Review article: pathophysiology and management of primary biliary cholangitis
Bibliographic record
Abstract
BACKGROUND: Primary biliary cholangitis (PBC), an immune-mediated disease characterised by destruction of intrahepatic bile ducts, results in progressive damage to the biliary tree, cholestasis and ultimately advanced liver disease. In the last decade, advances in practice have improved clinical care, driven novel therapeutic options and improved risk stratification tools. AIMS: To provide an overview of the disease characteristics of PBC and review a patient-centred management approach for the clinical team caring for those with PBC. METHODS: We reviewed the current literature and guidelines on PBC with a focus on management and therapies. RESULTS: A confident diagnosis of PBC is usually made based on serum liver tests and immune serology. Management of PBC should focus on three main 'process' pillars: (a) treat and risk-stratify through use of biochemical and prognostic criteria; (b) manage concurrent symptoms and other associated diseases; and (c) stage disease, monitor progression and prevent complications. With ongoing complexities in management, including a newly licensed therapy (obeticholic acid) and alternative non-licensed treatments and ongoing clinical trials, discussion with PBC expert centres is encouraged. CONCLUSIONS: PBC is a dynamic disease wherein current treatment goals have become appropriately ambitious. Goals of care should prioritise prevention of end-stage liver disease and amelioration of patient symptom burden for all.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".