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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 and functional decline indices predict poor outcomes in hospitalised older people
Elsa Dent1, Ian Chapman2, Stuart Howell3
1Discipline of Medicine, University of Adelaide, Adelaide, South Australia, Australia.
Background:
admission to a Geriatric Evaluation and Management Unit (GEMU) can optimise a patient's chance of functional recovery.
Objective:
to evaluate the ability of several commonly used frailty and functional decline indices to predict GEMU outcomes, both at discharge and at 6 months.
Design:
prospective, observational study.
Setting And Participants:
consecutive GEMU patients aged ≥70 years.
Methods:
patients were classified as 'frail' or 'at high risk of functional decline' using several frailty and functional decline instruments. Predictive ability was evaulated using logistic regression and area under receiver operator characteristic (ROC) curves (auROC).
Results:
a total of 172 patients were included. Frailty prevalence varied from 24 to 94% depending on the instrument used. Several instruments predicted patients at risk of poor outcome, including the Frailty Index of Accumulative Deficits (FI-CD), Fried's Cardiovascular Health Study index, the Study of Osteoporotic Fractures index, an adapted Katz score of activities of daily living (ADL), Instrumental ADL, the Score Hospitalier d'Evaluation du Risque de Perte d'Autonomie (SHERPA) and grip strength [odds ratio (OR) range of 2.06-6.47]. Adequate discriminatory power for discharge outcome was achieved by the FI-CD (auROC = 0.735, P < 0.001) and an adapted Katz score (auROC = 0.704, P = < 0.001). The FI-CD also showed adequate discriminatory power for a poor 6-month outcome (auROC = 0.702, P < 0.001).
Conclusion:
frailty and functional decline instruments can predict older patients at risk of poor outcome. However, only the FI-CD showed adequate discriminatory power for outcome prediction at both follow-up time-points.
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