Association of patterns of methadone use with antiretroviral therapy discontinuation : a prospective cohort study
Bibliographic record
Abstract
Background Methadone maintenance therapy (MMT) is a proven treatment strategy for opioid dependent patients. Although studies have demonstrated that MMT increases contact with the medical system and improves adherence to antiretroviral therapy (ART) in HIV-positive people who inject drugs (PWID), the effect of MMT discontinuation on ART discontinuation has not been well described. Methods We examined the impact of continuous MMT use, MMT non-use and MMT discontinuation on the time to ART discontinuation (defined as 90 days of continuous non-use following previous enrolment) in a community-recruited prospective cohort of HIV-positive PWID followed between May 1996 and May 2013 in Vancouver, Canada. Multivariate Cox proportional hazards regression was used to examine the association between MMT use patterns and time to ART discontinuation while adjusting for socio-demographic confounders. Results A total of 794 HIV-positive PWID were included during the study period. In an adjusted analysis, in comparison to those who were continuously on MMT, MMT non-use (Adjusted Hazard Ratio [AHR] = 1.44, 95 % Confidence Interval [CI]: 1.19–1.73) as well as discontinuing MMT (AHR = 1.82, 95 % CI: 1.27–2.60) were both found to be independently associated with time to ART discontinuation. Conclusions This study reinforces the known benefits of MMT use on ART adherence and demonstrates how discontinuation of MMT is independently associated with an increased risk of ART cessation. These data highlight the importance of retaining PWID on MMT.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".