The aim of this study was to evaluate risk factors affecting graft and patient survival after transplantation from deceased donors.

We retrospectively analyzed the outcomes of 186 transplantations from deceased donors performed at our center between 2006 and 2014. The recipients were divided into two groups: Group I (141 recipients without graft loss) and Group II (45 recipients with graft loss). Kaplan-Meier, log-rank test, and Cox proportional hazard regressions were used.

The characteristics of both groups were similar except renal resistive index at the last follow-ups. When graft survival and mortality at the first, third, and fifth years were analyzed, tacrolimus (Tac)-based regimens were superior to cyclosporine (CsA)-based regimens (P < .001). Risk factors associated with graft survival at the first year included cardiac cause of death (versus cerebrovascular accident [CVA]; hazard ratio [HR], 6.36; 95% confidence interval [CI], 1.84-22.05; P = .004), older transplant age (HR, 1.05; 95% CI, 1.02-1.08; P < .001), and high serum creatinine level at 6 months post-transplantation (HR, 1.74; 95% CI, 1.48-2.03; P < .001), whereas younger donor age decreased risk (HR, 0.97; 95% CI, 0.95-1.00; P = .019). Also, the Tac-based regimen had a 3.63-fold (95% CI, 1.47-8.97; P = .005) lower risk factor than the CsA-based regimen, and 2.93-fold (95% CI, 1.13-7.63; P = .027) than other regimens without calcineurin inhibitors. When graft survival at 3 years was analyzed, diabetes mellitus was lower than idiopathic causes and pyelonephritis (P = .035). In Cox regression analysis at year 3, older transplantation age (HR, 1.20; 95% CI, 1.04-1.39; P = .014) and serum creatinine level at month 6 post-transplantation (HR, 1.65; 95% CI, 1.42-1.90; P < .001) were significant risk factors for graft survival. Hemodialysis (HD) plus peritoneal dialysis (PD) treatment was 2.22-fold (95% CI, 1.08-4.58; P = .03) risk factor than only HD before transplantation. When graft survival and mortality at year 5 were analyzed, diabetes mellitus was lower compared with all other diseases. In Cox regression analysis at year 5, younger donor age (HR, 0.73; 95% CI, 0.62-0.86; P < .001) was protective for graft survival, whereas older transplantation age (HR, 1.40; 95% CI, 1.20-1.64; P < .001) and serum creatinine level at month 6 of post-transplantation (HR, 1.39; 95% CI, 1.19-1.61; P < .001) were significant risk factors. PD increased 3.32 (95% CI, 1.28-8.61; P = .014) times the risk than HD. In Cox regression analysis at year 1, cardiac cause of death (versus CVA; HR, 5.28; 95% CI, 1.37-20.31; P = .016), CsA-based regimen (versus Tac; HR, 4.95; 95% CI, 1.78-13.78; P = .002), HD plus PD treatment (versus alone HD; HR, 3.26; 95% CI, 1.28-8.30; P = .013), older transplantation age (HR, 1.08; 95% CI, 1.04-1.11; P < .001), serum creatinine level at month 6 post-transplantation (HR, 1.34; 95% CI, 1.11-1.62; P = .003), and low HLA mismatches (HR, 1.67; 95% CI 1.01-2.70; P = .044) were risk factors for mortality. At year 3, CsA-based regimen (versus Tac; HR, 3.54; 95% CI, 1.32-9.47; P = .012), PD (versus HD; HR, 5.04; 95% CI, 1.41-18.05; P = .013), HD plus PD treatment (versus alone HD; HR, 3.51; 95% CI, 1.37-9.04; P = .009), and older transplantation age (HR, 1.27; 95% CI 1.05-1.53; P = .015) were risk factors for mortality. At year 5, older age at transplantation (HR, 1.47; 95% CI, 1.23-1.77; P < .001), PD (versus HD; HR, 9.21; 95% CI, 3.09-27.45; P < .001), and CsA-based regimen (versus Tac; HR, 2.75; 95% CI, 1.04-7.23; P = .041) were risk factors for mortality, whereas younger donor age decreased risk (HR, 0.71; 95% CI, 0.56-0.86; P < .001).

Death of donor with cardiac cause, CsA-based immunosuppressive regimen, donor age, serum creatinine level at month 6 post-transplantation, and renal replacement therapy before transplantation affected mortality and graft survival in deceased donors.

Accumulating literature indicates that late acute rejection (LAR) after kidney transplantation portends an unfavourable prognosis. There are no data on the incidence of LAR in Asian subjects, or its risk factors and associated clinical outcomes.

We conducted a retrospective single-centre case-+control study to investigate the incidence, risk factors and prognosis of LAR in Chinese kidney transplant recipients. Subjects with or without LAR were matched for age, gender, era of transplantation, allograft type, and maintenance immunosuppression regimen.

Thirty-two episodes of LAR occurred within an observation period of 12 years giving an incidence rate of 0.46 episodes per 1000 patient-years. Acute rejection within the first year after transplantation was associated with an increased risk of LAR (OR 3.59, P = 0.041). In patients receiving maintenance immunosuppression regimen with steroid, cyclosporin A (CsA) and mycophenolate or an m-TOR inhibitor, patients with LAR showed lower trough CsA levels prior to and at the time of rejection compared to Controls (86.0 ± 26.1 vs. 105.6 ± 13.3 μg/L, P = 0.049; and 75.7 ± 35.7 vs. 106.0 ± 20.5 μg/L, P = 0.032, respectively). Trough CsA level below 80 μg/L was associated with the development of LAR (OR 10.82, P = 0.032). Patients with LAR showed an inferior allograft survival (P < 0.001) while patient survival rates were similar (P = 0.122).

Late acute rejection is uncommon in Chinese kidney transplant recipients but is associated with reduced allograft survival. Risk factors include acute rejection in the first post-transplant year and trough CsA level below 80 μg/L in patients on CsA-based maintenance immunosuppression. Minimization of immunosuppression in apparently stable kidney transplant recipients must be exercised with caution.

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature.

Delayed graft function (DGF) after kidney transplantation (KTx) ranges between 2% and 50%. The mechanisms leading to DGF deserve special interest because DGF exerts negative influences on long-term outcomes. We studied gene expression profiles in deceased donor kidney (DDK) biopsies with and without DGF.

Gene expression profiling was performed on donor kidney tissues from 33 DDK with the use of microarrays. DDK were classified as grafts with immediate function (non-DGF; n=21) and grafts with DGF (n=12). DGF was defined as a dialysis requirement in the first week after transplantation. Demographic donor and recipient information was collected. The robust-multiarray average method was used to estimate probe set expression summaries. Logistic regression was used to identify genes significantly associated with DGF development.

Patients were followed for 3 months after KTx. Thirty-eight probe sets (n=36 genes) were univariably differentially expressed in DDK with DGF when compared with DDK with non-DGF (alpha=0.001). Sixty-nine probe sets (n=65 genes) were differentially expressed in DDK with DGF when compared with DDK with non-DGF after adjusting for cold ischemia time (alpha=0.001). Gene ontology terms classified the overexpressed genes in DDK with DGF as principally related to cell cycle/growth (e.g., IGFBP5, CSNK2A2), signal transduction (e.g., RASGRP3), immune response (e.g., CD83, BCL3, MX1), and metabolism (e.g., ENPP4, GBA3). TNFRSF1B was overexpressed in DDK with DGF.

Cold ischemia time was a predictor of DGF independently of the preservation method. We identified a set of 36 genes candidates of DGF in DDK, with genes involved in the inflammatory response being the more important.