Facing the Challenge of Acute Autoimmune Liver Disease: Report of a Case and Review of the Literature
Bibliographic record
Abstract
Autoimmune liver diseases (ALD) comprise two broad categories: those with a hepatic predominance, autoimmune hepatitis (AIH), and those with a predominance of cholestatic features including primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). An overlap syndrome (OS) is thought to exist where a patient appears with clinical features of more than one immune-mediated liver disease. Based on one personal observation we report a case of histologically proven OS. The relevant literature is briefly reviewed. A 68-year-old male was admitted in our department with general malaise, anorexia and jaundice. Trans-abdominal ultrasonography as well as computerized tomography showed a slightly enlarged liver with mild fatty deposition and the patient was submitted to transcutaneous liver biopsy. Histological features included inflammatory infiltration of intra-hepatic bile ducts with the presence of endoepithelial lymphocytes and plasma cells, degenerative distortions and even focal damage of relevant epithelial cellular structures, periductal fibrosis, portal inflammation, interface hepatitis, ductular proliferation and canalicular cholestasis. It is apparent that exact definitions pertaining the OS are limited and general consensus on the precise determinations of overlap/variant syndromes is warranted in order to enable more accurate future research and establish common guidelines in the management of the condition.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.012 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".