Kidney Graft Outcome and Quality (After Transplantation) From Uncontrolled Deceased Donors After Cardiac Arrest


Corresponding author: William Hanf,


The use of uncontrolled deceased donors after cardiac arrest (uDDCA) has been developed in France to compensate for organ shortage. The quality of these kidneys remains unclear. We analyzed kidney graft function and histology from 27 uDDCA and compared them with kidneys from 30 extended criteria donors (ECD) and from 24 simultaneous pancreas kidney (SPK) donors as a control group of optimal deceased donors. Kidneys from ECD and SPK donors were preserved by static cold storage while kidneys from uDDCA were preserved by pulsatile perfusion. The uDDCA graft function at 3 years posttransplantation (estimated with MDRD and measured with inulin clearance) did not differ from that of the ECD group (eGFR 44.1 vs. 37.4 mL/min/1.73 m2, p = 0.13; mGFR 44.6 vs. 36.1 mL/min/1.73 m2, p = 0.07 in the uDDCA and ECD groups, respectively). The histological assessment of 3-month and 1-year protocol biopsies did not show differences for interstitial lesions between the uDDCA and ECD grafts (IF score at M3 was 30 vs. 28% and at M12 36 vs. 33%, p = NS). In conclusion, the results at 3 years with carefully selected and machine-perfused uDDCA kidneys have been comparable to ECD kidneys and encourage continuation of this program and development of similar programs.


acute-antibody mediated rejection


calcineurin inhibitor


delayed graft function


deceased donor after cardiac arrest


extended criteria donor


interstitial fibrosis


mammalian target of rapamycin


machine perfusion


primary nonfunction


simultaneous pancreas and kidney


standard criteria donor


T-cell mediated rejection


The use of marginal donors such as extended criteria donors (ECD) or deceased donors after cardiac arrest (DDCA) has been developed in renal transplantation over the last two decades to counteract organ shortage. DDCA strategy for organ procurement, which was initially developed in the Netherlands (1,2), might increase the number of donors by approximately 20–30% (3,4). DDCA donors are individuals that failed to reach the criteria for brain stem death. They may be classified according to the Maastricht criteria: (i) uncontrolled DDCA (uDDCA) donors who are deceased on arrival at the hospital (category 1) or die due to failed resuscitation (category 2), (ii) controlled DDCA (cDDCA) where the decision to withdraw organ-perfusion support was previously planned (category 3), or those with cardiac arrest while brain dead (category 4). These two classes of patients (uncontrolled vs. controlled uDDCA) have a different prognosis with best results in the cDDCA group (5). Most of the centers that have undertaken DDCA programs use category 3 donors (cDDCA).

The use of DDCA was initially limited by the significant rate of primary nonfunction (PNF) and delayed graft function (DGF) in comparison with heart beating donors (6). The use of machine perfusion appeared to reduce the PNF rate but without amelioration of the DGF rate (7,8). Graft survival, early and long-term kidney outcome from cDDCA seemed to be similar to those with matched heart beating donors, except for a higher rate of DGF that did not influence the long-term kidney graft function (4,6,9–14).

Very few studies have assessed the outcome and the quality of kidneys from uDDCA. In the short term, studies have shown that the incidence of DGF rate is higher than that observed in heart beating donors with a similar PNF rate (15). However, little is known about the evolution of kidney graft function that might be impaired by the development of chronic histological lesion (interstitial fibrosis or vascular damage) as a result of strong ischemia-reperfusion injury.

In order to evaluate the quality of kidney grafts from uDDCA we have prospectively assessed estimated (simplified MDRD) and measured (inulin clearance) graft filtration rate and performed morphometric quantification of interstitial fibrosis (IF), a new procedure recently developed to improve IF quantification on systematic needle core biopsy (16,17). In addition, kidney grafts from uDDCA were compared both with kidney grafts from extended criteria donors (ECD) and with kidney grafts from optimal deceased donors, in simultaneous pancreas and kidney transplanted patients.

Patients and methods

Patient characteristics and organ preservation

Data were prospectively obtained from 27 nonsensitized patients who received a graft from uDDCA, between September 2006 and September 2009. The data were analyzed until September 2010. All transplantation procedures were conducted in a single center at the Edouard Herriot Hospital, Lyon, France. uDDAC inclusion criteria were based on the French program, as follows: Maastricht categories 1 and 2 with cardiac arrest without cardiopulmonary resuscitation (no flow period) less than 30 min, donor age less than 55 or more than 18 years old and no history of chronic kidney disease or hypertension or history of diabetes, sepsis, neoplasm, drug addiction or traumatic cardiac arrest. Maastricht category 3 donors were excluded from the DDCA program as required by French law. Recipients criteria were age less than 60 years old, first renal transplantation and no previous HLA sensitization, ABO compatibility.

