Treatment of Chronic Hepatitis C Infection among Current And Former Injection Drug Users within a Multidisciplinary Treatment Model at a Community Health Centre
Bibliographic record
Abstract
The aim of the present prospective observational study was to assess uptake and success of hepatitis C virus (HCV) treatment among a group of former and current injection drug users with chronic HCV infection at the Street Health Centre in Kingston, Ontario. The Street Health Centre offers hepatitis C education, assessment and treatment within a multidisciplinary, integrated and collaborative treatment model of care delivered by primary care professionals. The study enrolled a convenience sample of 34 patients. Seventy per cent of study patients had no postsecondary education, 85% were unemployed and one-third were unstably housed. A majority of study patients self-reported mental health problems. Of the 14 patients who initiated antiviral treatment in the study period, eight (57%) achieved sustained virological response. Regardless of virological outcome, patients who initiated treatment showed positive trends toward increased social and psychiatric stability, and decreases in high-risk behaviours. These results suggest that not only is successful treatment of chronic HCV infection in current and former injection drug users with concurrent psychiatric disorders possible, but the benefits of such treatment delivered in a community-based, multidisciplinary, primary care model may extend beyond narrowly defined virological outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".