Thoracic organ donation after circulatory determination of death
Bibliographic record
Abstract
The availability of thoracic organ transplantation as the treatment of choice for end-stage cardiac or pulmonary diseases is limited by the insufficient number of donor organs from brain dead donors, especially for organs where live-donation is not an option. Patients, who have not progressed to brain death, but have exhausted therapeutic options and life sustaining therapies are withdrawn can become donors with circulatory determination of death (DCD) when they meet criteria for the definition of this state. This approach can fulfill the wish of a patient to become an organ donor and also help to increase the number of donor organs. The DCD process exposes organs to prolonged warm ischemia that increases the possibility of primary graft dysfunction and failure. However, new technologies help in protecting the organs from cold preservation-related ischemia and facilitate resuscitation and monitoring of viability after the occurrence of the DCD-related ischemic insult. Herein, we review the opportunities and challenges in DCD thoracic organ transplantation, emerging techniques in preservation and monitoring of these organs and the potential effect of DCD thoracic organ transplantation on expanding the donor pool.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".