Predicting people with stroke at risk of falls

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

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

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.

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.

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