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Perit Dial Int. 2005 Jul-Aug;25(4):320-32.

Characterizing comorbidity in dialysis patients: principles of measurement and applications in risk adjustment and patient care.

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  • 1Division of Nephrology, New England Medical Center, Boston, Massachusetts 02111, USA. dmiskulin@tufts-nemc.org

Abstract

Comorbid conditions are highly prevalent in dialysis patients and are significant predictors of mortality and other adverse outcomes. Accordingly, it is important to account for differences in comorbid illness burden among groups of dialysis patients being compared. At present, there is no consensus on what conditions matter, how each should be defined, and what weights each carries when defining an individual's risk or case-mix severity. A number of comorbidity instruments, generic or disease specific, have been employed in dialysis populations. They differ by the representation and definition of conditions as well as instrument scoring. No instrument has been found to be superior to another in terms of predictive accuracy for mortality, and accuracy across the board is low. Further studies are needed to determine whether improvements would be found with the use of more specifically defined items and through assignment of item weights based on relationships for outcomes specifically in a dialysis population. The roles of other factors in risk prediction, such as markers of nutritional status, inflammation, or other physiological parameters, relative to comorbid conditions also need to be defined. Outcomes other than mortality are likely to identify different factors and/or different relationships than those noted for mortality, which also require study. Comorbidity is important for risk adjusting comparative analyses in nonrandomized trials and quality of care assessments and may, in future, influence payment for dialysis services. Efforts to improve the management of comorbid illnesses are needed. Comorbid conditions must be documented accurately and uniformly in all dialysis patients to enable these applications.

PMID:
16022085
[PubMed - indexed for MEDLINE]
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