends on the patient population. In this study, we determine the optimal comorbidity scoring system for predicting survival of incident Chinese PDpatients. METHODS: We studied 461 incident PDpatients. The performance of Charlson Comorbidity Index (CCI), Hemmelgarn score, and Liu score as the survival predictor was compared. RESULTS: The mean age was 57.7 ± 13.7 years. The median CCI, Hemmelgarn, and Liu scores were 4 [inter-quartile range (IQR) 2-5], 1 (IQR 0-2), and 4 (IQR 2-5), respectively. Patients were followed for 45.5 ± 33.0 months. All 3 comorbidity scores were predictors of patient survival by univariate analysis. After adjusting for confounding factors, CCI was the best predictor of patient survival among the 3 indices, with each point increase in CCI conferring 31% excess in mortality risk [95% confidence interval (CI) 21-41%, p < 0.001]. In contrast, each point increase in Liu score confers 20% excess in mortality risk (95% CI 13-27%, p < 0.001). Although the Hemmelgarn score is an independent predictor of patient survival, over 70% of patients score 0 or 1 by this system, limiting its role as a prognostic marker. CONCLUSION: CCI should be the preferred method for quantifying comorbidity load in incident Chinese PDpatients, and it is a good predictor of survival in this group of patients.
Authors: Manoch Rattanasompattikul; Usama Feroze; Miklos Z Molnar; Ramanath Dukkipati; Csaba P Kovesdy; Allen R Nissenson; Keith C Norris; Joel D Kopple; Kamyar Kalantar-Zadeh Journal: Int Urol Nephrol Date: 2011-11-30 Impact factor: 2.370
Authors: Jeannette G van Manen; Johanna C Korevaar; Friedo W Dekker; Elisabeth W Boeschoten; Patrick M M Bossuyt; Raymond T Krediet Journal: Am J Kidney Dis Date: 2002-07 Impact factor: 8.860
Authors: Ryan T Anderson; Hailey Cleek; Atieh S Pajouhi; M Fernanda Bellolio; Ananya Mayukha; Allyson Hart; LaTonya J Hickson; Molly A Feely; Michael E Wilson; Ryan M Giddings Connolly; Patricia J Erwin; Abdul M Majzoub; Navdeep Tangri; Bjorg Thorsteinsdottir Journal: Clin J Am Soc Nephrol Date: 2019-07-30 Impact factor: 8.237