Rizatriptan for the acute treatment of migraine: Consistency, preference, satisfaction, and quality of life
Bibliographic record
Abstract
Rizatriptan for the acute treatment of migraine: Consistency, preference, satisfaction, and quality of life Farnaz Amoozegar, Tamara PringsheimCalgary Headache Assessment and Management Program, Department of Clinical Neurosciences, University of Calgary, Calgary, AB, CanadaAbstract: Rizatriptan is a 5HT (IB/ID) agonist with proven efficacy in the acute treatment of migraine headache. We performed a systematic review of the literature for clinical trials of rizatriptan incorporating important patient outcomes including consistency of response, preference, satisfaction, and quality of life. We found evidence that rizatriptan provides consistent relief of migraine attacks and that patients prefer rizatriptan over other treatments because of its speed of relief. Patient satisfaction with rizatriptan is significantly higher than placebo, but appears equivalent to most other triptans. Migraine-specific quality of life at 24 hours is significantly better in patients treated with rizatriptan compared to placebo, while overall long-term quality of life is less affected. The published clinical trials included in this systematic review are subject to bias due to the open-label nature of preference trials and the doses chosen for comparison in head-to-head trials.Keywords: migraine, rizatriptan, patient preference
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".