Liver transplantation with grafts donated after circulatory death: Current insights and new perspectives
Bibliographic record
Abstract
Liver transplantation (LT) remains the only curative treatment option for end-stage liver disease. In 1967, Starzl and colleagues were the first to perform a successful human orthotropic liver transplantation. The first organ transplantations with grafts from post-mortem donors have all been executed with grafts obtained from donors after circulatory death (DCD). However, after a clear definition of the concept of brain death had been formulated in 1968, the use of organs donated after brain death (DBD) became the worldwide gold standard. As a result of the growing shortage of donor organs, the use of DCD grafts for liver transplantation regained international interest in the 1990s. Since its renewed introduction, the landscape of DCD-LT has changed significantly: the number of countries implementing a (national) DCD-LT program has increased substantially, and over 400 scientific articles on DCD-LT have been published in the past two decades. Nowadays, DCD-LT is on the verge of a new era, in which the long-lasting gold standard of DCD-LT with conventional static cold storage will probably be replaced by either a combination of static cold storage with machine perfusion or solely machine perfusion. This thesis is divided in three parts. The first part provides insight in the current status of DCD-LT in the Netherlands and in other countries in Europe and North America. The second part of this thesis focuses on the effect of several phases of (relative) ischemia on the outcomes of DCD-LT. In part three, the focus is shifted to new ways to use the pool of DCD liver grafts to its full potential. For example, by organ donation after euthanasia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".