title: Predicting hospitalization and mortality in end-stage renal disease (ESRD) patients using an Index of Coexisting Disease (ICED)-based risk stratification model.
abstract: We evaluated the use of an additive Index of Coexisting Diseases (ICED)-based stratification schema to determine subsequent hospitalization and mortality in a hemodialysis population. Patients from five commercial health plans were stratified into low-, medium-, and high-risk groups and followed for up to 1 year. Patients were reassessed and restratified at 90-day intervals and censored when disease management ceased. Outcome measures collected through selfreports and health plan records were captured in an active database. Survival to first hospitalization/ mortality was compared by Kaplan Meier curves, survivor function differences by the Wilcoxon test, and group comparisons by ANOVA and chi square. Population characteristics included mean age of 63.0, 57.7% male, and 58.8% diabetic. Mortality was 13.0% per patient year (standardized mortality ratio 0.43) and the hospitalization rate was 0.59 per patient year (standardized hospitalization ratio 0.24). Survival curves demonstrated differences in mortality and hospitalization between the patients in different initial risk categories (p < 0.01). Mean hospitalizations were 0.81 +/- 1.53 per patient year (high risk), 0.45 +/- 0.99 (medium risk), and 0.15 +/- 0.51 for the low-risk group (p < 0.001). Stratification was dynamic; 47.3% decreased and 4.7% increased risk level between the first and second assessment. These changes were associated with survival differences for initial low (p = 0.06) or medium patients (p < 0.01), and hospital-free survival for initial medium (p = 0.08) or high patients (p < 0.05). In conclusion, this ICED-based stratification schema predicted mortality and hospitalization for hemodialysis patients participating in our disease management program.
authors.affiliation: Fresenius Medical Care North America, Lexington, Massachusetts, USA. jeffrey.sands@fmc-na.com
authors.forename: Jeffrey J
authors.initials: JJ
authors.lastname: Sands
authors.forename: Gina D
authors.initials: GD
authors.lastname: Etheredge
authors.forename: Arti
authors.initials: A
authors.lastname: Shankar
authors.forename: John
authors.initials: J
authors.lastname: Graff
authors.forename: Joanne
authors.initials: J
authors.lastname: Loeper
authors.forename: Mary
authors.initials: M
authors.lastname: McKendry
authors.forename: Robert
authors.initials: R
authors.lastname: Farrell
mesh_terms: D000704:Analysis of Variance; D016009:Chi-Square Distribution; D015897:Comorbidity; D005260:Female; D006305:Health Status Indicators; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D006435:Renal Dialysis; D018570:Risk Assessment; D012307:Risk Factors