Associations Between Self-Reported Symptoms and Gait Parameters Using In-Home Sensors in Persons With Multiple Sclerosis.


Journal

Rehabilitation nursing : the official journal of the Association of Rehabilitation Nurses
ISSN: 2048-7940
Titre abrégé: Rehabil Nurs
Pays: United States
ID NLM: 8104825

Informations de publication

Date de publication:
Historique:
pubmed: 17 1 2019
medline: 24 10 2020
entrez: 17 1 2019
Statut: ppublish

Résumé

Multiple sclerosis (MS) is a progressive neurological disorder, characterized by exacerbations and remissions, often resulting in disability affecting multiple neurological functions. The purpose of this article was (1) to describe the frequencies of self-reported symptoms in a natural environment and (2) to determine characteristics and associations between self-reported symptoms and home gait parameters (speed, stride time, and stride length) at baseline and at 3 months in patients with MS. Participants completed the self-report MS-Related Symptom Scale to measure symptoms. A three-dimensional depth imaging system (Foresite Healthcare) was used to measure gait parameters in the home environment. These data show significant correlations between the following symptoms: knee locking or collapsing, difficulty sleeping, depression, and anxiety with decreased number of average walks per day; however, the symptoms including trouble-making toilet: day and difficulty in starting urine were positively correlated with average walks per day. The symptom numbness was significantly correlated with decreased speed and decreased stride length. Our findings suggest that certain groups of symptoms were more frequently reported with certain gait parameters (stride time/speed) in persons with MS. Rehabilitation nurses can provide optimal care to prevent future decline in symptoms and gait.

Sections du résumé

BACKGROUND AND PURPOSE OBJECTIVE
Multiple sclerosis (MS) is a progressive neurological disorder, characterized by exacerbations and remissions, often resulting in disability affecting multiple neurological functions. The purpose of this article was (1) to describe the frequencies of self-reported symptoms in a natural environment and (2) to determine characteristics and associations between self-reported symptoms and home gait parameters (speed, stride time, and stride length) at baseline and at 3 months in patients with MS.
METHODS METHODS
Participants completed the self-report MS-Related Symptom Scale to measure symptoms. A three-dimensional depth imaging system (Foresite Healthcare) was used to measure gait parameters in the home environment.
RESULTS RESULTS
These data show significant correlations between the following symptoms: knee locking or collapsing, difficulty sleeping, depression, and anxiety with decreased number of average walks per day; however, the symptoms including trouble-making toilet: day and difficulty in starting urine were positively correlated with average walks per day. The symptom numbness was significantly correlated with decreased speed and decreased stride length.
DISCUSSION AND CONCLUSIONS CONCLUSIONS
Our findings suggest that certain groups of symptoms were more frequently reported with certain gait parameters (stride time/speed) in persons with MS. Rehabilitation nurses can provide optimal care to prevent future decline in symptoms and gait.

Identifiants

pubmed: 30649037
doi: 10.1097/rnj.0000000000000210
doi:

Types de publication

Journal Article

Langues

eng

Pagination

80-87

Auteurs

Pamela Newland (P)

Barnes Jewish College Goldfarb School of Nursing, St Louis, MO, USA.

Amber Salter (A)

Division of Biostatistics, Washington University, St Louis, MO, USA.

Alicia Flach (A)

Department of Physical Therapy and Athletic Training, Saint Louis University, St. Louis, MO, USA.

Louise Flick (L)

Saint Louis University, St. Louis, MO, USA.

Florian P Thomas (FP)

Multiple Sclerosis Center, Department of Neurology and Neuroscience Institute, Hackensack University Medical Center and Seton Hall-Hackensack-Meridian School of Medicine, Hackensack, NJ, USA.

Elsie E Gulick (EE)

College of Nursing, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.

Marilyn Rantz (M)

Sinclair School of Nursing, University of Missouri-Columbia, Columbia, MO, USA.

Marjorie Skubic (M)

Electrical Engineering and Computer Science Department, University of Missouri Columbia-Columbia, Columbia, MO, USA.

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