Parenteral metoclopramide for acute migraine: meta-analysis of randomised controlled trials
Bibliographic record
Abstract
OBJECTIVE: To assess the evidence from controlled trials on the efficacy and tolerability of parenteral metoclopramide for acute migraine in adults. DATA SOURCES: Cochrane Central Register of Controlled Trials, Medline, Embase, LILACS, CINAHL, conference proceedings, clinical practice guidelines, and other sources. SELECTION CRITERIA: Randomised controlled trials of parenteral metoclopramide for acute migraine in adults. RESULTS: We reviewed 596 potentially relevant abstracts and found 13 eligible trials totalling 655 adults. In studies comparing metoclopramide with placebo, metoclopramide was more likely to provide significant reduction in migraine pain (odds ratio 2.84, 95% confidence interval 1.05 to 7.68). Used as the only agent, metoclopramide showed mixed effectiveness when compared with other single agents. Heterogeneity of studies for combination treatment prevented statistical pooling. Treatments that did include metoclopramide were as, or more, effective than comparison treatments for pain, nausea, and relapse outcomes reported in all studies. CONCLUSIONS: Metoclopramide is an effective treatment for migraine headache and may be effective when combined with other treatments. Given its non-narcotic and antiemetic properties, metoclopramide should be considered a primary agent in the treatment of acute migraines in emergency departments.
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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 | 0.027 | 0.075 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.030 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".