Liver transplantation for cholestatic liver diseases: Timing and disease recurrence
Bibliographic record
Abstract
Though rare, primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) account for 8%-14% of liver transplants (LTs) in North America and Europe and the journey of these patients across the peri-transplant period is unique. Equitable access to LT is an important challenge, as the MELD score and its derivatives inadequately reflect the morbidity and mortality related to these diseases failing to capture disease-specific complications, such as recurrent cholangitis, malignancy risk, severe portal hypertension, and sarcopenia. The waitlist experience is high-risk, prolonged, and a distinct form of "MELD purgatory." Once barriers to access are overcome, posttransplant outcomes are generally excellent; however, disease recurrence affects 15%-35% at 5-10 years after LT with increasing rates over time. Diagnosing recurrence is challenged by a broad differential for posttransplant biliary injury, and the risk factors for its development remain controversial. While post-LT use of ursodeoxycholic acid in PBC is clearly beneficial, no effective medical therapy currently exists for recurrent PSC. A heightened focus on control of inflammatory bowel disease activity is critical as a potentially important modifiable risk factor for rPSC, including escalation of medical therapy as needed and timely colectomy when indicated. This review outlines the journey for patients with PBC and PSC, from transplant listing to posttransplant management, emphasizing the need for unique and tailored approaches to optimize outcomes and long-term survival.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".