Evidence map›Paper›PMID 36688161›Full record

SynthesisFrontiers in aging neuroscience2022

Comparative efficacy of transcranial magnetic stimulation on different targets in Parkinson's disease: A Bayesian network meta-analysis.

Ke Dong, Xiaoxia Zhu, Wenwu Xiao, Chu Gan, Yulu Luo, Manying Jiang, Hanjun Liu, Xi Chen

Registry-linked trialOpen access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07316413 (Repetitive Transcranial Magnetic Stimulation in Frontotemporal Lobar Degeneration), which is not on this map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

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.

2 · The registry

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.

NCT07316413 narecruitingnot on this mapstarted 2025, after this paper: background citation

Repetitive Transcranial Magnetic Stimulation in Frontotemporal Lobar Degeneration

TypeinterventionalSponsorUniversità degli Studi di BresciaRan2025 to 2029Enrolled120ConditionsFTLD, FTD, bvFTD, PPAArmsTheta burst stimulation, Sham Theta burst stimulation
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. The effects of transcranial magnetic stimulation in motor symptoms of Parkinson's disease: an overview of systematic reviews with meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Pooled it
  3. Article
  4. Review
  5. Article
  6. Mechanisms of Action of TMS in the Treatment of Depression.Current topics in behavioral neurosciences · 2024
    Review
  7. 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

8 authors at 1 institution in 1 country.

Ke DongDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xiaoxia ZhuDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Wenwu XiaoDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Chu GanDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yulu LuoDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Manying JiangDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Hanjun LiuDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xi ChenDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/Objective: The efficacy of transcranial magnetic stimulation (TMS) on Parkinson's disease (PD) varies across the stimulation targets. This study aims to estimate the effect of different TMS targets on motor symptoms in PD. Methods: A Bayesian hierarchical model was built to assess the effects across different TMS targets, and the rank probabilities and the surface under the cumulative ranking curve (SUCRA) values were calculated to determine the ranks of each target. The primary outcome was the Unified Parkinson's Disease Rating Scale part-III. Inconsistency between direct and indirect comparisons was assessed using the node-splitting method. Results: Thirty-six trials with 1,122 subjects were included for analysis. The pair-wise meta-analysis results showed that TMS could significantly improve motor symptoms in PD patients. Network meta-analysis results showed that the high-frequency stimulation over bilateral M1, bilateral DLPFC, and M1+DLPFC could significantly reduce the UPDRS-III scores compared with sham conditions. The high-frequency stimulation over both M1 and DLPFC had a more significant effect when compared with other parameters, and ranked first with the highest SCURA value. There was no significant inconsistency between direct and indirect comparisons. Conclusion: Considering all settings reported in our research, high-frequency stimulation over bilateral M1 or bilateral DLPFC has a moderate beneficial effect on the improvement of motor symptoms in PD (high confidence rating). High-frequency stimulation over M1+DLPFC has a prominent beneficial effect and appears to be the most effective TMS parameter setting for ameliorating motor symptoms of PD patients (high confidence rating).

Indexed as

motor recoverynetwork meta-analysesParkinson’s diseasestimulation targetstranscranial magnetic stimulation

Identifiers

PMID36688161
PMCPMC9845788
OpenAlexW4313585558

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.