Hepatitis C Virus Seroprevalence, Incidence, and Screening Patterns in Ontario Preexposure Prophylaxis Users
Bibliographic record
Abstract
Abstract Background Hepatitis C virus (HCV) has emerged as a sexually transmitted infection in gay, bisexual, and other men who have sex with men (GBM). We estimated the seroprevalence and incidence of HCV infection and examined patterns of HCV testing among GBM using human immunodeficiency virus preexposure prophylaxis (PrEP) in Ontario, Canada. Methods We analyzed data from the Ontario PrEP Cohort Study (ON-PrEP), a prospective cohort of PrEP users from 10 Ontario clinics. Participants completed an online questionnaire and study staff collected clinical information into a study database biannually for 2 years. We estimated the baseline seroprevalence and incidence of HCV infection and examined patterns of HCV testing during follow-up. We further explored differences in sociodemographic/clinical variables between those with and without prevalent/incident HCV infection through bivariate analysis. Results Among 557 eligible PrEP users, 382 (68.6%) underwent baseline HCV antibody testing, of whom 5 tested HCV seropositive, giving a seroprevalence of 1.3% (95% confidence interval [CI], .43%–3.03%). Only 245 (43.9%) participants underwent HCV antibody testing after baseline, and median time to participants’ first follow-up test was 245 days. During follow-up, 2 participants tested newly HCV seropositive, giving an incidence of 0.47/100 person-years (95% CI, .06–1.69) over 428.9 years of follow-up. Participants with prevalent/incident HCV infection during the study appeared more likely to report giving money, drugs, gifts, or services for sex in the 3 months preceding enrollment compared to those who never tested HCV seropositive (P = .02). Conclusions HCV seroprevalence and incidence were low but not negligible among Ontario PrEP users. HCV antibody and RNA testing were suboptimal.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".