Predictive Score Model for Delayed Graft Function Based on Easily Available Variables before Kidney Donation after Cardiac Death

Acute Kidney Injury (AKI) before and after Kidney Transplantation: Causes, Medical Approach, and Implications for the Long-Term Outcomes

Acute kidney injury (AKI) is a common finding in kidney donors and recipients. AKI in kidney donor, which increases the risk of delayed graft function (DGF), may not by itself jeopardize the short- and long-term outcome of transplantation. However, some forms of AKI may induce graft rejection, fibrosis, and eventually graft dysfunction. Therefore, various strategies have been proposed to identify conditions at highest risk of AKI-induced DGF, that can be treated by targeting the donor, the recipient, or even the graft itself with the use of perfusion machines. AKI that occurs early post-transplant after a period of initial recovery of graft function may reflect serious and often occult systemic complications that may require prompt intervention to prevent graft loss. AKI that develops long after transplantation is often related to nephrotoxic drug reactions. In symptomatic patients, AKI is usually associated with various systemic medical complications and could represent a risk of mortality. Electronic systems have been developed to alert transplant physicians that AKI has occurred in a transplant recipient during long-term outpatient follow-up. Herein, we will review most recent understandings of pathophysiology, diagnosis, therapeutic approach, and short- and long-term consequences of AKI occurring in both the donor and in the kidney transplant recipient.

Comprehensive assessment of deceased donor kidneys with clinical characteristics, pre-implant biopsy histopathology and hypothermic mechanical perfusion parameters is highly predictive of delayed graft function

Background: Due to the current high demand for transplant tissue, an increasing proportion of kidney donors are considered extended criteria donors, which results in a higher incidence of delayed graft function (DGF) in organ recipients. Therefore, it is important to fully investigate the risk factors of DGF, and establish a prediction system to assess donor kidney quality before transplantation.Methods: A total of 333 donation after cardiac death kidney transplant recipients were included in this retrospective study. Both univariate and multivariate analyses were used to analyze the risk factors of DGF occurrence. Receiver operating characteristic (ROC) curves were used to analyze the predictive value of variables on DGF posttransplant.Results: The donor clinical scores, kidney histopathologic Remuzzi scores and hypothermic mechanical perfusion (HMP) parameters (flow and resistance index) were all correlated. 46 recipients developed DGF postoperatively, with an incidence of 13.8% (46/333). Multivariate logistic regression analysis of the kidney transplants revealed that the independent risk factors of DGF occurrence post-transplantation included donor score (OR = 1.12, 95% CI 1.06-1.19, p < 0.001), Remuzzi score (OR = 1.21, 95% CI 1.02-1.43, p = 0.029) and acute tubular injury (ATI) score (OR = 4.72, 95% CI 2.32-9.60, p < 0.001). Prediction of DGF with ROC curve showed that the area under the curve was increased to 0.89 when all variables (donor score, Remuzzi score, ATI score and HMP resistance index) were considered together.Conclusions: Combination of donor clinical information, kidney pre-implant histopathology and HMP parameters provide a more accurate prediction of DGF occurrence post-transplantation than any of the measures alone.

Beneficial Effect of Moderately Increasing Hypothermic Machine Perfusion Pressure on Donor after Cardiac Death Renal Transplantation

Background:

Vascular resistance and flow rate during hypothermic machine perfusion (HMP) of kidneys is correlated with graft function. We aimed to determine the effects of increasing HMP pressure versus maintaining the initial pressure on kidney transplantation outcomes.

Methods:

We retrospectively reviewed the data of 76 primary transplantation patients who received HMP-preserved kidneys from 48 donors after cardiac death between September 1, 2013, and August 31, 2015. HMP pressure was increased from 30 to 40 mmHg (1 mmHg = 0.133 kPa) in kidneys with poor flow and/or vascular resistance (increased pressure [IP] group; 36 patients); otherwise, the initial pressure was maintained (constant pressure group; 40 patients). Finally, the clinical characteristics and transplantation outcomes in both groups were assessed.

Results:

Delayed graft function (DGF) incidence, 1-year allograft, patient survival, kidney function recovery time, and serum creatinine level on day 30 were similar in both groups, with improved flow and resistance in the IP group. Among patients with DGF, kidney function recovery time and DGF duration were ameliorated in the IP group. Multivariate logistic regression analysis revealed that donor hypertension (odds ratio [OR]: 1.43, 95% confidence interval [CI]: 1.02–2.06, P = 0.035), donor terminal serum creatinine (OR: 1.27, 95% CI: 1.06–1.62, P = 0.023), warm ischemic time (OR: 3.45, 95% CI: 1.97–6.37, P = 0.002), and terminal resistance (OR: 3.12, 95% CI: 1.76–6.09, P = 0.012) were independent predictors of DGF. Cox proportional hazards analysis showed that terminal resistance (hazard ratio: 2.06, 95% CI: 1.32–5.16, P = 0.032) significantly affected graft survival.

Conclusion:

Increased HMP pressure improves graft perfusion but does not affect DGF incidence or 1-year graft survival.

Predictive Score Model for Delayed Graft Function Based on Hypothermic Machine Perfusion Variables in Kidney Transplantation

Background:

Hypothermic machine perfusion (HMP) is being used more often in cardiac death kidney transplantation; however, the significance of assessing organ quality and predicting delayed graft function (DGF) by HMP parameters is still controversial. Therefore, we used a readily available HMP variable to design a scoring model that can identify the highest risk of DGF and provide the guidance and advice for organ allocation and DCD kidney assessment.

Methods:

From September 1, 2012 to August 31, 2016, 366 qualified kidneys were randomly assigned to the development and validation cohorts in a 2:1 distribution. The HMP variables of the development cohort served as candidate univariate predictors for DGF. The independent predictors of DGF were identified by multivariate logistic regression analysis with a P < 0.05. According to the odds ratios (ORs) value, each HMP variable was assigned a weighted integer, and the sum of the integers indicated the total risk score for each kidney. The validation cohort was used to verify the accuracy and reliability of the scoring model.

Results:

HMP duration (OR = 1.165, 95% confidence interval [CI ]: 1.008–1.360, P = 0.043), resistance (OR = 2.190, 95% CI: 1.032–10.20, P < 0.001), and flow rate (OR = 0.931, 95% CI: 0.894–0.967, P = 0.011) were the independent predictors of identified DGF. The HMP predictive score ranged from 0 to 14, and there was a clear increase in the incidence of DGF, from the low predictive score group to the very high predictive score group. We formed four increasingly serious risk categories (scores 0–3, 4–7, 8–11, and 12–14) according to the frequency associated with the different risk scores of DGF. The HMP predictive score indicates good discriminative power with a c-statistic of 0.706 in the validation cohort, and it had significantly better prediction value for DGF compared to both terminal flow (P = 0.012) and resistance (P = 0.006).

Conclusion:

The HMP predictive score is a good noninvasive tool for assessing the quality of DCD kidneys, and it is potentially useful for physicians in making optimal decisions about the organs donated.