These 27 patients were compared with two groups of patients that were transplanted at the same period in the same center. The first group included nonsensitized patients that received kidneys from brain-dead extended criteria donors (ECD group, n = 30). Extended donors were defined according to the united network for organ sharing criteria (18) and included all donors aged 60 years and older and those aged 50–59 years with at least two of the other three conditions (cerebrovascular cause of death, renal insufficiency with serum creatinine less than or equal to 1.5 mg/dL, and hypertension). Ten ECD patients were excluded because of the presence of anti-HLA antibodies. Five ECD were excluded because they received anti-IL2R as induction therapy.

The second control group was simultaneous nonsensitized kidney pancreas transplanted patients (SPK group, n = 24) that received kidneys from optimal donors. We included all SPK patients during the same period.

Kidneys from ECD and SPK donors were preserved by static cold storage before the transplantation (IGL-1®, Institut Georges Lopez, Saint-Didier-au-Mont-d'Or, France).

The uDDAC organ procurement procedure was as follows: after death diagnosis (5 min without a heartbeat), an intraaortic double-balloon catheter (Gillot catheter) and a venous vent were surgically inserted via an incision in the right side of the groin, with injection of 25 000 UI heparin bolus. The arterial inlet was perfused with a heparinized (5000 UI/L) preservation solution (IGL-1®, Institut Georges Lopez, Saint-Didier-au-Mont-d'Or, France) at a rate of 20 L within 180 min. After kidney retrieval, preservation protocol consisted in hypothermic (1–4°C) pulsatile perfusion (RM3®, Waters Medical Systems) and the organ preservation solution was the UW solution (Belzer MPS®). Organ viability was assessed by measuring the ex vivo intrarenal vascular resistance. Kidneys with intrarenal vascular resistance above 0.35 mmHg/mL/min after 6 hours of perfusion were discarded.

In the uDDCA group, the mean total ischemic time was similar to the one in the ECD group (1041.2+/−266.8 vs. 1095+/−335.8 min), respectively. It was inferior to the mean total ischemic time in the SPK group (762+/−127.6 min, p < 0.0001). The warm ischemic time (defined by the time between cardiac arrest and the kidney perfusion) in the uDDCA group was 106.5+/−14.8 min.

Written consent was obtained from all study participants.


In the three groups, patients received antithymoglobulin (ATG®, Genzyme) for induction therapy (1.25 mg/kg/day for 10 days). Maintenance immunosuppression included (i) calcineurin inhibitors which were introduced later in the uDDCA group (days 6–8) than in the two other groups (day 5 for the ECD group and day 0 for the SPK group)—cyclosporine (Néoral®, Novartis Pharma AG) or tacrolimus (Prograf®, Astellas Pharma) doses were adjusted to get a trough level between 100–150 ng/mL and 8–12 ng/mL, respectively, during the first year, (ii) mycophenolate mofetil (Cellcept®, Roche Pharmaceuticals) 2 g/day with the dose adapted to patient tolerance and (iii) steroid quickly tapered to 5 mg/day within the first 2 months after transplantation.

SPK patients were treated by tacrolimus as suggested by the results of the EUROSPK study (19). For the ECD and the uDDCA recipients, cyclosporine was used for patients with BMI>25 kg/m2 and/or past medical history of diabetes, and tacrolimus for the others.

Graft function

Graft function was assessed by estimated GFR (eGFR) with simplified modification of diet renal disease (MDRD) (20) formula at 1, 3, 6, 12, 24 and 36 months (M1, M3, M6, M12, M24 and M36, respectively) and measured GFR (mGFR) with inulin clearance at M12 and M36 as previously described (20,21). The local reference value for inulin clearance was (mean +/− SD) 117 +/− 16 mL/min per 1.73 m2 and was determined in 99 healthy renal donors (males 47%, age 37 +/− 10 years).

Proteinuria was measured in daily urine recovery at M1, M3, M6, M12, M24 and M36.

