Is Donation after Circulatory Determination of Death in Japan Uncontrolled or Controlled?
Bibliographic record
Abstract
Using donation after circulatory determination of death (DCD) donors has been shown to be a potential means of increasing the number of donors for organ transplantation. The purpose of this study was to examine the published practice of DCD in Japan to properly define their practice as controlled or uncontrolled. Through the Web of Science database, we systematically searched articles describing uncontrolled DCD, controlled DCD or Maastricht classification. A total of 12 articles (ten articles related to kidney, one to pancreas, another to islet transplantation), which were published between 1999 and 2023 from Japanese institutes, were eligible for our study. Systematic review revealed that most DCD in Japan occurs when a terminally ill patient undergoes an expected cardiac arrest without rapid discontinuation from a ventilator, and in some cases with premortem interventions such as cannulation to the femoral vessels. Surprisingly, these DCD donors in Japan have been categorized as uncontrolled DCD. This categorization confuses the donation and transplantation community globally because the international consensus is that uncontrolled DCD occurs after an unexpected cardiac arrest. Further clear definition of terminology would be required within Japan as well as other countries practicing uncontrolled DCD.
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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 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".