Predicting accidental falls in people with multiple sclerosis — a longitudinal study

Abstract

Objective: To investigate accidental falls and near fall incidents in people with multiple sclerosis with respect to clinical variables and the predictive values of four tests. Design: A longitudinal, multi-centred cohort study with prospectively collected falls. Procedures: Self-reported incidents during the three months following a standardized test procedure. Subjects: Seventy-six people with multiple sclerosis and an Expanded Disability Status Scale score between 3.5 and 6.0. Main outcome measures: Berg Balance Scale, Timed Up and Go cognitive, Four Square Step Test (FSST) and 12-item Multiple Sclerosis Walking Scale. Results: Forty-eight people (63%) registered 270 falls. Most falls occurred indoors during activities of daily life. We found a correlation of rs=0.57 between near falls and falls, and of rs = 0.82 between registered and retrospectively recalled falls. Fallers and non-fallers differed significantly regarding Expanded Disability Status Score (odds ratio (OR) 1.99, 95% confidence interval (CI) 1.22; 3.40), spasticity (OR 1.14, CI 1.02; 1.31), proprioception (OR 2.50, CI 1.36; 5.12) and use of walking aids (OR 2.27, CI 1.23; 4.37). Reported use of walking aids both indoors and outdoors increased the odds of falling fivefold while disturbed proprioception increased the odds 2.5—15.6 times depending on severity. The odds of falling were doubled for each degree of increased Expanded Disability Status Score and more than doubled for each degree of increased spasticity. The Berg Balance Scale, use of walking aids and Timed Up and Go cognitive best identified fallers (73—94%) and proprioception, Expanded Disability Status Score, 12-item Multiple Sclerosis Walking Scale and Four Square Step Test best identified non-fallers (75—93%). Conclusions: In clinical practice, looking at the use of walking aids, investigating proprioception and spasticity, rating Expanded Disability Status Score and using Berg Balance Scale or Timed Up and Go cognitive all contribute when identifying fallers.