Ribavirin revisited in the era of direct‐acting antiviral therapy for hepatitis C virus infection
Bibliographic record
Abstract
Over the past two decades, ribavirin has been an integral component of treatment for hepatitis C virus (HCV) infection, where it has been shown to improve the efficacy of (pegylated) interferon. However, because of treatment-limiting side effects and its additive toxicity with interferon, the search for interferon- and ribavirin-free regimens has been underway. The recent approvals of all-oral direct acting antivirals (DAAs) have revolutionized the HCV therapeutic landscape, and initially it was expected that the role of ribavirin with DAA regimens would be eliminated. On the contrary, what we have witnessed is that ribavirin retains an important role in the optimal treatment of some subgroups of patients, particularly those that historically have been considered the most difficult to cure. Fortunately, it has also been recognized that the safety profile of ribavirin is improved when co-administered with all-oral DAA combinations in the absence of interferon. Despite the antiviral mechanism of action of ribavirin being poorly understood, we now have a range of novel insights into the potential role of ribavirin in all-oral DAA HCV treatment and greater insight into the antiviral mechanism by which it continues to provide clinical benefit for defined patient groups.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".