Prevalence of Human Immunodeficiency Virus-1 Integrase Strand Transfer Inhibitor Resistance in British Columbia, Canada Between 2009 and 2016: A Longitudinal Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Integrase strand transfer inhibitors (INSTIs) are highly efficacious and well tolerated antiretrovirals with fewer adverse side-effects relative to other classes of antiretrovirals. The use of INSTIs raltegravir, elvitegravir, and dolutegravir has increased dramatically over recent years. However, there is limited information about the evolution and prevalence of INSTI resistance mutations in clinical human immunodeficiency virus populations. Methods Human immunodeficiency virus-1-positive individuals ≥19 years were included if they received ≥1 dispensed prescription of antiretroviral therapy (ART) in British Columbia between 2009 and 2016 (N = 9358). Physician-ordered drug resistance tests were analyzed and protease inhibitor (PI), reverse-transcriptase inhibitor (RT), and INSTI resistance were defined as having ≥1 sample with a combined, cumulative score ≥30 by Stanford HIV Drug Resistance Algorithm version 7.0.1. Results Although most ART-treated individuals were tested for PI and RT resistance, INSTI resistance testing lagged behind the uptake of INSTIs among INSTI-treated individuals (11% in 2009; 34% in 2016). The prevalence of INSTI resistance was relatively low, but it increased from 1 to 7 per 1000 ART-treated individuals between 2009 and 2016 (P < .0001, R2 = 0.98). Integrase strand transfer inhibitor resistance mutations increased at integrase codons 66, 97, 140, 148, 155, and 263. Conclusions The prevalence of INSTI resistance remains low compared with PI and RT resistance in ART-treated populations but is expanding with increased INSTI use.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it