153 10-year analysis of the impact of normothermic regional perfusion in simultaneous pancreas and kidney transplant
Bibliographic record
Abstract
Abstract Background Deceased Cardiac Donors (DCD) organs are increasingly being used for simultaneous pancreas and kidney (SPK) transplant. The number recovered following in-situ normothermic regional perfusion (NRP) is also increasing. This study reviewed a 10-year UK experience of SPK transplantation following NRP in DCD. Methods Data were collected on all first DCD SPK transplants (n=426) performed during 2013-2023 from the UK Transplant Registry. NRP and non-NRP donors were compared using adjusted regression models. Multiple imputation was used to deal with missing data. Results Most grafts were from non-NRP donors n=379 (89%) with n=47 (11%) from NRP donors. Median warm ischaemic time (withdrawal to start of aortic cold or normothermic perfusion) was longer with NRP (17 vs 12 minutes; p=0.005). For all other parameters donors and recipients were well matched. Univariable analysis showed no statistically significant difference in one-year pancreas graft (NRP 93.6%, non-NRP 89.2%, p=0.206). A multivariable model adjusted for donor and recipient factors showed lower pancreas graft loss with NRP, but this did not reach statistical significance (aHR 0.56, 95%CI 0.17-1.80, p=0.327). Sensitivity analyses adjusting for PDRI showed similar results. NRP was not associated with 3-month insulin independence (p=0.51) or pancreas graft rejection (p=0.48). Conclusions Concerns exist that NRP may be detrimental to the pancreas. This 10-year UK analysis is the largest reported. We found lower pancreas graft loss in the NRP group, though not statistically significant. This data, along with previous benefits demonstrated in liver and kidney, support continued expansion of the NRP programmes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".