Additional Effects of Transcranial Direct-Current Stimulation and Trigger-Point Injection for Treatment of Myofascial Pain Syndrome: A Pilot Study with Randomized, Single-Blinded Trial
Bibliographic record
Abstract
BACKGROUND: Chronic pain caused by myofascial pain syndrome (MPS) results in generalized and debilitating conditions. Trigger-point injection (TPI) is the mainstay of MPS management to reduce acute and localized pain. Other adjunctive intervention to modulate the central pain pathway might be helpful if they are combined with TPI. Transcranial direct-current stimulation (tDCS), which is a form of neurostimulation, has been reported to be safe and effective in treating chronic pain by changing cortical excitability. OBJECTIVES: To determine whether there is an additional effect of tDCS and TPI to reduce pain in patients with MPS. PATIENTS: Twenty-one patients with newly diagnosed MPS of shoulder girdle muscles. INTERVENTIONS: Patients were randomly assigned into 1 of 3 groups (2 active and 1 sham stimulation groups) and received TPI. Immediately after TPI, tDCS (2 mA for 20 minutes on 5 consecutive days) was administered. For the active stimulation groups, tDCS was applied over 2 different locations (primary motor cortex and dorsolateral prefrontal cortex [DLPFC]). OUTCOME MEASURES: Visual analogue scale (VAS), Pain Threshold Test, and short form of the McGill Pain Questionnaire were measured before and immediately after stimulation for 5 consecutive days. RESULTS: The mean VAS values were decreased in all three groups after 5 days. There was a significant change between before and after stimulation only in the DLPFC group. The significant change in the mean VAS value was shown from after the second stimulation session (p=0.031), and this remained significant until the last stimulation session (p=0.027). CONCLUSION: This study suggests that tDCS over DLPFC may have additional effects with TPI to reduce pain in patients with MPS. tDCS over DLPFC can be used to reverse central pain pathway by modulating cortical plasticity.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.008 | 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".