Safety profile of a special butterbur extract from<i>Petasites hybridus</i>in migraine prevention with emphasis on the liver
Bibliographic record
Abstract
Background: Butterbur supplements are available in the USA and Canada and are commonly used for treating migraines. Petadolex, a special butterbur extract from Petasites hybridus, is a natural herbal product and the only butterbur extract with proven clinical efficacy in migraine prevention. The Complimentary Migraine Guidelines of the AAN mention butterbur as level A recommendation for the prevention of chronic episodic migraine. However, these guidelines have been retired. Methods: We review suspected serious liver cases, pyrrolizidine alkaloids, regulatory issues, preclinical and clinical data of the special butterbur extract Petadolex. Results: The RUCAM (Roussel Uclaf Causality Assessment Method) test found no probable relationship between the butterbur root extract Petadolex® and cases of serious liver injury. Two cases of non-serious reversible liver enzyme elevations were rated as probably related to Petadolex®. The safety is supported by preclinical data in animals as well as in-vitro toxicology experiments. In addition, Petadolexis free of detectable levels of pyrrolizidine alkaloids. Conclusion: There is no evidence that the special butterbur root extract Petadolex poses a substantial risk of liver injury for patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".