A42 LIVE DONOR LIVER TRANSPLANTATION IN PRIMARY SCLEROSING CHOLANGITIS: AN INDICATOR OF AN ORGAN ALLOCATION SYSTEM NOT ADDRESSING PATIENT NEED
Bibliographic record
Abstract
Abstract Background Liver transplantation is frequently lifesaving for people living with primary sclerosing cholangitis (PSC). However, patients are waitlisted for liver transplant (LT) according to the MELD-Na score, which may not accurately reflect the burden of living with PSC. Purpose We sought to describe and analyze the clinical trajectory for patients with PSC referred for LT, in a mixed deceased donor/live donor transplant programme. Method This was a retrospective cohort study from November 2012 to December 2019 including all patients with PSC referred for assessment at the University Health Network Liver Transplant Clinic. Patients who required multiorgan transplant or re-transplantation were excluded. Liver symptoms, hepatobiliary malignancy, MELD-Na progression, and death were abstracted from chart review. Competing Risk analysis was used for timing of LT, transplant type, and death. Result(s) Of 172 PSC patients assessed, 144 (84%) were listed, of whom 106/144 (74%) were transplanted. Mean age was 47.6 years and 66% were male. During follow-up through to 2021, 23/144 (16%) were removed from the waitlist due to infection, clinical deterioration, liver-related mortality or new cancer; 3 had clinical improvement. At the time of listing, 118/144 (81.95%) had a potential Living Donor (pLD) of whom 94 were transplanted: 64 live donor and 30 deceased donor. Patients with pLD had 79% lower mortality (p<0.001), and higher rates of transplantation (80% vs 46%). Exception points were granted to 13/172 (7.5%) patients. Conclusion(s) In a high-volume North American liver transplant centre, most patients with PSC assessed for transplant were listed and subsequently transplanted. However, this was a consequence of patients engaging in live donor transplantation. Our findings support the concern from patients with PSC that MELD-Na allocation does not adequately address their needs. Please acknowledge all funding agencies by checking the applicable boxes below CIHR, Other Please indicate your source of funding; This study was supported by PSC Partners Canada, Canadian Institutes of Health Research (CIHR), Toronto General and Western Hospital Foundation. Disclosure of Interest None Declared
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".