Pain Reduction in Myofascial Pain Syndrome by Anodal Transcranial Direct Current Stimulation Combined With Standard Treatment
Bibliographic record
Abstract
BACKGROUND: Myofascial pain syndrome (MPS) in the shoulder is among the most prevalent pain problems in the middle-aged population worldwide. Evidence suggests that peripheral and central sensitization may play an important role in the development and maintenance of shoulder MPS. Given previous research supporting the potential efficacy of anodal transcranial direct current stimulation (tDCS) for modulating pain-related brain activity in individuals with refractory central pain, we hypothesized that anodal tDCS when applied over the primary motor cortex (M1) combined with standard treatment will be more effective for reducing pain in patients with MPS than standard treatment alone. METHODS AND MATERIALS: Study participants were randomized to receive either (1) standard treatment with 5 consecutive days of 1 mA anodal tDCS over M1 for 20 minutes; or (2) standard treatment plus sham tDCS. Measures of pain intensity, shoulder passive range of motion (PROM), analgesic medication use, and self-reported physical functioning were administered before treatment and again at posttreatment and 1-, 2-, 3-, and 4-week follow-up. RESULTS: Thirty-one patients with MPS were enrolled. Participants assigned to the active tDCS condition reported significantly more pretreatment to posttreatment reductions in pain intensity that were maintained at 1-week posttreatment, and significant improvement in shoulder adduction PROM at 1-week follow-up than participants assigned to the sham tDCS condition. CONCLUSIONS: Five consecutive days of anodal tDCS over M1 combined with standard treatment appears to reduce pain intensity and may improve PROM, faster than standard treatment alone. Further tests on the efficacy and duration of effects of tDCS in the treatment of MPS are warranted.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".