Comparison of gait parameters between drug-naïve patients diagnosed with multiple system atrophy with predominant parkinsonism and Parkinson's disease

Na, Boo Suk; Ha, Jihun; Park, Ji‐Hyung; Ahn, Jong Hyeon; Kim, Min-Kyeong; Kim, Ji Sun; Kim, Hee Tae; Cho, Jin Whan; Youn, Jinyoung

doi:10.1016/j.parkreldis.2018.09.018

Cited by 10 publications

(5 citation statements)

References 32 publications

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“…A number of studies in other cohorts suggested slow walking to be directly correlated with an increase in gait variability because it requires more stability in the medio-lateral axis [23]. Here, one might argue that this phenomenon may reflect the major impairment of balance affecting MSA-P patients [12]. As a consequence, tandem gait cannot be performed in the vast majority of MSA-P patients [13] and riding a bike results very difficult even in early stages [14].…”

Section: Discussionmentioning

confidence: 99%

“…While several studies mainly focused on PD patients, only a few data have been reported for atypical parkinsonism including MSA-P. A quantitative analysis of gait parameters revealed a significant reduction of average gait velocity and stride length in patients with atypical parkinsonism compared to PD patients [11] and further observations also demonstrated increased GV [1]. Previous research described a disease-characteristic balance impairment in the medio-lateral axis displayed by patients with atypical parkinsonism [12], which is unveiled by an abnormal tandem gait test and by the information that patients stop riding a bicycle [13,14]. However, detailed information about GV-as well as the impact of walking velocity on GV-in MSA-P patients is lacking.…”

Section: Introductionmentioning

confidence: 88%

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Characterization of gait variability in multiple system atrophy and Parkinson’s disease

et al. 2020

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Background Gait impairment is a pivotal feature of parkinsonian syndromes and increased gait variability is associated with postural instability and a higher risk of falls. Objectives We compared gait variability at different walking velocities between and within groups of patients with Parkinson-variant multiple system atrophy, idiopathic Parkinson’s disease, and a control group of older adults. Methods Gait metrics were recorded in 11 multiple system atrophy, 12 Parkinson’s disease patients, and 18 controls using sensor-based gait analysis. Gait variability was analyzed for stride, swing and stance time, stride length and gait velocity. Values were compared between and within the groups at self-paced comfortable, fast and slow walking speed. Results Multiple system atrophy patients displayed higher gait variability except for stride time at all velocities compared with controls, while Parkinson’s patients did not. Compared with Parkinson’s disease, multiple system atrophy patients displayed higher variability of swing time, stride length and gait velocity at comfortable speed and at slow speed for swing and stance time, stride length and gait velocity (all P < 0.05). Stride time variability was significantly higher in slow compared to comfortable walking in patients with multiple system atrophy (P = 0.014). Variability parameters significantly correlated with the postural instability/gait difficulty subscore in both disease groups. Conversely, significant correlations between variability parameters and MDS-UPDRS III score was observed only for multiple system atrophy patients. Conclusion This analysis suggests that gait variability parameters reflect the major axial impairment and postural instability displayed by multiple system atrophy patients compared with Parkinson’s disease patients and controls.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 88%

Characterization of gait variability in multiple system atrophy and Parkinson’s disease

et al. 2020

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“…We decided to study these axial and postural symptoms and also parkinsonism using the same scale as those employed for the study of IPD. Indeed, the subtests of MDS-UPDRS have previously been used to assess signs of parkinsonism, posture and postural stability [2, 34, 35]. For those patients presenting IPD, we did not distinguish between Postural Instability–Gait Difficulty [24] and Tremor-Dominant subtypes.…”

Section: Discussionmentioning

confidence: 99%

Older Persons Displaying Parkinsonian Gait: Prediction and Explanation of the Recurrent Falling Phenomenon and Its Related Poor Prognosis

