American Journal of Transplantation 2015; 15: 1632–1643 Wiley Periodicals Inc.
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Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons doi: 10.1111/ajt.13162
Early Graft Loss After Kidney Transplantation: Risk Factors and Consequences M. O. Hamed1, Y. Chen2, L. Pasea3, C. J. Watson1, N. Torpey4, J. A. Bradley1, G. Pettigrew1 and K. Saeb-Parsy1,* 1
Department of Surgery, University of Cambridge, and NIHR Cambridge Biomedical Research Centre, Cambridge, UK 2 Department of Pure Mathematics and Mathematical Statistics, Cambridge, UK 3 Centre for Applied Medical Statistics, University of Cambridge, Cambridge, UK 4 Department of Renal Medicine, Addenbrooke’s Hospital, Cambridge, UK Corresponding author: Kourosh Saeb-Parsy, [email protected]
Early graft loss (EGL) after kidney transplantation is a catastrophic outcome that is assumed to be more likely after the use of kidneys from suboptimal donors. We therefore examined its incidence, risk factors and consequences in our center in relation to different donor types. Of 801 recipients who received a kidney-only transplant from deceased donors, 50 (6.2%) suffered EGL within 30 days of transplantation. Significant risks factors for EGL were donation after circulatory death (DCD) (odds ratio [OR] 2.88; p ¼ 0.006), expanded criteria donor (ECD) transplantation (OR 4.22; p ¼ 0.010), donor age (OR 1.03; p ¼ 0.044) and recipient past history of thrombosis (OR 4.91; p ¼ 0.001). Recipients with EGL had 12.28 times increased risk of death within the first year, but long-term survival was worse for patients remaining on the waiting list. In comparison with patients on the waiting list but not transplanted, and with all patients on the waiting list, the risk of death after EGL decreased to baseline 4 and 23 months after transplantation, respectively. Our findings suggest that DCD and ECD transplantation are significant risk factors for EGL, which is a major risk factor for recipient death. However, long-term mortality is even greater for those remaining on the waiting list.
Abbreviations: ATG, antithymocyte globulin; ATN, acute tubular necrosis; BMI, body mass index; CIT, cold ischaemia time; DBD, donation after brain death; DCD, donation after circulatory death; DGF, delayed graft function; ECD, expanded criteria donor; EGL, early graft loss; ESRD, end-stage renal disease; HLA, human 1632
leukocyte antigen; PNF, primary non-function; SCD, standard criteria donor Received 26 September 2014, revised 12 December 2014 and accepted for publication 14 December 2014
Introduction For selected patients with end-stage renal disease (ESRD), kidney transplantation is associated with improved quality of life, longer patient survival and reduced costs compared to remaining on dialysis (1,2). Kidney transplant outcomes have improved incrementally over the last two decades (3), attributed to better surgical and medical care, improved immunosuppressive regimens and Human Leucocyte Antigen (HLA) testing and matching of recipients, HLAantibody screening, and better prophylaxis and management of infections and other complications (4). However, long waiting lists and the shortage of optimal donors have necessitated the use of kidneys from increasingly more sub-optimal donors (5). The use of kidneys from suboptimal donors has been shown to be associated with worse longterm graft outcomes in some studies (6,7) and there is a perception that the use of suboptimal kidneys may also increase the risk of early graft loss (EGL). However, the assertion that the use of suboptimal kidneys increases the risk of EGL after kidney transplantation has not been definitively examined. EGL, defined as graft loss occurring within 30 days after kidney transplantation, is relatively uncommon and occurs in approximately 5% of kidney transplants (3). However, it is a physically and emotionally devastating outcome for both the recipient and the transplant team: The recipients are exposed to the risks of medical and surgical postoperative complications, compounded by a period of immunosuppression and with remaining on, or returning rapidly to, dialysis. EGL may also lead to sensitisation to HLA, reducing the likelihood and/or success of re-transplantation (8,9). Although hyperacute or accelerated acute rejections are occasionally responsible for EGL, the most common causes are nonimmunological; vascular thrombosis accounts for up to one third of early kidney transplant loss (10,11). Primary non-function (PNF) is also an important and potentially avoidable cause of EGL that may reflect the quality of the donor organ.
Early Kidney Graft Loss
Clinicians and patients offered a kidney from a suboptimal donor, therefore, face a difficult and poorly understood choice: should the patient be transplanted with that kidney and face an increased risk of EGL, or remain on the waiting list for a better offer while continuing to endure the risks associated with dialysis? Informed judgment about this difficult choice requires a detailed analysis of the incidence, risk factors and consequences of EGL. It is important to perform this analysis in the context of the increasing use of kidneys from donation after circulatory death (DCD) and expanded criteria (ECD) donors compared to donation after brain death (DBD) donors and standard criteria (SCD) donors. In this study, we report our single center experience of EGL following renal transplantation and examine the associated risk factors and consequences. Because a high proportion of renal transplants undertaken at our centre are from DCD and ECD donors, we were able to systematically examine the risk factors for EGL amongst the different deceased donor types.
