Does prolonged cold ischemia affect outcomes in donation after cardiac death donor kidney transplants?
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to analyze the combined effect of cold ischemia time (CIT) and donation after cardiac death (DCD, with requisite warm ischemia time, WIT) on kidney transplant (KT) outcomes. METHODS: Single center retrospective review of DCD KT recipients stratified by CIT. RESULTS: From 6/08 to 10/20, we performed 446 DCD KTs (115 CIT ≤20, 205 CIT 20-30, 88 CIT 30-40, 38 CIT ≥40 h). Mean WITs (26/25/27/23 min) and KDPI values (59%/55%/55%/59%) were similar while mean CITs (16.4/23.6/33.4/42.5 h) and pump times (10.3/13.6/16.1/20.4 h) differed across groups (P < .05). With a mean 6-year follow-up, patient survival (84%/84%/74%/84%) was similar. Kidney graft survival (GS) (72%/72%/56%/58%) and death censored GS (DCGS) (82%/80%/63%/67%) rates decreased whereas rates of primary nonfunction (PNF, .9%/2.4%/9.1%/7.9%) and delayed graft function (DGF) (36%/48%/50%/69%) increased with longer CIT (≥30 h, P < .05). Meaningful years free of dialysis, which we refer to as Allograft Life Years, were achieved in all cohorts (4.5/4.3/3.9/4.3 years per patient transplanted). CONCLUSION: DCD donor kidneys with prolonged CIT (≥30 h) are associated with increased rates of DGF and PNF, along with decreased GS and DCGS. Despite this, Allograft Life Years were gained even with longer CITs, demonstrating the utility of using these allografts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".