Adefovir dipivoxil for the treatment of lamivudine-resistant hepatitis B mutants
Bibliographic record
Abstract
Lamivudine has been shown to be an effective therapy for chronic hepatitis B, but resistance to this nucleoside agent is common after prolonged use. Five patients with chronic hepatitis B virus (HBV) infection developed resistance to lamivudine after 9 to 19 months of treatment. In 4 patients this occurred after liver transplantation and the remaining individual had stable cirrhosis. In each case, resistance was confirmed to be caused by one or more mutations in the HBV-DNA polymerase gene and was associated with active underlying liver disease. The patients were treated with adefovir dipivoxil in a dose of 5 to 30 mg daily. Two to 4 log(10) reductions in HBV-DNA levels were observed in 4 cases, and the fifth patient became negative by quantitative polymerase chain reaction (PCR) after retransplantation in conjunction with hepatitis B immunoglobulin (HBIg). Virologic improvement was associated with stable or declining serum alanine transaminase levels in 4 patients. HBV-DNA suppression has been sustained during a mean treatment period of 13 months (range 11 to 15 months), including 1 patient in whom lamivudine has been discontinued. Mild changes in renal function were observed during treatment in most cases but did not require early discontinuation of the drug. This study provides evidence that adefovir dipivoxil can be an effective treatment for lamivudine-resistant HBV mutants as well as wild-type 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) | 0.000 | 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".