Materials and Methods Recipients of deceased donor kidney-only transplants between January 2002 and April 2012 in our center who suffered graft loss within 30 days after transplantation were identified from a prospectively maintained database. Patient demographics and medical history were obtained by review of the database, pre- and post-transplant communication letters (including with referral centers), discharge summaries relating to hospital admissions, and by review of case notes where necessary. Waiting list patients included active and suspended patients, as well as highly sensitized patients, in our center only. Factors associated with EGL were determined by univariate and multivariate analysis in comparison to the cohort whose grafts survived beyond 30 days. EGL was defined as graft nephrectomy or loss of kidney transplant function resulting in the recipient becoming dialysis dependent within 30 days of kidney transplantation (and never achieving graft function thereafter) or death with a non-functioning graft within 30 days. Death with a functioning graft (i.e. no requirement for dialysis) was not included as EGL. Recipients of double kidney transplants who lost only one graft and subsequently did not require dialysis were not included in the EGL group. Primary non-function (PNF), defined as permanent lack of graft function from the time of transplantation, was diagnosed when a kidney graft was well perfused (confirmed by ultrasound examination) but never functioned, necessitating dialysis after kidney transplantation; it was confirmed by at least one transplant biopsy to exclude other causes of non-function. The diagnosis of acute vascular occlusion was suggested by Duplex ultrasound examination and confirmed intra-operatively and/or by histological analysis of the graft following transplant nephrectomy. Graft loss secondary to acute rejection was defined as acute irreversible deterioration of graft function not responding to immunosuppressive treatment requiring renal replacement therapy within 30 days after transplant and confirmed by biopsy. Further details on DCD and ECD donors, the transplant operation and immunosuppressive regimens are included in the supplementary materials. Mann–Whitney rank sum tests and Pearson’s Chi-squared tests were used to compare continuous and categorical variables respectively between the
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two groups (graft survival 30 days and >30 days). Multivariate logistic regression models were used to calculate adjusted estimate effects of the variables on risk of EGL, and to assess the impact of EGL on the short-term patient survival (defined as death within the first year after kidney transplantation). A Cox proportional hazards model was used to estimate an adjusted hazard ratio for long-term patient survival (defined as survival for at least 1 year after kidney transplantation). Kaplan–Meier plots and Greenwood’s formula were used to analyze graft and patient survival between groups until all-cause mortality or the end of follow-up (1st April 2013). The one-year risk of death (defined as the probability of death within the next 365 days) was calculated by Kaplan–Meier plot and the relative risk was taken as the ratio of the risk of death among different groups. Missing observations were assumed to be missing at random and partial deletion was used to handle missing observations. All tests were performed at the 5% significance level. Except for univariate analysis, data were analyzed twice with deceased donors categorized as DBD or DCD (donor type classification I) or as SCD or ECD (donor-type classification II). This was because ECD and DCD donor types were highly correlated and not independent: of the 288 ECD donors, 174 (60.4%) where also DCD donors. Including both DCD and ECD donor types in the same analysis, therefore, would have required a much higher number of observations to reach definitive conclusions. Moreover, it was important to be able to determine the impact of both DCD and ECD donor types separately, as one or the other classification is often used by transplant centers and reported in the literature.
Results Incidence of EGL During the 10-year study period, 801 adult patients received a deceased donor kidney-only transplant, of which 435 (54.3%) were from DCD donors and 366 (45.7%) were from DBD donors. Of the 801 transplants, 288 (36.0%) were performed using ECD grafts and 465 (58.0%) using SCD grafts and 48 donors (6.0%) could not be classified as ECD or SCD due to missing data. EGL occurred in 50 (6.2%) recipients. Causes of EGL are summarised in Table 1 and included PNF (20; 2.5%), arterial or venous thrombosis (18; 2.2%), haemorrhage (6; 0.7%) and acute rejection (3; 0.4%). Further details on causes of EGL are provided in the supplementary materials. In comparison, only 2 (of 288; 0.7%) recipients of living donor kidneys suffered EGL during the study period. The incidence of EGL was higher among recipients of DCD grafts compared to DBD grafts (8.3% vs. 3.8%; p ¼ 0.018) . The increased EGL among DCD transplants was due to a numerically higher incidence of PNF (3.2% vs. 1.6%; p ¼ 0.180) and acute vascular occlusions (3.0% vs. 1.4%; p ¼ 0.155), although these differences did not reach statistical significance (Table 1a). The incidence of EGL was also higher among recipients of ECD grafts compared to SCD grafts (10.1% vs. 4.1%; p ¼ 0.003). The increased EGL among ECD transplants was due to a higher number of 1633
Hamed et al Table 1: Causes of EGL after kidney transplantation. a) The overall incidence of EGL was higher among DCD recipients compared to DBD recipients (p < 0.001), consisting of a higher number of grafts lost due to PNF (3.2% vs. 1.6%; p ¼ 0.18) and acute vascular occlusions (3.0% vs. 1.4%; p ¼ 0.16). b) The overall incidence of EGL was higher among ECD recipients compared to SCD recipients (p < 0.001), consisting of a higher number of grafts lost due to PNF (4.2% vs. 1.5%; p ¼ 0.03) and acute vascular occlusions (4.2% vs. 1.3%; p ¼ 0.03) Deceased donor type classification I (%) Causes of early graft loss
Total, n ¼ 801
DCD, n ¼ 435
DBD, n ¼ 366
20 (2.5%) 15 (1.9%) 3 (0.4%) 6 (0.7%) 3 (0.4%) 3 (0.4%) 50 (6.2%)
14 (3.2%) 10 (2.3%) 3 (0.7%) 4 (0.9%) 2 (0.5%) 3 (0.7%) 36 (8.3%)
6 (1.6%) 5 (1.4%) 0 2 (0.5%) 1 (0.3%) 0 14 (3.8%)
a) Primary non-function (PNF) Acute venous thrombosis Acute arterial thrombosis Haemorrhage Acute rejection Other Total
Deceased donor type classification II (%) Causes of early graft loss
Total, n ¼ 801
SCD, n ¼ 465
ECD, n ¼ 288
Unknown*, n ¼ 48
12 (4.2%) 10 (3.5%) 2 (0.7%) 3 (1.0%) 2 (0.7%) 0 29 (10.1%)
1 (2.1%) 0 0 0 1 (2.1%) 0 2 (4.2%)
b) Primary non-function (PNF) Acute venous thrombosis Acute arterial thrombosis Haemorrhage Acute rejection Other Total
20 (2.5%) 15 (1.9%) 3 (0.4%) 6 (0.7%) 3 (0.4%) 3 (0.4%) 50 (6.2%)
7 5 1 3
(1.5%) (1.1%) (0.2%) (0.6%) 0 3 (0.7%) 19 (4.1%)
*
Unknown; unclassified deceased donors due to missing data.
grafts lost due to PNF (4.2% vs. 1.5%; p ¼ 0.033) and acute vascular occlusions (4.2% vs. 1.3%; p ¼ 0.025, Table 1b). The risk of EGL was numerically higher in recipients of kidneys from donors who were both ECD and DCD (23 of 174; 13.2%) compared to recipients of DCD or ECD grafts only (8.3% and 10.1%, respectively) but the difference was not statistically significant (p ¼ 0.177). Excluding kidneys that were transplanted in pairs or when one kidney from the pair was discarded, the relative risk of EGL of the second kidney in the pair was higher when the first kidney suffered EGL (12.5 vs. 6.2%), but the difference was not statistically significant (p ¼ 0.176).
