International Headache society evidence-based guidelines on the use of non-invasive neuromodulation devices for the acute and preventive treatment of migraine
Bibliographic record
Abstract
ObjectiveTo develop evidence-based clinical practice guidelines for non-invasive neuromodulation devices in acute and preventive migraine treatment.MethodsA systematic review was conducted across six databases from 1946 to April 2025. Randomized controlled trials evaluating Food and Drug Administration-cleared or Conformité Européenne (CE)-marked non-invasive neuromodulation devices were included. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology, and recommendations were developed through consensus following GRADE Evidence-to-Decision frameworks. The working group comprised 15 senior members and six junior members.ResultsFrom 1536 initial records, 15 studies met the inclusion criteria and were finally used to develop evidence-based recommendations. Evidence quality ranged from very low to moderate. Weak recommendations were issued for SAVI Dual, Cefaly, Relivion, and Nerivio in the treatment of acute migraine attacks, and for gammaCore Sapphire, Cefaly, and Nerivio in the preventive migraine treatment. Other cleared devices received no recommendations or have no eligible studies for the GRADE assessment. The primary limitations across studies included imprecision due to small sample sizes and various methodological concerns. Additionally, expert consensus recommendations were developed for devices and clinical scenarios not adequately covered by randomized controlled trials, including potential applications in pediatric populations, vestibular migraine, chronic migraine, menstrual migraine, and medication overuse headache.ConclusionNon-invasive neuromodulation devices offer promising alternatives to drug treatment for migraine management. These devices are safe and generally well tolerated and devoid of drug interactions. While current evidence quality varies, ongoing research and technological advancements show encouraging potential. Future studies should adhere to International Headache Society guidelines for neuromodulation device trials, address proper sham controls and blinding assessment, and account for patient adherence challenges in device use. Expanded insurance coverage would enhance cost-effectiveness and device accessibility. These guidelines provide a framework for clinical decision-making while highlighting areas requiring further research.
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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 | 0.040 | 0.105 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.029 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".