Motor Cortex Stimulation for Neuropathic Pain: A Randomized Cross-over Trial
Bibliographic record
Abstract
BACKGROUND: Chronic motor cortex stimulation (MCS) has been used to treat medically refractory neuropathic pain over the past 20 years. We investigated this procedure using a prospective multicentre randomized blinded crossover trial. METHODS: Twelve subjects with three different neuropathic pain syndromes had placement of MCS systems after which they were randomized to receive low ("subtherapeutic") or high ("therapeutic") stimulation for 12 weeks, followed by a crossover to the other treatment group for 12 weeks. The primary outcome measure was the pain visual analogue scale (VAS). Secondary outcome measures included McGill Pain Questionnaire (MPQ), Beck Depression Inventory-II, medication log, work status, global impression of change, and SF-36 quality of life scale. RESULTS: The trial was halted early due to lack of efficacy. One subject withdrew early due to protocol violation and five subjects withdrew early due to transient adverse events. Six subjects with upper extremity pain completed the study. There was no significant change in VAS with low or high stimulation and no significant improvement in any of the outcome measures from low to high stimulation. SF-36 role physical and mental health scores were worse with high compared to low stimulation (p=0.024, p=0.005). CONCLUSIONS: We failed to show that MCS is an effective treatment for refractory upper extremity neuropathic pain and suggest that previous studies may have been skewed by placebo effects, or ours by nocebo. We suggest that a healthy degree of skepticism is warranted when considering this invasive therapy for upper extremity pain syndromes.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".