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Record W4407512300 · doi:10.1186/s12913-025-12374-9

Scaling up hepatitis C testing and linkage-to-care among people who use drugs: lessons learned from a pilot project implemented at a supervised consumption site

2025· article· en· W4407512300 on OpenAlexaffabout
Nandini Krishnan, Kirti Singh, Shannon Bytelaar, Deb Schmitz, Sofia Bartlett, David S. Hall, Rolando Barrios, Julio Montaner, Marianne Harris, Mark Hull, Kate Salters

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of British ColumbiaBC Centre for Disease ControlAIDS Vancouver
FundersGilead Sciences
KeywordsMedicineNursing researchFamily medicinePopulationPublic healthHepatitis CHealth careHealth administrationEnvironmental healthNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Despite rolling out publicly-funded hepatitis C virus (HCV) treatment across the province of British Columbia (BC), Canada, 35% of people returning positive HCV RNA results in 2020 did not initiate treatment. The HCV epidemic in Canada continues to disproportionately impact people who use drugs and yet, this population has the lowest proportional uptake of HCV treatment. Evidence suggests linkages to healthcare after diagnosis is one of the key factors that impacts uptake of HCV treatment among this priority population. The Hep C Connect pilot project was implemented to characterize HCV testing outcomes and linkage-to-care rates within a low-barrier supervised consumption site (SCS) in Vancouver, BC. METHODS: All clients (aged ≥ 19 years) attending the Hope to Health SCS in Vancouver, Canada were invited to participate in the pilot study between November 2021 and December 2022. Interviewer-led surveys were conducted and participants were offered same-day HCV point-of-care (POC) antibody (Ab) testing. Participants received a cash honorarium for sharing their time and experiences. Descriptive statistics are shared in order to describe the reach and impact of this pilot project. RESULTS: The study enrolled 186 participants including 123(66.1%) men and 59(31.7%) women, with a median age of 42 (Q1,Q3- 34,49). Forty-seven (25.3%) participants stated that they use an SCS regularly and 123(66.1%) stated that they get new rigs every day. Notably, 64(34.4%) participants reported not having a primary care provider yet more than three-quarters of the participants (144, 77.4%) reported having been ever tested for HCV. All 186 participants agreed to HCV POC Ab testing with 59.7% returning a positive HCV POC Ab result. Despite good HCV POC Ab uptake and high rates of HCV knowledge, 49(44.1%) of the HCV Ab positive participants chose not to engage in confirmatory ribonucleic acid (RNA) testing. CONCLUSIONS: The Hep C Connect pilot explored the gaps evident in the HCV cascade-of-care as it pertains to people who use drugs. Findings suggest that, despite high levels of HCV knowledge, the employment of blood draw RNA testing deterred people from engaging in confirmatory testing. Improving the HCV cascade-of-care will require alternative strategies that are more acceptable to this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.686

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0030.002
Open science0.0040.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.214
GPT teacher head0.478
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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