Investigating the efficacy of transcranial direct current stimulation on chronic pain management in endometriosis patients: A randomized controlled trial protocol
Bibliographic record
Abstract
INTRODUCTION: Similar to chronic pain conditions, individuals with endometriosis can be affected by central sensitization syndrome (CSS), which is characterized by a loss of analgesia and central amplification of pain. Transcranial direct current stimulation (tDCS) has shown potential as an effective intervention to improve pain generated by other chronic pain conditions impacted by CSS, such as fibromyalgia and chronic pelvic issues. This study aims to evaluate the effectiveness of tDCS on pain, fatigue, and quality of life among patients affected by endometriosis. METHODS: This is a single-center, parallel, double-blinded, randomized, controlled clinical trial protocol study. We aim to recruit 40 participants affected by endometriosis (active group, n = 20; sham group, n = 20). Anodal tDCS will be delivered at an intensity of 2mA, applied over the primary motor cortex for 20 minutes per day for 10 consecutive days. There will be four assessment times: 1 week before beginning the intervention; on the 10th day following the last tDCS session; and 1 and 2 months after the last tDCS session. Pain evaluated by the algometry will be the primary outcome. Pain intensity, quality of life, fatigue, and global perception of change will be the secondary outcomes. We will calculate the effects of the active versus sham stimulation on primary and secondary outcomes by using generalized estimated equations or mixed model analysis. The effect size calculation will represent the effect measure. We expect that only the active group show reductions in pain, fatigue, and quality of life. The results of this trial will produce an important first step in providing evidence on the effectiveness of neuromodulation for the management of pain and will provide data to support new studies on tDCS. REGISTRATION: Brazilian Clinical Trials Registry (RBR-4q69573).
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".