One Year of Hepatitis B Immunoglobulin Plus Tenofovir Therapy is Safe and Effective in Preventing Recurrent Hepatitis B Infection Post-Liver Transplantation
Bibliographic record
Abstract
BACKGROUND: Hepatitis B immunoglobulin (HBIG) given in combination with a nucleos(t)ide analogue has reduced the rate of recurrent hepatitis B virus (HBV) infection following liver transplantation (LT); however, the most effective protocol remains unclear. OBJECTIVE: To evaluate the use of tenofovir disoproxil fumarate (TDF) in combination with one year of low-dose HBIG. METHODS: Twenty-four adults who underwent LT for HBV-related liver disease at the University Health Network (Toronto, Ontario) and received TDF (± lamivudine) and one year of HBIG to prevent recurrent HBV infection from June 2005 to June 2011 were evaluated. RESULTS: The median length of follow-up post-LT was 29.1 months. Three patients died during the follow-up period. Patient survival was 100% and 84.1% at one and five years, respectively. None of the patients developed recurrent HBV infection. No significant adverse event was observed due to TDF administration; renal function pre- and post-LT were also acceptably preserved. CONCLUSION: The present study demonstrated that a short, finite course of low-dose HBIG combined with maintenance of long-term TDF staring before LT is cost-effective and safe. However, further prospective study involving a larger patient cohort with a longer follow-up period is required to confirm the results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".