LAMIVUDINE FOR HEPATITIS B IN LIVER TRANSPLANTATION
Bibliographic record
Abstract
BACKGROUND: Liver transplantation for hepatitis B virus (HBV) has been associated with a high rate of reinfection and graft failure. Lamivudine, a potent inhibitor of HBV replication, has been shown to prevent viral recurrence after transplantation. METHODS: The effectiveness of lamivudine monotherapy for the management of HBV recurrence after liver transplantation was assessed. Lamivudine was used in three patient groups: (1) patients started before transplantation and continued after transplantation (n = 13); (2) patients treated after transplantation (n = 15); and (3) patients with de novo hepatitis B after transplantation (n = 4). RESULTS: Median follow-up on lamivudine was 24 months. Active viral replication (HBV-DNA+) was seen in 17 (53%) of 32 at treatment initiation. All lost HBV-DNA at a mean of 2.4+/-1.6 months after lamivudine initiation. Twenty-six (81%) patients remain free of viral recurrence. Six (19%) patients have evidence of breakthrough infection with the YMDD mutant of HBV, two of whom progressed to graft failure. All four patients in group 1 who developed breakthrough had evidence of hepatitis B surface antigen expression in the explanted liver by immunohistochemistry despite being serum HBV-DNA negative before transplantation. No difference was observed among the three groups in DNA clearance or breakthrough rates. CONCLUSIONS: Lamivudine achieves viral DNA clearance in almost all patients. Expression of viral antigens in the liver seems to identify patients at risk of developing HBV-DNA recurrence. Disease-free survival of 81% at 22 months is similar to data with hepatitis B immunoglobulin therapy. Given the safe clinical profile and high efficacy in the prevention of disease recurrence, lamivudine will favorably change the outlook of liver transplantation for HBV.
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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) | 0.001 | 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 | 0.001 |
| 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".