Key words : Kidney transplantation, Preservation, United Network for Organ Sharing

Introduction

Kidney transplant (KT) is the most effective treatment for end-stage renal disease.1,2 Recipients have better long-term survival rates than those undergoing dialysis.¹ Despite the increased life expectancy offered with KT, organ shortages prevent many from receiving one.²

Increasing the donor pool with extended criteria donor (ECD) kidneys, or kidneys with a high Kidney Donor Risk Index (KDRI) or Kidney Donor Profile Index (KDPI), is a promising method to address organ shortages.³ Donors classified as ECD are either ?60 years of age or between the ages of 50 and 59 years with at least 2 of 3 additional criteria: history of hypertension, serum creatinine level ?1.5 mg/dL, or death resulting from a cerebrovascular accident.² Kidney Donor Risk Index is based on donor characteristics and predicts the relative risk of graft failure per given donor.^4,5 This score can be converted to KDPI, which is the percent chance of graft failure for a particular kidney compared with all kidneys procured for transplant during the previous year.^4,5 Kidneys with KDPI >85% are comparable to ECD kidneys.⁴ Another important barrier is transplant of organs with long cold ischemic time (CIT). Longer CIT has been correlated with high rates of delayed graft function (DGF),⁶ although CIT has also been reported to not be a significant predictive value for graft and patient survival.⁷ Although many researchers have also documented success in KT with prolonged CIT using static cold storage, the American Society of Transplant Surgeons (ASTS) recommends reducing both CIT and warm ischemic time to improve outcomes.^8-10

One strategy for increasing the ability to transplant ECD or high KDRI/KDPI kidneys while reducing ischemic times is with machine perfusion for organ preservation.³ The ASTS guidelines suggest a low threshold for use of machine perfusion in KT.¹⁰ Although early literature did not identify a significant difference in rates of acute tubular necrosis between machine perfusion and static cold storage for long CIT grafts,11 a recent meta-analysis of 14 randomized controlled trials concluded that hypothermic machine perfusion was superior in reducing DGF for both donation after brain death and donation after cardiac death (DCD) kidneys compared with cold storage.¹² Another trial discovered significantly higher utilization of ECD kidneys along with a significant decrease in DGF in ECD kidneys when preserved with machine perfusion versus cold storage.¹³ In machine-perfused kidneys from donors ?65 years of age, there was significant reduction in primary nonfunction (PNF) and improvement in graft survival 1 year after initial DGF.¹⁴ Machine perfusion was also found to reduce graft rejection.¹⁵

While there is consensus that machine perfusion is beneficial and it has become common practice among transplant centers, there remains a lack of unanimity on the best formula for perfusion solution. All organ procurement organizations (OPOs) in the United States use either Waters IGL Pulsatile Perfusion Solution by Waters Medical Systems or KPS-1 Kidney Perfusion Solution by Organ Recovery Systems for machine perfusion of kidneys. These solutions have the same base components. However, the medications that OPOs add to these solutions are inconsistent. Despite limited preclinical and clinical evidence to suggest the need for additives to perfusion solutions, OPOs do make additions. Here, we aimed to catalog the additives that each OPO included in their perfusion solution and to determine the impact of different formulas on transplant outcomes.

Materials and Methods

A telephone survey of all 58 OPOs in the United States inquiring about their respective formula additive practices was conducted. The survey results were merged with the United Network for Organ Sharing (UNOS) transplant registry data using the OPO identification code as the common identifier. The registry data included 28?292 KT recipients between January 2014 and March 2019. This study did not require institutional review board approval.

Basic characteristics of the donors and recipients who received kidneys from OPOs that typically used or did not use additives were compared. The characteristics were chosen by identification of standard risk factors, including basic demographic and clinical covariates. The variables between the 2 groups were compared depending on the sample size and the distribution of the variables included. The t tests/Wilcoxon-Mann-Whitney tests were used for continuous variables, and the chi-square/Fishers exact tests were used for categorical variables.

