Time to direct-acting antiviral initiation and liver-related events in people with HIV and hepatitis C virus
Bibliographic record
Abstract
OBJECTIVE: People with HIV-hepatitis C virus (HCV) co-infection need antiretroviral treatment (ART) to suppress HIV and direct-acting antivirals (DAAs) to cure HCV. ART is typically prioritized, but delays in DAA initiation may increase the risk of liver-related events and HCV transmission to others. DESIGN: Target trial emulation with observational data collected in routine clinical practice from a collaboration of cohorts from Europe and North America. METHODS: We included DAA-naive adults with HIV-HCV co-infection who achieved HIV virologic suppression (HIV RNA <50 copies/ml) after starting ART between 2013 and 2020. We estimated the probability of not initiating DAAs at 6 and 36 months after HIV virologic suppression and emulated a target trial of early (≤6 months after HIV virological suppression) versus delayed (>6 months) DAA initiation and the 36-month risk of liver-related events (liver decompensation or hepatocellular carcinoma). RESULTS: Of 862 eligible individuals (median age 46 years; interquartile range 36-56), 14% were women, and 52% had a history of injection drug use. The 6-month and 36-month probabilities of not initiating DAA were 58% [95% confidence interval (CI): 55-61] and 24% (21-27), respectively. The 36-month risk of liver-related events was 1.1% (0.4-2.0) for early initiation and 1.7% (0.7-2.5) for delayed initiation; risk difference -0.5% (-1.2 to 0.4). CONCLUSION: Almost one-quarter of people with HIV-HCV co-infection on ART had not initiated DAA 3 years after HIV virologic suppression. Because the 3-year risk of liver-related events was low, estimates of the impact of delayed DAA initiation were imprecise.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".