Hepatitis C infection and hepatocellular carcinoma in liver transplantation: a 20‐year experience
Bibliographic record
Abstract
BACKGROUND: Hepatitis C infection (HCV) and hepatocellular carcinoma (HCC), the two main causes of liver transplantation (LT), have reduced survival post-LT. The impact of HCV, HCC and their coexistence on post-LT survival were assessed. METHODOLOGY: All 601 LT patients from 1992 to 2011 were reviewed. Those deceased within 30 days (n = 69) and re-transplants (n = 49) were excluded. Recipients were divided into four groups: (a) HCC-/HCV-(n = 252) (b) HCC+/HCV- (n = 58), (c) HCC-/HCV+ (n = 106) and (d) HCC+/HCV+ (n = 67). Demographics, the donor risk index (DRI), Model for End-Stage Liver Disease (MELD) score, survival, complications and tumour characteristics were collected. Statistical analysis included anova, chi-square, Fisher's exact tests and Cox and Kaplan-Meier for overall survival. RESULTS: Groups were comparable with regards to baseline characteristics, but HCC patients were older. After adjusting for age, MELD, gender and the donor risk index (DRI), survival was lower in the HCC+/HCV+ group (59.5% at 5 yrs) and the hazard ratio (HR) was 1.90 [95% confidence interval (CI),1.24-2.95, P = 0.003] and 1.45 (95% CI, 0.99-2.12, P = 0.054) for HCC-/HCV+. HCC survival was similar to controls (HR 1.18, 95% CI, 0.71-1.93, P = 0.508). HCC+/HCV- patients exceeded the Milan criteria (50% versus 31%, P < 0.04) and had more micro-vascular invasion (37.5% versus 20.6%, P = 0.042). HCC+/HCV+ versus HCC+/HCV- survival remained lower (HR 1.94, 95% CI, 1.06-3.81, P = 0.041) after correcting for tumour characteristics and treatment. CONCLUSION: HCV patients had lower survival post-LT. HCC alone had no impact on survival. Patient survival decreased in the HCC+/HCV+ group and this appears to be as a consequence of HCV recurrence.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".