Literature DB >> 29350300

The relationship between gait variability and cognitive functions differs between fallers and non-fallers in MS.

Alon Kalron1, Roy Aloni2, Mark Dolev2, Lior Frid2, Uri Givon2,3, Shay Menascu2,3.   

Abstract

The objective of the study was to determine if cognitive function is associated with step time variability in people with multiple sclerosis (PwMS). The study included 355 PwMS (218 women), average age 41.1 (SD = 13.5), disease duration 5.9 (SD = 7.3) years, and a median expanded disability status scale score of 2.5. We separately analyzed the sample group of fallers and non-fallers based on their fall history. Gait variability was measured by an electronic walkway and all participants completed a computerized cognitive test battery designed to evaluate multiple cognitive domains. Fallers (43.7%) demonstrated elevated step time variability (%CV), 5.0 (SD = 3.4) vs. 3.5 (SD = 1.6), P < 0.001 compared to the non-faller subjects. According to the regression analysis in the non-fallers' group, step time variability was found significantly associated with the global cognitive score (P = 0.001), executive function subcategory (P = 0.038), and motor skills subcategory (P < 0.001). No relationship between step time variability and any cognitive domain was demonstrated in the faller group. This study illustrated that the association between gait variability and cognition occurs only in PwMS without a fall history. From a clinical standpoint, these findings might help medical professionals to create improved assessment tests and rehabilitation strategies in the MS population.

Entities:  

Keywords:  Cognition; Falls; Gait variability; Multiple sclerosis; Neurological

Mesh:

Year:  2018        PMID: 29350300     DOI: 10.1007/s00702-018-1843-y

Source DB:  PubMed          Journal:  J Neural Transm (Vienna)        ISSN: 0300-9564            Impact factor:   3.575


  43 in total

Review 1.  Cognition in multiple sclerosis.

Authors:  Dawn W Langdon
Journal:  Curr Opin Neurol       Date:  2011-06       Impact factor: 5.710

2.  Higher gait variability is associated with decreased parietal gray matter volume among healthy older adults.

Authors:  Olivier Beauchet; Cédric Annweiler; Sébastien Celle; Robert Bartha; Jean-Claude Barthélémy; Frédéric Roche
Journal:  Brain Topogr       Date:  2013-05-17       Impact factor: 3.020

3.  Association between gait variability, falls and mobility in people with multiple sclerosis: A specific observation on the EDSS 4.0-4.5 level.

Authors:  Alon Kalron
Journal:  NeuroRehabilitation       Date:  2017       Impact factor: 2.138

4.  Does fear of falling predict gait variability in multiple sclerosis?

Authors:  Magali Laidet; François R Herrmann; Stéphane Armand; Frédéric Assal; Patrice H Lalive; Gilles Allali
Journal:  J Neurol Sci       Date:  2017-07-25       Impact factor: 3.181

5.  Cerebral Amyloid Deposition Is Associated with Gait Parameters in the Mayo Clinic Study of Aging.

Authors:  Alexandra M V Wennberg; Rodolfo Savica; Clinton E Hagen; Rosebud O Roberts; David S Knopman; John H Hollman; Prashanthi Vemuri; Clifford R Jack; Ronald C Petersen; Michelle M Mielke
Journal:  J Am Geriatr Soc       Date:  2016-11-21       Impact factor: 5.562

6.  The relationship between infratentorial lesions, balance deficit and accidental falls in multiple sclerosis.

Authors:  Luca Prosperini; Anna Kouleridou; Nikolaos Petsas; Laura Leonardi; Francesca Tona; Patrizia Pantano; Carlo Pozzilli
Journal:  J Neurol Sci       Date:  2011-03-12       Impact factor: 3.181

7.  Effects of cognitive challenge on gait variability in patients with Parkinson's disease.

Authors:  Jeffrey M Hausdorff; Jackov Balash; Nir Giladi
Journal:  J Geriatr Psychiatry Neurol       Date:  2003-03       Impact factor: 2.680

8.  Gait mechanics are different between healthy controls and patients with multiple sclerosis.

Authors:  Jessie M Huisinga; Kendra K Schmid; Mary L Filipi; Nicholas Stergiou
Journal:  J Appl Biomech       Date:  2012-08-22       Impact factor: 1.833

Review 9.  The topographical model of multiple sclerosis: A dynamic visualization of disease course.

Authors:  Stephen C Krieger; Karin Cook; Scott De Nino; Madhuri Fletcher
Journal:  Neurol Neuroimmunol Neuroinflamm       Date:  2016-09-07

10.  Gait variability and multiple sclerosis.

Authors:  Michael J Socie; Jacob J Sosnoff
Journal:  Mult Scler Int       Date:  2013-03-03
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  3 in total

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Authors:  Alon Kalron; Gilles Allali; Anat Achiron
Journal:  J Neurol       Date:  2018-02-02       Impact factor: 4.849

Review 2.  Cognitive-Motor Interference in Neurodegenerative Disease: A Narrative Review and Implications for Clinical Management.

Authors:  Tara L McIsaac; Nora E Fritz; Lori Quinn; Lisa M Muratori
Journal:  Front Psychol       Date:  2018-10-29

Review 3.  Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders.

Authors:  Christina Salchow-Hömmen; Matej Skrobot; Magdalena C E Jochner; Thomas Schauer; Andrea A Kühn; Nikolaus Wenger
Journal:  Front Hum Neurosci       Date:  2022-02-03       Impact factor: 3.169

  3 in total

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