Kiesmann¹,

Sauleau²,

Martin³

et al. 2022

Gerontology

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Introduction: Parkinsonian gait in older persons is a major risk factor for recurrent falling. This prospective, longitudinal study (named EVAMAR-AGEX) aimed to validate the threshold value of two or more falls per year for distinguishing non-recurrent (NRF) from recurrent fallers (RF), to explore predictive factors for recurrent falling, and to identify factors which underlie the transition of patients from NRF to RF. The study took place over 2 years, with an intermediate analysis at 1 year of follow-up. Herein, we report results after 2 years of follow-up. Methods: Participants over the age of 65, diagnosed with parkinsonian gait, were followed over the course of 2 years. Induced parkinsonian syndrome and uncontrolled orthostatic hypotension were excluded. Assessments of motor, visual, and cognitive functions were carried out during visits at baseline. Between visits at 12 and 24 months of follow-up, data were collected by phone call every 2 months (falls, traumatic falls, hospitalizations, cognitive fluctuations, delirium, and mortality). Odds ratios (ORs) for a panel of predictive factors for recurrent falling were established using a Bayesian model. Results: Sixty-six of the 79 initially enrolled participants progressed to the second year of the study, with a mean age of 80.57 (SD 6.3), 56% male, presenting parkinsonian gait (53% Parkinson’s disease, 15% atypical neurodegenerative parkinsonism, 21% vascular parkinsonism, and 11% diffuse Lewy body disease). At 2 years of follow-up, 67% were RF. Univariate analysis revealed a previous history of falls to be the most significant predictive factor of recurrent falls (OR 13.16, credibility interval [CrI] [95%] 4.04–53.73), and this was reinforced at 2 years of follow-up compared to the intermediate 1-year analysis (OR 11.73, CrI [95%] 4.33–35.28). Multivariate analysis confirmed a previous history of falls (OR 13.20, CrI [95%] 3.29–72.08) and abnormal posture (OR 3.59, CrI [95%] 1.37–11.26) to be predictive factors for recurrent falling. Cognitive decline and fluctuating cognition were associated with the transition from NRF to RF (−3.5 MMSE points for participants transitioning from NRF to RF). Conclusion: Within this population of older persons presenting parkinsonian gait, a previous history of falls and abnormal posture may be used to easily identify individuals at risk of recurrent falls. Cognitive decline and fluctuations may underlie the transition of NRF to RF.

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“…To determine the sample size, a power analysis was performed based on the previously published studies between MSA and PD. A sample size of at least 15 subjects per group was identified to detect an effect size of 0.5 with a power of 0.8 ( 35 ). A sample size of at least 15 subjects per group was needed.…”

Section: Methodsmentioning

confidence: 99%

Dynamic postural balance indices can help discriminate between patients with multiple system atrophy and Parkinson's disease

Bao

Li²,

Yang³

et al. 2023

Front. Neurol.

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BackgroundPatients with Parkinson's disease (PD) and those with multiple system atrophy (MSA) show similar symptoms but have different clinical treatments. It will be helpful to discriminate between these two kinds of patients at an early or middle stage. The purpose of this study is to highlight the differences in posturographic characterization between patients with PD and those with MSA during quiet standing and perturbed standing.MethodsA total of clinically diagnosed 42 patients with PD and 32 patients with MSA participated in the experiment. Patients were asked to first stand on a static balance force platform and then on a dynamic balance (medial-lateral rocker) force platform to measure the center of pressure (COP) trajectory during an eyes-open (EO) state. The posturographic parameters were obtained under the two standing conditions for statistical analysis.ResultsFour posturographic variables were calculated and analyzed, namely, the standard deviation of COP position (SD), sway path of COP position (SP), an elliptical area covering the 95% COP position trajectory (EA), sway path of COP position (SP), and integral area of the power spectral density at 0–0.5 Hz frequency band (PSD). Except for variable EA, the other three variables are all in the medial-lateral (ML) direction. In the static balance experiment, there were no significant differences between the four variables between patients with PD and those with MSA. However, in the dynamic balance experiment, the obtained four variables all presented significant differences between patients with PD and those with MSA.ConclusionThe dynamic posturographic variables with significant differences between patients with PD and those with MSA imply that patients with MSA have worse postural control ability in the medial-lateral (ML) direction compared to patients with PD. The obtained dynamic indices may help supplemental clinical evaluation to discriminate between patients with MSA and those with PD.

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Comparison of gait parameters between drug-naïve patients diagnosed with multiple system atrophy with predominant parkinsonism and Parkinson's disease

Cited by 10 publications

References 32 publications

Characterization of gait variability in multiple system atrophy and Parkinson’s disease

Characterization of gait variability in multiple system atrophy and Parkinson’s disease

Older Persons Displaying Parkinsonian Gait: Prediction and Explanation of the Recurrent Falling Phenomenon and Its Related Poor Prognosis

Dynamic postural balance indices can help discriminate between patients with multiple system atrophy and Parkinson's disease

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