DRUG THERAPY FOR MIGRAINE IN CHILDREN: A META-ANALYSIS OF RANDOMIZED CONTROLLED TRIALS
Bibliographic record
Abstract
Objectives: To systematically review all randomized controlled trials that examine abortive drug therapy for migraine in children between 3 and 18 years of age. Methods: Six electronic bibliographic databases were searched. Trials were included if they examined children with acute migraine and compared a drug to placebo, another drug, or standard care. Inclusion criteria were applied and methodological quality was assessed independently by two reviewers. Data were extracted using a structured form. Standard meta-analytic methods were used to combine study results. Results: Sixteen studies were included; few compared the same drugs. The most frequently studied class of drugs was the triptans (n=12); seven of these compared sumatriptan to placebo. Overall, the triptans showed mild benefit over placebo with respect to headache alleviation (RR 1.13; 95% CI 1.06, 1.20) and complete headache relief (RR 1.34; 95% CI 1.18, 1.52). Although the triptans resulted in more adverse events compared to placebo (RD 0.15; 95% CI 0.07, 0.23), in all cases these were minor. There was evidence of publication bias suggesting that the observed effects may be overestimates. Subgroup analyses showed some variation in efficacy by age, study design, and methodological quality. Headache alleviation and complete headache relief were significantly improved for ibuprofen vs. placebo (n=2), prochlorperazine vs. ketorolac (n=1), and rizatriptan vs. standard care (n=1); ibuprofen significantly reduced headache recurrence compared to placebo (n=2). There were no significant differences for acetaminophen vs. placebo (n=1), dihydroergotamine vs. placebo (n=1), or acetaminophen vs. ibuprofen (n=1). Placebo response rates varied greatly from study to study causing some heterogeneity in the estimates. Conclusion: Triptans, ibuprofen, and prochlorperazine may be somewhat effective as abortive therapy for migraines in children. There is a paucity of evidence for other medications.
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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 | 0.024 | 0.072 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.033 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".