Development of a multinational registry of pediatric deceased organ donation activity
Bibliographic record
Abstract
BACKGROUND: There are no currently agreed upon international standards for reporting of pediatric deceased organ donation activity. This leads to difficulty in comparisons between jurisdictions for both researchers and policy stakeholders. The goal of this project was to develop and test a standardized registry for pediatric deceased donation activity. METHODS: Four countries (Canada, Spain, USA, and the UK) with geographical and practice diversity were approached to participate. Iterative exchanges were used to create data fields and definitions that were acceptable to all participants. Data from 2011 to 2015 (inclusive) were requested from national health databases and analyzed on a secure, web-based survey platform. RESULTS: Data were obtained from three of the four countries (Canada unable to provide). Total pediatric donation rates were stable over the 5-year period, but with variation between countries. pDCD rates were the most variable, representing 32.2% of total pediatric donation in the UK, 14.4% in the United States, and 2.6% in Spain during the studied period. Most organs from pediatric donors were allocated to adult recipients, though the rates of allocation of pediatric kidneys to pediatric recipients ranged from 7% in the United States to 40% in Spain. DISCUSSION: In this limited cohort of three countries, we demonstrated substantial variation in pediatric donation rates and practice. These data highlight opportunities for practice improvement such as the development of rigorous clinical practice guidelines. Future development of this registry will seek to engage more countries, and address barriers that prevented full participation of approached jurisdictions.
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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 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".