Introduction to the Guideline, and General Principles of Acute Migraine Management
Bibliographic record
Abstract
ABSTRACT: Objectives: To provide an overview of the objectives and target population of the guideline, and to review the general principles of acute pharmacological migraine therapy. Methods: A general literature review and several consensus groups were used to formulate an expert consensus for the general use of acute migraine medications. Results: The objective of the guideline is to assist the physician in choosing an appropriate acute migraine medication for an individual with migraine, and thereby to reduce migraine-related disability. The target population includes adults with episodic migraine (patients with migraine headache < 15 days/month). This guideline is intended primarily for physicians who treat patients with migraine. Other health professionals may also find this guideline helpful. Acute migraine therapy should be considered for the great majority of patients with migraine. A specific acute medication is chosen based on evidence for efficacy, tolerability, migraine attack severity, patient preference, and on the presence of co-existing disorders. General principles of acute migraine therapy include that the response of a patient to any given medication cannot be predicted with certainty, and that treatment early in the attack is generally more effective than treatment later once the migraine attack is fully developed. A suitable treatment approach (stratified or stepped approaches) and drug formulation (injection, tablet, wafer, powdered formulation, or nasal spray) should be chosen based on patient clinical features. Excessively frequent use of acute medications (medication overuse) should be avoided. Two or more acute medications can be combined if necessary. Conclusions: This guideline provides evidence-based advice on the use of acute medications for migraine, and should provide useful guidance for acute migraine therapy to both health professionals and patients.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".