Histological assessment

Patients underwent systematic 16-G needle-core biopsies at M3 and M12 after transplantation, performed under ultrasonographic control using an automated biopsy gun. Paraffin sections were stained with Masson's trichrome and periodic acid–Schiff. Chronic and acute lesions were evaluated by a pathologist (BMcG) according to the Banff 2007 classification (22).

All the acute rejection episodes were proven by biopsies. Subsets of acute rejection episodes were defined as follows: (i) clinical acute rejection with serum creatinine increase more than 20% over baseline, (ii) subclinical rejection without serum creatinine increase, diagnosed in systematic needle biopsies with histological lesions of acute rejection.

The borderline changes were also analyzed.

Quantitative image analysis of fibrosis

Masson-stained interstitial fibrosis (IF) was automatically quantified by computerized color image analysis as described (16,23). The method is based on clustering techniques and particularly on color image quantization, followed by combining color, spatial and shape feature segmentation. Briefly, the developed software automatically extracts the green areas characteristic of IF in Masson trichrome, followed by removal of nonspecific IF staining (capsula, glomeruli, normal basement membrane) and computes an index. It also automatically counts the number of glomeruli. This new quantification method devoted to the quantification of IF in transplant kidneys, has been shown to quantify fibrosis in a robust and highly reproducible manner (23).

Statistical analysis

Qualitative variables were described as a percentage and 95% confidence intervals.

Quantitative variables are described as mean +/− standard deviation.

Qualitative variables were compared using a chi-square test whereas quantitative variables were compared using a Student t-test or a Wilcoxon–Mann–Whitney test after checking whether or not the hypothesis of normal distribution was verified (Kolmagorov–Smirnov test).

eGFR evolution over the follow-up period was described using a linear mixed model for repeated measures.

Linear mixed models were used to model the change in outcome across time. In each model, there were fixed effects for time, the baseline covariates of interest and to account for the correlated observations within each subject, a random effect was included.

Pairwise interactions between the time and baseline covariates were tested and included in the model if significant. Of interest is a significant interaction between a particular baseline covariate and a year, which would suggest that the covariate affects the trajectory of the outcome across time.

First, a univariate analysis was conducted by fitting a linear mixed model with time, the relevant baseline covariate in each group and their respective interaction, if significant.

Variables were selected for multivariate regression when significant or marginally significant (p < 0.1) in univariate analysis.

Survival curves were obtained with a Kaplan–Meier model and compared using the log-rank test.

Statistical significance was first established at p < 0.05. All statistics were performed using SAS software version 9.1.3.


Study population

A total of 81 patients were analyzed after single kidney transplantation (uDDCA n = 27 and ECD n = 30) or simultaneous kidney–pancreas transplantation (SPK n = 24).

All the patients in the uDDCA and SPK groups were receiving their first kidney transplantation while 10% of patients from ECD group were receiving a second graft.

Recipients' and donors' characteristics are summarized in Table 1. As expected, donor and recipient mean ages were different between the three groups. In the uDDCA group, donors were only male (100%) as compared with the ECD (53.8%) and SPK (66.7%) groups. Hemorrhagic stroke was the major cause of death in the SPK donor group (83.3%) while in the ECD group, 36.7% of deaths were due to ischemic stroke and cardiorespiratory causes (one aortic dissection and one acute coronary syndrome).

Table 1.  Characteristics of uncontrolled deceased donors after cardiac arrest (uDDCA), extended criteria donors (ECD) and simultaneous pancreas kidney donors (SPK) renal transplant
 n = 27n = 30n = 24uDDCA vs. ECDuDDCA vs. SPK
  1. NA = not analyzed.

  2. Test used: 1Fisher exact test, 2nonparametric Wilcoxon test.

Donor related     
 Gender (%M/F)100/053.8/46.266.7/33.3<0.0001#<0.0001#
 Cause of death (%)     
  Cardiac arrest10000NANA
  Hemorrhagic stroke060.083.3NANA
  Ischemic stroke030.14.2NANA
  Cardiorespiratory causes06.60NANA
Graft related     
 n (first/retransplanted)27/027/324/0NANA
 HLA mismatches4.5+/−1.04.1+/−0.94.7+/−1.20.21*0.24*
 Total ischemic time (minutes)1041.2 +/−266.81095.4 +/−335.8762.1 +/−127.60.66* 0.005*
Recipient related     
 Age45.6+/−11.362.9+/−5.938.7+/−7.6 <0.0001*0.03*
 Gender (%M/F)70.3/29.750/5045.8/54.20.18#0.02#
 HLA antibodies (%)000NANA

Mean ischemic time and mean number of HLA mismatches did not differ in uDDCA and ECD groups. Moreover, the immunosuppressive treatment and the trough levels of calcineurin inhibitors were similar in the three groups (Figure 1).

