Effect of Single-Session Repetitive Transcranial Magnetic Stimulation Applied Over the Hand Versus Leg Motor Area on Pain After Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Neuropathic pain often follows spinal cord injury (SCI). OBJECTIVE: To compare the effect of repetitive transcranial magnetic stimulation (rTMS) applied over different motor cortex targets (hand vs leg area) versus sham stimulation on neuropathic pain and local neurophysiological changes in patients with SCI. METHODS: A total of 16 patients with complete or incomplete motor SCI and chronic neuropathic pain participated in a double-blind, cross-over randomized study. Three single sessions of sham or active rTMS (10 Hz, total of 2000 stimuli) were applied in random order over the hand or leg area with a minimal 2-week interval. THE MAIN OUTCOME MEASURES: were the numeric rating scale for pain sensation and parameters derived from motor mapping of the first dorsal interosseous muscle, including maximal amplitude of evoked response as well as map area, volume, and location. RESULTS: rTMS applied to either the hand or the leg area, but not sham stimulation, induced a significant but equivalent reduction in pain for the first 48 hours postintervention (P < .05). Participants with an incomplete lesion showed greater analgesia than those with a complete lesion (21% vs. 3%, respectively; P < .05). The main change observed for motor map measurements was an increase in corticospinal excitability after stimulation of the hand area (P = .04) but not for the other conditions. CONCLUSION: rTMS applied over the hand or leg motor cortex decreased neuropathic pain regardless of any change in cortical excitability, suggesting that the analgesic effect is not associated with local changes at the motor cortex level itself.
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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) | 0.001 | 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 | 0.001 | 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".