Affiliation:
1. School of Health Professions, Plymouth University, UK
2. Centre for Medical Statistics and Bioinformatics, Plymouth University, UK
Abstract
Background: People with multiple sclerosis (MS) experience frequent falls, which are associated with impairments and limitations to activities and participations. Objective: The objective of this paper is to evaluate falls risk factors using robust clinical measures. Methods: A total of 150 individuals (confirmed MS diagnosis, Expanded Disability Status Scale (EDSS) 3.5–6.5) were recruited, with 148 participants included in the final analysis. Demographic data were collected and performance assessed in eight predictor measures (Physiological Profile Assessment (PPA), Brief Ataxia Rating scale, Ashworth scale (Ashworth), Modified Falls Efficacy scale, Symbol Digit Modalities Test, dual-task interference, lying/standing blood pressure, static/dynamic visual acuity). Participants prospectively recorded falls over three months using a daily diary. People were classified as “fallers” based on reports of ≥ two falls. Results: A total of 104 participants recorded 672 falls; 78 (52.7%) reported ≥ two falls. Continence issues, previous falls history and use of prescribed medications were each associated with increased risk of being a “faller”. Ashworth and PPA risk score contributed significantly to a logistic regression model predicting faller/non-faller classification. The reduced model (Ashworth, PPA, EDSS) showed fair-to-good predictive ability (ROC c-statistic 0.73, sensitivity 70%, specificity 69%). Conclusion: This study confirms the high prevalence of falls in ambulant people with MS. Important potentially modifiable risk factors are identified, suggesting aspects to target in falls interventions.
Subject
Clinical Neurology,Neurology
Cited by
104 articles.
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