Targeted Review: Medications for Acute Migraine Treatment
Bibliographic record
Abstract
ABSTRACT: Objective: To assess the evidence base for drugs used for acute treatment of episodic migraine (headache on < 14 days a month) in Canada. Methods: A detailed search strategy was employed to find relevant published clinical trials of drugs used in Canada for the acute treatment of migraine in adults. Primarily meta-analyses and systematic reviews were included. Where these were not available for a drug or were out of date, individual clinical trial reports were utilized. Only double-blind randomized clinical trials with placebo or active drug controls were included in the analysis. Recommendations and levels of evidence were graded according to the principles of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group, using a consensus group. Results: Eighteen acute migraine medications and two adjunctive medications were evaluated. Twelve acute medications received a strong recommendation with supporting high quality evidence for use in acute migraine therapy (almotriptan, eletriptan, frovatriptan, naratriptan, rizatriptan, sumatriptan, zolmitriptan, ASA, ibuprofen, naproxen sodium, diclofenac potassium, and acetaminophen). Four acute medications received a weak recommendation for use with low or moderate quality evidence (dihydroergotamine, ergotamine, codeine-containing combination analgesics, and tramadol-containing combination analgesics). Three of these medications were NOT recommended for routine use (ergotamine, and codeine- and tramadol-containing medications), and strong recommendations were made to avoid use of butorphanol and butalbital-containing medications. Both metoclopramide and domperidone received a strong recommendation for use with acute migraine attack medications where necessary. Conclusion: Our targeted review formulated recommendations for the available acute medications for migraine treatment according to the GRADE method. This should be helpful for practitioners who prescribe medications for acute migraine treatment.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".