Suboptimal plasma HIV-1 RNA suppression and adherence among sex workers who use illicit drugs in a Canadian setting : an observational cohort study
Bibliographic record
Abstract
Objective—Studies have demonstrated the central function of plasma HIV-1 RNA viral load (pVL) levels on determining the risk of HIV disease progression and transmission. However, there is limited empirical research on virologic outcomes among sex workers who use illicit drugs (SWDU). Methods—Data were derived from the AIDS Care Cohort to evaluate Exposure to Survival Services, a cohort of HIV-positive illicit drug users. Using generalised estimating equations, we studied the longitudinal relationship between sex work and pVL suppression. We also tested whether adherence to antiretroviral therapy (ART) mediated the relationship between sex work and pVL suppression. Results—Between May 1996 and May 2012, 587 ART-exposed participants (2224 person-years of observation) were included in the study, among whom 127 (21.6%) reported sex work. In a time-updated multivariate model adjusted for various demographic, socioeconomic and clinical confounders (eg, gender, incarceration, CD4 cell count), SW-DU had an independently reduced odds of pVL suppression compared to non-SW-DU (adjusted OR (AOR)=0.66; 95% CI 0.45 to 0.96). However, adding ART adherence to the multivariate model eliminated this association (p>0.05), suggesting adherence mediated the relationship between sex work and pVL suppression. Conclusions—Evidence-based interventions to improve adherence to ART among SW-DU are urgently needed to help produce the maximum HIV treatment and prevention benefit of ART among this highly vulnerable population.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".