Developing and Expanding Deceased Organ Donation to Its Maximum Therapeutic Potential: An Actionable Global Challenge From the 2023 Santander Summit
Bibliographic record
Abstract
On November 9 and 10, 2023, the Organización Nacional de Trasplantes (ONT), under the Spanish Presidency of the Council of the European Union, convened in Santander a Global Summit entitled "Towards Global Convergence in Transplantation: Sufficiency, Transparency and Oversight." This article summarizes two distinct but related challenges elaborated at the Santander Summit by Working Group 2 that must be overcome if we are to develop and expand deceased donation worldwide and achieve the goal of self-sufficiency in organ donation and transplantation. Challenge 1: the need for a unified concept of death based on the permanent cessation of brain function. Working group 2 proposed that challenge 1 requires the global community to work toward a uniform, worldwide definition of human death, conceptually unifying circulatory and neurological criteria of death around the cessation of brain function and accepting that permanent cessation of brain function is a valid criterion to determine death. Challenge 2: reducing disparities in deceased donation and increasing organ utilization through donation after the circulatory determination of death (DCDD). Working group 2 proposed that challenge 2 requires the global community to work toward increasing organ utilization through DCDD, expanding DCDD through in situ normothermic regional perfusion, and expanding DCDD through ex situ machine organ perfusion technology. Recommendations for implementation are described.
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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 | 0.024 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".