A series of logistic regressions were performed to estimate the associations between additives (if any) and PNF, DGF, or early graft failure (EGF) individually. For EGF, logistic regressions were used as opposed to Cox regressions as there were no censored cases for EGF (ie, those cases where the graft failed after 90 days were not considered EGF); our intention was to estimate perfusion effects on binary outcomes rather than on changes in the failure rate over time. To adjust for bias from the inherent violation of independence and the small standard errors in the observations within each OPO, we used cluster-robust standard errors instead of the conventional standard errors.¹⁶ To reduce possible biases across OPOs, pediatric, multiorgan, and retransplant recipients were excluded. The regressions were run separately for each type of additive and for the most common combinations of the additives, adjusting for those kidneys perfused without any additives. This approach allowed us to estimate the impact of individual and common combinations of additives compared with the average impact of all other additives. Following convention, DGF, PNF, and EGF were defined as requirement for dialysis during the first week after transplant, graft failure without established cause, and graft failure from any cause within 90 days after transplant, respectively.

In the regression analysis, KDRI was utilized to control for all donor characteristics. Recipients with high KDRI were defined as those who received kidneys where KDRI was above the mean (KDRI ?1.22). The variables reflecting donor characteristics such as age, DCD, ECD, body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), history of hypertension, and creatinine level were tested individually in the bivariate analysis but were excluded from the final regression model to avoid multicollinearity bias on P values. To examine the possible effects of additives on the outcomes of receiving lower-quality kidneys, interactions between high KDRI and individual additives were included in separate regressions. We explored various models with a different set of covariates to examine the reliability of the coefficient estimates. Only the models that provided a stable set of coefficient estimates were retained for the final results. Calculations were performed using STATA SE version 15 software. All statistics were evaluated at the 5% and 1% significance levels.

Results

The telephone survey of all 58 OPOs achieved a 100% response rate. Table 1 shows the specific additives used by the OPOs. Most OPOs did not use any additives. Of additives used, mannitol was the most common, followed by dexamethasone, insulin, and verapamil. Figure 1 illustrates the OPOs per OPTN region that utilized additives of any kind, and Figure 2 shows the number of OPOs that reported using an additive alone or a combination of additives. Several combinations of additives were reported: mannitol with verapamil; mannitol with insulin and dexamethasone; mannitol with verapamil, insulin, dexamethasone, sodium bicarbonate, and prostaglandin E (PGE); mannitol with insulin, dexamethasone, and penicillin/ampicillin; dexamethasone with insulin; dexamethasone with insulin and penicillin/ampicillin; methylprednisolone with insulin; and arginine with glutathione.

Table 2 summarizes KT donor and recipient characteristics (n = 68?792). Among recipients, 41% received kidneys perfused with additives. Regarding recipient characteristics, several significant dif­ferences were noted between those who were transplanted with kidneys perfused with additives and those who were not. These differences included age (52.69 vs 53.05 years; P < .001), sex (59.93% males vs 60.97% males; P = .006), percent African American (18.12% vs 14.65%; P < .001), percent Hispanic (8.35% vs 8.73%; P = .011), waiting times (715 vs 794 days;P < .001), and HLA mismatch level (P = .039) for recipients of kidneys perfused with and without additives, respectively.

With regard to donor demographics, significant differences included age (40.07 vs 40.60 years; P < .001), sex (60.48% male vs 61.26% male; P = .040), BMI (28.67 vs 28.51; P = .002), creatinine level (1.26 vs. 1.28 mg/dL; P < .006), no history of hypertension (30.40% vs 28.97%; P < .001), DCD (19.68% vs 21.97%; P < .001), and ECD (14.42% vs 15.05%; P = .022) between those who donated kidneys perfused with and without additives.

Significant differences in organ factors included CIT (18.019 vs 17.60 hours P < .001), percent local (71.08% vs 72.21%; P = .001), and percent regional (13.01% vs 11.82%; P < .001) between kidneys perfused with and without additives, respectively.

