Prescription opioid injection and risk of hepatitis C in relation to traditional drugs of misuse in a prospective cohort of street youth
Bibliographic record
Abstract
OBJECTIVE: Despite dramatic increases in the misuse of prescription opioids, the extent to which their intravenous injection places drug users at risk of acquiring hepatitis C virus (HCV) remains unclear. We sought to compare risk of HCV acquisition from injection of prescription opioids to that from other street drugs among high-risk street youth. DESIGN: Prospective cohort study. SETTING: Vancouver, British Columbia, Canada from September 2005 to November 2011. PARTICIPANTS: The At-Risk Youth Study (ARYS) is a prospective cohort of drug-using adolescents and young adults aged 14-26 years. Participants were recruited through street-based outreach and snowball sampling. PRIMARY OUTCOME MEASURE: HCV antibody seroconversion, measured every 6 months during follow-up. Risk for seroconversion from injection of prescription opioids was compared with injection of other street drugs of misuse, including heroin, cocaine or crystal methamphetamine, using Cox proportional hazards regression controlling for age, gender and syringe sharing. RESULTS: Baseline HCV seropositivity was 10.6%. Among 512 HCV-seronegative youth contributing 860.2 person-years of follow-up, 56 (10.9%) seroconverted, resulting in an incidence density of 6.5/100 person-years. In bivariate analyses, prescription opioid injection (HR=3.48; 95% CI 1.57 to 7.70) predicted HCV seroconversion. However, in multivariate modelling, only injection of heroin (adjusted HR=4.56; 95% CI 2.39 to 8.70), cocaine (adjusted HR=1.88; 95% CI 1.00 to 3.54) and crystal methamphetamine (adjusted HR=2.91; 95% CI 1.57 to 5.38) remained independently associated with HCV seroconversion, whereas injection of prescription opioids did not (adjusted HR=0.94; 95% CI 0.40 to 2.21). CONCLUSIONS: Although misuse of prescription opioids is on the rise, traditional street drugs still posed the greatest threat of HCV transmission in this setting. Nonetheless, the high prevalence and incidence of HCV among Canadian street youth underscore the need for evidence-based drug prevention, treatment and harm reduction interventions targeting this 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".