Risk factors for EGL Donor and recipient demographics are shown in Table 2. Univariate analysis revealed that higher donor age (55.2 vs. 49.0 y, p ¼ 0.005), recipient past history of venous thrombosis (p ¼ 0.004), DCD donor type (p ¼ 0.014) and ECD donor type (p < 0.001) were significantly associated with EGL (Table 2). Of note, cold ischaemia time (CIT), recipient age, recipient past history of hypertension or diabetes mellitus, peritoneal dialysis, surgeon grade, sensitisation status and HLA mismatch status were not associated with EGL. 1634
In multivariate logistic regression analysis using deceased donor type classification I (DBD/DCD), recipient past history of thrombosis (odds ratio [OR] 4.91; p ¼ 0.001), donor age (OR 1.03; p ¼ 0.044) and DCD donor type (OR 2.88 vs. DBD donors; p ¼ 0.006) were significant risk factors for EGL (Table 3a). Donor age was >50 years in 27 (of 36; 75.0%) DCD recipients with EGL compared to 233 (of 399; 58.4%) DCD recipients in the control (No EGL) group (p ¼ 0.344). Seven (of 50; 14.0%) recipients with EGL had a past history of venous thrombosis; four recipients had a past history of pulmonary embolism (PE), two recipients had a past history of deep venous thrombosis (DVT) and PE, two recipients with a past history of DVT only, and one EGL recipient lost two previous renal grafts due to venous thrombosis. When using deceased donor type classification II (SCD/ECD), ECD donor type (OR 4.22 vs. SCD donors; p ¼ 0.010) and history of thrombosis (OR 4.79; p ¼ 0.001) were significant risk factors for EGL (Table 3b). Of note, donor age was not a significant risk factor for EGL when including ECD donor type in the analysis; this was not unexpected since age is included in the definition of ECD donors and the two variables are therefore highly correlated. Although DCD donor type was significantly associated with EGL, there was no significant difference in long-term graft survival between recipients of DCD and DBD American Journal of Transplantation 2015; 15: 1632–1643
Early Kidney Graft Loss Table 2: Univariate analysis of risk factors for EGL Graft survival Variable Recipient age (years) Donor age (years) Recipient gender male Recipient comorbidities Diabetes Hypertension History of thrombosis HLA-A mismatch 0 1 2 Unknown HLA-B mismatch 0 1 2 Unknown HLA-DR mismatch 0 1 2 Unknown Cold ischaemia time (hours) Anastomosis time (hours) Recipient BMI Donor BMI Donor type classification I DBD DCD Donor type classification II SCD ECD Unknown Sensitization Not sensitized Sensitized Highly sensitized Unknown 1st transplant 2nd transplant 3rd transplant Peritoneal dialysis Surgeon grade Consultant* not present Consultant present – not scrubbed Consultant present – scrubbed Unknown Gender mismatch None Male recipient/female donor Female recipient/male donor Side mismatch None Right recipient/left donor Left recipient/right donor Unknown
30 days n ¼ 50
>30 days n ¼ 751
52.9 12.8 55.2 15.7 34 (68%)
49.4 13.3 49.0 16.6 493 (66%)
0.063 0.005 0.853
5 (10%) 24 (48%) 7 (14%)
60 (8%) 293 (39%) 30 (4%)
0.813 0.268 0.004
9 (18%) 26 (52%) 15 (30%) 0
172 (23%) 386 (51%) 189 (25%) 4 (1%)
0.753
4 (8%) 33 (66%) 13 (26%) 0
141 (19%) 493 (66%) 114 (15%) 3 (0.4%)
0.083
24 (48%) 25 (50%) 1 (2%) 0 15.1 4.0 0.79 0.22 26.0 4.3 27.2 6.9
405 (54%) 307 (41%) 33 (4%) 6 (1%) 14.6 4.6 0.78 0.44 25.9 4.4 26.5 5.8
0.516
14 (28%) 36 (72%)
352 (47%) 399 (53%)
18 (36%) 30 (60%) 2 (4%)
447 (60%) 258 (34%) 46 (6%)
28 (56%) 17 (34%) 4 (8%) 1 (2%) 43 (86%) 7 (14%) 0 15 (30%)
477 (63%) 201 (27%) 65 (9%) 4 (1%) 658 (88%) 78 (10%) 14 (2%) 251 (34%)
0.486
13 (26%) 7 (14%) 29 (58%) 1 (2%)
257 (34%) 98 (13%) 379 (51%) 17(2%)
0.680
29 (58%) 17 (34%) 4 (8%)
388 (52%) 218 (29%) 145 (19%)
0.137
32 (64%) 7 (14%) 6 (12%) 5 (10%)
424 115 107 105
0.746
(56%) (15%) (14%) (14%)
p-value
0.178 0.509 0.785 0.833 0.014
85%)
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whose graft survived more than 30 days (76.0% vs. 98.1%; p ¼ 0.005). A multivariate logistic regression analysis using donor type classification I (DBD/DCD) revealed that patients with EGL had 12.28 times increased short-term (within 1 year after kidney transplantation) odds ratio death compared to the control cohort whose grafts survived beyond 30 days (p < 0.001; Table 5a). The increased odds ratio was 12.17 times (p < 0.001; Table 5b) when using donor type classification II (SCD/ECD). No other variable, including donor type, was a significant risk factor for patient death at 1 year in the presence of the EGL indicator (Table 5a and b). To assess the effect of EGL on long-term patient survival, a Cox proportional hazard analysis was performed on a subgroup of patients who survived at least 1 year after the kidney transplantation (Table 6). This revealed that EGL had a significant negative impact on long-term patient survival using both donor type classification I (HR of 5.36; p ¼ 0.003; Table 6a) and donor type classification II (HR of 5.33; p ¼ 0.004; Table 6b). EGL, therefore, had a detrimental impact on both short- and long-term patient survival (Figure 2A). Importantly, in the presence of EGL, donor type itself was not a risk factor for long term patient death using donor type classification I (DCD 96.7% vs. DBD 97.0%; p ¼ 0.732; Figure 2B) or donor type classification II (ECD 95.1% vs. SCD 97.8%; p ¼ 0.071; Figure 2C).
