Knowledge of hepatitis C and awareness of reinfection risk among people who successfully completed direct acting antiviral therapy
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) education may be changing following the simplification of HCV treatment and emergence of direct acting antiviral (DAA). We aimed to characterize HCV knowledge among people who recently completed DAA therapy. METHODS: The Per-SVR (Preservation of Sustained Virologic Response) is a prospective cohort of patients who achieved a sustained virologic response upon successful completion of DAA therapy. The per-SVR study provided the sampling frame of participants who completed a psychometrically validated 19-item HCV knowledge scale at cohort entry (n = 227). To score the questionnaire, for each correct response one point was awarded, with no point for incorrect response. We assessed mean HCV knowledge score in the overall sample and mutually exclusive populations: people who inject drug (PWID) (n = 71); people with co-occurring HIV (n = 23); PWID and co-occurring HIV (n = 29), and others (n = 104) Using a latent class analysis based on distal outcome, we identified unobserved subgroups and assessed HCV knowledge amongst them. RESULTS: Total mean (SD) percent of correct responses were 83 (11) in the overall sample; 83 (10) in PWID; 79 (12) in people with co-occurring HIV; 81 (10) in PWID and co-occurring HIV, and 84 (11) in rest of the sample Three latent groups were identified: baby boomers who ever experienced homelessness (n = 126); women sex workers who ever experienced homelessness (n = 68); men who inject drug, ever experienced homelessness and had ever diagnosis of mental health disorders (n = 18). Mean percent of correct responses were 85 (8), 82 (11), 85 (10), in latent class 1, 2, and 3, respectively. CONCLUSION: Patients successfully treated with DAAs had a high HCV knowledge. High knowledge and awareness of reinfection among complex patient groups often facing barriers to HCV care is encouraging and emphasizes the positive outcomes of universal access to treatment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".