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Association of the Dynamic Gait Index to fall history and muscle function in people with multiple sclerosis.

Mark M ManagoMichelle CameronMargaret Schenkman
Published in: Disability and rehabilitation (2019)
Background and purpose: This study examined the association of a commonly used gait assessment, the Dynamic Gait Index, with falls and lower extremity and trunk muscle function in people with multiple sclerosis.Materials and methods: Cross-sectional data from 72 people with multiple sclerosis (Expanded Disability Status Scale 3.5 ± 1.14) were used. The ability of the Dynamic Gait Index to identify fallers was evaluated using the receiver operating characteristic curve. Multiple linear regression determined contributions of muscle function variables to Dynamic Gait Index scores.Results: Thirty-seven participants reported at least one fall in the previous 3 months (51%). The area under the curve for the Dynamic Gait Index was 0.80 (95% CI: 0.69-0.90), indicating a good ability to identify fallers with a cutoff of ≤19/24. After adjusting for age, sex, and disability level, a one standard deviation increase in ankle plantarflexion (15.2 repetitions) and trunk flexion (15.1 repetitions) endurance were associated with an increase in Dynamic Gait Index score of 0.73 (95% CI: 0.07-1.39) and 0.62 (95% CI: 0.002-1.25), respectively.Conclusions: The Dynamic Gait Index may be a useful tool to identify fallers, and was associated with ankle plantarflexion and trunk flexion endurance.Implications for rehabilitationThe Dynamic Gait Index appears to be a useful tool to identify people with multiple sclerosis at increased risk for falls using a cutoff score of ≤19/24.The ability to do fewer than 13 single leg heel raises had a moderate ability to identify fallers in this study.Out of 11 lower extremity and trunk muscles, only ankle plantarflexion and trunk flexion muscle endurance were significant predictors of Dynamic Gait Index scores.Clinicians may consider targeting ankle plantarflexion and trunk muscle endurance to improve dynamic gait and fall risk in patients with multiple sclerosis.
Keyphrases
  • multiple sclerosis
  • skeletal muscle
  • cerebral palsy
  • high intensity
  • cross sectional
  • white matter
  • lower limb
  • machine learning
  • electronic health record
  • drug delivery
  • big data