Figure 1: Long-term graft survival. (A) There was no significant difference in long-term graft survival between recipients of DCD and DBD transplants (5-year graft survival; DCD 86.4% vs. SCD 90.0%; p ¼ 0.257). (B) Long-term graft survival was inferior in recipients of ECD compared to SCD grafts (5-year graft survival; ECD 83.7% vs. SCD 91.4%; p ¼ 0.017).
kidneys (5-year graft survival; DCD 86.4% vs. SCD 90.0%; p ¼ 0.257; Figure 1A). However, 5-year graft survival in recipients of ECD kidneys was inferior compared to SCD kidneys (ECD 83.7% vs. SCD 91.4%; p ¼ 0.017; Figure 1B).
Consequences of EGL Sixteen (of 50; 32.0%) recipients with EGL died within the study period. Causes of patient mortality in the EGL group are shown in Table 4. One-year patient survival was markedly inferior in the EGL group compared to those 1636
We next examined how patient survival after EGL compared to remaining on the kidney transplant waiting list. As expected, patients remaining on the transplant waiting list (i.e. listed but not transplanted) had a higher mortality rate compared to all patients on the waiting list (i.e. including patients who received a transplant; p < 0.001; Figure 3A). This analysis confirmed the survival benefit to those receiving a transplant compared to all patients on the waiting list. Importantly, it also enabled us to quantify, at a population level, the ‘‘best-case scenario’’ and ‘‘averagecase scenario’’ impact of EGL on patient survival compared to remaining on the waiting list. This analysis can potentially help the recipient and the transplant team when faced with the choice to accept or decline a kidney that is associated with a high risk of EGL, because the recipient and the transplant team are generally unable to predict if, and when, the recipient will be offered another organ if the transplant is declined. As shown in Figure 3B, compared to all patients on the waiting list, EGL resulted in a very high (>8 fold) initial risk of recipient death. This increased risk of patient death attributable to EGL persisted for 23 months (time to equal risk) after transplantation; patients experiencing EGL, therefore, must survive for a mean of 23 months after transplantation before their risk of death equals that of other patients on the waiting list. The corresponding time to equal survival was 76 months compared to all patients on the waiting list, defined as the time needed before the American Journal of Transplantation 2015; 15: 1632–1643
Early Kidney Graft Loss Table 3: Multivariate analysis of risk factors of EGL. a) DCD donor type, donor age, and recipient past history of thrombosis were significant risk factors for EGL. b) ECD donor type and recipient past history of thrombosis were significant risk factors for EGL Variable
Odds ratio
95% CI
p value
CIT
1.00 – 1.01 – 4.91 1.03 – 2.88 1.04
0.97–1.03 – 0.52–1.98 – 1.89–12.73 1.00–1.05 – 1.36–6.13 0.96–1.12
0.864 – 0.975 – 0.001 0.044 – 0.006 0.223
Variable
Odds ratio
95% CI
p value
1.00 – 0.96 – 4.79 0.99 – 4.22 1.02
0.97–1.03 – 0.49–1.88 – 1.87–12.27 0.96–1.03 – 1.41–12.59 0.95–1.10
0.928 – 0.899 – 0.001 0.625 – 0.010 0.541
a) Recipient age Recipient gender Recipient past history of thrombosis Donor age Donor type classification I
Female Male No Yes DBD DCD
b) Recipient age Recipient gender Recipient past history of thrombosis Donor age Donor type classification II
Female Male No Yes SCD ECD
CIT
transplant offers a survival advantage compared to remaining on the transplant waiting list. When compared to patients on the waiting list that do not receive a transplant (Figure 3C), however, EGL was associated with a much smaller (4) was sufficiently high to suggest that this group may benefit from intensive monitoring or modified management such as detailed screening for thrombotic tendencies and/or modified posttransplant anti-thrombotic prophylaxis. In our analysis, the detrimental impact of EGL on patient survival was most pronounced within the first year after transplantation. However, the increased mortality amongst recipients with early kidney graft loss was directly related to surgical complications of the transplant in only five cases. It is likely, therefore, that in addition to postoperative medical and surgical complications, the negative impact of returning to dialysis, the risks and complications associated with ESRD and exposure to immunosuppression combine to dramatically increase mortality risk after EGL. This is consistent with a previous study which reported an increased risk of death in the 60 days post graft loss, irrespective of when graft loss occurred (22). Despite the association of DCD donor type with EGL, there were no significant differences in the long-term graft survival outcomes between DCD and DBD donors, as previously reported by our center and others (6,12,15). This finding suggests that the early impact of the DCD donation American Journal of Transplantation 2015; 15: 1632–1643
on graft survival is ‘‘diluted’’ by other factors affecting graft survival later in the first year. An important finding of our study is that, despite their increased mortality risk, recipients with EGL had better longterm outcomes than patients on the transplant waiting list. Starting from an initial increased risk of 1 year mortality of more than eightfold, patient survival in the EGL group gradually reduced to equal the risk of death for all patients on the transplant waiting list at 23 months (Figure 2B). The increased mortality risk after EGL was much smaller (less than twofold) when compared to patients on the waiting list who were not transplanted, and reduced to baseline by 4 months (Figure 2C). In comparison, the relative risk of death of recipients has previously been reported to be 2.8 times higher than patients on the waiting list after transplantation, decreasing to unity (time to equal risk) by 3.5 months (23). Our results are consistent with the high mortality rate reported for patients on dialysis (24) and suggest that, in the face of lengthening kidney transplant waiting lists, increasing use of kidneys from suboptimal donors must be considered despite their predisposition to the catastrophic outcome of EGL. A caveat to this conclusion, and a limitation of this study, is the selection bias that is inherent in this comparison: it is likely that patients selected from a waiting list to receive a kidney transplant are a more optimal group (e.g. less sensitized) than those that remain on the 1641
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waiting list without being transplanted. These and other factors may have resulted in a selection bias, not quantified in our analysis, which affects the comparison between patients on the waiting list who are transplanted and those who are not. Nonetheless, our results suggest that the additional mortality risk associated with EGL is, in the long-term, less than the alternative of remaining on the transplant waiting list. While this does not justify the injudicious use of suboptimal organs, it serves to draw attention to the risks that patients on the waiting list are exposed to every time a kidney is declined for transplantation. Our findings are consistent with a previous report that demonstrated DCD kidney transplantation offers a survival benefit over those waiting for DBD grafts (25). They go further, however, and suggest that when the waiting list is considered in its entirety, use of even very suboptimal kidneys may offer a survival advantage for the population on the waiting list. In this study, 1-year graft survival after kidney retransplantation following EGL was 85.7% (compared to 90.8% after re-transplantation following late graft loss). This is consistent with previous reports on outcomes for second kidney grafts (1-year graft survival 85–89%) (26,27). Our findings, therefore, suggest that re-transplantation after EGL should be considered for selected cases. Our results suggest that EGL is more frequent after DCD and ECD kidney transplantation and is a major risk factor for patient mortality. However, long-term patient survival after EGL is still better than those remaining on the kidney transplant waiting list. Kidney re-transplantation after EGL is associated with a good outcome and should be considered.
