Hepatitis B e Antigen Status and Hepatitis B DNA Levels in Women of Childbearing Age with Chronic Hepatitis B Infection Screening for Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Perinatal or mother-to-child transmission of hepatitis B virus (HBV) results in a high frequency of chronic infection. Risk of mother-to-child transmission is associated with maternal viral factors including hepatitis B e antigen (HBeAg) positivity and viral load. AIM: To investigate associations between age, HBeAg status, HBV DNA levels and genotype in female patients screened for inclusion into two contemporary, randomized HBV trials. METHODS: Retrospective analyses focused on differences between women of childbearing age (≤44 years) and older women. Female patients (N = 355; 18-69 years) were included in the analysis: 41.7% of patients were Asian. In total, 44.4% were HBeAg-positive. RESULTS: Significantly more women aged ≤44 years were HBeAg-positive compared to women ≥45 years (57.2% versus 27.5%, respectively, p<0.0001), this proportion declined with increasing age. Younger women were significantly more likely to have high HBV viral load (HBV DNA>108 copies mL: ≤44 years 46.0% vs ≥45 years 25.5%, respectively; p<0.0001), and this declined with increasing age. HBeAg positivity was slightly higher in Asian women, associated with a higher proportion of HBV genotypes B and C in this population. There was no obvious relationship between genotype and viral load. CONCLUSIONS: Women of childbearing age with CHB are more likely to have high HBV viral load and HBeAg positivity than older women; this likelihood decreases with age. Maternal serological and virological status should therefore be established early in pregnancy, taking into account age and genotype, and a risk-reducing strategy implemented in any patient who is HBeAg positive and has a high viral load.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".