Recurrent hepatitis C posttransplant: Early preservation injury may predict poor outcome
Bibliographic record
Abstract
Organ cold/warm ischemia is thought to be a risk factor for increased severity of recurrence of hepatitis C (HCV) post liver transplantation. We had noted some HCV patients with preservation injury (PI) to have particularly poor outcomes. Our goal was to determine if PI on biopsy in HCV patients is associated with earlier, more rapidly progressive recurrence or graft and patient survival. Sixty-nine patients from the University of Nebraska transplant database were included: 23 HCV patients with PI (group = 1), 23 non-HCV patients with PI (group = 2), and 23 HCV patients without PI (group = 3). Patient groups were matched for gender, age, immunosuppression, and time of transplantation for analysis. No difference in time to recurrence was noted between HCV groups (256 vs. 316 days posttransplant). More patients in group 1 had progression to stage 3 or 4 fibrosis, compared to group 3 (43 vs. 9%, P = 0.02). One-year survival for groups 1, 2, and 3 was 78, 82, and 100% respectively, whereas 3-yr survival was 59, 82, and 88% (group 1 vs. group 2 or 3 respectively, P = 0.0055). There was no difference in survival between groups 2 and 3. Patients in group 1 that received antiviral treatment had improved survival, compared to those who did not (P = 0.012). Risk factors for poor survival on univariate analysis included severity of PI (Relative Risk = 2.78, P < 0.001) and donor age of >55 (P = 0.014). Multivariate analysis shows HCV is the most important factor. In conclusion, HCV transplant patients with evidence of early PI on biopsy have poorer survival outcomes than non-HCV transplant patients with PI or HCV transplant patients without PI. Consideration for antiviral therapy early in the posttransplant course may be warranted in this subset of patients.
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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 | 0.000 | 0.002 |
| 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".