Age, race and viral genotype are associated with the prevalence of hepatitis B e antigen in children and adults with chronic hepatitis B
Bibliographic record
Abstract
Hepatitis B e antigen (HBeAg) is an important serological marker of hepatitis B virus (HBV) infection and is associated with higher levels of viraemia, increased risk of infectivity to others and increased risk of hepatocellular carcinoma. We analysed HBeAg status in a large cohort of adults and children enrolled in Cohort Studies of the Hepatitis B Research Network, long-term natural history studies of chronic HBV infection. A cross-sectional analysis examined factors associated with HBeAg positivity, including demographic and virologic data, across the age spectrum. Among 2241 enrolled participants who met criteria for this analysis, 825 (37%) were seropositive for HBeAg. The prevalence of HBeAg was lower in those with older age, ranging from 85% among those up to 10 years of age to only 12% among those older than 50 years. In addition to age, both race and HBV genotype were independently associated with HBeAg positivity. There was a significant interaction between age and race; the prevalence of HBeAg was significantly higher among Asians > 10-30 years old vs Whites or Blacks who were >10 to 30 years old and those infected with HBV genotype C. Conversely, the presence of the basal core promoter and precore variants was associated with significantly lower prevalence of HBeAg, even when adjusted for age, race and genotype. These data will provide a better understanding of factors associated with seropositivity for HBeAg and may lead to better strategies for preventing HBV infection and broader indications for antiviral therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".