Sofosbuvir-Based Antiviral Therapy Is Highly Effective In Recurrent Hepatitis C in Liver Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: This study evaluates the efficacy, safety, and tolerability of regimens containing sofosbuvir (SOF) in the treatment of hepatitis C virus (HCV) recurrence in all genotypes in patients outside of clinical trials in all Canadian transplant centers. METHODS: One hundred twenty liver transplantation recipients from across Canada with HCV recurrence were started on SOF-based regimens (SOF + simeprevir ± ribavirin (RBV), n = 53; SOF + pegylated interferon + RBV, n = 25; SOF + RBV, n = 36; and SOF + ledipasvir, n = 6) between January and November 2014. Mean age 58 ± 6.85 years, majority (83%) were genotype 1, male (81%), and treatment experienced (82%). Twenty-seven percent had fibrosing cholestatic hepatitis/early aggressive HCV in the graft, and 48% had F3/4 fibrosis. The primary outcomes included patient and graft survival, on- and end-of-treatment response and sustained virological response at 12 weeks after treatment end (SVR12), and adverse events. RESULTS: One hundred thirteen of 120 (94%) patients were HCV RNA undetectable at end of treatment, and SVR12 was achieved in 102/120 (85%) patients, with 7 relapses, 1 nonresponder, and 10 deaths (liver-related complications). Sixty-three percent had HCV RNA levels below the lower limit of quantification at week 4. Serum creatinine levels remained stable throughout the treatment. Severe anemia occurred in 13% of patients, primarily in RBV-based regimens. CONCLUSIONS: Sofosbuvir-based antiviral therapy for HCV recurrence after liver transplantation was well tolerated, with an overall high SVR12 rate (85%) including patients with severe disease recurrence and F3-4 cirrhosis. The response rate was higher (91%) in mild HCV recurrence, suggesting earlier treatment might be beneficial.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".