Figure 1.

Evolution of CNI trough level in uDDCA, ECD and SPK renal transplant recipients. (A) Cyclosporine trough level. (B) Tacrolimus trough level.

Perfusion parameters used in the uDDCA group

Perfusion machine monitoring was performed in all the patients in the uDDCA group. Time on the perfusion machine varied between 270 and 1200 min.

Mean renal blood flow increased from 41.8+/−25.9 to 82.7+/−16.6 mL/min/100 g. Mean intrarenal vascular resistance decreased from 0.85+/−0.6 to 0.3+/−0.07 mmHg/mL/min/100 g as illustrated in Figure 2. Temperature and mean renal pressure remained stable (data not shown).

Figure 2.

Evolution of mean renal blood flow (dark bar) and of mean intrarenal resistance (gray bar) during perfusion machine process.

Patient and kidney graft survival

Patients survival rate at M12 and M36 was 100% in each group. The kidney graft survival rate (defined by the dialysis requirement) was 100, 90 and 100% at M12 and 100, 82 and 94% at M36 in the uDDCA, ECD and SPK groups, respectively (Figure 3). The uDDCA graft survival rate was significantly higher than the ECD graft survival rate (p = 0.03).

Figure 3.

Overall kidney graft survival of uncontrolled deceased donors after cardiac arrest, extended criteria donors and kidney from simultaneous kidney and pancreas transplantation.

In the ECD group, 6 grafts were lost during the 3-year follow-up for the following reasons: acute humoral rejection (n = 1), acute cellular rejection (n = 1), surgical complications before M1 (n = 2), recurrent multiresistant bacteria pyelonephritis (n = 1), rejection due to immunosuppression withdrawal related to posttransplantation lymphoma and prostate adenocarcinoma (n = 1).

In the SPK group, the cause of graft loss at M26 after transplantation was due to the consequence of a severe rejection episode (TCMR IIB) that occurred at M6.

Early graft outcome

As shown in Table 2, there was no primary nonfunction (PNF) in each group. The incidence of delayed graft function (DGF) was significantly higher in the uDDCA group than in the ECD group and the SPK group (p < 0.001 for both comparisons). More dialysis sessions were performed in the uDDCA group than in the ECD group (p < 0.001). Renal function recovery (defined by the onset of serum creatinine decrease) was delayed in the uDDCA group as opposed to the ECD group (p < 0.0001) while graft function recovery was immediate in the SPK group.

Table 2.  Early graft outcome in uDDCA, ECD and SPK groups
 n = 27n = 30n = 24uDDCA vs. ECDuDDCA vs. SPK
  1. Test used: 1Fisher exact test.

  2. PNF, primary nonfunction = absence of renal function recovery after kidney transplantation; DGF, delayed graft function = need for at least one dialysis session during the first week after transplantation, except for hyperkalaemia posttransplantation; HD, hemodialysis. Renal function recovery is defined when two decreases of serum creatinine are observed.

PNF (%)000NANA
DGF (%)81.527.60<0.00011NA
Mean HD session (n)4.7+/−3.90.7+/−1.40<0.00011NA
Mean time of HD (days)15.6+/−132.8+/−5.90<0.00011NA
Mean time of renal function recovery (days)17.8+/−9.25.0+/−5.20<0.00011NA


The incidence of clinical rejection did not differ between the ECD and the uDDCA groups (23.3% vs. 18.5%, p = 0.62); it tended to be inferior in the SPK group (8.3%, p = 0.24).

The incidence of subclinical rejection was 7.4%, 7.5% and 0% in the uDDCA, ECD and SPK groups respectively (p = 0.73 for uDDCA vs. ECD, Table 3). Clinical and subclinical rejections (but not borderline changes) were treated by boluses of steroids.

Table 3.  Comparison of the number and the time of occurrence of clinical, subclinical and borderline changes in uDDAC, ECD and SPK groups
  1. 1All the borderline changes were subclinical.

