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Record W3172905499 · doi:10.1089/aid.2021.0027

Short Communication: Prevalence of Transmitted Resistance to Non-Nucleoside Reverse Transcriptase Inhibitors in European and North American Countries Over 20 Years: An Updated Meta-Analysis

2021· review· en· W3172905499 on OpenAlexaboutno aff
Sonya J. Snedecor

Bibliographic record

VenueAIDS Research and Human Retroviruses · 2021
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrase inhibitorIntegraseVirologyResistance (ecology)Drug resistanceReverse transcriptaseMedicineHuman immunodeficiency virus (HIV)Reverse-transcriptase inhibitorEnvironmental healthBiologyAntiretroviral therapySidaViral diseasePolymerase chain reactionGeneticsViral load

Abstract

fetched live from OpenAlex

The prevalence of transmitted non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance around the world has been estimated up to 2010. Treatment recommendations have since evolved from NNRTIs to integrase strand inhibitors (INSTIs). This analysis estimates more recent trends in transmitted NNRTI resistance given emerging INSTI use. Studies reporting prevalence of transmitted NNRTI resistance in Europe, the United States, and Canada were meta-analyzed to generate yearly estimates in four regions. Overall prevalence of transmitted resistance continued to rise in the United States to >10% in 2015. Prevalence in European countries with larger surveillance networks was consistent at ∼4% from 2000 through 2012, increasing to 7% in 2016. Prevalence in European countries with fewer available data was generally <5%. Two publications with Canadian data were identified, reporting 0%-3% resistance. This analysis showed increasing prevalence of transmitted NNRTI resistance up to 2016, despite the availability of newer classes of treatments.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
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 head0.134
GPT teacher head0.405
Teacher spread0.271 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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