Descriptive epidemiology of hepatitis C in individuals referred for specialized HCV care in Newfoundland and Labrador, 1996–2014
Bibliographic record
Abstract
Background: Despite growing awareness of the significant burden of disease caused by hepatitis C virus (HCV) infection worldwide, understanding of the epidemiology and demographic distribution of HCV infection in Canada, specifically in Atlantic Canada, is limited. Currently, data on the demographic and clinical profile of HCV-infected individuals in Newfoundland and Labrador is limited. The aim of this study is to address this knowledge gap. Methods: A retrospective cohort study of HCV-positive individuals referred for specialized care in St. John's, Newfoundland, between 1996 and 2014, was conducted. Descriptive data were obtained through chart review and access to a database consisting of individuals referred for specialized HCV care in St. John's. Results: During the study period, 767 individuals were referred for specialized HCV care, of whom 714 were included in our analysis. These individuals represent 57.5% of HCV-positive cases identified by the province's public health department during the same time frame. HCV infection was more common among men (68.2%) and urban dwellers (74.8%). The majority of cases were HCV genotype 1 (52.1%). Intravenous and intranasal drug use were the most common self-reported risk factors for HCV transmission. High loss-to-follow-up rates were found among those referred from the province's correctional system. Conclusions: This study provides important insights into the demographic and clinical profile of individuals referred for HCV-related care in Newfoundland and Labrador and fills a gap in the current understanding of HCV-positive individuals in this Atlantic province. These findings can help inform future directions for HCV-related health policy, resource allocation, and clinical care initiatives in Newfoundland and Labrador and across Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".