Acknowledgments We are grateful to the NHS Blood and Transplant (NHSBT) for their help in providing the relevant data for this paper from the UK transplant registry. The study was approved by our institution’s review board as a service evaluation audit. Yining Chen was supported by the Engineering and Physical Sciences Research Council Grant EP/J017213/1.
Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
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Supporting Information Additional Supporting Information may be found in the online version of this article. Supplementary Materials and Methods
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Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons doi: 10.1111/ajt.13162
Early Graft Loss After Kidney Transplantation: Risk Factors and Consequences M. O. Hamed1, Y. Chen2, L. Pasea3, C. J. Watson1, N. Torpey4, J. A. Bradley1, G. Pettigrew1 and K. Saeb-Parsy1,* 1
Department of Surgery, University of Cambridge, and NIHR Cambridge Biomedical Research Centre, Cambridge, UK 2 Department of Pure Mathematics and Mathematical Statistics, Cambridge, UK 3 Centre for Applied Medical Statistics, University of Cambridge, Cambridge, UK 4 Department of Renal Medicine, Addenbrooke’s Hospital, Cambridge, UK Corresponding author: Kourosh Saeb-Parsy, [email protected]
Early graft loss (EGL) after kidney transplantation is a catastrophic outcome that is assumed to be more likely after the use of kidneys from suboptimal donors. We therefore examined its incidence, risk factors and consequences in our center in relation to different donor types. Of 801 recipients who received a kidney-only transplant from deceased donors, 50 (6.2%) suffered EGL within 30 days of transplantation. Significant risks factors for EGL were donation after circulatory death (DCD) (odds ratio [OR] 2.88; p ¼ 0.006), expanded criteria donor (ECD) transplantation (OR 4.22; p ¼ 0.010), donor age (OR 1.03; p ¼ 0.044) and recipient past history of thrombosis (OR 4.91; p ¼ 0.001). Recipients with EGL had 12.28 times increased risk of death within the first year, but long-term survival was worse for patients remaining on the waiting list. In comparison with patients on the waiting list but not transplanted, and with all patients on the waiting list, the risk of death after EGL decreased to baseline 4 and 23 months after transplantation, respectively. Our findings suggest that DCD and ECD transplantation are significant risk factors for EGL, which is a major risk factor for recipient death. However, long-term mortality is even greater for those remaining on the waiting list.
Abbreviations: ATG, antithymocyte globulin; ATN, acute tubular necrosis; BMI, body mass index; CIT, cold ischaemia time; DBD, donation after brain death; DCD, donation after circulatory death; DGF, delayed graft function; ECD, expanded criteria donor; EGL, early graft loss; ESRD, end-stage renal disease; HLA, human 1632
leukocyte antigen; PNF, primary non-function; SCD, standard criteria donor Received 26 September 2014, revised 12 December 2014 and accepted for publication 14 December 2014
Introduction For selected patients with end-stage renal disease (ESRD), kidney transplantation is associated with improved quality of life, longer patient survival and reduced costs compared to remaining on dialysis (1,2). Kidney transplant outcomes have improved incrementally over the last two decades (3), attributed to better surgical and medical care, improved immunosuppressive regimens and Human Leucocyte Antigen (HLA) testing and matching of recipients, HLAantibody screening, and better prophylaxis and management of infections and other complications (4). However, long waiting lists and the shortage of optimal donors have necessitated the use of kidneys from increasingly more sub-optimal donors (5). The use of kidneys from suboptimal donors has been shown to be associated with worse longterm graft outcomes in some studies (6,7) and there is a perception that the use of suboptimal kidneys may also increase the risk of early graft loss (EGL). However, the assertion that the use of suboptimal kidneys increases the risk of EGL after kidney transplantation has not been definitively examined. EGL, defined as graft loss occurring within 30 days after kidney transplantation, is relatively uncommon and occurs in approximately 5% of kidney transplants (3). However, it is a physically and emotionally devastating outcome for both the recipient and the transplant team: The recipients are exposed to the risks of medical and surgical postoperative complications, compounded by a period of immunosuppression and with remaining on, or returning rapidly to, dialysis. EGL may also lead to sensitisation to HLA, reducing the likelihood and/or success of re-transplantation (8,9). Although hyperacute or accelerated acute rejections are occasionally responsible for EGL, the most common causes are nonimmunological; vascular thrombosis accounts for up to one third of early kidney transplant loss (10,11). Primary non-function (PNF) is also an important and potentially avoidable cause of EGL that may reflect the quality of the donor organ.
