ArticleFrontiers in aging neuroscience2026
Potential for distinguishing the parkinsonian subtype of multiple system atrophy from Parkinson's disease: a three-dimensional gait analysis study.
Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Distinguishing the parkinsonian subtype of multiple system atrophy (MSA-P) from Parkinson's disease (PD) at an early stage was a challenge, and gait analysis based on wearable sensors offers a reliable method to quantify gait parameters. In this study, we used a three-dimensional gait motion capture system based on wearable sensors to identify potential gait-based biomarkers that might assist in distinguishing MSA-P from PD. Methods: Participants were enrolled in this observational study from the Department of Neurology at the People's Hospital of Xinjiang Uygur Autonomous Region from June 2024 to October 2025 and were required to complete the timed up and go (TUG) test, Cognitive Load Test, and Endogenous Beat Test according to our instructions. Multivariate analysis of covariance (MANCOVA) was used to conduct overall comparisons of gait characteristics among groups, and predictive ability was tested through 5-fold cross-validated receiver operating characteristic curves and sensitivity analysis. Results: A total of 74 PD patients, 33 MSA-P patients, and 79 healthy controls (HCs) were enrolled in this study. When PD patients and MSA-P patients exhibited similar clinical performance and drug dosage, MSA-P patients had a 4.9-year younger age of symptom onset and a duration of symptoms that was 19.4 months shorter. Both PD patients and MSA-P patients exhibited reduced stride length, reduced velocity, reduced bilateral step length, anterior pelvic tilt, and broadly reduced range of motion (ROM) of the pelvis and the lower limb joints compared to HCs. The negative impact of the Cognitive Load Test on gait seemed to be far greater than that of the Endogenous Beat Test, and PD patients might be more sensitive to the Endogenous Beat Test than MSA-P patients. The ROM of hip flexion-extension in the Endogenous Beat Test demonstrated the most favorable discriminative and potential predictive capacity for distinguishing MSA-P patients from PD patients, and the results were stable across different subgroups of patients according to sensitivity analysis. Discussion: The ROM of hip flexion-extension in the Endogenous Beat Test might have a potential capacity to distinguish MSA-P patients from PD patients. Three-dimensional gait analysis based on wearable sensors might hold considerable application potential for the clinical differential diagnosis of neurodegenerative diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.