Systematic Review of Episodic Migraine Prophylaxis: Efficacy of Conventional Treatments Used in Comparisons with Acupuncture
Bibliographic record
Abstract
Objective: A Cochrane Systematic Review published by Linde et al. in 2016 found moderate evidence suggesting that acupuncture is “at least non-inferior” to conventional prophylactic drug treatments (flunarizine, metoprolol, and valproic acid) for episodic migraine prophylaxis. The evidence for the efficacy of these conventional treatments must be verified to strengthen and validate the original comparison made in Linde et al.'s 2016 review. The aim of the current authors' systematic review was to verify the efficacy of the conventional treatments used in Linde et al.'s 2016 comparison with acupuncture. Materials and Methods: Search strategies were applied to find studies that could verify the efficacy of conventional treatments for treating episodic migraines. Relevant outcomes and dosages were extracted from the retrieved studies. Each study's quality was assessed, using the Cochrane's collaboration tool for assessing risk of bias and the Cochrane GRADE [Grading of Recommendations Assessment, Development, and Evaluation] scale. Results: There is high-quality evidence suggesting that prophylactic drug treatment, at the treatment dosage ranges used in Linde et al.'s 2016 review, reduced headache frequency at a 3-month follow-up, compared to placebo. Headache frequency at a 6-month follow-up, and responses (at least 50% reduction of headache frequency) at 3-month and 6-month follow-ups could not be assessed. Conclusions: These findings strengthened Linde et al.'s 2016 comparison of conventional treatments and acupuncture for reducing headache frequency at a 3-month follow-up. For episodic migraine prophylaxis, moderate evidence suggests that acupuncture is “at least non-inferior,” to now-proven, conventional treatments. This raises significant questions in the debate concerning claims that acupuncture is a placebo-based treatment and the prescriptions of proven conventional treatments that have similar effects as acupuncture.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".