Natural history and long–term management of autoimmune hepatitis
Bibliographic record
Abstract
INTRODUCTION: Autoimmune hepatitis (AIH) is a relatively infrequent and complex liver disease characterized by acute or chronic inflammation, interface hepatitis in histology examination, elevation of immunoglobulin G (IgG), production of autoantibodies, and is often responsive to immunosuppression. The incidence of AIH has been increasing worldwide, affecting people of all ages and sexes. AIH represents a diagnostic challenge because of its heterogeneous presentation and the lack of pathognomonic findings. Even when treated, AIH can remain a progressive disease. In this review, we present recent data on the natural history of AIH and the developing evidence on the management of patients with AIH. AREAS COVERED: This review outlines the clinical presentation, risk factors linked to poorer clinical outcomes, the diagnostic algorithm, and the current management strategies for individuals living with AIH. EXPERT OPINION: AIH remains a clinical challenge, and new tools for better diagnosis and stratification of risk are needed. In addition, better treatments are needed as a complete response is achieved in less than 60% of cases, and intolerance to first-line treatment is frequent. The use of biological treatment in AIH seems to improve the response rate and minimize the risk of side effects of current medication in this increasingly prevalent disease.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".