Autoimmune hepatitis in children
Bibliographic record
Abstract
Autoimmune hepatitis (AIH) is an immune-mediated necroinflammatory disease of the liver characterized by elevation of IgG, presence of characteristic autoantibodies, and histological features of interface hepatitis. Two types of juvenile AIH have been recognized according to seropositivity for smooth muscle and/or antinuclear antibody (AIH type 1) or liver kidney microsomal antibody (AIH type 2). The exact pathogenesis of AIH is still unclear, but it is known that unidentified environmental factors, and occasionally drugs, might trigger disease in genetically susceptible individuals. The clinical spectrum of this disease is very wide, ranging from asymptomatic individuals with abnormal liver function to those with fulminant liver failure. The diagnosis is based on a combination of biochemical and histological parameters and on exclusion of other liver diseases. It is a relatively rare but devastating disease, which progresses rapidly unless immunosuppressive treatment is started promptly. Standard therapy consists of a combination of corticosteroids and azathioprine, which is efficacious in 80% of patients. Alternative therapies are increasingly being explored in patients who do not respond to standard treatment and/or have intolerable side-effects. The purpose of this paper is to review our current knowledge about AIH in children, evaluating mainly the therapeutic options for its treatment, considering also the newer immunosuppressant agents used in difficult-to-treat cases.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".