A Risk Prediction Model for Delayed Graft Function in the Current Era of Deceased Donor Renal Transplantation

Abstract

Delayed graft function (DGF) impacts short- and long-term outcomes. We present a model for predicting DGF after renal transplantation. A multivariable logistic regression analysis of 24,337 deceased donor renal transplant recipients (2003-2006) was performed. We developed a nomogram, depicting relative contribution of risk factors, and a novel web-based calculator (http://www.transplantcalculator.com/DGF) as an easily accessible tool for predicting DGF. Risk factors in the modern era were compared with their relative impact in an earlier era (1995-1998). Although the impact of many risk factors remained similar over time, weight of immunological factors attenuated, while impact of donor renal function increased by 2-fold. This may reflect advances in immunosuppression and increased utilization of kidneys from expanded criteria donors (ECDs) in the modern era. The most significant factors associated with DGF were cold ischemia time, donor creatinine, body mass index, donation after cardiac death and donor age. In addition to predicting DGF, the model predicted graft failure. A 25-50% probability of DGF was associated with a 50% increased risk of graft failure relative to a DGF risk < 25%, whereas a > 50% DGF risk was associated with a 2-fold increased risk of graft failure. This tool is useful for predicting DGF and long-term outcomes at the time of transplant.