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Interactions between protease inhibitors and acid‐reducing agents: a systematic review

2007· review· en· W2080148423 on OpenAlexaff
L Béïque, Pierre Giguère, Charles la Porte, Jonathan B. Angel

Bibliographic record

VenueHIV Medicine · 2007
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsOttawa Public HealthOttawa Hospital
FundersBristol-Myers Squibb
KeywordsMedicinePharmacokineticsPharmacologyPharmacokinetic interactionMEDLINEDrugProteaseDrug interactionBioinformaticsBiochemistryEnzymeChemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this article is to provide a systematic review of the available pharmacokinetic and clinical data on drug interactions between protease inhibitors (PIs) and acid-reducing agents, and their clinical relevance. METHODS: A literature search was performed using Medline and EMBASE, abstracts of the previous 2 years of major conferences were searched and the drug information service of the manufacturer of every currently available PI was contacted. All data were summarized, and verified by at least two authors. RESULTS: A total of 1231 references were identified, 22 of which were studies of pharmacokinetic interactions between PIs and acid-suppressive agents and a further 12 of which provided pharmacokinetic and/or clinical data. CONCLUSIONS: Many pharmacokinetic studies show a lack of a drug interaction between at least one acid-reducing agent and most PIs. Little clinical information is available, except on interactions between atazanavir and acid-reducing agents. This is probably a consequence of the complexity of the interaction.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.440
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.088
GPT teacher head0.396
Teacher spread0.309 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations26
Published2007
Admission routes1
Has abstractyes

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