Literature DB >> 20207785

Predicting habitual walking performance in multiple sclerosis: relevance of capacity and self-report measures.

Domien Gijbels1, Geert Alders, Elke Van Hoof, Caroline Charlier, Machteld Roelants, Tom Broekmans, Bert Op 't Eijnde, Peter Feys.   

Abstract

The objective was to establish the extent to which physical functioning capacity and self-report measures are able to predict the habitual walking performance in ambulatory persons with multiple sclerosis. Fifty persons with multiple sclerosis (Expanded Disability Status Scale, EDSS, 1.5-6.5) were tested on leg muscle strength as well as walking and balance capacity, and completed self-report indices on perceived physical functioning. Habitual walking performance, that is, the real amount of steps that is performed in the customary living environment, was registered by means of an ambulant accelerometer-based monitor during seven consecutive days. Mild (EDSS 1.5-4.0, n = 29) and moderate (EDSS 4.5-6.5, n = 21) multiple sclerosis subgroups were additionally distinguished as predictor variables and values were hypothesized to differ depending on multiple sclerosis severity and concomitant ambulatory function. Multiple regression analyses yielded a single most significant predictor for each (sub)group with other variables making no independent contribution to the variation in habitual walking performance. For the total study sample, this was the 6-Minute Walking Test (R(2) = 0.458, p < 0.01). In the mild multiple sclerosis subgroup, the 6-Minute Walking Test was again most predictive, yet to a modest degree (R(2) = 0. 187, p = 0.02). In the moderate multiple sclerosis subgroup, the 2-Minute Walking Test explained over half of the variance (R(2) = 0.532, p < 0.01). Habitual walking performance is best reflected by longer walking capacity tests. The extent to which it can be predicted based on clinical testing is larger in a multiple sclerosis patient sample with more severe walking disability. Ambulatory monitoring, however, includes aspects of community ambulation not captured in the clinic, and must be considered as an additional outcome for evaluating interventions in multiple sclerosis.

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Year:  2010        PMID: 20207785     DOI: 10.1177/1352458510361357

Source DB:  PubMed          Journal:  Mult Scler        ISSN: 1352-4585            Impact factor:   6.312


  39 in total

1.  Walking function in clinical monitoring of multiple sclerosis by telemedicine.

Authors:  Núria Sola-Valls; Yolanda Blanco; Maria Sepúlveda; Sara Llufriu; Elena H Martínez-Lapiscina; Delon La Puma; Francesc Graus; Pablo Villoslada; Albert Saiz
Journal:  J Neurol       Date:  2015-05-10       Impact factor: 4.849

2.  Does a waist-worn accelerometer capture intra- and inter-person variation in walking behavior among persons with multiple sclerosis?

Authors:  Robert W Motl; Jacob J Sosnoff; Deirdre Dlugonski; Yoojin Suh; Myla Goldman
Journal:  Med Eng Phys       Date:  2010-09-26       Impact factor: 2.242

3.  Evaluating walking in patients with multiple sclerosis: which assessment tools are useful in clinical practice?

Authors:  Francois Bethoux; Susan Bennett
Journal:  Int J MS Care       Date:  2011

4.  Between-rater reliability of the 6-minute walk test, berg balance scale, and handheld dynamometry in people with multiple sclerosis.

Authors:  Elaine Toomey; Susan Coote
Journal:  Int J MS Care       Date:  2013

5.  Understanding walking activity in multiple sclerosis: step count, walking intensity and uninterrupted walking activity duration related to degree of disability.

Authors:  An Neven; Annelien Vanderstraeten; Davy Janssens; Geert Wets; Peter Feys
Journal:  Neurol Sci       Date:  2016-05-20       Impact factor: 3.307

6.  Pulse Width Does Not Influence the Gains Achieved With Neuromuscular Electrical Stimulation in People With Multiple Sclerosis: Double-Blind, Randomized Trial.

Authors:  Awad M Almuklass; Leah Davis; Landon D Hamilton; Jeffrey R Hebert; Enrique Alvarez; Roger M Enoka
Journal:  Neurorehabil Neural Repair       Date:  2018-01-24       Impact factor: 3.919

7.  Detection of subtle gait disturbance and future fall risk in early multiple sclerosis.

Authors:  Rachel Brandstadter; Oluwasheyi Ayeni; Stephen C Krieger; Noam Y Harel; Miguel X Escalon; Ilana Katz Sand; Victoria M Leavitt; Michelle T Fabian; Korhan Buyukturkoglu; Sylvia Klineova; Claire S Riley; Fred D Lublin; Aaron E Miller; James F Sumowski
Journal:  Neurology       Date:  2020-02-26       Impact factor: 9.910

8.  Possible clinical outcome measures for clinical trials in patients with multiple sclerosis.

Authors:  Myla D Goldman; Robert W Motl; Richard A Rudick
Journal:  Ther Adv Neurol Disord       Date:  2010-07       Impact factor: 6.570

9.  Gait abnormalities in multiple sclerosis: pathogenesis, evaluation, and advances in treatment.

Authors:  Michelle H Cameron; Joanne M Wagner
Journal:  Curr Neurol Neurosci Rep       Date:  2011-10       Impact factor: 5.081

10.  Emerging evidence-based physical rehabilitation for multiple sclerosis - towards an inventory of current content across Europe.

Authors:  Kamila Rasova; Peter Feys; Thomas Henze; Hans van Tongeren; Davide Cattaneo; Johanna Jonsdottir; Alena Herbenova
Journal:  Health Qual Life Outcomes       Date:  2010-07-28       Impact factor: 3.186

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