Acute treatment of paediatric migraine: A meta‐analysis of efficacy
Bibliographic record
Abstract
AIM: To undertake a meta-analysis of all randomised controlled trials (RCTs) on the acute pharmacologic treatment of children and adolescents with migraine headache. METHODS: In total, 139 abstracts of clinical trials specific to the acute treatment of paediatric migraine were appraised. Inclusion criteria required clinical trials to be randomised, blinded, placebo-controlled studies with comparable endpoints. Non- English language publications were excluded. 11 clinical trials qualified for inclusion in the final meta-analysis. Two endpoints were analysed: the proportion of patients with (1) headache relief, and (2) complete pain relief, 2 h post-treatment. RESULTS: The following medications were included in the analysis: acetaminophen (n = 1), ibuprofen (n = 2), sumatriptan (n = 5), zolmitriptan (n = 1), rizatriptan (n = 2) and dihydroergotamine (n = 1). Results are expressed as a relative benefit (RB) conferred over placebo and the number needed to treat (NNT). Only ibuprofen and sumatriptan provided a statistically significant relative efficacy in comparison with placebo. Two hours post-treatment, ibuprofen was associated with an RB 1.50 (95% CI 1.15-1.95) in the generation of headache relief (NNT 2.4) and RB 1.92 (95% CI 1.28-2.86) in the production of complete pain relief (NNT 4.9). Sumatriptan rendered an RB 1.26 (95% CI 1.13-1.41) in headache relief (NNT 7.4) and an RB 1.56 (95% CI 1.26-1.93) in the production of complete pain relief (NNT 6.9). CONCLUSION: Despite the pharmacological options for the management of acute migraine, few RCTs in the paediatric population exist. Composite data demonstrate that only ibuprofen and sumatriptan are significantly more effective than placebo in the generation of headache relief in children and adolescents.
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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 | 0.030 | 0.045 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.073 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".