Advancing the Scientific Basis for Determining Death in Controlled Organ Donation After Circulatory Determination of Death
Bibliographic record
Abstract
In controlled organ donation after circulatory determination of death (cDCDD), accurate and timely death determination is critical, yet knowledge gaps persist. Further research to improve the science of defining and determining death by circulatory criteria is therefore warranted. In a workshop sponsored by the National Heart, Lung, and Blood Institute, experts identified research opportunities pertaining to scientific, conceptual, and ethical understandings of DCDD and associated technologies. This article identifies a research strategy to inform the biomedical definition of death, the criteria for its determination, and circulatory death determination in cDCDD. Highlighting knowledge gaps, we propose that further research is needed to inform the observation period following cessation of circulation in pediatric and neonatal populations, the temporal relationship between the cessation of brain and circulatory function after the withdrawal of life-sustaining measures in all patient populations, and the minimal pulse pressures that sustain brain blood flow, perfusion, activity, and function. Additionally, accurate predictive tools to estimate time to asystole following the withdrawal of treatment and alternative monitoring modalities to establish the cessation of circulatory, brainstem, and brain function are needed. The physiologic and conceptual implications of postmortem interventions that resume circulation in cDCDD donors likewise demand attention to inform organ recovery practices. Finally, because jurisdictionally variable definitions of death and the criteria for its determination may impede collaborative research efforts, further work is required to achieve consensus on the physiologic and conceptual rationale for defining and determining death after circulatory arrest.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| 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".