Transcranial Magnetic and Direct Current Stimulation (TMS/tDCS) for the Treatment of Headache: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Headache is among the most prevalent causes of disability worldwide. Non-pharmacologic interventions, including neuromodulation therapies, have been proposed in patients who are treatment resistant or intolerant to medications. OBJECTIVE: To perform a systematic review on the use of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) for the treatment of specific headache disorders (ie, migraine, tension, cluster, posttraumatic). METHODS: Data sources: Ovid MEDLINE, Cochrane Central Register of Clinical Trials, Embase, Scopus, PsycINFO. DATA EXTRACTION: All references were reviewed by 2 independent researchers (3039 abstracts, duplicates removed). Records were selected by inclusion criteria for participants (adults 18-65 with primary or secondary headaches), interventions (TMS and tDCS applied as headache treatment), comparators (sham or alternative standard of care), and study type (cohort, case-control, and randomized controlled trials [RCT]). Studies were assessed using the Cochrane Risk of Bias Tool and overall quality determined through the GRADE Tool. A structured synthesis was performed due to heterogeneity of participants and methods. RESULTS: Thirty-four studies were included: 16 rTMS, 6 TMS (excluding rTMS), and 12 tDCS. The majority investigated treatment for migraine (19/22 TMS, 8/12 tDCS). Quality of evidence ranged from very low to high. CONCLUSION: Of all TMS and tDCS modalities, rTMS is most promising with moderate evidence that it contributes to reductions in headache frequency, duration, intensity, abortive medication use, depression, and functional impairment. However, only few studies reported changes greater than sham treatment. Further high-quality RCTs with standardized protocols are required for each specific headache disorder to validate a treatment effect. Registration Number: PROSPERO 2017 CRD42017076232.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".