A Review of Evidence-Based Medicine and Meta-Analytic Reviews in Migraine
Bibliographic record
Abstract
The following systematic reviews and meta-analyses are presented and the results discussed: the evidence-based American guidelines, five systematic reviews on naratriptan, rizatriptan, eletriptan, sumatriptan and propranolol; a meta-analysis of sumatriptan, a meta-analysis of acute migraine therapy, a meta-analysis of triptans available in Canada and a large meta-analysis of oral triptans. The systematic reviews of several randomized trials of one drug overcome random effects in estimating treatment effect of the reviewed drug. The results from the large meta-analysis of several drugs are compared with head-to-head comparative trials. Results are generally the same in the meta-analysis and in the comparative trials, with some exceptions. Head-to-head comparisons should remain the 'gold standard' and meta-analyses are a useful supplement in cases when comparative trials are relatively small and when no comparative trials exist.
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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 | 0.025 | 0.084 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.016 |
| Bibliometrics | 0.019 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".