Normothermic Ex Vivo Kidney Perfusion Following Static Cold Storage—Brief, Intermediate, or Prolonged Perfusion for Optimal Renal Graft Reconditioning?
Bibliographic record
Abstract
Normothermic ex vivo kidney perfusion (NEVKP) demonstrated superior results compared to hypothermic storage in donation after circulatory death (DCD) kidney transplantation. It is unknown whether an optimal perfusion time exists following hypothermic storage to allow for the recovery of renal grafts from cold ischemic injury. In a porcine model of DCD kidney autotransplantation, the impact of initial static cold storage (SCS) (8 h) followed by various periods of NEVKP recovery was investigated: group A, 8 hSCS only (control); group B, 8 hSCS + 1 hNEVKP (brief NEVKP); group C, 8 hSCS + 8 hNEVKP (intermediate NEVKP); and group D, 8 hSCS + 16 hNEVKP (prolonged NEVKP). All grafts were preserved and transplanted successfully. One animal in group D was sacrificed and excluded by postoperative day 3 due to hind limb paralysis, but demonstrated good renal function. Postoperative graft assessment during 8 days' follow-up demonstrated lowest levels of peak serum creatinine for intermediate (C) and prolonged (D) NEVKP (p = 0.027). Histological assessment on day 8 demonstrated a significant difference in tubular injury (p = 0.001), with highest values for group B. These results suggest that longer periods of NEVKP following SCS are feasible and safe for postponing surgical transplant procedure and superior to brief NEVKP, reducing the damage caused during cold ischemic storage of renal grafts.
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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) | 0.001 | 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 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".