Normothermic Ex Vivo Kidney Perfusion Reduces Warm Ischemic Injury of Porcine Kidney Grafts Retrieved After Circulatory Death
Bibliographic record
Abstract
BACKGROUND: Cold storage is poorly tolerated by kidney grafts retrieved after donation after circulatory death. It has been determined that normothermic ex vivo kidney perfusion (NEVKP) preservation decreases injury by minimizing cold ischemic storage. The impact of NEVKP on warm ischemic injury is unknown. METHODS: We compared pig kidneys retrieved after 30 minutes warm ischemia and immediate transplantation (no-preservation) with grafts that were exposed to 30 minutes of warm ischemia plus 8-hour NEVKP or plus 8-hour static cold storage (SCS). RESULTS: After transplantation, the NEVKP group demonstrated lower daily serum creatinine levels indicating better early graft function compared with no-preservation (P = 0.02) or SCS group (P < 0.001). In addition, NEVKP preserved grafts had a significantly lower grade of tubular injury and interstitial inflammation 30 minutes after reperfusion compared to grafts without any storage (injury score, NEVKP 1-2 vs no-preservation, 2-2, P = 0.029; inflammation score, NEVKP, 0-0.5 vs no-preservation, 1-2; P = 0.002), although it did not reach significance level when compared to the SCS group (injury score, 1-2, P = 0.071; inflammation score, 1-1; P = 0.071). Regeneration was assessed 30 minutes after reperfusion by Ki-67 staining. The NEVKP group demonstrated significantly higher number of Ki-67-positive cells: 9.2 ± 3.7 when compared with SCS group (3.9 ± 1.0, P = 0.015) and no-preservation group (4.2 ± 0.7, P = 0.04). CONCLUSIONS: In this porcine model of donation after circulatory death kidney transplantation NEVKP reduced kidney injury and improved graft function when compared with no-preservation. The results suggest that NEVKP does not cause additional damage to grafts during the preservation period, but may reverse the negative effects of warm ischemic insult itself and promotes regeneration.
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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) | 0.001 | 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".