Early Kidney Graft Loss
Clinicians and patients offered a kidney from a suboptimal donor, therefore, face a difficult and poorly understood choice: should the patient be transplanted with that kidney and face an increased risk of EGL, or remain on the waiting list for a better offer while continuing to endure the risks associated with dialysis? Informed judgment about this difficult choice requires a detailed analysis of the incidence, risk factors and consequences of EGL. It is important to perform this analysis in the context of the increasing use of kidneys from donation after circulatory death (DCD) and expanded criteria (ECD) donors compared to donation after brain death (DBD) donors and standard criteria (SCD) donors. In this study, we report our single center experience of EGL following renal transplantation and examine the associated risk factors and consequences. Because a high proportion of renal transplants undertaken at our centre are from DCD and ECD donors, we were able to systematically examine the risk factors for EGL amongst the different deceased donor types.
Materials and Methods Recipients of deceased donor kidney-only transplants between January 2002 and April 2012 in our center who suffered graft loss within 30 days after transplantation were identified from a prospectively maintained database. Patient demographics and medical history were obtained by review of the database, pre- and post-transplant communication letters (including with referral centers), discharge summaries relating to hospital admissions, and by review of case notes where necessary. Waiting list patients included active and suspended patients, as well as highly sensitized patients, in our center only. Factors associated with EGL were determined by univariate and multivariate analysis in comparison to the cohort whose grafts survived beyond 30 days. EGL was defined as graft nephrectomy or loss of kidney transplant function resulting in the recipient becoming dialysis dependent within 30 days of kidney transplantation (and never achieving graft function thereafter) or death with a non-functioning graft within 30 days. Death with a functioning graft (i.e. no requirement for dialysis) was not included as EGL. Recipients of double kidney transplants who lost only one graft and subsequently did not require dialysis were not included in the EGL group. Primary non-function (PNF), defined as permanent lack of graft function from the time of transplantation, was diagnosed when a kidney graft was well perfused (confirmed by ultrasound examination) but never functioned, necessitating dialysis after kidney transplantation; it was confirmed by at least one transplant biopsy to exclude other causes of non-function. The diagnosis of acute vascular occlusion was suggested by Duplex ultrasound examination and confirmed intra-operatively and/or by histological analysis of the graft following transplant nephrectomy. Graft loss secondary to acute rejection was defined as acute irreversible deterioration of graft function not responding to immunosuppressive treatment requiring renal replacement therapy within 30 days after transplant and confirmed by biopsy. Further details on DCD and ECD donors, the transplant operation and immunosuppressive regimens are included in the supplementary materials. Mann–Whitney rank sum tests and Pearson’s Chi-squared tests were used to compare continuous and categorical variables respectively between the
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two groups (graft survival 30 days and >30 days). Multivariate logistic regression models were used to calculate adjusted estimate effects of the variables on risk of EGL, and to assess the impact of EGL on the short-term patient survival (defined as death within the first year after kidney transplantation). A Cox proportional hazards model was used to estimate an adjusted hazard ratio for long-term patient survival (defined as survival for at least 1 year after kidney transplantation). Kaplan–Meier plots and Greenwood’s formula were used to analyze graft and patient survival between groups until all-cause mortality or the end of follow-up (1st April 2013). The one-year risk of death (defined as the probability of death within the next 365 days) was calculated by Kaplan–Meier plot and the relative risk was taken as the ratio of the risk of death among different groups. Missing observations were assumed to be missing at random and partial deletion was used to handle missing observations. All tests were performed at the 5% significance level. Except for univariate analysis, data were analyzed twice with deceased donors categorized as DBD or DCD (donor type classification I) or as SCD or ECD (donor-type classification II). This was because ECD and DCD donor types were highly correlated and not independent: of the 288 ECD donors, 174 (60.4%) where also DCD donors. Including both DCD and ECD donor types in the same analysis, therefore, would have required a much higher number of observations to reach definitive conclusions. Moreover, it was important to be able to determine the impact of both DCD and ECD donor types separately, as one or the other classification is often used by transplant centers and reported in the literature.
Results Incidence of EGL During the 10-year study period, 801 adult patients received a deceased donor kidney-only transplant, of which 435 (54.3%) were from DCD donors and 366 (45.7%) were from DBD donors. Of the 801 transplants, 288 (36.0%) were performed using ECD grafts and 465 (58.0%) using SCD grafts and 48 donors (6.0%) could not be classified as ECD or SCD due to missing data. EGL occurred in 50 (6.2%) recipients. Causes of EGL are summarised in Table 1 and included PNF (20; 2.5%), arterial or venous thrombosis (18; 2.2%), haemorrhage (6; 0.7%) and acute rejection (3; 0.4%). Further details on causes of EGL are provided in the supplementary materials. In comparison, only 2 (of 288; 0.7%) recipients of living donor kidneys suffered EGL during the study period. The incidence of EGL was higher among recipients of DCD grafts compared to DBD grafts (8.3% vs. 3.8%; p ¼ 0.018) . The increased EGL among DCD transplants was due to a numerically higher incidence of PNF (3.2% vs. 1.6%; p ¼ 0.180) and acute vascular occlusions (3.0% vs. 1.4%; p ¼ 0.155), although these differences did not reach statistical significance (Table 1a). The incidence of EGL was also higher among recipients of ECD grafts compared to SCD grafts (10.1% vs. 4.1%; p ¼ 0.003). The increased EGL among ECD transplants was due to a higher number of 1633
Hamed et al Table 1: Causes of EGL after kidney transplantation. a) The overall incidence of EGL was higher among DCD recipients compared to DBD recipients (p < 0.001), consisting of a higher number of grafts lost due to PNF (3.2% vs. 1.6%; p ¼ 0.18) and acute vascular occlusions (3.0% vs. 1.4%; p ¼ 0.16). b) The overall incidence of EGL was higher among ECD recipients compared to SCD recipients (p < 0.001), consisting of a higher number of grafts lost due to PNF (4.2% vs. 1.5%; p ¼ 0.03) and acute vascular occlusions (4.2% vs. 1.3%; p ¼ 0.03) Deceased donor type classification I (%) Causes of early graft loss
Total, n ¼ 801
DCD, n ¼ 435
DBD, n ¼ 366
20 (2.5%) 15 (1.9%) 3 (0.4%) 6 (0.7%) 3 (0.4%) 3 (0.4%) 50 (6.2%)
14 (3.2%) 10 (2.3%) 3 (0.7%) 4 (0.9%) 2 (0.5%) 3 (0.7%) 36 (8.3%)
6 (1.6%) 5 (1.4%) 0 2 (0.5%) 1 (0.3%) 0 14 (3.8%)
a) Primary non-function (PNF) Acute venous thrombosis Acute arterial thrombosis Haemorrhage Acute rejection Other Total
Deceased donor type classification II (%) Causes of early graft loss
Total, n ¼ 801
SCD, n ¼ 465
ECD, n ¼ 288
Unknown*, n ¼ 48
12 (4.2%) 10 (3.5%) 2 (0.7%) 3 (1.0%) 2 (0.7%) 0 29 (10.1%)
1 (2.1%) 0 0 0 1 (2.1%) 0 2 (4.2%)
b) Primary non-function (PNF) Acute venous thrombosis Acute arterial thrombosis Haemorrhage Acute rejection Other Total
20 (2.5%) 15 (1.9%) 3 (0.4%) 6 (0.7%) 3 (0.4%) 3 (0.4%) 50 (6.2%)
7 5 1 3
(1.5%) (1.1%) (0.2%) (0.6%) 0 3 (0.7%) 19 (4.1%)
*
Unknown; unclassified deceased donors due to missing data.
