Natural Health Product-Drug Interactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Interactions between natural health products (NHP) and prescription medications are of increasing concern. This paper aims to identify all clinical trials of NHP-drug interactions. To determine the prevalence and outcomes of clinical investigations of NHP-drug pharmacokinetic interactions, electronic databases were searched from inception through March 2004, as well as reference lists from published reports and experts in the field for unpublished studies. Eligible studies were clinical investigations of the interaction between a NHP and the metabolism of a regulated medication in humans. Studies were excluded that only investigated the metabolism of an NHP or examined food-drug or NHP-NHP interactions. Two reviewers selected studies for inclusion and independently extracted data. Forty-seven trials were identified, studying an average of 14 participants/study (95% confidence interval [CI] 11-18), examined drug interactions with 19 different herbal preparations. All trials were pharmacokinetic studies, 41 of healthy volunteers and 6 of patients. Ten different herbal medicines as well as 5 different traditional herbal concoctions were studied. Potentially clinically significant drug interactions were observed with St. John wort (16/24 studies), garlic (2/5 studies), and American ginseng (1 study). Research on NHP-drug interactions is limited in number and scope. With the exception of St. John wort, clinicians and the public do not have information that permits strong inferences about interactions between NHPs and conventional medications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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 it