Outcomes Following Donation After Brain Death and Donation After Circulatory Death Liver Transplantation in Patients with Primary Sclerosing Cholangitis
Bibliographic record
Abstract
Background: Primary sclerosing cholangitis (PSC) accounts for 10–15% of liver transplants but is the leading cause of retransplant. This study evaluates whether PSC patients have different survival and graft outcomes when receiving grafts from donors after brain death (DBD) versus circulatory (DCD) death. Methods: Using the SRTR database (2004–2024), we compared PSC patients receiving DCD vs. DBD grafts. Demographics and outcomes including graft loss, mortality, and retransplant were analyzed using multivariable logistic and Cox regression, along with propensity-matched analysis. Results: Among 5762 PSC patients, 391 (6.8%) received DCD grafts. Patients receiving DCD grafts were older but had lower MELD scores (19 vs. 22; p < 0.001) and were less often functionally dependent (11.3% vs. 24.4%; p < 0.001). Multivariable Cox regression demonstrated that receipt of a DCD graft was independently associated with time to graft loss (HR 1.59; CI 1.10–2.31; p = 0.013. Similarly, DCD graft receipt significantly increased the likelihood of requiring retransplant (HR 3.25; CI: 1.93–5.46; p < 0.001) but did not increase the likelihood of mortality. Propensity matched analysis further supported these finding with significantly higher graft loss with DCD grafts at one and two years and higher retransplant rates at all time points including 5-years (+7.9%, CI 4.4 to 11.4%; p < 0.001). Conclusions: DCD grafts in PSC patients are linked to worse graft survival and higher retransplant rates. They may be best suited for older, lower-MELD patients, but further studies on perfusion strategies are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".