Ineffectiveness of hepatitis B vaccination in cirrhotic patients waiting for liver transplantation
Bibliographic record
Abstract
Cirrhotic patients who undergo liver transplantation are at risk of acquiring de novo hepatitis B virus (HBV) infection at the time of transplantation. It is common practice to immunize these patients against HBV, but the efficacy of vaccination is uncertain. The response to vaccination with a recombinant HBV vaccine was examined in 49 patients with cirrhosis before liver transplantation. Patients received three doses (20 mg) of Engerix-B (SmithKline Beecham) at zero, one and two months before transplantation, and their response was measured on the day of liver transplantation (9.3+/-1.2 months after the initial dose of vaccine). Results were compared with those reported in healthy adults vaccinated according to the same schedule. Fourteen of 49 cirrhotic patients (28%) developed antibodies to hepatitis B surface antigen (anti-HBs) levels of more than 10 U/L after vaccination compared with 97% of healthy controls. Four patients (8%) had anti-HBs levels of more than 100 U/L compared with 83% in healthy individuals. Mean anti-HBs titre in the 14 responders was 62 U/L compared with 348 U/L in controls. No factor was identified that predicted response to vaccination. One of 49 patients acquired de novo HBV infection at the time of liver transplantation. Current HBV vaccination of cirrhotic patients waiting for liver transplantation is ineffective, and new strategies need to be developed to increase the response rate.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".