Towards HCV elimination among people who inject drugs in Hai Phong, Vietnam: study protocol for an effectiveness-implementation trial evaluating an integrated model of HCV care (DRIVE-C: DRug use & Infections in ViEtnam–hepatitis C)
Bibliographic record
Abstract
INTRODUCTION: In Vietnam, people who inject drugs (PWID), who are the major population infected by hepatitis C virus (HCV), remain largely undiagnosed and unlinked to HCV prevention and care despite recommended universal hepatitis C treatment. The data on the outcomes of HCV treatment among PWID also remain limited in resource-limited settings. The DRug use & Infections in ViEtnam-hepatitis C (DRIVE-C) study examines the effectiveness of a model of hepatitis C screening and integrated care targeting PWID that largely uses community-based organisations (CBO) in Hai Phong, Vietnam. In a wider perspective, this model may have the potential to eliminate HCV among PWID in this city. METHODS AND ANALYSIS: The model of care comprises large community-based mass screening, simplified treatment with direct-acting antivirals (DAAs) and major involvement of CBO for PWID reaching out, linkage to care, treatment adherence and prevention of reinfection. The effectiveness of DAA care strategy among PWID, the potential obstacles to widespread implementation and its impact at population level will be assessed. A cost-effectiveness analysis is planned to further inform policy-makers. The enrolment target is 1050 PWID, recruited from the DRIVE study in Hai Phong. After initiation of pan-genotypic treatment consisting of sofosbuvir and daclatasvir administrated for 12 weeks, with ribavirin added in cases of cirrhosis, participants are followed-up for 48 weeks. The primary outcome is the proportion of patients with sustained virological response at week 48, that will be compared with a theoretical expected rate of 70%. ETHICS AND DISSEMINATION: The study was approved by Haiphong University of Medicine and Pharmacy's Ethics Review Board and the Vietnamese Ministry of Health. The sponsor and the investigators are committed to conducting this study in accordance with ethics principles contained in the World Medical Association's Declaration of Helsinki (Ethical Principles for Medical Research Involving Human Subjects). Informed consent is obtained before study enrolment. The data are anonymised and stored in a secure database. The study is ongoing. Results will be presented at international conferences and submitted to international peer-review journals. TRIAL REGISTRATION NUMBER: NCT03537196.
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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 | 0.018 | 0.013 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 0.007 |
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".