The results of the logistic regressions are summarized in Table 3 and Table 4. Models 1.1, 1.2, 1.3, and 1.4 in Table 3 present the correlation between various additives and graft outcomes for all kidneys. Table 4 features models 1.5, 1.6, 1.7, and 1.8, which demonstrate the correlation between different additives and graft outcomes for low-quality kidneys (defined as KDRI ?1.22). Donor and recipient covariates were included in the regression for model estimation but not included in the tables.

The logistic regression revealed several significant associations between additives and KT outcomes. Mannitol had a significant negative correlation with graft failure regardless of kind of graft failure (P < .01). It also demonstrated a negative correlation with DGF alone (P < .01) in all kidneys and those of lower quality.

Dexamethasone was found to have a significant positive correlation with PNF (P < .05) in all transplanted kidneys. Verapamil demonstrated a significant positive correlation with graft failure regardless of type (P < .05), with DGF (P < .05), and with PNF (P < .05) in all kidneys. When considering low-quality kidneys alone (Table 4), verapamil also demonstrated a positive association with graft failure of any type (P < .01) and with DGF (P < .05). Penicillin/ampicillin had a significant negative correlation with graft failure (P < .05) and with DGF (P<0.05) in all kidneys. Prostaglandin E was determined to have a significant negative correlation with PNF (P < .05) in transplanted kidneys overall. However, it also had a significant positive association with PNF (P < .01) in kidneys of lower quality.

Sodium bicarbonate also had a significant negative correlation with PNF (P < .05) in transplanted kidneys overall, yet a significant positive association with PNF (P < .01) in kidneys of lower quality. Prostaglandin E and sodium bicarbonate had the same exact results because they were the only additives used together in only 1 combination of additives and by only 1 OPO. Arginine and glutathione had a significant positive correlation with graft failure regardless of cause (P < .01) and DGF (P < .01) when considering all kidneys and low-quality kidneys alone. This combination also had a significant negative correlation with EGF (P < .05) in all kidneys, yet a positive correlation with PNF (P < .01) in low-quality kidneys. The combination of mannitol with insulin, dexamethasone, and penicillin/ampicillin is positively correlated with graft failure (P < .01) and DGF (P < .01) and is negatively correlated with PNF (P < .05) in all kidneys. The same combination is negatively correlated with DGF (P < .05) in low-quality kidneys. The combination of mannitol and verapamil had a significant negative correlation with PNF (P < .01) in kidneys overall and a significant negative correlation with graft failure regardless of cause (P < .01) and DGF (p<0.01) in kidneys of lower quality.

Figure 3 is a coefficient plot that summarizes the results of logistic regression model 1.5.

Discussion

There is a range of medications added to perfusion formulas, yet there is limited research concerning their efficacy in machine perfusion of donated kidneys.

Among OPOs, we found that mannitol was the most commonly included in perfusion solutions (29.3%). However, it is already a component of the base perfusion solution. Its popularity in machine perfusion likely originates from its ability to increase renal blood flow as well as its ability to prevent acute kidney injury and acute tubular necrosis.17-19 Despite its popularity, few have directly assessed the effects of the osmotic agent in machine perfusion solutions. Polyak and colleagues determined that mannitol as an additive to Belzer II solution for preservation of ECD kidneys exerted no effects on either perfusion pump parameters or EGF.20 However, Kozaki and colleagues concluded that its addition to Belzer gluconate solution in the preservation of DCD kidneys resulted in reduced edema and improved graft function.21 In our analysis, mannitol was associated with lower rates of graft failure regardless of type of failure, as well as lower rates of DGF specifically. This held true both for all kidneys and kidneys of lower quality.