  2. Test used: 2Fisher exact test, 3nonparametric Wilcoxon test.

Clinical rejection     
 - n (%)5 (18.5)7 (23.3)2 (8.3)0.6230.243
 - Mean time of occurrence (months)7.5 (5.7)4.9 (4.8)5.5 (2.1)0.7420.672
 - TCMR351  
   II B     
 - AAMR100  
Subclinical rejection     
 - Total, n (%)2 (7.4)3 (10.0)0 (0)0.7130.233
   M3, n (%)1 (3.3)1 (3.4)/(/)  
   M12, n (%)1 (3.4)2 (6.6)/(/)  
Borderline changes1     
 - Total, n (%)12 (44.4)8 (26.6)4 (16.6)0.1530.013
   M3, n (%)8 (29.6)2 (6.6)1 (4.2)  
   M12, n (%)4 (14.8)6 (20.0)3 (12.4)  

Evolution of graft function

As illustrated in Figure 4A, mGFR was not statistically different at M12 and at M36 among the uDDCA and the ECD groups (44.3 vs. 40.2 mL/min/1.73 m2, p = 0.31 and 44.6 vs. 36.1 mL/min/1.73 m2, p = 0.07, respectively). In the SPK group, mGFR was higher than in the two other groups (68.3 mL/min/1.73 m2 at M12 and 63.3 mL/min/1.73 m2 at M36, p < 0.001).

Figure 4.

Evolution of graft function. (A) Comparative renal graft function (mean+/− SD mGFR based on inulin clearance measurement) in uncontrolled deceased donors after cardiac arrest (uDDCA), extended criteria donors (ECD) and simultaneous pancreas kidney donors (SPK) renal transplants at M12 and M36. (B) Comparative monthly renal graft function (mean+/− SD eGFR based on the simplified MDRD formula) in uDDCA, ECD and SPK renal transplants.

Evolution of eGFR in the three groups is shown in Figure 4B. In the uDDCA group, eGFR was inferior to that in the ECD group at M1 (23.4 vs. 40.2 mL/min/1.73 m2, respectively, p < 0.01) but did not differ at M3, M6, M12, M24 and M36 in the two groups. After M3, there was no difference of eGFR evolution between these two groups. In the SPK group, eGFR was always significantly higher than in the other two groups at each follow-up visit (p < 0.001).

Age of donor, recipient age, clinical and subclinical rejection, cyclosporine and tacrolimus trough levels, perfusion machine duration time and resistance index (in the uDDCA group only) were tested in the uDDCA and ECD groups as covariates that influence eGFR evolution. Univariate and multivariate analyses were performed and results are shown in Table 4 and 5. In the univariate analysis, donor age and clinical acute rejection were significantly associated with renal function (p < 0.1) and were included as variables in the multivariate regression. In the multivariate analysis clinical rejection was the only significant predictive parameter of evolution for eGFR in the uDDCA group. We also performed univariate and multivariate analyses that included donor age among the ECD and uDDCA groups. Donor age had a significant impact on renal function in the univariate analysis (p = 0.03) but not in the multivariate analysis (p = 0.58) (data not shown).

Table 4.  Mixed model univariate regression analysis for MDRD clearance among uDDCA
 CoefficientStandard errorp-Value
  1. Statistical significance is established at p < 0.1.

Variables in the uDDCA group   
 Donor age0.310.170.07
 Recipient age−
 Clinical acute rejection (Y vs. N)11.104.450.015
 Subclinical rejection (Y vs. N)−0.767.460.92
 Tacrolimus level (ng/mL)−0.460.400.25
 Cyclosporine level (ng/mL)
 Perfusion machine duration (min)−0.0020.0080.73
 Resistance index3.374.410.45
Variables in the ECD group   
 Donor age0.120.410.77
 Recipient age−0.400.450.39
 Clinical acute rejection (Y vs. N)8.976.500.17
 Subclinical rejection (Y vs. N)
 Tacrolimus level (ng/mL)−0.530.380.17
 Cyclosporine level (ng/mL)−
Table 5.  Mixed model multivariate regression analysis for MDRD clearance among uDDCA
VariablesCoefficientStandard errorp-Value
Donor age0.050330.17540.7749
Clinical acute rejection (Y vs. N)10.90533.63030.0035

Proteinuria ranged between 0.1 and 0.3 g/day in the three groups and tended to decrease during the follow-up time. It did not differ at any time point in the three groups (data not shown).