grafts lost due to PNF (4.2% vs. 1.5%; p ¼ 0.033) and acute vascular occlusions (4.2% vs. 1.3%; p ¼ 0.025, Table 1b). The risk of EGL was numerically higher in recipients of kidneys from donors who were both ECD and DCD (23 of 174; 13.2%) compared to recipients of DCD or ECD grafts only (8.3% and 10.1%, respectively) but the difference was not statistically significant (p ¼ 0.177). Excluding kidneys that were transplanted in pairs or when one kidney from the pair was discarded, the relative risk of EGL of the second kidney in the pair was higher when the first kidney suffered EGL (12.5 vs. 6.2%), but the difference was not statistically significant (p ¼ 0.176).
Risk factors for EGL Donor and recipient demographics are shown in Table 2. Univariate analysis revealed that higher donor age (55.2 vs. 49.0 y, p ¼ 0.005), recipient past history of venous thrombosis (p ¼ 0.004), DCD donor type (p ¼ 0.014) and ECD donor type (p < 0.001) were significantly associated with EGL (Table 2). Of note, cold ischaemia time (CIT), recipient age, recipient past history of hypertension or diabetes mellitus, peritoneal dialysis, surgeon grade, sensitisation status and HLA mismatch status were not associated with EGL. 1634
In multivariate logistic regression analysis using deceased donor type classification I (DBD/DCD), recipient past history of thrombosis (odds ratio [OR] 4.91; p ¼ 0.001), donor age (OR 1.03; p ¼ 0.044) and DCD donor type (OR 2.88 vs. DBD donors; p ¼ 0.006) were significant risk factors for EGL (Table 3a). Donor age was >50 years in 27 (of 36; 75.0%) DCD recipients with EGL compared to 233 (of 399; 58.4%) DCD recipients in the control (No EGL) group (p ¼ 0.344). Seven (of 50; 14.0%) recipients with EGL had a past history of venous thrombosis; four recipients had a past history of pulmonary embolism (PE), two recipients had a past history of deep venous thrombosis (DVT) and PE, two recipients with a past history of DVT only, and one EGL recipient lost two previous renal grafts due to venous thrombosis. When using deceased donor type classification II (SCD/ECD), ECD donor type (OR 4.22 vs. SCD donors; p ¼ 0.010) and history of thrombosis (OR 4.79; p ¼ 0.001) were significant risk factors for EGL (Table 3b). Of note, donor age was not a significant risk factor for EGL when including ECD donor type in the analysis; this was not unexpected since age is included in the definition of ECD donors and the two variables are therefore highly correlated. Although DCD donor type was significantly associated with EGL, there was no significant difference in long-term graft survival between recipients of DCD and DBD American Journal of Transplantation 2015; 15: 1632–1643
Early Kidney Graft Loss Table 2: Univariate analysis of risk factors for EGL Graft survival Variable Recipient age (years) Donor age (years) Recipient gender male Recipient comorbidities Diabetes Hypertension History of thrombosis HLA-A mismatch 0 1 2 Unknown HLA-B mismatch 0 1 2 Unknown HLA-DR mismatch 0 1 2 Unknown Cold ischaemia time (hours) Anastomosis time (hours) Recipient BMI Donor BMI Donor type classification I DBD DCD Donor type classification II SCD ECD Unknown Sensitization Not sensitized Sensitized Highly sensitized Unknown 1st transplant 2nd transplant 3rd transplant Peritoneal dialysis Surgeon grade Consultant* not present Consultant present – not scrubbed Consultant present – scrubbed Unknown Gender mismatch None Male recipient/female donor Female recipient/male donor Side mismatch None Right recipient/left donor Left recipient/right donor Unknown
30 days n ¼ 50
>30 days n ¼ 751
52.9 12.8 55.2 15.7 34 (68%)
49.4 13.3 49.0 16.6 493 (66%)
0.063 0.005 0.853
5 (10%) 24 (48%) 7 (14%)
60 (8%) 293 (39%) 30 (4%)
0.813 0.268 0.004
9 (18%) 26 (52%) 15 (30%) 0
172 (23%) 386 (51%) 189 (25%) 4 (1%)
0.753
4 (8%) 33 (66%) 13 (26%) 0
141 (19%) 493 (66%) 114 (15%) 3 (0.4%)
0.083
24 (48%) 25 (50%) 1 (2%) 0 15.1 4.0 0.79 0.22 26.0 4.3 27.2 6.9
405 (54%) 307 (41%) 33 (4%) 6 (1%) 14.6 4.6 0.78 0.44 25.9 4.4 26.5 5.8
0.516
14 (28%) 36 (72%)
352 (47%) 399 (53%)
18 (36%) 30 (60%) 2 (4%)
447 (60%) 258 (34%) 46 (6%)
28 (56%) 17 (34%) 4 (8%) 1 (2%) 43 (86%) 7 (14%) 0 15 (30%)
477 (63%) 201 (27%) 65 (9%) 4 (1%) 658 (88%) 78 (10%) 14 (2%) 251 (34%)
0.486
13 (26%) 7 (14%) 29 (58%) 1 (2%)
257 (34%) 98 (13%) 379 (51%) 17(2%)
0.680
29 (58%) 17 (34%) 4 (8%)
388 (52%) 218 (29%) 145 (19%)
0.137
32 (64%) 7 (14%) 6 (12%) 5 (10%)
424 115 107 105
0.746
(56%) (15%) (14%) (14%)
p-value
0.178 0.509 0.785 0.833 0.014
85%)