Dexamethasone, a glucocorticoid, was added to perfusion solutions by 9 OPOs (15.5%). Glucocor­ticoids are likely included for their anti-inflammatory and immunosuppressive properties.^22,23 In addition, one of the manufacturers of the base perfusion solution, Waters Medical Systems, lists dexamethasone as a possible additive recommended by the University of Wisconsin (UW). Dexamethasone was originally included in the UW solution because it was believed to limit lysosomal enzyme release during ischemia and act as a membrane stabilizer.²⁴ Methylprednisolone, another glucocorticoid, was included in the perfusion solution of 1 OPO (1.7%). Methylprednisolone is frequently included in immunosuppression regimens of KT recipients.²² Its pretransplant administration is associated with decreased incidence of DGF.²³ Despite their benefits, glucocorticoid use after KT has declined in favor of newer immunosuppressants.²² Our analysis suggests that dexamethasone increases the rate of PNF in all kidneys. We discovered that methylprednisolone did not have any impact on the incidence of DGF, PNF, or EGF.

Insulin was supplemented in the perfusion formulas by 9 OPOs (15.5%). This agent was one of the components of the original UW solution.24 Waters Medical Systems lists insulin as a possible additive, as recommended by UW. Insulin increases sodium retention by the kidney, which may explain its application in machine perfusion.25 Our analysis demonstrated that insulin alone did not have any impact on the incidence of DGF, PNF, or EGF.

Verapamil, a calcium channel blocker, was utilized by 6 OPOs (10.3%). This agent may be beneficial in machine perfusion because of its antihypertensive and vasodilatory effects.^13,26 Polyak and colleagues reported that verapamil in machine perfusion did not have any effect on early graft function.20 However, Nguan and colleagues observed that, at 6 and 12 months, renal function posttransplant was significantly improved in verapamil-perfused kidneys.²⁷ Our analysis revealed that verapamil may increase the incidence DGF and PNF in all kidneys. In kidneys of lower quality, verapamil increased rates of graft failure and DGF.

Penicillin and ampicillin are antibiotics that were added to perfusion solutions by 6 OPOs (10%). Waters Medical Systems lists penicillin as a possible additive, as recommended by the UW. This agent was originally included in the UW solution to limit infection.²⁴ We discovered penicillin and ampicillin decreased the incidence rates of graft failure regardless of type and DGF in all kidneys.

Prostaglandin E was supplemented in the perfusion solution of 1 OPO (1.7%). Polyak and colleagues posited that only the addition of PGE1 increased renal flow, decreased renal resistance, and was associated with improved EGF compared with all other groups.²⁰ Similarly, Guarrera and colleagues evaluated the effects of a modified Belzer solution with the addition of PGE1, nitroglycerin, and polyethylene glycol-superoxide dismutase. They concluded that the combination significantly improved rates of DGF and 6-month graft survival compared with Belzer MPS and Belzer II albumin gluconate solutions.²⁸ In our analysis, PGE decreased the risk of PNF in kidneys overall. However, it was associated with increased PNF in kidneys of lower quality. Further investigations are warranted as PGE was used by only 1 OPO, and thus other OPO-specific factors could have influenced the outcomes.

Sodium bicarbonate was added by 1 OPO (1.7%). One possible explanation for its use in machine perfusion is that the correction of serum bicarbonate levels in patients with chronic kidney disease can slow the rate of decline by decreasing the effects of chronic metabolic acidosis.²⁹ Our analysis showed that sodium bicarbonate may decrease the risk of PNF in kidneys overall, yet it was associated with increased PNF in kidneys of lower quality. However, the fact that sodium bicarbonate was utilized by only 1 OPO means the outcomes may be because of factors related to this particular OPO only.

