Tenofovir disoproxil fumarate therapy to prevent hepatitis B virus vertical transmission—A review of maternal and infant outcomes
Bibliographic record
Abstract
Hepatitis B virus (HBV) is a global health problem. Vertical transmission of HBV from HBV surface antigen (HBsAg)-positive mothers to their infants is the most common cause of HBV infection worldwide. The use of passive-active immunoprophylaxis is >90% effective in reducing the risk of vertical transmission, but immunoprophylaxis failure can occur in infants born to mothers with high viraemia. Thus, it is recommended that pregnant women with HBV-DNA level >200 000 IU/ml receive nucleos(t)ide analogue (NA) treatment [i.e. tenofovir disoproxil fumarate (TDF), lamivudine or telbivudine] during third trimester to prevent infant immunoprophylaxis failure. TDF is recommended as the first-line therapy based on available data on efficacy, safety and resistance profile. However, maternal immunological reconstitution following parturition can increase immune-mediated flares to viral antigens that is potentially exacerbated following TDF withdrawal. In this article, we review available data on the efficacy and safety of TDF administration to prevent HBV mother-to-child transmission. We also discuss changes in maternal viral markers [i.e. HBV-DNA, HBV e antigen and HBsAg] and alanine aminotransferase during follow-up post-partum in mothers received NA to prevent HBV vertical transmission.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".