Missed opportunities for DCD kidney donors: Evaluation of warm ischemic time and associated functional warm ischemic time
Bibliographic record
Abstract
INTRODUCTION: Many transplant centers utilize a hard cutoff of 2 hours of warm ischemic time (WIT), defined as the time from withdrawal of life-sustaining measures to cold organ flush, to exclude donation after circulatory determination of death (DCD) kidney donation. As a result, almost a quarter of withdrawals to retrieve DCD organs fail to produce kidney transplants in Ontario. In order to assess our ability to increase organ yield, we wanted to characterize WIT and functional WIT (fWIT, time from systolic blood pressure <50 mm Hg to cold organ flush), as well as determine the time at which potential donors eventually die in those that did not become organ donors. METHODS: A retrospective review of all DCD kidney donors in Ontario was performed utilizing the Trillium Gift of Life Database from April 2013 to February 2018. RESULTS: Of 350 DCD kidney donors analyzed, 46.9% had < 0.5 hours, 51.7% between 0.5 and 2 hours, and 1.4% >2 hours of WIT. In each of these categories (WIT <0.5 hours, 0.5-2 hours and >2 hours), the percentage of patients with fWIT <30 minutes was 100%, 94.4%, and 100%, respectively (P = NS). There were 106 potential donors who did not end up donating due to WIT >2 hours. Of these, 20.8% died between 2 and 4 hours, 10.4% between 4 and 6 hours, and 68.8% beyond 6 hours. DISCUSSION: The percentage of donors with fWIT >30 minutes did not increase with increasing WIT in DCD donors that went on to donate organs. These data support assessment of waiting up to 4 hours for DCD kidney donation as long as fWIT remains low.
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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 | 0.002 | 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) | 0.001 | 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 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".