Consultation and Survey for Drug Interaction in Outpatients Taking the Medicines Potentially Interact with St. John's Wort
Bibliographic record
Abstract
Ministry Health Welfare of Japan announced the caution for drug interaction of St. John's Wort (SJW), a herbal supplement occasionally used for depression, on May, 2000. Immediately after the announcement, we conducted drug consultation for outpatients prescribed the medicines potentially interacting with SJW. We provided information concerning possible drug interaction with SJW for 741 outpatients (except for pediatrics) during the period of May 22-June 16, 2000. The potential drugs prescribed frequently were warfarin (28.0%), theophylline (19.7%), digitalis (18.4%), carbamazepine (7.2%), disopyramide (6.9%) and cyclosporin (6.3%). Of the patients, 401 subjects were surveyed by collecting the questionnaires to clarify the background of SJW drug interaction. Twenty-two subjects (5.5%) have known commercially available SJW products, 5 subjects (1.2%) have ever taken SJW products before and 2 subjects (0.5%) have taken SJW products concomitant with prescribed medicines. Gender difference was observed in paying attention to SJW products; female subjects (8.6%) tended to have more interest in SJW products than male subjects (2.8%). Two subjects taking SJW have realized for the first time that the supplements they took were SJW products when their package photographs were shown at the consultation. Showing the package photographs might be helpful for making the patients easy to identify the SJW products, because most patients do not pay attention to whether the supplements contain SJW or not. It is recommended that drug consultation should be provided to avoid serious drug interaction with SJW while the outpatients are taking potential medicines prescribed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".