Drug Interaction between St. John's Wort and Cyclosporine
Bibliographic record
Abstract
OBJECTIVE: To report a probable drug interaction between the herbal dietary supplement St. John's wort and cyclosporine. CASE REPORT: A 29-year-old white woman who received a cadaveric kidney and pancreas transplant, with stable organ function and stable cyclosporine concentrations began self-medicating with St. John's wort. After taking St. John's wort supplements for four to eight weeks, her cyclosporine concentrations became subtherapeutic; this was associated with organ rejection. Four weeks after stopping St. John's wort, her cyclosporine concentrations again became therapeutic. Subsequent to this rejection episode, she has developed chronic rejection and now has returned to dialysis. DISCUSSION: St. John's wort is suspected to be a significant inducer of CYP3A4 isoenzyme activity and of P-glycoprotein (P-gp) expression, both of which are important in the metabolism and absorption of cyclosporine. Cyclosporine exhibits a relatively small therapeutic window and is sensitive to medications that can modulate the CYP3A4 isoenzyme and P-gp in both the liver and small intestines. CONCLUSIONS: Patients taking St. John's wort concomitant with other prescription medications whose absorption and metabolism are mediated by the CYP3A4 isoenzyme and P-gp require close monitoring. Patient medication histories should include inquiries into the use of herbal dietary supplements.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".