Laboratory Medicine Approaches for Assessing Delayed Graft Function in Renal Transplant

Delayed graft function (DGF) remains a significant complication in renal transplantation, adversely affecting graft survival, patient quality of life, and healthcare costs. As kidney transplantation rates rise in the United States, there is increasing emphasis on optimizing donor organ selection and improving posttransplant outcomes. A key challenge lies in the early identification and prediction of graft dysfunction to guide timely interventions.

This review examines the multifactorial causes, risk factors, and consequences of DGF, including ischemia-reperfusion injury and both recipient and donor determinants. It highlights emerging biomarkers, such as neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, proenkephalin, and interleukin-18, that hold promise for early detection and risk stratification. The integration of artificial intelligence into predictive modeling is explored as a means to combine molecular, clinical, and procedural variables into comprehensive tools for improving organ allocation and individualized management.

Expanding biomarker assessment to the donor preoperative phase may yield earlier and more holistic insights into organ quality. Standardization in biomarker measurement and greater focus on donor characterization are essential to strengthen predictive reliability and clinical translation.