4.7 Article Proceedings Paper

Comorbidity assessment using the Index of Coexistent Diseases in a multicenter clinical trial

期刊

KIDNEY INTERNATIONAL
卷 60, 期 4, 页码 1498-1510

出版社

BLACKWELL SCIENCE INC
DOI: 10.1046/j.1523-1755.2001.00954.x

关键词

case-mix adjustment; risk assessment; randomized clinical trial; population sampling; dialysis; instrument

资金

  1. NIDDK NIH HHS [U01DK 49241, U01DK 49243, U01DK 49244, U01DK 49249, U01DK 49252, U01DK 49254, U01DK 49259, U01DK 49261, U01DK 49264, U01DK 49271, UO1DK49242, U01 DK 46114, U01DK 46109, U01DK 46126, U01DK 46143, U01DK 49240] Funding Source: Medline

向作者/读者索取更多资源

Background. The Hemodialysis (HEMO) Study is a multicenter trial designed to determine whether hemodialysis dose and membrane flux affect survival. Comorbid conditions are also important determinants of survival, and thus, an accurate and reliable method to assess comorbidity was required. Comorbidity was being assessed at baseline and annually in the HEMO Study using the Index of Coexistent Disease (ICED). We describe the instrument. its implementation in the HEMO Study, and the results of comorbidity assessment in the first 1000 randomized patients in the trial. Methods. The ICED aggregated the presence and severity of 19 medical conditions and 11 physical impairments within two scales: the Index of Disease Severity (IDS) and the Index of Physical Impairment (IPI). The final ICED score was determined by an algorithm combining the peak scores for the IDS and IPI. The range of the ICED was from 0 to 3, reflecting increasing severity. Results. Study personnel at 15 clinical centers were trained to update and abstract data from the dialysis medical records. Availability of data, measures of construct validity, and measures of reliability were adequate; 99.8% and 60.6% of patients had comorbid conditions in at least one IDS or IPI category, respectively. The distribution of patients by ICED level was 0 (02%), 1 (34.9%). 2 (31.2%), and 3 (33.7%). In multivariable analysis, the following factors were significantly associated with more severe comorbidity: older age, diabetes and other causes of renal disease, a lower level of education, employment status (unemployed and retired), longer duration of dialysis, and lower serum creatinine. There was a significant variation in the severity of comorbidity among clinical centers after adjustment for other factors. The R-2 of the model was 25.3%, indicating that a substantial proportion of the variation in the ICED was not explained by these factors. Conclusions. We conclude that comorbidity assessment using the ICED is feasible in multicenter clinical trials of dialysis patients. There is a large burden of comorbidity in dialysis patients, which is not well explained by the cause of renal disease, demographic, and socioeconomic factors and common clinical and laboratory measurements. These variables should not be considered substitutes for comorbid conditions in case-mix adjustment. Comorbidity assessment is useful to describe the sample population, to improve the precision of the treatment effect, and to use possibly as an outcome measurement.

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