A166 SOFOSBUVIR-BASED THERAPY IN THE PRE-LIVER TRANSPLANT SETTING: THE CANADIAN NATIONAL EXPERIENCE
Bibliographic record
Abstract
To assess the efficacy of SOF-based therapy in HCV infected transplant eligible patients and to evaluate decompensated liver disease patients with respect to changes that occur in liver function in the short term and the resultant effect on their liver transplant status A retrospective multicentre Canadian study of liver transplant candidates with advanced HCV cirrhosis treated with SOF-based therapy. Outcomes included sustained virologic response (SVR), changes in MELD-Na score, Child-Pugh score and liver transplant status 96 liver transplant candidates with advance liver disease due to HCV were evaluated. 69 (71%) of patients have genotype 1, SVR was 88.3% (94% for G1, 68 % for non- G1). 49 patients were treated in the pre-assessment period and 47 patients were treated while awaiting transplantation. Of the 49 treated in the pre-assessment period, no significant difference in their average MELD-Na score (12 vs 12, p=ns) nor Child-Pugh score (7 vs 6 p=ns) occurred from baseline to SVR 12 date. However, among patients treated while wait listed for transplant, 14/47 (30%) remained active on the liver transplant list at the time of SVR12, 9/47 (19%) patients were delisted, 16/47 (34%) underwent liver transplantation. Progression of HCC lead to delisting of 1 and 8 deaths (1 after transplant) occurred. Among delisted patients, the average MELD-Na changed from 15 to 12 SOF-based therapy for patients progressing to liver transplantation leads to high SVR rates, short term stability in liver function, and in a sizable portion leads to delisting. These improvements may increase over time. Longer term follow up and further analysis is needed to understand the overall impact this will have on wait list deaths, number of transplants required for HCV and survival of non-HCV recipients. None
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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".