Histological analysis of 3- and 12-month systematic biopsies

Twenty-five percent of systematic biopsies were not performed because of patient refusal, anticoagulant treatment and posttransplantation arterio-venous fistula. In addition, 10% of the biopsies performed were not sufficient for histological assessment and were discarded from the Banff criteria analysis. The total number of systematic biopsies not performed or not sufficient for histological assessment was 26/81 at M3 and 30/81 at M12. Systematic biopsies performed at M3 and M12 were available for a similar proportion in the three patient groups.

The incidence of borderline changes observed on these systematic biopsies was 44.4%, 26.6% and 16.6% in the uDDCA, ECD and SPK groups, respectively, and appeared earlier in the uDDCA group (Table 3). All the borderline changes were subclinical.

We have focused our analysis on vascular lesions (cv) according to the Banff 2007 classification and interstitial fibrosis measured by color image analysis.

The mean cv score at M3 and at M12 was not significantly different between the uDDCA and ECD groups (Table 6). Compared to the SPK group, the mean cv score in the uDDCA group was significantly higher at M3 (p = 0.04) but not at M12 (p = 0.25).

Table 6.  Semiquantitative analysis of chronic vascular lesions in 3- and 12-month systematic biopsies in uDDCA, ECD and SPK groups
 n = 17n = 16n = 19  
Meann(%)n(%)n(%)p uDDCA vs. ECDp SPK vs. uDDCA
  1. Test used: 1Chi-square test.

cv M3        
cv M12        

As illustrated in Figure 5, the IF score was neither different at M3 (30% vs. 28%) nor at M12 (36% vs. 33%) in the ECD and the uDDCA groups, respectively. The IF score at M3 and at M12 (15% and 13%, respectively) was significantly lower in the SPK group than in the uDDCA and ECD groups (p < 0.001).

Figure 5.

Comparison of quantification of interstitial fibrosis (IF) expressed as a percentage in uncontrolled deceased donors after cardiac arrest, extended criteria donors and simultaneous pancreas kidney donor renal transplants.


The purpose of this study was to analyze the outcome of renal transplantation from uDDCA and to define whether this category of donors should be considered as ECD or not. The consequences are the choice of appropriate recipients in the context of organ shortage. We also used a control group from SPK donors that provides the best kidneys in the deceased donor setting. The French DDAC program that started in 2006 and includes only uDDAC (Maastricht categories 1 and 2) gave us the opportunity to prospectively assess the quality of uDDAC kidneys. The graft outcome, renal function and histology of a cohort of patients that received a renal graft from uDDAC, ECD or optimal SPK donors were compared. In the three groups, recipients were nonsensitized, had similar HLA mismatches and received comparable immunosuppression, avoiding bias due to the impact of immune response on allograft outcome. In addition, trough levels of calcineurin inhibitors were similar in the three groups and should not have interfered with the assessment of graft function and fibrosis. S/CD were not included as a control group because they constitute a more heterogeneous group with many biases.

Graft survival was higher at M36 in the uDDAC group compared to the ECD group and there was no PNF in the uDDAC group, confirming previously published data (6,15) that the use of uDDAC is a safe procedure at the intermediate-term follow-up and that these grafts should not be discarded in an organ shortage period. The absence of PNF is probably due to the use of machine perfusion (MP) in all uDDAC. This also confirms that MP are of great interest for selecting kidneys electable for transplantation in uDDAC. In our study, not all kidneys from the uDDCA donors were transplanted: 30% of retrieved kidneys were discarded because of failure to meet the machine perfusion criteria. The resistance index cutoff criteria in the RM3 MP that was associated with good results was 0.35 mmHg/mL/min.

We have focused our study on the quality of the grafts, assessed by renal function and histology on protocol biopsies performed at M3 and M12 posttransplantation. The renal function of uDDAC remains not well defined (2,15,23) because the majority of published studies on DDCA outcome have included mostly Maastricht 3 category donors. Moreover, to our knowledge, systematic histological analysis of uDDAC grafts after transplantation has not yet been reported on.

The uDDCA kidney graft function was not statistically different from the ECD graft function at every follow-up visit whereas it was significantly inferior to that of SPK group at all time points. In the uDDCA group, renal function improved until M3 to M6 after transplantation, probably due to the slow tubular function recovery consequently to the severe tubular necrosis induced by the warm ischemia time. Thereafter, renal function remained stable between M24 and M36 posttransplantation. We acknowledge that one limit on the study is the weak number of patients and that more definitive results will be obtained from longer follow-up.

