Renal transplantation using non-heart-beating donors: a potential solution to the organ donor shortage in Canada.
Bibliographic record
Abstract
INTRODUCTION: There is a chronic shortage of cadaveric organ donors for renal transplantation, which might be solved by the use of non-heart-beating donors (patients who suffer cardiac arrest and whose kidneys are harvested subsequently when irreversible heart and respiratory function occur). We carried out a chart review to determine whether the renal transplantation rate would improve if a non-heart-beating donor program was introduced at a Canadian centre. METHODS: We reviewed the charts of all 1547 patients who died in the emergency department or intensive care unit of the Ottawa Hospital, a tertiary care centre serving 1.2 million people in eastern Ontario, between January 1999 and May 2001. The number of potential non-heart-beating donors was determined by the use of predefined criteria. The number of additional kidneys that could be obtained with a non-heart-beating donor program was estimated and compared to the actual number of kidneys procured from conventional brain-dead donors during the same period. The potential increase in the renal transplantation rate was calculated. RESULTS: There were 83 potential non-heart-beating donors during the 29-month study period. The mean (and standard deviation) age of the donors was 40.6 (13.1) years, and 20% were female. The mean serum creatinine value was 75 (29) micromol/L; 44.6% of donors died secondary to trauma. We estimated that the use of non-heart-beating donors would have provided 14 to 41 additional donors during the study period (12-34 kidneys/yr). The cadaveric renal transplantation rate would have increased between 30% and 87%. CONCLUSION: The cadaveric renal transplantation rate could improve significantly if non-heart-beating donors were used in Canadian hospitals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".