Predictive model for delayed graft function based on easily available pre-renal transplant variables

Pietro Manuel Ferraro, Giovanni Gambaro, Gianluigi Zaza, Gianpaolo Tessari, Silvio Sandrini, Maria Piera Scolari, Irene Capelli, Enrico Minetti, Loreto Gesualdo, Giampiero Girolomoni, Antonio Lupo, Luigino Boschiero

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Identification of pre-transplant factors influencing delayed graft function (DGF) could have an important clinical impact. This could allow clinicians to early identify dialyzed chronic kidney disease (CKD) patients eligible for special transplant programs, preventive therapeutic strategies and specific post-transplant immunosuppressive treatments. To achieve these objectives, we retrospectively analyzed main demographic and clinical features, follow-up events and outcomes registered in a large dedicated dataset including 2,755 patients compiled collaboratively by four Italian renal/transplant units. The years of transplant ranged from 1984 to 2012. Statistical analysis clearly demonstrated that some recipients' characteristics at the time of transplantation (age and body weight) and dialysis-related variables (modality and duration) were significantly associated with DGF development (p ≤ 0.001). The area under the receiver-operating characteristic (ROC) curve of the final model based on the four identified variables predicting DGF was 0.63 (95 % CI 0.61, 0.65). Additionally, deciles of the score were significantly associated with the incidence of DGF (p value for trend <0.001). Therefore, in conclusion, in our study we identified a pre-operative predictive model for DGF, based on inexpensive and easily available variables, potentially useful in routine clinical practice in most of the Italian and European dialysis units.
Original languageEnglish
Pages (from-to)N/A-N/A
JournalINTERNAL AND EMERGENCY MEDICINE
DOIs
Publication statusPublished - 2014

Keywords

  • transplant

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