56.17 In situ Viability Testing during NRP Predict EAD in DCD Liver Transplant Recipients

Posted on May 12, 2025

A.H. Ha1, C. Goncalves1, D. Reynolds1, D. Chen1, C. Yoshida1, K. Gustilo1, I. Rodriguez1, W. Lariviere1, D. Brosi1, B. Kaplan1, J. Pomposelli1, J. Schold1, Y. Bababekov1  1University of Colorado School of Medicine, Transplant Surgery, Aurora, CO, USA

Introduction:
Normothermic regional perfusion (NRP) is increasingly utilized in donation after circulatory death (DCD) liver transplantation (LT). Despite potential benefits of NRP, the relationship between NRP and early allograft dysfunction (EAD) remains poorly understood. We aimed to investigate if variables specific to NRP-related procurement may predict EAD in DCD NRP LT.  

Methods:
All adult DCD NRP LT recipients from 2/2022 to 5/2024 were reviewed at University of Colorado Hospital. EAD was defined following Olthoff criteria. The UK DCD Risk Score and Donor Risk Index were included to account for donor and recipient risk factors. In situ viability assessment during NRP included peak AST, peak ALT, peak lactate and peak biliary bicarbonate. Multivariable logistic regression was performed to assess the presence of EAD.  

Results:
There was a total of 80 NRP cases during the study period and 40 developed EAD. The median UK DCD Risk score was 3 (3-5); median DRI was 2.43 (2.03-2.76). On NRP the median peak AST, ALT, lactate, and biliary bicarbonate were 79 U/L (51.5-200), 76 U/L (30 – 130), 8.8mg/dL (7.8-9.9), and 28.3 mEq/L (22.1-31.3), respectively. Median recipient laboratory MELD was 20 (17-24) (Table 1). The logistic regression model predicts EAD with 61% accuracy with AUC of 64% [43%-81%], PPV 73%, NPV 54%, and r^2 0.25.   

Conclusion:

EAD remains a challenging outcome to predict in DCD LT. Our study demonstrated that these NRP-related variables offered moderate predictability for EAD. As the transplant community continues to expand the organ pool through DCD allografts, enhancing donor-recipient matching may help reduce the risk of EAD. However, further research is needed to refine these predictive models and explore interventions that could better mitigate the risk of EAD in this population.