Variants of autoimmune liver diseases: how to diagnose? how to treat?
Bibliographic record
Abstract
Autoimmune liver diseases (AILDs), such as autoimmune hepatitis (AIH), primary sclerosing cholangitis (PSC), and primary biliary cholangitis (PBC), are classified as rare diseases, but their incidence is increasing. In this review, we present the characteristics of AILDs in adults, and mainly focus on their variants in terms of diagnosis and management. The classic AILDs have been well defined in clinical guidelines, but a proportion of patients with a single AILD tend to show features of other AILDs. In these cases, AIH‑PSC or AIH‑PBC variants should be suspected, prompting evaluation in experienced centers. These variants are more representative of clinical categories rather than pathological diagnoses, and the leading component of the disease determines its treatment. However, treating these patients is challenging, even for experienced clinicians. Progression to end‑stage liver disease is, unfortunately, not a rare course, despite combined and second‑line therapies, particularly for AIH‑PSC variants. Thus, studies based on prospective registers are necessary to elaborate upon widely accepted guidelines, to offer better care to these patients, and to improve their prognosis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".