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Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Frailty bias in comorbidity risk adjustments of community-dwelling elderly populations
1Columbia University, College of Physicians and Surgeons, Gertrude H. Sergievsky Center, New York, New York 10032, USA.
Abstract:
Our objective was to describe distortion in outcome studies due to "frailty bias" or differential susceptibility to adverse health outcomes due to frailties but attributed to other factors. We linked an administrative database to survey data (n = 5934) containing functional, condition, and outcome measures. The disease classification scheme of an empirically derived mortality model was used to categorize 7500 ICD-9-CM codes into five risk levels. Cox and logistic regressions were used to compare outcomes. Commonly employed measures differ in their sensitivity to detect and control frailty bias across a spectrum of major chronic diseases. Survival is inversely related to increasing functional impairment after adjusting for age, race, gender, education, number of comorbid conditions, and highest disease risk occurring during follow-up. Functional status appears to be a superior and essential element for control of the frailty bias that threatens comparability of outcome measures across community-dwelling populations containing chronically-ill disabled elderly.
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