Machine Perfusions in Liver Transplantation: The Evidence‐Based Position Paper of the Italian Society of Organ and Tissue Transplantation
Bibliographic record
Abstract
The use of machine perfusion (MP) in liver transplantation (LT) is spreading worldwide. However, its efficacy has not been demonstrated, and its proper clinical use has far to go to be widely implemented. The Società Italiana Trapianti d'Organo (SITO) promoted the development of an evidence-based position paper. A 3-step approach has been adopted to develop this position paper. First, SITO appointed a chair and a cochair who then assembled a working group with specific experience of MP in LT. The Guideline Development Group framed the clinical questions into a patient, intervention, control, and outcome (PICO) format, extracted and analyzed the available literature, ranked the quality of the evidence, and prepared and graded the recommendations. Recommendations were then discussed by all the members of the SITO and were voted on via the Delphi method by an institutional review board. Finally, they were evaluated and scored by a panel of external reviewers. All available literature was analyzed, and its quality was ranked. A total of 18 recommendations regarding the use and the efficacy of ex situ hypothermic and normothermic machine perfusion and sequential normothermic regional perfusion and ex situ MP were prepared and graded according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method. A critical and scientific approach is required for the safe implementation of this new technology.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".