Effect of repetitive peripheral magnetic stimulation for patients with chronic stroke: a case report using an AB design
Bibliographic record
Abstract
Objective: To determine the effects of repetitive peripheral magnetic stimulation in a patient with chronic stroke. Design: Case report. Patients: A man in his 70s presented with left hemiplegia secondary to cerebral hemorrhage. Methods: An AB design was used: phase A (sham stimulation) and phase B (active stimulation). Magnetic stimulation was applied using a peripheral magnetic stimulator (Pathleader™, IFG, Sendai, Japan). Outcomes were assessed at four points: before the intervention, after phase A, after phase B, and at follow-up (3 weeks after phase B) using the Modified Ashworth Scale, range of motion, Fugl-Meyer Assessment, Simple Test for Evaluating Hand Function, and Canadian Occupational Performance Measures. Results: The Modified Ashworth Scale score for the wrist extensor remained unchanged in phase A but improved after phase B and was sustained at follow-up. The range of motion showed no change. The Fugl-Meyer Assessment scores were 40, 41, 44, and 45, respectively, and the Simple Test for Evaluating Hand Function scores were 1, 4, 3, and 5, respectively, at the four time points. One Canadian Occupational Performance Measure item improved after phase B and remained stable. Conclusion: In patients with chronic stroke and severe hemiplegia, repetitive peripheral magnetic stimulation may be effective in reducing spasticity and improving motor function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".