Seroprevalence of hepatitis C and correlates of seropositivity among men who have sex with men in Vancouver, Canada: a cross-sectional survey: Table 1
Bibliographic record
Abstract
OBJECTIVES: We sought to determine the prevalence of hepatitis C virus (HCV) infection among men who have sex with men (MSM) in Vancouver, Canada, and associations of risk behaviours with HCV serostatus. METHODS: We used data from the ManCount Study, a cross-sectional survey of MSM selected through a venue-based, time-location sampling method. Bivariate analyses and multivariate logistic regression modelling were used to determine correlates of HCV seropositivity. Bivariate analyses of participants who reported no history of injection drug use (IDU) were used to explore sexual behaviours associated with HCV seropositivity. RESULTS: HCV seroprevalence was 4.9% (56/1132). Among HCV-seropositive participants who responded to the question, 22.4% (11/49) were unaware of their HCV-seropositive status, 84.9% (45/53) reported a history of IDU and 60.7% (34/56) were HIV positive by dried blood spot. Multivariate modelling found previous IDU (adjusted OR (AOR): 26.30, 95% CI 11.15 to 62.03), receiving goods, drugs or money for sex (AOR 4.98, 95% CI 2.43 to 10.20) and current smoking (AOR 3.46, 95% CI 1.47 to 8.16) were associated with HCV seropositivity. Among MSM who reported no history of IDU, HCV seropositivity was associated with bleeding after receptive anal sex (p=0.001) and a previous diagnosis of gonorrhoea (p=0.007). CONCLUSIONS: HCV seroprevalence among a sample of MSM is higher than the general population and associated with a history of IDU. Among those who did not report IDU, we found evidence that suggests sexual exposure could be the route of transmission.
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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".