Current issues in the management of paediatric viral hepatitis
Bibliographic record
Abstract
Viral hepatitis poses important problems for children. In preschoolers, hepatitis A virus (HAV) infection frequently causes acute liver failure. Vaccinating toddlers against HAV in countries with high endemicity is expected to decrease mortality. HAV vaccine demonstrates efficacy (comparable to immunoglobulin) as post-exposure prophylaxis. A recently developed vaccine against hepatitis E virus (HEV) may benefit fetal health, because pregnant women are most prone to acute liver failure as a result of HEV. Hepatitis B vaccine continues to demonstrate value and versatility for preventing serious liver disease. With chronic infection, undetectable levels of serum HBV DNA complement e-seroconversion as the preferred outcome measure; suppressed viral load correlates with long-term complications better than HBeAg status. Among Taiwanese children, low pretreatment HBV DNA (<2 x 10(8) copies/ml) strongly predicted response to interferon-alpha. Future paediatric studies must incorporate HBV DNA levels. The rationale for routine treatment of immunotolerant hepatitis B during childhood remains uncertain. Any treatment of chronic hepatitis B in childhood requires consideration of the risks and benefits. Childhood hepatitis C virus (HCV) infection results mainly from mother-to-infant transmission. Babies of HCV-infected women should be tested for serum HCV RNA at 1 month of age. If negative, confirmatory anti-HCV antibody testing may be performed between 12 and 15 months of age. Children with chronic hepatitis C may develop progressive fibrosis/cirrhosis, particularly in the setting of obesity and insulin resistance. Treatment of children chronically infected with genotype 2 or 3 is highly successful: combination therapy of pegylated interferon-alpha and ribavirin is well tolerated and superior to pegylated interferon-alpha alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".