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Record W2132806259 · doi:10.1086/324351

The Effect of Garlic Supplements on the Pharmacokinetics of Saquinavir

2002· article· en· W2132806259 on OpenAlexaff
Stephen C. Piscitelli, Aaron H. Burstein, Nada Welden, Keith Gallicano, Judith Falloon

Bibliographic record

VenueClinical Infectious Diseases · 2002
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsSeagen (Canada)
Fundersnot available
KeywordsSaquinavirMedicineCmaxPharmacokineticsDosingPharmacologyTrough ConcentrationImmunology

Abstract

fetched live from OpenAlex

Herbal therapies are widely used, but there are few data on their interactions with conventional medications. This study evaluated the effect of garlic supplements on the pharmacokinetics of saquinavir. Ten healthy volunteers received 10 doses of saquinavir (Fortovase) at a dosage of 1200 mg 3 times daily with meals for 4 days on study days 1-4, 22-25, and 36-39, and they received a total of 41 doses of garlic caplets taken 2 times daily on study days 5-25. Blood samples were obtained on study days 4, 25, and 39 for determination of saquinavir plasma pharmacokinetic parameters. In the presence of garlic, the mean saquinavir area under the curve (AUC) during the 8-h dosing interval decreased by 51%, trough levels at 8 h after dosing decreased by 49%, and the mean maximum concentrations (Cmax) decreased by 54%. After the 10-day washout period, the AUC, trough, and Cmax values returned to 60%-70% of their values at baseline. Patients should use caution when combining garlic supplements with saquinavir when it is used as a sole protease inhibitor.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.042
GPT teacher head0.385
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations430
Published2002
Admission routes1
Has abstractyes

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