1. Newly Identified Gait Patterns in Patients With Multiple Sclerosis May Be Related to Push-off Quality
- Author
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Caroline A.M. Doorenbosch, Vincent de Groot, Heleen Beckerman, J.C.E. Kempen, Dirk L. Knol, Rehabilitation medicine, EMGO - Musculoskeletal health, and MOVE Research Institute
- Subjects
Adult ,Male ,030506 rehabilitation ,medicine.medical_specialty ,Multiple Sclerosis ,medicine.medical_treatment ,Video Recording ,Physical Therapy, Sports Therapy and Rehabilitation ,Electromyography ,Cerebral palsy ,03 medical and health sciences ,0302 clinical medicine ,Physical medicine and rehabilitation ,medicine ,Humans ,Ground reaction force ,Gait Disorders, Neurologic ,Aged ,Aged, 80 and over ,Rehabilitation ,Expanded Disability Status Scale ,medicine.diagnostic_test ,business.industry ,Middle Aged ,medicine.disease ,Gait ,Latent class model ,Biomechanical Phenomena ,Cross-Sectional Studies ,Gait analysis ,Physical therapy ,Female ,0305 other medical science ,business ,human activities ,030217 neurology & neurosurgery - Abstract
Background Limited walking ability is an important problem for patients with multiple sclerosis. A better understanding of how gait impairments lead to limited walking ability may help to develop more targeted interventions. Although gait classifications are available in cerebral palsy and stroke, relevant knowledge in MS is scarce. Objective The aims of this study were: (1) to identify distinctive gait patterns in patients with MS based on a combined evaluation of kinematics, gait features, and muscle activity during walking and (2) to determine the clinical relevance of these gait patterns. Design This was a cross-sectional study of 81 patients with MS of mild-to-moderate severity (Expanded Disability Status Scale [EDSS] median score=3.0, range=1.0–7.0) and an age range of 28 to 69 years. Method The patients participated in 2-dimensional video gait analysis, with concurrent measurement of surface electromyography and ground reaction forces. A score chart of 73 gait items was used to rate each gait analysis. A single rater performed the scoring. Latent class analysis was used to identify gait classes. Results Analysis of the 73 gait variables revealed that 9 variables could distinguish 3 clinically meaningful gait classes. The 9 variables were: (1) heel-rise in terminal stance, (2) push-off, (3) clearance in initial swing, (4) plantar-flexion position in mid-swing, (5) pelvic rotation, (6) arm-trunk movement, (7) activity of the gastrocnemius muscle in pre-swing, (8) M-wave, and (9) propulsive force. The EDSS score and gait speed worsened in ascending classes. Limitations Most participants had mild-to-moderate limitations in walking ability based on their EDSS scores, and the number of walkers who were severely limited was small. Conclusions Based on a small set of 9 variables measured with 2-dimensional clinical gait analysis, patients with MS could be divided into 3 different gait classes. The gait variables are suggestive of insufficient ankle push-off.
- Published
- 2016
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