Predicting people with stroke at risk of falls

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Description/Abstract

Background: falls are common following a stroke, but knowledge about predicting future fallers is lacking.

Objective: to identify, at discharge from hospital, those who are most at risk of repeated falls.

Methods: consecutively hospitalised people with stroke (independently mobile prior to stroke and with intact gross cognitive function) were recruited. Subjects completed a battery of tests (balance, function, mood and attention) within 2 weeks of leaving hospital and at 12 months post hospital discharge.

Results: 122 participants (mean age 70.2 years) were recruited. Fall status at 12 months was available for 115 participants and of those, 63 [55%; 95% confidence interval (CI) 46–64] experienced one or more falls, 48 (42%; 95% CI 33–51) experienced repeated falls, and 62 (54%) experienced near-falls. All variables available at discharge were screened as potential predictors of falling. Six variables emerged [near-falling in hospital, Rivermead leg and trunk score, Rivermead upper limb score, Berg Balance score, mean functional reach, and the Nottingham extended activities of daily living (NEADL) score]. A score of near-falls in hospital and upper limb function was the best predictor with 70% specificity and 60% sensitivity.

Conclusion: participants who were unstable (near-falls) in hospital with poor upper limb function (unable to save themselves) were most at risk of falls.