Early Successes in an Open Access, Provincially Funded Hepatitis C Treatment Program in Prince Edward Island
Bibliographic record
Abstract
INTRODUCTION: The availability of curative hepatitis C therapies has created an opportunity to improve delivery and access. Local providers, government, industry, and community groups in Prince Edward Island developed an innovative province-wide care model. Our goal was to describe the first year of program implementation. MATERIAL AND METHODS: Using a community based prospective observational study design, all chronic hepatitis C referrals received from April 2015 to April 2016 were recorded in a database. Primary analysis assessed the time from referral to assessment/treatment, as well as the number of referrals, assessments, and treatment initiations. Secondary objectives included: 1) Treatment effectiveness using intention-to-treat analysis; and 2) Patient treatment experience assessed using demographics, adverse events, and medication adherence. RESULTS: During the study period 242 referrals were received, 123 patients were seen for intake assessments, and 93 initiated direct-acting antiviral therapy based on medical need. This is compared to 4 treatment initiations in the previous 2 years. The median time from assessment to treatment initiation was 3 weeks. Eighty-two of 84 (97.6%, 95% CI 91.7 - 99.7%) patients for whom outcome data were available achieved sustained virologic response at 12 weeks post-treatment; 1 was lost to follow-up and 1 died from an unrelated event. In the voluntary registry, 39.7% of patients reported missed treatment doses. CONCLUSION: In conclusion, results from the first 12 months of this multi-phase hepatitis C elimination strategy demonstrate improved access to treatment, and high rates of safe engagement and cure for patients living with chronic hepatitis C genotype 1 infections.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".