An improved comorbidity index for outcome analyses among dialysis patients

被引:275
作者
Liu, Jiannong [1 ]
Huang, Zhi [2 ]
Gilbertson, David T.
Foley, Robert N. [3 ]
Collins, Allan J. [3 ]
机构
[1] US Renal Data Syst, Coordinating Ctr, Minneapolis, MN 55404 USA
[2] Abbott Labs, GPRD, Clin Stat, Abbott Pk, IL USA
[3] Univ Minnesota, Dept Med, Minneapolis, MN 55455 USA
关键词
comorbidity score; dialysis patients; outcome analysis; validation; PERITONEAL-DIALYSIS; SURVIVAL; HEMODIALYSIS; DISEASE;
D O I
10.1038/ki.2009.413
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Since comorbid conditions are highly prevalent among patients with end-stage renal disease, indexes measuring them have been widely used to describe the comorbidity burden and to predict outcomes as well as adjust for their roles as confounders. The current comorbidity indexes, however, were developed for general populations or on small patient cohorts. In this study we developed a new index for mortality analyses of dialysis patients based on the 2000 US incident dialysis population, and validated this using the 1999 and 2001 incident and 2000 prevalent dialysis patient populations. Numerical weights were assigned to the comorbid conditions of atherosclerotic heart disease, congestive heart failure, cerebrovascular accident/transient ischemic attack, peripheral vascular disease, dysrhythmia, other cardiac diseases, chronic obstructive pulmonary disease, gastrointestinal bleeding, liver disease, cancer, and diabetes. A patient's comorbidity score was the sum of the weights corresponding to the individual conditions present and could be used as a continuous variable in analyses. Our index performance was almost identical to the individual comorbid conditions regarding model fit, predictive ability, and effect on inference, and it outperformed the widely used Charlson Comorbidity Index.
引用
收藏
页码:141 / 151
页数:11
相关论文
共 21 条
[1]  
[Anonymous], USRDS 2005 ANN DAT R
[2]   Comorbidity assessment in hemodialysis and peritoneal dialysis using the index of coexistent disease [J].
Athienites, NV ;
Miskulin, DC ;
Fernandez, G ;
Bunnapradist, S ;
Simon, G ;
Landa, M ;
Schmid, CH ;
Greenfield, S ;
Levey, AS ;
Meyer, KB .
SEMINARS IN DIALYSIS, 2000, 13 (05) :320-326
[3]   A simple comorbidity scale predicts clinical outcomes and costs in dialysis patients [J].
Beddhu, S ;
Bruns, FJ ;
Saul, M ;
Seddon, P ;
Zeidel, ML .
AMERICAN JOURNAL OF MEDICINE, 2000, 108 (08) :609-613
[4]   A NEW METHOD OF CLASSIFYING PROGNOSTIC CO-MORBIDITY IN LONGITUDINAL-STUDIES - DEVELOPMENT AND VALIDATION [J].
CHARLSON, ME ;
POMPEI, P ;
ALES, KL ;
MACKENZIE, CR .
JOURNAL OF CHRONIC DISEASES, 1987, 40 (05) :373-383
[5]   Comparison and survival of hemodialysis and peritoneal dialysis in the elderly [J].
Collins, AJ ;
Weinhandl, E ;
Snyder, JJ ;
Chen, SC ;
Gilbertson, D .
SEMINARS IN DIALYSIS, 2002, 15 (02) :98-102
[6]   COMORBIDITY, UREA KINETICS, AND APPETITE IN CONTINUOUS AMBULATORY PERITONEAL-DIALYSIS PATIENTS - THEIR INTERRELATIONSHIP AND PREDICTION OF SURVIVAL [J].
DAVIES, SJ ;
RUSSELL, L ;
BRYAN, J ;
PHILLIPS, L ;
RUSSELL, GI .
AMERICAN JOURNAL OF KIDNEY DISEASES, 1995, 26 (02) :353-361
[7]   ADAPTING A CLINICAL COMORBIDITY INDEX FOR USE WITH ICD-9-CM ADMINISTRATIVE DATABASES [J].
DEYO, RA ;
CHERKIN, DC ;
CIOL, MA .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 1992, 45 (06) :613-619
[8]   Charlson comorbidity index as a predictor of outcomes in incident peritoneal dialysis patients [J].
Fried, L ;
Bernardini, J ;
Piraino, B .
AMERICAN JOURNAL OF KIDNEY DISEASES, 2001, 37 (02) :337-342
[9]  
Harrell FE., 2001, Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis
[10]  
Hebert P L, 1999, Am J Med Qual, V14, P270, DOI 10.1177/106286069901400607