Increased Prevalence of Controlled Viremia and Decreased Rates of HIV Drug Resistance Among HIV-Positive People Who Use Illicit Drugs During a Community-wide Treatment-as-Prevention Initiative
Bibliographic record
Abstract
BACKGROUND: Although treatment-as prevention (TasP) is a new cornerstone of global human immunodeficiency virus (HIV)-AIDS strategies, its effect among HIV-positive people who use illicit drugs (PWUD) has yet to be evaluated. We sought to describe longitudinal trends in exposure to antiretroviral therapy (ART), plasma HIV-1 RNA viral load (VL) and HIV drug resistance during a community-wide TasP intervention. METHODS: We used data from the AIDS Care Cohort to Evaluate Exposure to Survival Services study, a prospective cohort of HIV-positive PWUD linked to HIV clinical monitoring records. We estimated longitudinal changes in the proportion of individuals with VL <50 copies/mL and rates of HIV drug resistance using generalized estimating equations (GEE) and extended Cox models. RESULTS: Between 1 January 2006 and 30 June 2014, 819 individuals were recruited and contributed 1 or more VL observation. During that time, the proportion of individuals with nondetectable VL increased from 28% to 63% (P < .001). In a multivariable GEE model, later year of observation was independently and positively associated with greater likelihood of nondetectable VL (adjusted odds ratio = 1.20 per year; P < .001). Although the proportion of individuals on ART increased, the incidence of HIV drug resistance declined (adjusted hazard ratio = 0.78 per year; P = .011). CONCLUSIONS: We observed significant improvements in several measures of exposure to ART and virologic status, including declines in HIV drug resistance, in this large long-running community-recruited cohort of HIV-seropositive illicit drug users during a community-wide ART expansion intervention. Our findings support continued efforts to scale up ART coverage among HIV-positive PWUD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".