Evidence map›Paper›PMID 39478696›Full record

ArticleFrontiers in aging neuroscience2024

Efficacy of high-frequency rTMS in the treatment of gait disorder and cognition in patients with Parkinson's disease based on wearable devices and eye-movement assessments.

Hong Yin Tang, XiangLian Liao, Peng Li, Pengfei Zhang, Jian Yao, Yilan Xing, Xin Zhao, Xuying He, Jie Zan, Guihua Li

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hong Yin Tang *Department of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
XiangLian Liao *Department of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Peng Li *Department of Anesthesiology and Surgery, Liwan Central Hospital of Guangzhou, Guangzhou, China.
Pengfei ZhangGuangdong Key Laboratory of Nanomedicine, CAS-HK Joint Lab of Biomaterials, CAS Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China.
Jian YaoDepartment of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Yilan XingDepartment of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Xin ZhaoDepartment of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Xuying HeDepartment of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Jie ZanSchool of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou, Guangdong, China.
Guihua LiDepartment of Neurology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postural instability and gait disorder and cognitive dysfunction are common symptoms of Parkinson's disease (PD). Scale assessment is frequently used in the clinic to evaluate PD, but this technique is limited by its lack of sensitivity to changes in disease progression and its difficulty in capturing subtle movements and changes in cognitive function. It is currently believed that high-frequency repetitive transcranial magnetic stimulation (rTMS) can improve motor and cognitive dysfunction in patients with PD, though it remains controversial. Therefore, it is imperative to monitor and dynamically identify changes in postural instability and gait disorder, as well as those in cognitive dysfunction, in PD to develop targeted interventions. In this study, we observed the effect of high-frequency rTMS on gait disorders and cognitive functions in patients with PD by comparing data from wearable devices and eye-tracking devices before and after treatment. Methods: A total of 159 patients with PD were included in this study. A GYENNO MATRIX wearable gait analyzer was used to monitor the objective gait data (including the timed up-and-go, narrow-track, and turning tests), the Eyeknow eye-tracking evaluation system was used to monitor the patient's eye movement cognition data (including the smooth pursuit, pro-saccade, and anti-saccade tests), and gait and cognitive function-related scales, including the Tinetti Balance Scale, Tinetti Gait Scale, Berg Balance Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment (MoCA), were evaluated at the same time before and after high-frequency rTMS treatment. Results: The mean step length, mean stride velocity, stride length, and mean step frequency of patients with PD in the timed up-and-go test all increased compared with those before rTMS treatment, whereas the mean stride time and double support decreased. In the narrow-track test, the mean stride velocity increased and the mean stride time decreased. In the turning test, the turning left duration, turning right duration, mean duration, mean number of steps, and average step duration decreased, while the mean angular velocity increased after rTMS treatment. Compared with those before rTMS treatment, the latency period of patients with PD in overlapping saccades decreased, the completion time of overlapping saccades decreased, and the average saccade speed increased. In the anti-saccade test, the completion time decreased and the average saccade speed increased after rTMS treatment. Compared with those before rTMS treatment, the Tinetti Balance Scale, Tinetti Gait Scale, Berg Balance Scale, Mini-Mental State Examination, and MoCA scores increased, and the MoCA sub-items improved in terms of visual-spatial and executive function, language, abstraction, delayed recall, and orientation after rTMS treatment. Conclusion: High-frequency rTMS may be an effective therapy for improving gait disorders and cognitive functions in patients with PD.

Indexed as

cognitioneye movement assessmentsgait disorderParkinson’s diseasewearable gait analyzer

Identifiers

PMID39478696
PMCPMC11521881

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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.