The Potential for Heart Donation After Death Determination by Circulatory Criteria in the Province of Québec
Bibliographic record
Abstract
Background: Heart donation (HD) by those with death determination by circulatory criteria (DDCC) has been proposed as a method to increase the heart donor pool in response to the growing need for heart transplantation (HT). However, the potential level of HD after DDCC in the province of Québec has not yet been reported. This study aims to assess the suitability for HD among donors with DDCC, and to estimate its impact on HT activity. Methods: Donation records by those with DDCC in the province of Québec, from January 2016 to December 2020, were retrospectively reviewed for donor and predonation characteristics. Predetermined exclusion criteria were used to evaluate eligibility for HD. Results: Of the 122 patients with DDCC who were included, 42 (34%) were identified as potentially-eligible heart donors. The median age of potentially-eligible donors was 52 years; 60% were female; and the most prevalent causes leading to organ donation in this group were medical aid in dying (26%), traumatic brain injury (26%), and anoxia (24%). A 19% increase (42 of 225) in potential HT activity was estimated using strict criteria. In only one case did functional warm ischemia time exceed the 30-minute limit. Conclusions: Using those with DDCC as a new source of heart donors can significantly increase the volume of heart donation in the province of Québec. Implementing an HD program for those with DDCC in Québec may reduce waiting time and increase the number of heart recipients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".