Use of St. John's Wort in Potentially Dangerous Combinations
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to assess how often St. John's wort (SJW) is prescribed with medications that may interact dangerously with it. DESIGN: The study design was a retrospective analysis of nationally representative data from the National Ambulatory Medical Care Survey. SETTINGS: The study setting was U.S. nonfederal outpatient physician offices. SUBJECTS: Those prescribed SJW between 1993 and 2010 were the subjects. OUTCOME MEASURES: The outcome measures were medications co-prescribed with SJW. RESULTS: Twenty-eight percent (28%) of SJW visits involved a drug that has potentially dangerous interaction with SJW. These included selective serotonin reuptake inhibitors, benzodiazepines, warfarin, statins, verapamil, digoxin, and oral contraceptives. CONCLUSIONS: SJW is frequently used in potentially dangerous combinations. Physicians should be aware of these common interactions and warn patients appropriately.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".