Identifying falls remotely in people with multiple sclerosis

J Neurol. 2022 Apr;269(4):1889-1898. doi: 10.1007/s00415-021-10743-y. Epub 2021 Aug 17.


Background: Falling is common in people with multiple sclerosis (MS) but tends to be under-ascertained and under-treated.

Objective: To evaluate fall risk in people with MS.

Methods: Ninety-four people with MS, able to walk > 2 min with or without an assistive device (Expanded Disability Status Scale (EDSS ≤ 6.5) were recruited. Clinic-based measures were recorded at baseline and 1 year. Patient-reported outcomes (PROs), including a fall survey and the MS Walking Scale (MSWS-12), were completed at baseline, 1.5, 3, 6, 9, and 12 months. Average daily step counts (STEPS) were recorded using a wrist-worn accelerometer.

Results: 50/94 participants (53.2%) reported falling at least once. Only 56% of participants who reported a fall on research questionnaires had medical-record documented falls. Fallers had greater disability [median EDSS 5.5 (IQR 4.0-6.0) versus 2.5 (IQR 1.5-4.0), p < 0.001], were more likely to have progressive MS (p = 0.003), and took fewer STEPS (mean difference - 1,979, p = 0.007) than Non-Fallers. Stepwise regression revealed MSWS-12 as a major predictor of future falls.

Conclusions: Falling is common in people with MS, under-reported, and under-ascertained by neurologists in clinic. Multimodal fall screening in clinic and remotely may help improve patient care by identifying those at greatest risk, allowing for timely intervention and referral to specialized physical rehabilitation.

Keywords: Fall; Falling; Multiple sclerosis; Outcome measurement; Quality improvement; Remote monitoring.

MeSH terms

  • Humans
  • Multiple Sclerosis* / complications
  • Multiple Sclerosis* / diagnosis
  • Multiple Sclerosis* / epidemiology
  • Multiple Sclerosis, Chronic Progressive*
  • Patient Reported Outcome Measures
  • Walking