Review of machine perfusion studies in vascularized composite allotransplant preservation
Bibliographic record
Abstract
The applications of Vascularized composite allotransplantation (VCA) are increasing since the first successful hand transplantation in 1998. However, the abundance of muscle tissue makes VCA's vulnerable to ischemia-reperfusion injury (IRI), which has detrimental effects on the outcome of the procedure, restricting allowable donor-to-recipient time and limiting its widespread use. The current clinical method is Static cold storage (SCS) and this allows only 6 h before irreversible damage occurs upon reperfusion. In order to overcome this obstacle, the focus of research has been shifted towards the prospect of ex-vivo perfusion preservation which already has an established clinical role in solid organ transplants especially in the last decade. In this comprehensive qualitative review, we compile the literature on all VCA machine perfusion models and we aim to highlight the essentials of an ex vivo perfusion set-up, the different strategies, and their associated outcomes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".