Optimizing assessment and treatment for hepatitis C virus infection in illicit drug users: a novel model incorporating multidisciplinary care and peer support
Bibliographic record
Abstract
OBJECTIVES: We evaluated assessment and treatment for hepatitis C virus (HCV) among illicit drug users accepting referral to a weekly HCV peer-support group at a multidisciplinary community health centre. METHODS: From March 2005 to 2008, HCV-infected individuals were referred to a weekly peer-support group and assessed for HCV infection. A retrospective chart review of outcomes 3 years after the initiation of the group was conducted (including HCV assessment and treatment). RESULTS: Two hundred and four HCV antibody-positive illicit drug users accepted referral to a weekly HCV peer-support group. Assessment for HCV occurred in 53% of patients(n= 109), with 13% (n= 14) having initiated or completed treatment for HCV infection before attending the support group, evaluation ongoing in 10% (n= 11) and treatment deferred/not indicated in 25% (n= 27). The major reasons for HCV treatment deferral included early disease (30%),drug dependence (37%), other medical (11%) or psychiatric comorbidities (4%). Sixty-eight percent of those deferred for reasons other than early liver disease showed multiple reasons for treatment deferral. The first 4 weeks of support group attendance predicted successful HCV assessment (odds ratio: 6.03, 95% confidence interval:3.27-11.12, P < 0.001). Overall, 28% (n= 57) received treatment. Among individuals having completed pegylated-interferon and ribavirin therapy with appropriate follow-up (n =19), the rate of sustained virologic response was 63% (12/19), despite illicit drug use in 53%. CONCLUSION: A high proportion of illicit drug users accepting referral to a weekly HCV peer-support group at a multidisciplinary health centre were assessed and treated for HCV infection. Peer support coupled with multidisciplinary care is an effective strategy for engaging illicit drug users in HCV care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".