Using Dual-Target rTMS, Single-Target rTMS, or Sham rTMS on Post-Stroke Cognitive Impairment
Bibliographic record
Abstract
Background: The clinical application of 10 Hz repetitive transcranil magnetic stimulation (rTMS) remains limited despite its demonstrated effectiveness in enhancing cortical excitability and improving cognitive function. The present study used a novel stimulus target [left dorsolateral prefrontal cortex + primary motor cortex] to facilitate the enhancement of cognitive function through the bidirectional promotion of cognitive and motor functions; Methods: Post-stroke cognitive impairment patients (n = 48) were randomly assigned to receive either dual-target, single-target, or sham rTMS for 4 weeks. Before and after 4 weeks of treatment, participants were asked to complete the Montreal Cognitive Assessment (MoCA) test, the Modified Barthel Index (MBI), the Trail-making Test (TMT), and the Digital Span Test (DST). In addition, the levels of brain-derived neurotrophic factor (BDNF) and vascular endothelial growth factor (VEGF) in serum were also measured. Results: After adjusting for pre-intervention (baseline) MoCA scores, the post-intervention MoCA scores varied significantly. After post-hoc analysis, differences existed between the post-treatment scores of the dual-target rTMS group and the sham rTMS group (the experimental group scores were significantly higher), and between those of the dual-target rTMS group and the single-target rTMS group (the dual-target rTMS scores were significantly higher). The serum VEGF levels of the dual-target rTMS group were significantly higher those that of the sham rTMS group. Conclusions: The present study presented data showing that a dual-target rTMS therapy is effective for Post-stroke cognitive impairment (PSCI). The stimulation exhibited remarkable efficacy, suggesting that dual-target stimulation (left dorsolateral prefrontal cortex+motor cortex (L-DLPFC+M1)) holds promise as a potential target for TMS therapy in individuals with cognitive impairment after stroke. Clinical Trial Registration: No: ChiCTR220066184. Registered 26 November, 2022, https://www.chictr.org.cn.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".