The Use of Tenofovir Disoproxil Fumarate in the Management of eAg-Negative Chronic Hepatitis B Infection
Bibliographic record
Abstract
Background/Objectives: Currently, there are insufficient data to recommend the treatment of patients with hepatitis B e antigen (HBeAg)-negative chronic infection who have normal ALT and low HBV DNA, since the prognosis is generally regarded as favorable. The aim of this pilot study was to determine whether the use of tenofovir disoproxil fumarate (TDF) 300 mg/day for 3 years was able to achieve functional cure (HBsAg loss) and HBsAg seroconversion in HBeAb-positive individuals. Methods: Fifty patients not on antiviral therapy (40% men, mean age 48.9 ± 10.9 years, 84% Asians) with minimal fibrosis were enrolled. Results: TDF reduced HBV DNA significantly to undetectable levels after 6 months. Overall, 48.3% of inactive carriers (baseline HBV DNA < 2000 IU/mL) remained HBV DNA negative 6 months after treatment withdrawal, which was significantly higher than the 5.6% in those who were not inactive carriers (baseline HBV DNA ≥ 2000 IU/mL) (p = 0.003). The HBsAg levels did not drop throughout the study period with no difference between inactive carriers versus those who were not. Five inactive carriers achieved functional cure, but none of these were amongst those who were not inactive carriers. No renal dysfunction or ALT flare on treatment withdrawal was observed. Conclusions: TDF could potentially be used to induce functional cure in patients who are inactive carriers with normal ALT, low HBV DNA and without advanced fibrosis.
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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) | 0.000 | 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 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".