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Predictors for living at home after geriatric inpatient rehabilitation: A prospective cohort study.

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OBJECTIVE To evaluate patient characteristics predicting living at home after geriatric rehabilitation. DESIGN Prospective cohort study. PATIENTS A total of 210 patients aged 65 years or older receiving inpatient rehabilitation.… Click to show full abstract

OBJECTIVE To evaluate patient characteristics predicting living at home after geriatric rehabilitation. DESIGN Prospective cohort study. PATIENTS A total of 210 patients aged 65 years or older receiving inpatient rehabilitation. METHODS Candidate predictors evaluated during rehabilitation were: age, vulnerability (Vulnerable Elders Survey), multimorbidity (Cumulative Illness Rating Scale), cognition (Mini-Mental State Examination), depression (Hospital Anxiety and Depression Scale), living alone, previous independence in activities of daily living, fall risk, and mobility at discharge (Timed Up and Go test). Multiple imputation data-sets, bivariate and multiple regression were used to build a predictive model for living at home, which was evaluated at 3-month follow-up. RESULTS A total of 210 patients (mean age 76.0 years, 46.2% women) were included in the study. Of these, 87.6% had been admitted to geriatric rehabilitation directly from acute hospital care. Follow-up was complete in 75.2% of patients. The strongest predictor for living at home was better mobility at discharge (Timed Up and Go test < 20 s), followed by lower multimorbidity, better cognition, and not living alone. In bivariate regression, living at home was also associated with age, fall risk, vulnerability, depression, and previous independence in activities of daily living. CONCLUSION Mobility is the most important predictive factor for living at home after geriatric rehabilitation. Assessment and training of mobility are therefore key aspects in geriatric rehabilitation.

Keywords: study; geriatric rehabilitation; home geriatric; living home; rehabilitation

Journal Title: Journal of rehabilitation medicine
Year Published: 2017

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