Variability in pediatric and neonatal organ offering, acceptance and utilization: a survey of Canadian pediatric transplant programs and organ donation organizations
Bibliographic record
Abstract
Introduction: Solid organ transplantation in children is a lifesaving therapy, however, pediatric organ donation rates remain suboptimal. Methods: We conducted a cross-sectional survey of Canadian organ donation organizations (ODOs) and pediatric transplant programs (TPs), aiming to describe policies and practices for pediatric organ allocation, acceptance, and utilization in Canada. Results: Response rates were 82% and 83% respectively for ODOs and transplant programs comprising 7 kidney, 3 heart, 2 lung, 2 liver and 1 intestine programs. All 9 ODOs reported offering pediatric organs following death by neurological criteria (DNC), while 8 reported offering organs following death by circulatory criteria (DCC) for some organs. Variability was found across ODOs and TPs. There was little agreement on both absolute and organ-specific donor exclusion criteria between ODOs. There was further disagreement in organ specific acceptance criteria between ODOs and TPs and between TPs themselves. Notably, despite the development of pediatric donation after DCC guidelines, organs from DCC donors are excluded by many ODOs and TPs. Discussion: Further variability in pediatric specific training, policies, and allocation guidelines are also documented. Significant areas for improvement in standardization in organ acceptance, offering, and allocation in pediatric donation and transplantation across Canada were identified.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".