Gender-based factors associated with hepatitis C testing in people who inject drugs: results from the French COSINUS cohort
Bibliographic record
Abstract
OBJECTIVE: We identified factors associated with hepatitis C virus (HCV) testing in the previous 6 months in people who inject drugs (PWID) according to gender. DESIGN: ) is a multisite longitudinal cohort study conducted between June 2016 and May 2019. SETTING: Harm reduction facilities in two French cities (Marseille and Bordeaux). PARTICIPANTS: Eligibility criteria were as follows: 18 years of age or older, French speaking, regular use of illegal drugs or of prescribed medication, having injected at least once in the previous month and being able to provide informed consent to participate. We selected data for 298 participants (624 observations). PRIMARY OUTCOME: Self-reporting HCV testing in the previous 6 months. Gender was defined as self-identifying as a woman, man or transgender person. RESULTS: Seventy-nine per cent (n=235) of the sample were men, and 63% (n=189) reported HCV testing in the previous 6 months. Our results suggest that men recently incarcerated (OR (95% CI): 3.26 (1.31, 8.12), p=0.011), those regularly attending harm reduction facilities (OR (95% CI): 2.49 (1.47, 4.22), p=0.001), and those with lifetime attempted suicide (OR (95% CI): 2.07 (1.08, 3.95), p=0.028) were more likely to have been tested for HCV in the previous 6 months, whereas older men were less likely (OR (95% CI): 0.46 (0.24, 0.89), p=0.022). Women who had slept in the street (OR (95% CI): 3.95 (1.12, 13.89), p=0.032) were more likely to have been tested for HCV in the previous 6 months, whereas those employed (OR (95% CI): 0.31 (0.12, 0.83), p=0.019) and those with lifetime attempted suicide (OR (95% CI): 0.39 (0.16, 0.97), p=0.044) were less likely. CONCLUSION: Our results highlight the importance of improving current harm reduction facilities for PWID by adapting them to women's needs and paying special attention to women's mental health. Furthermore, in the context of primary care, improving provider training and reducing injection-related stigma may improve HCV testing uptake in older men and employed women.
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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 | 0.001 |
| Research integrity | 0.001 | 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".