4.7 Article

Fall predictors in older cancer patients: a multicenter prospective study

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BMC GERIATRICS
卷 14, 期 -, 页码 -

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BMC
DOI: 10.1186/1471-2318-14-135

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Older persons; Cancer; Falls; Geriatric assessment

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  1. Vlaamse Liga tegen Kanker

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Background: In the older population falls are a common problem and a major cause of morbidity, mortality and functional decline. The etiology is often multifactorial making the identification of fall predictors essential for preventive measures. Despite this knowledge, data on falls within the older cancer population are limited. The objective of this study was to evaluate the occurrence of falls within 2 to 3 months after cancer treatment decision and to identify predictors of falls (>= 1 fall) during follow-up. Methods: Older patients (70 years or more) with a cancer treatment decision were included. At baseline, all patients underwent geriatric screening (G8 and Flemish Triage Risk Screening Tool), followed by a geriatric assessment including living situation, activities of daily living (ADL), instrumental activities of daily living (IADL), fall history in the past 12 months, fatigue, cognition, depression, nutrition, comorbidities and polypharmacy. Questionnaires were used to collect follow-up (2-3 months) data. Univariate and multivariate analyses were performed to identify predictors for falls (>= 1 fall) during follow-up. Results: At baseline, 295 (31.5%) of 937 included patients reported at least one fall in the past 12 months with 88 patients (29.5%) sustaining a major injury. During follow-up (2-3 months), 142 (17.6%) patients fell, of whom 51.4% fell recurrently and 17.6% reported a major injury. Baseline fall history in the past 12 months (OR = 3.926), fatigue (OR = 0.380), ADL dependency (OR = 0.492), geriatric risk profile by G8 (OR = 0.471) and living alone (OR = 1.631) were independent predictors of falls (>= 1 fall) within 2-3 months after cancer treatment decision. Conclusion: Falls are a serious problem among older cancer patients. Geriatric screening and assessment data can identify patients at risk for a fall. A patient with risk factors associated with falls should undergo further evaluation and intervention to prevent potentially injurious fall incidents.

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