BACKGROUND: Retrospective evidence suggests that lactate dehydrogenase, aspartate aminotransferase, total glutathione-S-transferase (GST), alanine-aminopeptidase, N-acetyl-β-D-glucosaminidase (NAG), and heart-type fatty acid binding protein (H-FABP) measured during kidney machine perfusion (MP) could have predictive value for posttransplant outcome. However, these data may be biased due to organ discard based on biomarker measurements, and previous analyses were not adjusted for likely confounding factors. No reliable prospective evidence has been available so far. Nevertheless, some centers already use these biomarkers to aid decisions on accepting or discarding a donor kidney. METHODS: From 306 deceased-donor kidneys donated after brain death or controlled cardiac death and included in an international randomized controlled trial, these six biomarkers were measured in the MP perfusate. In this unselected prospective data set, we tested whether concentrations were associated with delayed graft function, primary nonfunction, and graft survival. Multivariate regression models investigated whether the biomarkers remained independent predictors when adjusted for relevant confounding factors. RESULTS: GST, NAG, and H-FABP were independent predictors of delayed graft function but not of primary nonfunction and graft survival. Lactate dehydrogenase, aspartate aminotransferase, and alanine-aminopeptidase had no independent prognostic potential for any of the endpoints. Perfusate biomarker concentrations had no relevant correlation with cold ischemic time or renal vascular resistance on the pump. CONCLUSIONS: Increased GST, NAG, or H-FABP concentrations during MP are an indication to adjust posttransplant recipient management. However, this study shows for the first time that perfusate biomarker measurements should not lead to kidney discard.
966 - 973
Acetylglucosaminidase, Adolescent, Adult, Aged, Biomarkers, CD13 Antigens, Fatty Acid-Binding Proteins, Female, Glutathione Transferase, Graft Survival, Humans, Kidney Transplantation, Male, Middle Aged, Multivariate Analysis, Perfusion, Predictive Value of Tests, Proportional Hazards Models, Treatment Outcome