Reestablishment of Active Immunity against HBV Graft Reinfection after Liver Transplantation for HBV-Related End Stage Liver Disease
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to establish a hepatitis B virus (HBV) vaccination protocol among orthotopic liver transplantation (OLT) recipients under the coverage of a low-dose hepatitis B immunoglobulin (HBIG) combined with an antiviral agent prophylaxis protocol. METHOD: Two hundred OLT recipients were included in this study. The vaccine was injected at months 0, 1, 2, and 6. Low-dose HBIG combined with antiviral agent prophylaxis protocol was continued before reestablishment of active immunity against HBV in order to maintain a steady anti-HBs titer. RESULTS: Active immunity against HBV was reestablished in 50 patients, for an overall response rate of 25%. Of the 50 patients, 24 discontinued HBIG without any HBV graft reinfection during a follow-up period of 26.13 ± 7.05 months. 21 patients discontinued both HBIG and antiviral agents during a follow-up period of 39.86 ± 15.47 months, and 4 patients among them appeared to be HBsAg positive. There was no recipient death or graft loss because of HBV reinfection. CONCLUSIONS: Vaccination preventing HBV reinfection for OLT recipients is feasible. The strategy withdrawal of HBIG with induction of active immunity against hepatitis B is reasonable for long-term survivors of OLT; however, discontinuation nucleoside analogues should be cautious.
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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 | 0.000 | 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".