Dispensation of antiretroviral therapy and methadone maintenance therapy at the same facility in a low‐barrier setting linked to optimal adherence to <scp>HIV</scp> treatment
Bibliographic record
Abstract
OBJECTIVES: We sought to examine the association between dispensation of methadone maintenance therapy (MMT) and antiretroviral therapy (ART) at the same facility, across multiple low-barrier dispensing outlets, and achieving optimal adherence to ART among people who use illicit drugs (PWUD). METHODS: We used data from the AIDS Care Cohort to Evaluate Exposure to Survival Services (ACCESS) study, a long-running study of a community-recruited cohort of HIV-positive PWUD, linked to comprehensive HIV clinical records in Vancouver, Canada, a setting of no-cost, universal access to HIV care. The longitudinal relationship between MMT-ART dispensation at the same facility and the odds of ≥ 95% ART adherence was analysed using multivariable generalized linear mixed-effects modelling. We conducted a further analysis using a marginal structural mode with inverse probability of treatment weights as a sensitivity analysis. RESULTS: This study included data on 1690 interviews of 345 ART- and MMT-exposed participants carried out between June 2012 and December 2017. In the final multivariable model, MMT-ART dispensation, compared with nondispensation at the same facility, was associated with greater odds of achieving ≥ 95% adherence [adjusted odds ratio (AOR) 1.56; 95% confidence interval (CI) 1.26-1.96]. A marginal structural model estimated a 1.48 (95% CI 1.15-1.80) greater odds of ≥ 95% adherence among participants who reported MMT-ART dispensation at the same facility compared with those who did not. CONCLUSIONS: The odds of achieving optimal adherence to ART were 56% higher during periods in which MMT and ART medications were dispensed at the same facility, in a low-barrier setting. Our findings highlight the need to consider a simpler integrated approach with medication dispensation at the same facility in low-threshold settings.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".