Treatment of Children With Migraine in the Emergency Department
Bibliographic record
Abstract
OBJECTIVE: To evaluate which treatment could be effective in the emergency department (ED) for children with migraine and status migrainosus, we carried out a qualitative systematic review of randomized controlled trials (RCTs) that evaluated treatment that could be used for those conditions. METHODS: Databases (Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Cochrane Controlled Trials Register, MedLine, and EMBASE) were searched for RCTs that evaluated treatment of migraine in children (<18 years of age). Guidelines published on the subject were checked for missed references. Characteristics of the identified studies as well as primary outcome (headache relief), other recognized primary outcomes, and adverse events were abstracted. Quality of the RCTs was evaluated using the Jadad score. RESULTS: Of the 14 trials included in the review, only 1 was performed in an ED after other treatments have failed. In that situation, prochlorperazine was more effective than ketorolac in relieving pain at 1 hour. Other treatments were evaluated by neurologists on their outpatients who started the studied drugs early at the beginning of the migraine without previous treatment. In that situation, ibuprofen (n = 3) and acetaminophen (n = 1) were better than placebo for pain relief. The efficacy of intranasal sumatriptan (n = 4), oral rizatriptan (n = 3), and oral zolmitriptan (n = 2) for pain relief was unclear. Oral sumatriptan (n = 1) and oral dihydroergotamine (n = 1) were not effective. CONCLUSIONS: There is a lack of studies addressing the question of treatment in the ED for children experiencing migraine. Although other treatments were found effective in children with migraine, none was evaluated in the ED except prochlorperazine and ketorolac.
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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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".