A26 TREATMENT OUTCOMES OF HCV-INFECTED PATIENS IDENTIFIED THROUGH THE COMMUNITY POP-UP CLINIC
Bibliographic record
Abstract
In Canada, it is estimated that over 300,000 individuals are infected with HCV, with 60,000 residing in British Columbia. The prevalence of infection on Vancouver’s Downtown East Side (DTES) may exceed 70%, with relatively few individuals having been treated to date. This may relate to a lack of engagement in medical care. We developed a novel model of intervention, the Community Pop-up Clinics (CPC) as a tool to enhance access to medical care and HCV therapy in this vulnerable population. We aim to further understand the treatment outcomes of HCV infected individuals identified through this initiative. Participants were recruited at CPCs held at several community centres. OraQuick® HCV Rapid Antibody and HIV Rapid Antibody point-of-care testing was offered. Participants identified as HCV positive were provided the opportunity to engage in care at a multidisciplinary clinic. A questionnaire was administered to collect demographic information, HCV disease knowledge, and data regarding barriers to receiving healthcare. A $10 gift-card incentive was provided for participants who completed the demographic questionnaire and testing. A total of 2378 participants (mean age 49.9 years, 93.4% male) were tested for HCV infection, with 658 (27.7%) infected with HCV including 51 (7.7%) co-infected with HIV. Among HCV infected participants, 157 (27.6%) were linked to care (76% male, 30% First Nations, 28% homeless, 78% recent PWID), 26 (16.9%) started treatment for HCV infection, 19 (73%) completed treatment, and 16 (84.2%) achieved sustained virologic response (SVR). Groups under-represented among those engaged in care include: females (7%), lack of knowledge about how to access health care (9%), homeless (9%), perceived their health status as good (14%), First Nations (15%). Our CPC approach in a neighborhood with HCV prevalence of 70% has successfully identified over 600 HCV-infected individuals and engaged a significant proportion of them in care. Additional efforts must be undertaken to engage certain populations such as women, First Nations and those who are homeless and in ensuring that engagement leads to enhanced access to curative HCV therapies in all eligible patients. None
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".