Journal Article

Modelli predittivi della funzione renale dopo il trapianto: un ponte verso un’immunosoppressione personalizzata

Carcano, Giulio, Guzzetti, Luca, Ietto, Giuseppe, Gallazzi, Mirco, Cristiano Salvino Baglieri, Bacuzzi, Alessandro, Iovino, Domenico

2021

Overview

Background. Renal transplantation is the gold standard treatment for end-stage renal disease, however, in 20% of cases, the graft develops a delayed graft function (DGF) that is associated with both early and late worsening of the outcome. The aim of our project was to explore the available scoring systems for DGF risk assessment in order to stratify the transplant recipients population for tailoring immunosuppressive therapy. Materials and methods. We conducted a systematic review of the literature to identify all the scoring systems predicting DGF to identify those applicable to the study population and subsequently comparing their appropriateness for defining the most accurate one. Results. We enrolled retrospectively a population of 247 renal transplanted patients where 41 cases (15.95%) developed DGF. For our population 3 of the 7 scoring systems to predict DGF available in scientific literature have resulted fit. The Irish score recognized 25 of 41 cases (60.98%), the Jeldres score 41 of 41 cases (100%), and the Chapal score only 7 of 41 (17.07%). Although the Irish score did not identify all cases of DGF, the analysis of data revealed that it is the most accurate, with area under the receiver operating characteristic almost overlapping. Conclusions. Our study identifies the Irish score as the most reliable for a population of transplant recipients in Italy. This first result has to be considered only as the base for the development of a new and more accurate predictive model for DGF risk assessment, which could benefit from the machine learning methods on a larger and multicentric population.

• Publisher: Pensiero Scientifico Editore
• Subject: Ischemia / Transplants & implants