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Record W1999659324 · doi:10.2174/1874357900701010008

Clinical Implications of Mutations at Reverse Transcriptase Codon 135 on Response to NNRTI-Based Therapy

2007· article· en· W1999659324 on OpenAlexafffund
Harout Tossonian, Jesse D. Raffa, Jason Grebely, Mark Viljoen, Annabel Mead, Milan Khara, Mark McLean, Ashok Krishnamurthy, Stanley DeVlaming, Brian Conway

Bibliographic record

VenueThe Open Virology Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsVancouver Coastal HealthUniversity of WaterlooUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsEtravirineReverse transcriptaseMutationVirologyMedicineReverse-transcriptase inhibitorLentivirusHuman immunodeficiency virus (HIV)Antiretroviral therapyStop codonBiologyRNAGeneticsGeneViral loadViral disease

Abstract

fetched live from OpenAlex

To evaluate the impact of mutations at reverse transcriptase codon 135 on treatment outcomes in patients receiving NNRTI-based antiretroviral therapy, a total of 68 patients (30 with and 38 without baseline mutations at codon 135) were evaluated. Median increases in CD4 counts were 135 and 90 cells/mm(3) (p=0.32), virologic suppression (HIV RNA < 400 copies/mL) was achieved in 16 (53%) and 16 (42%) patients (p=0.50), while NNRTI resistance was detected in 10/14 (71%) and 16/22 (73%) in patients with and without mutations at codon 135, respectively. Patients who experienced a virologic breakthrough and had a baseline mutation at codon 135 were more likely to evolve a single NNRTI resistance mutation (8/14 vs 4/22, p=0.029) but less likely to evolve multiple NNRTI resistance mutations (2/14 vs 12/22, p = 0.033). Mutations at codon 135 do not affect response rates, but affect the pattern of development of NNRTI resistance mutations. This has important implications for the subsequent use of newer NNRTIs such as etravirine in salvage therapy.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.088
GPT teacher head0.424
Teacher spread0.337 · 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

Citations4
Published2007
Admission routes2
Has abstractyes

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