The impact of universal access to direct-acting antiviral therapy on the hepatitis C cascade of care among individuals attending primary and community health services
Bibliographic record
Abstract
BACKGROUND: Hepatitis C elimination will require widespread access to treatment and responses at the health-service level to increase testing among populations at risk. We explored changes in hepatitis C testing and the cascade of care before and after the introduction of direct-acting antiviral treatments in Victoria, Australia. METHODS: De-identified clinical data were retrospectively extracted from eighteen primary care clinics providing services targeted towards people who inject drugs. We explored hepatitis C testing within three-year periods immediately prior to (pre-DAA period) and following (post-DAA period) universal access to DAA treatments on 1st March 2016. Among ever RNA-positive individuals, we constructed two care cascades at the end of the pre-DAA and post-DAA periods. RESULTS: The number of individuals HCV-tested was 13,784 (12.2% of those with a consultation) in the pre-DAA period and 14,507 (10.4% of those with a consultation) in the post-DAA period. The pre-DAA care cascade included 2,515 RNA-positive individuals; 1,977 (78.6%) were HCV viral load/genotype tested; 19 (0.8%) were prescribed treatment; and 12 had evidence of cure (0.5% of those RNA-positive and 63.6% of those eligible for cure). The post-DAA care cascade included 3,713 RNA-positive individuals; 3,276 (88.2%) were HCV viral load/genotype tested; 1,674 (45.1%) were prescribed treatment; and 863 had evidence of cure (23.2% of those RNA-positive and 94.9% of those eligible for cure). CONCLUSION: Marked improvements in the cascade of hepatitis C care among patients attending primary care clinics were observed following the universal access of DAA treatments in Australia, although improvements in testing were less pronounced.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".