The combination of arginine and glutathione was utilized by 1 OPO (1.7%). Glutathione, though not arginine, is already a component of the base perfusion solution. Polyak and colleagues investigated the addition of glutathione alone to UW solution and determined that it had no significant effect on early graft outcomes.³⁰ They suggested that, despite the manufacturer’s recommendation to do so, “supplementation of commercially available UW is not necessary.”³⁰ Glutathione is included in the UW solution in order to prevent reactive oxygen species formation.³¹ Arginine is likely added to perfusion solutions to provide substrate for the production of nitric oxide, which in turn decreases renal vascular resistance.³² Others have described exogenous arginine’s ability to decrease renal vascular resistance by attenuating the effect of angiotensin II.³³ Our regression analyses suggested that patients who received kidneys perfused with arginine and glutathione experienced increased rates of graft failure, including DGF, in all transplanted kidneys overall and in lower quality kidneys. Arginine and glutathione were also shown to decrease EGF in all kidneys but were shown to increase PNF only in low-quality kidneys. However, because only 1 OPO utilized the combination, these results may be due to alternative factors related to this specific OPO.

We note that our findings are generally robust as the analysis utilizes the most up-to-date nationwide transplant recipient data and the results are consistent even after controlling for key donor and recipient factors known to affect outcomes. However, given the limited research available concerning the efficacy of different additives to perfusion solutions, further investigations are warranted. Research on the additives discussed above, as well as on many other medications that have potential to improve graft outcomes, is needed. Mesenchymal stem cells, carbon monoxide-releasing molecules, heparin conjugate, thrombalexin, tissue plasminogen activator, ethyl nitrite, and oxygen are all examples of additives that show promise in hypothermic machine perfusion.^34-38 In addition, we recommend the creation of standardized guidelines based on future research on additives so that OPOs have a tool to determine when, and if at all, to include these additional agents. The elimination of regularly added agents revealed to be unnecessary could decrease cost and decrease machine perfusion preparation time. Renal resistance during machine perfusion can also aid in assessment of kidney quality and prediction of graft survival.³⁹ Thus, it is important to consider the potential effects of unnecessary additives on the interpretation of machine perfusion parameters. Furthermore, confirming which additives are beneficial, and consequently increasing their implementation, will lead to improved KT outcomes.

The conclusions drawn from our analysis have limitations. First, our telephone survey consisted of a single question. We asked each OPO which medications it adds to its machine perfusion solution of kidneys. We did not ask how long their current perfusion protocols had been in place at the time of the survey. Thus, we operated under the assumption that the perfusion practices shared with us had been consistent over those years. However, it is possible that OPOs have altered their practices within this time period, meaning our outcomes analysis could potentially be, in part, based on perfusion solutions with or without the medications presumed to be added to them or with or without additional medications as well. It is also possible that the medications reported to be added to perfusion solution by OPOs were only included under certain circumstances. Some OPOs may follow different algorithms for kidneys of different quality or function. The exact frequency at which OPOs add medications is data that we did not have.

Second, although ECD is an outdated term compared with KDRI, it remains highly utilized throughout the United States and around the world. We focused on ECD in discussions of relevant literature, but our analysis focused on KDRI. Third, as with statistical analysis utilizing any large database, limitations of relying on UNOS records included the possibility of missing variables and measurement errors at the level of data entry. Fourth, because several additives were utilized by only a single OPO, it is difficult to state that the outcomes of recipients of kidneys from these OPOs were strictly due to the additives and not due to confounding variables from nonmedication-related perfusion practices of the specific center. In trying to reduce biases across OPOs, as much as possible, pediatric, multiorgan, and retransplant recipients were excluded from the analysis. Additionally, although we sought to find general associations between additives and graft outcomes, because of the nature of the analysis, these relationships should not be viewed as true cause and effect.

Conclusions

Perfusion solution formulas vary by additive use across OPOs, yet there is limited research on the efficacy of the different medication additives in machine perfusion of donated kidneys. We discovered that variations in OPOs’ additive formulas are associated with disparities in rates of DGF, PNF, or EGF. In the future, randomized and controlled outcome trials on each additive and its effectiveness are necessary to create standard guidelines for machine perfusion. More research is recommended to assess OPO perfusion practices and medication additives.

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