Systematic analysis of chronic histological lesions in DDCA recipients has already been reported in a study (24) where the quantification of fibrosis by Sirius red staining was not different between DDCA and heart beating donors at M6 and M12 after transplantation. However, in this study, the CNI trough level was inferior in the DDCA group. In our study for the first time in a cohort of uDDCA, chronic histological lesions were evaluated on the basis of protocol needle core biopsies. At M3, we observed a lower cv score in the uDDCA group compared to the ECD group; this might be explained by a lower mean donor age in the uDDCA group. Quantitative analysis of interstitial fibrosis demonstrated similar IF scores at M3 and M12 that correlated with a similar renal function in the two groups, as already published in the CONCEPT study (17).

Therefore, despite a younger donor age in the uDDCA group, renal function and interstitial fibrosis were similar to that of the older group of ECD. This is probably due to the fact that in uDDCA, ischemia-reperfusion injury related to warm ischemia induced severe tubular necrosis, leading to the development of interstitial fibrosis within 3 months after transplantation. These permanent and definitive lesions of fibrosis could contribute to the poorer kidney graft function evolution observed in uDDCA and ECD recipients.

Interestingly, although the incidence of DGF was higher and was associated with slower renal function recovery in uDDCA than in ECD groups, renal function and interstitial fibrosis were similar in the two groups at M36, suggesting that DGF did not have the same impact in uDDAC as in ECD. The fact that the high rate of delayed graft function associated with renal transplantation from uDDCA does not lead to poor graft survival when compared with heart beating donors with delayed graft function has already been reported (10,25). This suggests that the brainstorm cytokine crisis that occurs after brain death (26) might be a crucial factor in the DGF process, in addition to the ischemia reperfusion injury which should be greater in uDDCA exposed to both warm ischemia and cold ischemia. Another important point that could explain our results might be the selection of uDDCA donors without past medical history and the use of a perfusion machine in the uDDCA groups.

Despite the fact that the incidence of acute rejection did not differ in the three groups, we also observed a higher incidence of borderline changes with more infiltrates in the uDDCA group; this might be related to the activation of the innate immune system, triggered by ischemia-reperfusion injury in the context of warm ischemia (27,28).

The incidence of acute rejection that was quite high in low immunological risk patients retrospectively confirms the choice of an induction therapy with depleting antibodies in the uDDCA group. Finally, the nonspecific inflammatory pictures on biopsies suggest maintaining steroids at least during the first 3 months posttransplantation.

This study also confirms the superiority of the SPK transplants which might be considered as the “gold standard” optimal kidneys from deceased donors: kidney graft function and fibrosis quantification score were always better than that in the other two groups. Our results were similar to those described in the study performed by Nankivel et al. in a large cohort of SPK transplants (29).

The interstitial fibrosis and renal function that were observed in our cohort of uDDCA suggest that several strategies should be developed to improve the outcome: (i) the replacement of the Gillot catheter by normothermic regional circulation (30), which in French law allows for an increase in the resuscitation time and also for removal of kidneys and other organs, such as the liver; (ii) the realization of studies about the RM3 Waters medical device to define the optimal perfusion cutoff parameters (for example, the perfusion time and the resistance index) and to increase the number of kidneys electable for transplantation; (iii) the development of a new preservation solution (31,32) to limit or avoid ischemia-reperfusion injury and possibly the rejection that we know is involved in the IF development and therefore the degradation of the graft function; and finally (iv) the use of nonnephrotoxic regimens.

In summary, despite a high incidence of DGF rate in uDDCA, our results are encouraging: the PNF rate is much lower than that reported in the literature (33) graft survival is excellent at 3 years, and the renal function remains stable over time. It is important to note that this favorable outcome might be the consequence of strict selection for donors and recipients. Therefore inclusion and exclusion criteria for use of uDDCA could be the following: (i) donor age less than 55 years, no donor history of chronic kidney disease or hypertension or diabetes; (ii) the use of machine perfusion and elimination of kidneys when arterial resistance is higher than 0.35; (iii) selection of nonsensitized recipients to avoid the deleterious combination of ischemia reperfusion lesion and allogeneic rejection; and finally (iv) the use of thymoglobulin induction.


The results at 3 years with carefully selected and machine-perfused uDDCA kidneys have been comparable to ECD kidneys and encourage continuation of this program and development of similar programs.


The authors wish to thank Martha Melter for her careful English proof reading.


The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.