Normothermic Ex Vivo Kidney Perfusion Improves Early DCD Graft Function Compared With Hypothermic Machine Perfusion and Static Cold Storage
Bibliographic record
Abstract
BACKGROUND: Better preservation strategies for the storage of donation after circulatory death grafts are essential to improve graft function and to increase the kidney donor pool. We compared continuous normothermic ex vivo kidney perfusion (NEVKP) with hypothermic anoxic machine perfusion (HAMP) and static cold storage (SCS) in a porcine kidney autotransplantation model. METHODS: Porcine kidneys were exposed to 30 minutes of warm ischemia and then reimplanted following either 16 hours of either SCS, HAMP (LifePort 1.0), or NEVKP before autotransplantation (n = 5 per group). The contralateral kidney was removed. Animals were followed for 8 days. RESULTS: Grafts preserved by NEVKP demonstrated improved function with more rapid recovery compared with HAMP and SCS (mean peak serum creatinine: 3.66 ± 1.33 mg/dL [postoperative d 1 [(POD1)], 8.82 ± 3.17 mg/dL [POD2], and 12.90 ± 2.19 mg/dL [POD3], respectively). The NEVKP group demonstrated significantly increased creatinine clearance calculated on POD3 (63.6 ± 19.0 mL/min) compared with HAMP (13.5 ± 10.3 mL/min, P = 0.001) and SCS (4.0 ± 2.6 mL/min, P = 0.001). Histopathologic injury scores on POD8 were lower in both perfused groups (NEVKP and HAMP, score: 1-1.5) compared with SCS (score: 1-3, P = 0.3), without reaching statistical significance. CONCLUSIONS: NEVKP storage significantly improved early kidney function compared with both cold preservation strategies, although HAMP also demonstrates improvement over SCS. NEVKP may represent a novel, superior preservation option for donation after circulatory death renal grafts compared with conventional hypothermic methods.
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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 | 0.000 | 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) | 0.002 | 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".