The evolving drug epidemic of prescription opioid injection and its association with HCV transmission among people who inject drugs in Montréal, Canada
Bibliographic record
Abstract
AIMS: To examine temporal trends in prescription opioid (PO) injection and to assess its association with hepatitis C virus (HCV) seroconversion among people who inject drugs (PWID). DESIGN: Prospective cohort study spanning 2004 to 2016. SETTING: Montréal, Canada. PARTICIPANTS: PWID reporting injection during the past 6 months. MEASUREMENTS: PWID were recruited between 2004 and 2016. At each 3-6-month follow-up visit, participants completed interview-administered questionnaires and were tested for HCV-antibody. FINDINGS: Among 1524 PWID [83% males, mean age 38 years, standard deviation (SD) = 10, 34% (31-36) prescription opioid (PO) injection past month] included in trends analyses, PO injection use expanded between 2004 and 2009, and plateaued between 2010 and 2016 (trend tests < 0.001 and 0.335, respectively). Of the 432 HCV-seronegative PWIDs followed at least once (81% males, mean age 34, SD 9.8, 38% injection PO), 153 became HCV-antibody-positive during 1230 years of follow-up, for an incidence of 12.4 per 100 person-years [95% confidence interval (CI) = 10.6, 14.6]. PO injectors were 3.9 times more likely to seroconvert to HCV, relative to non-PO injectors. In a multivariate analysis, a stronger association between PO injection and HCV seroconversion was found post-2009 [adjusted hazard ratio (aHR) = 5.4, 95% CI = 2.7, 10.8] than before (aHR = 1.5, 95% CI = 0.9, 2.4) (P-value for interaction = 0.001). CONCLUSION: Prescription opioid injection increased among people who inject drugs in Montréal, Canada from 2004 to 2009, to reach a plateau between 2010 and 2016. The association between prescription opioid injection and HCV seroconversion was stronger during the second period than the first according to the epidemic phase.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".