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Record W1557841390 · doi:10.1684/vir.2013.0479

Antiretroviral therapy with integrase inhibitors: more options.

2013· article· en· W1557841390 on OpenAlexaff
François Raffi, Mark A. Wainberg

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsElvitegravirDolutegravirCobicistatIntegraseRaltegravirIntegrase inhibitorRitonavirPharmacologyMedicineVirologyTenofovir alafenamideHuman immunodeficiency virus (HIV)Antiretroviral therapyViral load

Abstract

fetched live from OpenAlex

Strand transfer inhibitors of HIV-1 integrase represent a new and very potent class of compounds, besides reverse transcriptase and protease inhibitors. The first integrase inhibitor, raltegravir, was made available in 2007. Recently, phase 3 studies of two new compounds - elvitegravir which needs pharmacological boosting with either ritonavir or cobicistat, and dolutegravir - have been presented, showing high virologic success rates, over 48-96 weeks, both in first-line antiretroviral therapy and in the treatment of experienced patients. The clinical tolerance of the three inhibitors is good, and they have globally a good safety profile. Dolutegravir and cobicistat exerts a blockade of the renal tubular secretion of creatinine, leading to a decrease in estimated creatinine clearance, which does not reflect renal toxicity, i.e. decrease in glomerular filtration. Both dolutegravir and elvitegravir (within the fixed dose combination of TDF/FTC/elvitegravir/cobicistat) should be available in clinical practice soon, which will offer more options for the strategic use of integrase inhibitors to treat both HIV-1 and possibly HIV-2 infections.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.051
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0510.009

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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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 designNot applicable
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

Citations1
Published2013
Admission routes1
Has abstractyes

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