Population-level cascade of care for hepatitis C in Newfoundland and Labrador
Bibliographic record
Abstract
Background: Global elimination of hepatitis C virus (HCV) is feasible using existent tools. Reporting the provincial HCV care cascade will contribute to national and global HCV elimination efforts. Methods: This observational study was a secondary use of population-level medical record data, including laboratory results for HCV testing and prescription data for HCV treatment in the province of Newfoundland and Labrador (NL). All patients with HCV antibody testing performed between Jan 1, 2017 and Jan 1, 2022 were included. All prescriptions dispensed from a community pharmacy in NL for any HCV treatment during the same period were included. Results: There were 84,252 antibody tests included. Of these, 3,626 (4.3%) tests were positive for HCV antibodies. Seventy eight percent (1,377/1,766) of the individuals with positive antibody tests were tested for HCV RNA. Only 377/1,061 (35.5%) individuals with a positive RNA test were treated, and 257/395 (65.1%) achieved sustained virological response at 12 weeks. Conclusions: NL has successfully identified and treated HCV, but treatment access is low. Targets for improvement include increased screening, reflex testing of positive antibody with RNA, increased linkage to care, change in treatment funding policy, and quicker treatment funding decision.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".