Time trends in organ donation after neurologic determination of death: a cohort study
Bibliographic record
Abstract
Background: The cause of brain injury may influence the number of organs that can be procured and transplanted with donation following neurologic determination of death. We investigated whether the distribution of causes responsible for neurologic death has changed over time and, if so, whether this has had an impact on organ quality, transplantation rates and recipient outcomes. Methods: We performed a cohort study involving consecutive brain-dead organ donors in southern Alberta between 2003 and 2014. For each donor, we determined last available measures of organ injury and number of organs transplanted, and compared these variables for various causes of neurologic death. We compared trends to national Canadian data for 2000-2013 (2000-2011 for Quebec). Results: There were 226 brain-dead organ donors over the study period, of whom 100 (44.2%) had anoxic brain injury, 63 (27.9%) had stroke, and 51 (22.6%) had traumatic brain injury. The relative proportion of donors with traumatic brain injury decreased over time (> 30% in 2003-2005 v. 6%-23% in 2012-2014) (p = 0.004), whereas that with anoxic brain injury increased (14%-37% v. 46%-80%, respectively) (p < 0.001). Nationally, the annual number of brain-dead donors with traumatic brain injury decreased from 4.4 to less than 3 per million population between 2000 and 2013, and that with anoxic brain injury increased from 1.1 to 3.1 per million. Donors with anoxic brain injury had higher concentrations of creatinine, alanine aminotransferase and troponin T, and lower PaO2/FIO2 and urine output than donors with other diagnoses. The average number of organs transplanted per donor was 3.6 with anoxic brain injury versus 4.5 with traumatic brain injury or stroke (p = 0.002). Interpretation: Anoxic brain injury has become a leading cause of organ donation after neurologic determination of death in Canada. Organs from donors with anoxic brain injury have a greater degree of injury, and fewer are transplanted. These findings have implications for availability of organs for transplantation in patients with end-stage organ failure.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".