Effectiveness and Safety of Rizatriptan Benzoate 10 mg in the Treatment of Migraine Headaches
Bibliographic record
Abstract
Background Patients that do not achieve therapeutic response with over the counter non-triptan medications may benefit from triptan-based treatments. Objective Phase I V, open-label, multi-center, prospective cohort study assessing the effectiveness of rizatriptan in the management of migraines for patients that have not responded to non-triptan treatment. Methods Patients were treated with one rizatriptan (MAXALT RPD®) 10 mg wafer at the onset of each migraine attack and were assessed after a minimum of one and a maximum of two consecutive headache episodes. Outcome measures included self-reported assessments (severity and duration of migraine headache) and the Migraine ACT questionnaire. Results A total of 369 patients were enrolled, of which 291 and 215 reported one and two attacks, respectively. For the first and second attacks, 47.2% and 53.9% of patients reported complete resolution of pain while 73.6% and 77.0% reported pain severity reduction within two hours of onset. Mean (SD) pain severity score (four-point Likert scale) during the 488 migraine episodes was reduced significantly ( P < 0.001) from 2.56 (0.49) at onset to 1.91 (0.85) at 30, 1.31 (1.00) at 60 and 0.84 (1.00) at 120 minutes. Similar improvements were observed for changes in Migraine ACT questionnaire scores. No treatment-related serious adverse events were reported. The most frequently reported non-serious adverse events that were attributed to the study drug were dizziness (2.2%), chest discomfort (1.1%), nausea (1.1%), and somnolence (0.8%). Conclusion In a real-life setting, rizatriptan benzoate 10 mg is effective and safe in the treatment of acute migraine headaches in patients who do not respond to non-triptan treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".