Effects of Repetitive Transcranial Magnetic Stimulation on Neuropathic Pain and Walking Ability in Patients with Incomplete Spinal Cord Injury
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of rTMS on neuropathic pain and walking ability in patients with iSCI. 10 subjects were assigned to each of the experimental group (10 Hz rTMS) and the control group (5 Hz rTMS group). The rTMS intervention was administered 5 times a week for 20 minutes each time for 6 weeks. All measurements were performed before rTMS intervention and 6 weeks after rTMS intervention. In this study, VAS (Visual Analog Scale) and SF-MPQ (Short Form - McGill Pain Questionnaire) were applied to evaluate the pain of patients with spinal cord injuries. Gait endurance was evaluated by the 6-minute walking test (6MWT), and walking speed was evaluated by the 10-m walking test (10MWT). In the comparison between each group, the experimental group showed significant differences in the post-intervention SFMPQ, 6-minute walking test, and 10-meter walking test (p 0.05), and the control group showed a significant difference in the 10-minute walking test (p 0.05). In the comparison between the two groups, there was no significant difference in all variables after intervention (p 0.05). High-frequency rTMS can help reduce neuropathic pain in clinical practice and improve walking ability in patients with incomplete spinal cord injury.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".