Maintaining the permanence principle for death during in situ normothermic regional perfusion for donation after circulatory death organ recovery: A United Kingdom and Canadian proposal
Bibliographic record
Abstract
There is international variability in the determination of death. Death in donation after circulatory death (DCD) can be defined by the permanent cessation of brain circulation. Post-mortem interventions that restore brain perfusion should be prohibited as they invalidate the diagnosis of death. Retrieval teams should develop protocols that ensure the continued absence of brain perfusion during DCD organ recovery. In situ normothermic regional perfusion (NRP) or restarting the heart in the donor's body may interrupt the permanent cessation of brain perfusion because, theoretically, collateral circulations may restore it. We propose refinements to current protocols to monitor and exclude brain reperfusion during in situ NRP. In abdominal NRP, complete occlusion of the descending aorta prevents brain perfusion in most cases. Inserting a cannula in the ascending aorta identifies inadequate occlusion of the descending aorta or any collateral flow and diverts flow away from the brain. In thoracoabdominal NRP opening the aortic arch vessels to atmosphere allows collateral flow to be diverted away from the brain, maintaining the permanence standard for death and respecting the dead donor rule. We propose that these hypotheses are correct when using techniques that simultaneously occlude the descending aorta and open the aortic arch vessels to atmosphere.
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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 | 0.042 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.024 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".