Date: Saturday, June 1, 2019
Session Time: 5:30pm-7:30pm
Presentation Time: 5:30pm-7:30pm
Location: Hall C & D
*Purpose: Early allograft dysfunction as well as long-term graft loss are major obstacles to successful kidney transplantation. Currently, kidney donor risk index (KDRI) is used during kidney evaluation and there is a need to find new pretransplant biomarkers to predict the graft dysfunction that could be useful in making decisions for optimal allocation of donor kidneys. Earlier, pretransplant recipient circulating TNFR2+Treg cell has been shown as an immune marker for acute kidney injury (AKI). In this study we used donor and recipient metrics in combination with pretransplant percent of TNFR2+Treg to predict graft outcomes after renal transplantation.
*Methods: In this study, a cohort of 76 deceased donor kidney transplant recipients were prospectively followed after transplantation for outcomes parameters including delayed graft function (DGF; n=18) defined as recipients requiring dialysis within 7 days of transplantation, slow graft function (SGF; n=34) defined as recipients with a decrease in 24-hr serum creatinine by less than 20% , AKI (DGF or SGF, n=52), biopsy proven acute rejection (BPAR; n=12) at 6 months, and graft loss 8 years after transplantation (n=11). DGF and SGF were defined based on requirement of post-transplant dialysis and 24-hour serum creatinine. Pretransplant circulating CD4+CD127lo/-TNFR2+ Treg cells were measured by flow cytometry. The recipient, donor and organ procurement characteristics were collected prospectively. Binary logistic regression was performed to assess the predictive accuracy of donor, recipient and organ quality variables for the early transplant outcomes as well as graft loss 8 years after kidney transplantation. Analyses were performed using SPSS 20 and considered significant if p-value was 0.5 or less.
*Results: None of the recipients were on immunosuppressive therapy for at least 180 days before transplantation. All recipients received ATG, Campath or Daclizumab induction and tacrolimus based maintenance immunosuppression and immunosuppressive regimen were similar between groups. Variables likes KDRI, cold ischemic time (CIT) and sensitization were incorporated with pretransplant percent of CD4+CD127lo/-TNFR2+ Treg cells to create logistic regression models to predict DGF (AUC=.801, p value<.01), AKI (AUC=.910, p value<.01), BPAR (AUC=.861, p value<.01), and graft loss after 8 years (AUC=.765, p value<.01).
*Conclusions: Donor quality as identified by KDRI, immune status as identified by % functional Tregs (TNFR2+ve) and sensitization (cPRA) and CIT can together be used to more accurately predict short and long term graft outcomes and aid in better allocation of allografts. This concept needs to be validated in a larger multi center prospective study.
To cite this abstract in AMA style:Tchervenkov J, Nguyen M, Negi S, Paraskevas S. Predicting Allograft Outcomes of Renal Transplantation with Pretransplant Metrics [abstract]. Am J Transplant. 2019; 19 (suppl 3). https://atcmeetingabstracts.com/abstract/predicting-allograft-outcomes-of-renal-transplantation-with-pretransplant-metrics/. Accessed July 30, 2021.
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