Motion – Patients with Primary Sclerosing Cholangitis Should Undergo Early Liver Transplantation: Arguments against the Motion
Bibliographic record
Abstract
Liver transplantation is an accepted form of treatment for patients with primary sclerosing cholangitis (PSC) and can provide long term survival. Cholangiocarcinoma occurs in 10% to 20% of patients with PSC, is difficult to diagnose and has a poor prognosis. It has been proposed that liver transplantation be undertaken early in the course of the PSC, before cancer develops. Such a proposal would have significant implications for the method of assigning priority to patients awaiting liver transplantation. Other patients on the waiting list would experience further delays, while there is no proven benefit for PSC patients. Few patients with this disease are removed from the waiting list because they developed cancer. If one were to state that PSC patients warrant special consideration because of the hypothetical risk of cholangiocarcinoma, the same argument could be applied to patients with hepatitis C and other causes of cirrhosis, who are at increased risk of hepatocellular carcinoma. The transplant allocation system is applied in an equitable fashion to patients with a large variety of liver diseases. Alteration of this system to benefit a small number of patients with PSC would violate the principles on which it was created, and cannot be justified.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".