Pulsatile Perfusion Reduces the Risk of Delayed Graft Function in Deceased Donor Kidney Transplants, Irrespective of Donor Type and Cold Ischemic Time
Bibliographic record
Abstract
BACKGROUND: The role of pulsatile perfusion (PP) across different cold ischemic times (CIT) within different donor groups is unclear. This study examined the association of PP with delayed graft function (DGF) in all (n=94,709) deceased donor kidney transplants in the US between 2000 and 2011, as a function of CIT and donor type. METHODS: Using the Scientific Registry of Transplant Recipients data, all adult standard criteria donors (SCD, n=71,192), expanded criteria donors (ECD, n=15,122), and donors after circulatory death (DCD, n=8,395) kidney transplant recipients were identified. Within each donor group, transplants were stratified based on duration of CIT: 0 to 6 hours, 6.1 to 12 hours, 12.1 to 18 hours, 18.1 to 24 hours, 24.1 to 30 hours, 30.1 to 36 hours, and greater than 36 hours. Within each group, the odds of DGF with and without PP was determined after adjusting for donor, recipient, and transplant factors, including a propensity score for the likelihood of PP use, and clustering on transplant center using multivariable logistic regression. RESULTS: When stratified by donor type and CIT, the adjusted odds of DGF were lower with PP across all CIT in SCD transplants, when CIT was greater than 6 hours in ECD transplants, and when CIT was between 6 and 24 hours in DCD transplants. CIT was independently associated with a greater risk of DGF irrespective of storage method, but this effect was substantially modified by PP. CONCLUSION: PP is associated with a reduced risk of DGF irrespective of donor type and CIT. Although PP modifies the impact of CIT on the risk of DGF, it does not eliminate its association with DGF, suggesting the optimal strategy to reduce DGF is to minimize CIT and utilize PP in all deceased donor transplants.
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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) | 0.000 | 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".