Effects of repeated transcranial magnetic stimulation in the dorsolateral prefrontal cortex versus motor cortex in patients with neuropathic pain after spinal cord injury: a study protocol
Bibliographic record
Abstract
INTRODUCTION: Neuropathic pain is one of the common complications of spinal cord injuries (SCI), which will slow down the recovery process and result in lower quality of life. Previous studies have shown that repeated transcranial magnetic stimulation (rTMS) of the motor cortex (M1) can reduce the average pain and the most severe pain of neuropathic pain after SCI. The dorsolateral prefrontal cortex (DLPFC) area is a common target of rTMS. Recently, a few studies found that rTMS of DLPFC may relieve the neuropathic pain of SCI. Compared with the M1 area, the efficacy of rTMS treatment in the DLPFC area in improving neuropathic pain and pain-related symptoms in patients with SCI is still unclear. Therefore, our study aims to evaluate the non-inferiority of rTMS in the DLPFC vs M1 in patients with neuropathic pain after SCI, in order to provide more options for rTMS in treating neuropathic pain after SCI. METHODS AND ANALYSIS: We will recruit 50 subjects with neuropathic pain after SCI. They will be randomly assigned to the DLPFC- rTMS and M1-rTMS groups and be treated with rTMS for 4 weeks. Except for the different stimulation sites, the rTMS treatment programmes of the two groups are the same: 10 Hz, 1250 pulses, 115% intensity threshold, once a day, five times a week for 4 weeks. VAS, simplified McGill Pain Questionnaire, Spinal Cord Injury Pain Date Set, Pittsburgh Sleep Quality Index and Hamilton Anxiety Scale will be evaluated at baseline, second week of treatment, fourth week of treatment and 4 weeks after the end of treatment. And VAS change will be calculated. ETHICS AND DISSEMINATION: The Ethics Committee of the Affiliated Hospital of Southwest Medical University has approved this trial, which is numbered KY2020041. Written informed consent will be provided to all participants after verification of the eligibility criteria. The results of the study will be published in peer-reviewed publications. TRIAL REGISTRATION NUMBER: ChiCTR2000032362.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".