Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability

Allali, Gilles; Laidet, Magali; Herrmann, François; Armand, Stéphane; Edelsten, Charlotte; Assal, Frédéric; Lalive d'Epinay, Patrice

doi:10.1007/s00702-016-1511-z

Scientific article

English

Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability

ContributorsAllali, Gilles; Laidet, Magali; Herrmann, François; Armand, Stéphane

; Edelsten, Charlotte; Assal, Frédéric; Lalive d'Epinay, Patrice

Published inJournal of neural transmission, vol. 123, no. 4, p. 447-450

Publication date2016

Abstract

This longitudinal study aims to compare the role of stride time variability (STV) and EDSS for predicting falls in 50 patients with multiple sclerosis with low disability. 21.7 % developed falls (follow-up: 22 months). STV (IRR: 1.73, 95 % CI: 1.23-2.41, p = 0.001) and EDSS (IRR: 2.29, 95 % CI: 1.35-3.90, p = 0.002) were associated with the number of falls. Adding STV to EDSS improves the predictive power of the model from 21 to 26 %, but not adding EDSS to STV.

Keywords

Gait disorders
Falls
Disability
Longitudinal study
Multiple sclerosis

Affiliation entities

Research groups

Citation (ISO format)

ALLALI, Gilles et al. Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability. In: Journal of neural transmission, 2016, vol. 123, n° 4, p. 447–450. doi: 10.1007/s00702-016-1511-z

Article (Published version)

Identifiers

PID : unige:84216
DOI : 10.1007/s00702-016-1511-z
PMID : 26846418

Journal ISSN0300-9564

607views

1downloads

Creation11/03/2016 17:42:00

First validation11/03/2016 17:42:00

Update time15/03/2023 01:24:56

Status update15/03/2023 01:24:56

Last indexation31/10/2024 04:34:19

Archive ouverte UNIGE

Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability

Technical informations