A triple-biomarker approach for the detection of delayed graft function after kidney transplantation using serum creatinine, cystatin C, and malondialdehyde

• Main Author: Fonseca, I
• Publication Date: 2015
• Other Authors: Reguengo, H, Oliveira, JC, Martins, S, Malheiro, J, Almeida, M, Santos, J, Dias, L, Pedroso, S, Lobato, L, Henriques, AC, Mendonça, D
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10216/114662
• topic: Biomarkers; Malondialdehyde; Cystatin C; Delayed graft function; Kidney transplantation

Introduction: Serum creatinine (SCr) alone does not allow for the early diagnosis of delayed graft function (DGF) following kidney transplantation (KTx). Objective, design and methods: The diagnostic utility of urinary neutrophil gelatinase-associated lipocalin (uNGAL), serum leptin, malondialdehyde (MD.A), and cystatin C (CysC) for the early detection of DGF was previously evaluated by our group in a prospective cohort study of 40 consecutive adults undergoing KTx. Because no single biomarker achieved adequate sensitivity or specificity for practical purposes, this study was designed to evaluate the combined use of new markers with SCr. Urine and blood samples were collected 8-to-12 h after KTx (day-1). Logistic regression was used to combine the biomarkers, and receiver operating characteristic curves and areas under the curve (AUC–ROC) were generated. Results: Eighteen recipients developed DGF (dialysis requirement during the first post-transplant week). On day-1, the AUC for SCr to predict DGF was 0.73, 0.88 for uNGAL, 0.90 for MDA, 0.76 for leptin, and 0.91 for CysC. Adding new biomarkers to SCr enhanced the performance of DGF prediction, and the best combination was achieved with SCr, MDA, and CysC (AUC = 0.96, sensitivity = 100%; specificity = 86%). Conclusion: A combination of graft damage biomarkers outperformed SCr in the early diagnosis of DGF, and the best performance was achieved by a triple-marker approach, using SCr, MDA, and CysC.