Adefovir Dipivoxil for Wait-Listed and Post–Liver Transplantation Patients with Lamivudine-Resistant Hepatitis B
Bibliographic record
Abstract
Wait-listed (n = 226) or post-liver transplantation (n = 241) chronic hepatitis B (CHB) patients with lamivudine-resistant hepatitis B virus (HBV) were treated with adefovir dipivoxil for a median of 39 and 99 weeks, respectively. Among wait-listed patients, serum HBV DNA levels became undetectable (<1,000 copies/mL) in 59% and 65% at weeks 48 and 96, respectively. After 48 weeks, alanine aminotransferase (ALT), albumin, bilirubin, and prothrombin time normalized in 77%, 76%, 60%, and 84% of wait-listed patients, respectively. Among posttransplantation patients, serum HBV DNA levels became undetectable in 40% and 65% at weeks 48 and 96, respectively. After 48 weeks, ALT, albumin, bilirubin, and prothrombin time normalized in 51%, 81%, 76%, and 56% of posttransplantation patients, respectively. Among wait-listed patients who underwent on-study liver transplantation, protection from graft reinfection over a median of 35 weeks was similar among patients who did (n = 34) or did not (n = 23) receive hepatitis B immunoglobulin (HBIg). Hepatitis B surface antigen was detected on the first measurement only in 6% and 9% of patients who did or did not receive HBIg, respectively. Serum HBV DNA was detected on consecutive visits in 6% and 0% of patients who did or did not receive HBIg, respectively. Treatment-related adverse events led to discontinuation of adefovir dipivoxil in 4% of patients. Cumulative probabilities of resistance were 0%, 2%, and 2% at weeks 48, 96, and 144, respectively. In conclusion, adefovir dipivoxil is effective and safe in wait-listed or posttransplantation CHB patients with lamivudine-resistant HBV and prevents graft reinfection with or without HBIg.
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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 | 0.000 | 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".