Live donor liver transplantation with older donors: Increased long‐term graft loss due to <scp>HCV</scp> recurrence
Bibliographic record
Abstract
Using our prospectively collected database all adult hepatitis C virus (HCV)-positive patients receiving an adult-to-adult LDLT between October 2000 and May 2014 were identified. Outcome of LDLT with grafts from younger (<50 years=128) vs older donors (≥50 years=31) was compared. Post-transplant graft function, postoperative complications and incidence of HCV recurrence were evaluated. Long-term graft and patient survival was calculated. No difference in graft function was observed between younger and older grafts. Overall complications were similar between both groups. The severity of complications determined by the Dindo-Clavien score was similar. Graft loss from HCV recurrence was significantly less frequent in younger grafts (18% vs 62%, P = 0.001). Young vs older livers had a trend toward improved 1-, 5-, and 10-year graft survival (89% vs 87%, 77% vs 69%, 70% vs 55%, P = 0.096), while patient survival was comparable between both groups (91% vs 90%, 78% vs 69%, 71% vs 60%, P = 0.25). In conclusion, LDLT with older vs younger grafts are more frequently associated with long-term graft loss due to HCV recurrence. Differences in graft survival might be more prominent with prolonged (≥5-year) follow-up. Living donor-recipient matching is particularly important for younger HCV-positive recipients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".