Effect of opioid-substitution therapy and mental health counseling on HIV risk among hepatitis C-infected individuals
Bibliographic record
Abstract
BACKGROUND: Understanding differences in HIV incidence among people living with hepatitis C virus (HCV) can help inform strategies to prevent HIV infection. We estimated the time to HIV diagnosis among HCV-positive individuals and evaluated factors that could affect HIV-infection risk in this population. PATIENTS AND METHODS: The British Columbia Hepatitis Testers Cohort includes all BC residents (~1.5 million: about a third of all residents) tested for HCV and HIV from 1990 to 2013 and is linked to administrative health care and mortality data. All HCV-positive and HIV-negative individuals were followed to measure time to HIV acquisition (positive test) and identify factors associated with HIV acquisition. Adjusted HRs (aHRs) were estimated using Cox proportional-hazard regression. RESULTS: Of 36,077 HCV-positive individuals, 2,169 (6%) acquired HIV over 266,883 years of follow-up (overall incidence of 8.1 per 1,000 person years). Overall median (IQR) time to HIV infection was 3.87 (6.06) years. In Cox regression, injection-drug use (aHR 1.47, 95% CI 1.33-1.63), HBV infection (aHR 1.34, 95% CI 1.16-1.55), and being a man who has sex with men (aHR 2.78, 95% CI 2.14-3.61) were associated with higher risk of HIV infection. Opioid-substitution therapy (OST) (aHR 0.59, 95% CI 0.52-0.67) and mental health counseling (aHR 0.48, 95% CI 0.43-0.53) were associated with lower risk of HIV infection. CONCLUSION: Injection-drug use, HBV coinfection, and being a man who has sex with men were associated with increased HIV risk and engagement in OST and mental health counseling were associated with reduced HIV risk among HCV-positive individuals. Improving access to OST and mental health services could prevent transmission of HIV and other blood-borne infections, especially in settings where access is limited.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".