Analyzing association rules for graft failure following deceased and live donor Kidney transplantation

This paper investigates the clinical attributes that contribute to kidney graft failure following live and deceased donor transplantation using an association rule mining approach. The generated rules are used to analyze the distinctive cooccurrence of attributes for those with or without all-cause graft failure. Analysis of a kidney transplantation dataset acquired from the Scientific Registry of Transplant Recipients that included over 95000 deceased and live donor recipients over 5-years was performed. Using an association rule mining approach, we were able to confirm established risk factors for graft loss after live and deceased donor transplantation and identify novel combinations of factors that may have implications for clinical care and risk prediction post kidney transplantation. Using lift as the metric to evaluate association rules, our results indicate that advanced recipient age (i.e. over 60 years), end stage kidney disease due to diabetes, the presence of recipient peripheral vascular disease and recipient coronary artery disease have a high likelihood of graft failure within 5 years after transplantation.