Interaction of St John's wort with conventional drugs: systematic review of clinical trials
Bibliographic record
Abstract
OBJECTIVE: To determine the methodological quality of clinical trials that examined possible interactions of St John's wort with conventional drugs, and to examine the results of these trials. DESIGN: Systematic review. DATA SOURCES: Electronic databases from inception to April 2004, reference lists from published reports, and experts in the field. STUDY SELECTION: Eligible studies were prospective clinical trials evaluating the pharmacokinetic effect of St John's wort on the metabolism of conventional drugs. DATA EXTRACTION: Two reviewers selected studies for inclusion and independently extracted data. DATA SYNTHESIS: 22 pharmacokinetic trials studied an average of 12 (SD 5) participants; 17 trials studied healthy volunteers and five studied patients. Most (17) studies used a "before and after" design; four studies used control groups other than the active group. Three studies randomised the sequence of administration or the participants to study arms or periods; three studies blinded participants or investigators. In 15 trials, investigators independently assayed the herb. Of 19 trials with available plasma data, three found no important interaction (change in area under the curve < 20%) and 17 found a decrease in systemic bioavailability of the conventional drug; in seven studies the 95% confidence interval excluded a decrease of < 20%. CONCLUSION: Clinicians and patients should beware of possible decreases in the systemic bioavailability of conventional drugs when taken concomitantly with St John's wort.
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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 | 0.026 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".