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Newly Identified Gait Patterns in Patient With Multiple Sclerosis May Be Related to Push-Off Quality.
Kempen JC et al Phys Ther. 2016 May 12
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.
Identifying distinctive gait patterns in patients with MS, based on a combined evaluation of kinematics, gait features and muscle activity during walking, and determining the clinical relevance of these gait patterns.
Cross-sectional study in 81 patients with an age range of 28-69 years, and mild to moderate severity of MS (median Expanded Disability Status Scale 3.0; EDSS range 1.0-7.0).
Patients participated in 2D video gait analysis, with concurrent measurement of surface electromyography (EMG) 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 (LCA) was used to identify gait classes.
Analysis of the 73 gait variables revealed that nine variables could distinguish three clinically meaningful gait classes. These are heel-rise in terminal-stance, push-off, clearance in initial swing, plantar flexion position mid-swing, pelvic rotation, arm-trunk movement, activity of the m. gastrocnemius in pre-swing, M-wave and the propulsive force. The EDSS score and gait speed worsened in ascending classes.
Most participants had mild to moderate limitations in walking ability according to the EDSS, while the number of severely limited walkers was small.
Based on a small set of nine variables measured with 2D clinical gait analysis, patients with MS could be divided into three different gait classes. The gait variables are suggestive of insufficient ankle push-off.
The aim of this study was to examine the relationship of obesity with walking and balance in people with multiple sclerosis.
This was a cross-sectional study performed at the Multiple Sclerosis Center, Sheba Medical Center, Israel. Four hundred thirty-six people with multiple sclerosis were divided into obese (n = 178) and normal-weight (n = 258) groups. Spatiotemporal parameters of gait, 2-Minute Walk test, 6-Minute Walk test, Timed Up and Go test, Timed 25-Foot Walk test, Multiple Sclerosis Walking Scale self-reported questionnaire, and posturography measures were determined.
Compared with normal-weight patients, obese subjects walked significantly slower [98.7 (SD, 29.2) m/s vs. 106.4 (SD, 29.2) m/s; P = 0.01], with shorter step lengths [54.8 (SD, 11.6) cm vs. 58.1 (SD, 10.7) cm; P = 0.003] and a wider step width [12.1 (SD, 3.7) cm vs. 10.9 (SD, 4.6) cm; P = 0.01]. Furthermore, the obese group walked a shorter distance on the 6-Minute Walk test [378.2 (SD, 145.5) m vs. 426.1 (SD, 129.8) m; P ≤ 0.001] and slower on the Timed 25-Foot Walk test [9.0 (SD, 8.0) seconds vs. 7.2 (SD, 2.4) seconds; P = 0.006] and the Timed Up and Go test [9.2 (SD, 6.3) seconds vs. 10.0 (SD, 6.1) seconds; P = 0.002]. No significant differences between groups were noted in the Multiple Sclerosis Walking Scale self-reported questionnaire and postural control measures.
Obesity affects walking but not postural control in people with multiple sclerosis despite the level of neurological disability.
The use of laboratory gait analysis for understanding gait deterioration in people with multiple sclerosis Mult Scler June 30, 2016
Laboratory gait analysis or three-dimensional gait analysis (3DGA), which uses motion capture, force plates and electromyography (EMG), has allowed a better understanding of the underlying mechanisms of gait deterioration in patients with multiple sclerosis (PwMS). This review will summarize the current knowledge on multiple sclerosis (MS)-related changes in kinematics (angles), kinetics (forces) and electromyographic (muscle activation) patterns and how these measures can be used as markers of disease progression. We will also discuss the potential causes of slower walking in PwMS and the implications for 3DGA. Finally, we will describe new technologies and methods that will increase precision and clinical utilization of 3DGA in PwMS. Overall, 3DGA studies have shown that functionality of the ankle joint is the most affected during walking and that compensatory actions to maintain a functional speed may be insufficient in PwMS. However, altered gait patterns may be a strategy to increase stability as balance is also affected in PwMS.