Sofosbuvir-Based Therapy in the Pre-Liver Transplant Setting: The Canadian National Experience
Bibliographic record
Abstract
INTRODUCTION AND AIM: Sofosbuvir (SOF)-based regimen has been shown to have high efficacy even in patients with decompensated cirrhosis. Treated patients may experience various degrees of hepatic recovery ranging from stabilization of liver function, to removal from liver transplant wait lists. The frequency of these occurrences in larger transplant eligible patient populations is unknown. The aim of this study was to assess the efficacy of SOF-based therapy in HCV infected transplant eligible patients and to evaluate short term changes in liver function and the effect on their liver transplant status. MATERIAL AND METHODS: A retrospective multicenter Canadian study of liver transplant candidates with advanced HCV cirrhosis treated with SOF-based therapy. Outcomes included sustained virologic response (SVR), and liver transplant status. RESULTS: 105 liver transplant candidates with advanced liver disease due to HCV were evaluated. The overall SVR was 83.8%. Hepatocellular carcinoma was diagnosed in 39 (37.1%) prior to transplant evaluation. In short term follow-up, 14 (13.3%) remained active on the list at the time of SVR12, 22 (20.9%) patients underwent liver transplantation, 7 (6.6%) patients were deactivated due to clinical improvement, 3 patients were delisted, and 10 deaths were reported. CONCLUSIONS: SOF-based therapy for patients progressing to liver transplantation leads to high SVR rates, short term stability in liver function, and deactivation from the transplant list .
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".