Best Practices for Identifying In situ Normothermic Regional Perfusion and Ex Situ Machine Perfusion in OPTN/SRTR Data: A Validation Study.

The Scientific Registry of Transplant Recipients(SRTR) is the primary source of national transplant data in the United States; however, advanced perfusion techniques, including normothermic regional perfusion(NRP) and normothermic machine perfusion(NMP), are not consistently captured. We performed a multicenter validation study comparing SRTR-derived algorithms with confirmed reference standard cases from Mayo Clinic Florida, Mayo Clinic Arizona, and Tampa General Hospital. Algorithms were developed to identify NRP, in-transit NMP, and back-to-base NMP using existing SRTR variables. Performance was assessed by sensitivity, specificity,positive predictive value,negative predictive value,and overall accuracy. The validation cohort included 310 NRP, 1,313 in-transit NMP, and 564 back-to-base NMP cases. The NRP algorithm demonstrated 90.0% sensitivity, 99.9% specificity, and 98.7% overall accuracy. Both in-transit and back-to-base NMP algorithms demonstrated sensitivities and specificities exceeding 90%, with overall accuracies exceeding 93%. Most misclassifications resulted from inaccurate donor death or clamp times for NRP or incorrect machine perfusion coding for NMP. The proposed SRTR-based algorithms identify NRP, in-transit NMP, and back-to-base NMP with high accuracy, providing a practical framework for national registry studies of advanced liver perfusion. Although modest misclassification remains, these validated algorithms support registry-based research while emphasizing the need for improved prospective capture of advanced perfusion techniques.