Abstract

Background: Despite recent advances and refinements in perioperative management of kidney transplantation (KT), early renal graft injury (eRGI) remains a critical problem with serious impairment of graft function as well as short- and long-term outcome. Serial monitoring of peripheral blood innate immune cells might be a useful tool in predicting post-transplant eRGI and graft outcome after KT. Methods: In this prospective study, medical data of 50 consecutive patients undergoing KT at the University Hospital of Leipzig were analyzed starting at the day of KT until day 10 after the transplantation. The main outcome parameter was the occurrence of eRGI and other outcome parameters associated with graft function/outcome. eRGI was defined as graft-related complications and clinical signs of renal IRI (ischemia reperfusion injury), such as acute tubular necrosis (ATN), delayed graft function (DGF), initial nonfunction (INF) and graft rejection within 3 months following KT. Typical innate immune cells including neutrophils, natural killer (NK) cells, monocytes, basophils and dendritic cells (myeloid, plasmacytoid) were measured in all patients in peripheral blood at day 0, 1, 3, 7 and 10 after the transplantation. Receiver operating characteristics (ROC) curves were performed to assess their predictive value for eRGI. Cutoff levels were calculated with the Youden index. Significant diagnostic immunological cutoffs and other prognostic clinical factors were tested in a multivariate logistic regression model. Results: Of the 50 included patients, 23 patients developed eRGI. Mean levels of neutrophils and monocytes were significantly higher on most days in the eRGI group compared to the non-eRGI group after transplantation, whereas a significant decrease in NK cell count, basophil levels and DC counts could be found between baseline and postoperative course. ROC analysis indicated that monocytes levels on POD 7 (AUC: 0.91) and NK cell levels on POD 7 (AUC: 0.92) were highly predictive for eRGI after KT. Multivariable analysis identified recipient age (OR 1.53 (95% CI: 1.003–2.350), p = 0.040), recipient body mass index > 25 kg/m2 (OR 5.6 (95% CI: 1.36–23.9), p = 0.015), recipient cardiovascular disease (OR 8.17 (95% CI: 1.28–52.16), p = 0.026), donor age (OR 1.068 (95% CI: 1.011–1.128), p = 0.027), <0.010), deceased-donor transplantation (OR 2.18 (95% CI: 1.091–4.112), p = 0.027) and cold ischemia time (CIT) of the renal graft (OR 1.005 (95% CI: 1.001–1.01), p = 0.019) as clinically relevant prognostic factors associated with increased eRGI following KT. Further, neutrophils > 9.4 × 103/μL on POD 7 (OR 16.1 (95% CI: 1.31–195.6), p = 0.031), monocytes > 1150 cells/ul on POD 7 (OR 7.81 (95% CI: 1.97–63.18), p = 0.048), NK cells < 125 cells/μL on POD 3 (OR 6.97 (95% CI: 3.81–12.7), p < 0.01), basophils < 18.1 cells/μL on POD 10 (OR 3.45 (95% CI: 1.37–12.3), p = 0.02) and mDC < 4.7 cells/μL on POD 7 (OR 11.68 (95% CI: 1.85–73.4), p < 0.01) were revealed as independent biochemical predictive variables for eRGI after KT. Conclusions: We show that the combined measurement of immunological innate variables (NK cells and monocytes on POD 7) and specific clinical factors such as prolonged CIT, increased donor and recipient age and morbidity together with deceased-donor transplantation were significant and specific predictors of eRGI following KT. We suggest that intensified monitoring of these parameters might be a helpful clinical tool in identifying patients at a higher risk of postoperative complication after KT and may therefore help to detect and—by diligent clinical management—even prevent deteriorated outcome due to IRI and eRGI after KT.

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