Tendencias en las investigaciones y publicaciones sobre las interacciones hierba-fármacos
Bibliographic record
Abstract
"There is a lack of basic knowledge about the affirmation that herbs, vitamins, and other dietary supplements may augment or antagonize the actions of prescription and nonprescription drugs. This event should be taking account as to the indications for use and safety of herbal medicines regarding the possibility of herbal-drug interactions. The objectives of this study were to review the literature for evidence and tendencies on the use, safety and pharmacology of herbal-drug interactions. To do it was searched the PubMed electronic database papers regarding to "herbal-drug interactions" until December 2007 and compiled data according to the grade of evidence found. It was compiled a total of 413 papers related with the approached topic. The drugs more studied were warfarin, anti-neoplastic agents and digoxin and the herbals were hypericum, ginkgo, panax, kava, garlic, valerian and tea. The major investigations were executed on in vitro studies, principally on cytochrome P450 and P-glycoprotein. On the in vivo pre-clinical investigation; it was researched that the major papers used rats, mice, rabbits, and others. The countries with more publications were USA, Canada, United Kingdom, Japan, Germany, Australia, and Italy; the principal authors and Institutions were also from these countries. There was an increase in the published articles from 1999 reaching the maximal production in 2006 (74 papers). The journal with the major number of papers was Br J Clin Pharmacol. The type of article more written was the Review and the English was the language more used in these papers. There is an obvious interest regarding the herbal-drug interactions manifested in the increasing of the number of paper published about this topic. These investigations are not sufficient if we taking account the herbal medicine is one of most popular choices of complementary therapies and it could induce interactions with the conventional medicines translated in a deficient treatment or adverse reactions that conduce to an erroneous therapy. It is important to recognize that there are not papers from Latin-American & Caribbean region related with herbal-drug interactions."
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.
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 | 0.028 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.021 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".