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whose graft survived more than 30 days (76.0% vs. 98.1%; p ¼ 0.005). A multivariate logistic regression analysis using donor type classification I (DBD/DCD) revealed that patients with EGL had 12.28 times increased short-term (within 1 year after kidney transplantation) odds ratio death compared to the control cohort whose grafts survived beyond 30 days (p < 0.001; Table 5a). The increased odds ratio was 12.17 times (p < 0.001; Table 5b) when using donor type classification II (SCD/ECD). No other variable, including donor type, was a significant risk factor for patient death at 1 year in the presence of the EGL indicator (Table 5a and b). To assess the effect of EGL on long-term patient survival, a Cox proportional hazard analysis was performed on a subgroup of patients who survived at least 1 year after the kidney transplantation (Table 6). This revealed that EGL had a significant negative impact on long-term patient survival using both donor type classification I (HR of 5.36; p ¼ 0.003; Table 6a) and donor type classification II (HR of 5.33; p ¼ 0.004; Table 6b). EGL, therefore, had a detrimental impact on both short- and long-term patient survival (Figure 2A). Importantly, in the presence of EGL, donor type itself was not a risk factor for long term patient death using donor type classification I (DCD 96.7% vs. DBD 97.0%; p ¼ 0.732; Figure 2B) or donor type classification II (ECD 95.1% vs. SCD 97.8%; p ¼ 0.071; Figure 2C).
Figure 1: Long-term graft survival. (A) There was no significant difference in long-term graft survival between recipients of DCD and DBD transplants (5-year graft survival; DCD 86.4% vs. SCD 90.0%; p ¼ 0.257). (B) Long-term graft survival was inferior in recipients of ECD compared to SCD grafts (5-year graft survival; ECD 83.7% vs. SCD 91.4%; p ¼ 0.017).
kidneys (5-year graft survival; DCD 86.4% vs. SCD 90.0%; p ¼ 0.257; Figure 1A). However, 5-year graft survival in recipients of ECD kidneys was inferior compared to SCD kidneys (ECD 83.7% vs. SCD 91.4%; p ¼ 0.017; Figure 1B).
Consequences of EGL Sixteen (of 50; 32.0%) recipients with EGL died within the study period. Causes of patient mortality in the EGL group are shown in Table 4. One-year patient survival was markedly inferior in the EGL group compared to those 1636
We next examined how patient survival after EGL compared to remaining on the kidney transplant waiting list. As expected, patients remaining on the transplant waiting list (i.e. listed but not transplanted) had a higher mortality rate compared to all patients on the waiting list (i.e. including patients who received a transplant; p < 0.001; Figure 3A). This analysis confirmed the survival benefit to those receiving a transplant compared to all patients on the waiting list. Importantly, it also enabled us to quantify, at a population level, the ‘‘best-case scenario’’ and ‘‘averagecase scenario’’ impact of EGL on patient survival compared to remaining on the waiting list. This analysis can potentially help the recipient and the transplant team when faced with the choice to accept or decline a kidney that is associated with a high risk of EGL, because the recipient and the transplant team are generally unable to predict if, and when, the recipient will be offered another organ if the transplant is declined. As shown in Figure 3B, compared to all patients on the waiting list, EGL resulted in a very high (>8 fold) initial risk of recipient death. This increased risk of patient death attributable to EGL persisted for 23 months (time to equal risk) after transplantation; patients experiencing EGL, therefore, must survive for a mean of 23 months after transplantation before their risk of death equals that of other patients on the waiting list. The corresponding time to equal survival was 76 months compared to all patients on the waiting list, defined as the time needed before the American Journal of Transplantation 2015; 15: 1632–1643
Early Kidney Graft Loss Table 3: Multivariate analysis of risk factors of EGL. a) DCD donor type, donor age, and recipient past history of thrombosis were significant risk factors for EGL. b) ECD donor type and recipient past history of thrombosis were significant risk factors for EGL Variable
Odds ratio
95% CI
p value
CIT
1.00 – 1.01 – 4.91 1.03 – 2.88 1.04
0.97–1.03 – 0.52–1.98 – 1.89–12.73 1.00–1.05 – 1.36–6.13 0.96–1.12
0.864 – 0.975 – 0.001 0.044 – 0.006 0.223
Variable
Odds ratio
95% CI
p value
1.00 – 0.96 – 4.79 0.99 – 4.22 1.02
0.97–1.03 – 0.49–1.88 – 1.87–12.27 0.96–1.03 – 1.41–12.59 0.95–1.10
0.928 – 0.899 – 0.001 0.625 – 0.010 0.541
a) Recipient age Recipient gender Recipient past history of thrombosis Donor age Donor type classification I
Female Male No Yes DBD DCD
b) Recipient age Recipient gender Recipient past history of thrombosis Donor age Donor type classification II
Female Male No Yes SCD ECD
CIT
transplant offers a survival advantage compared to remaining on the transplant waiting list. When compared to patients on the waiting list that do not receive a transplant (Figure 3C), however, EGL was associated with a much smaller (4) was sufficiently high to suggest that this group may benefit from intensive monitoring or modified management such as detailed screening for thrombotic tendencies and/or modified posttransplant anti-thrombotic prophylaxis. In our analysis, the detrimental impact of EGL on patient survival was most pronounced within the first year after transplantation. However, the increased mortality amongst recipients with early kidney graft loss was directly related to surgical complications of the transplant in only five cases. It is likely, therefore, that in addition to postoperative medical and surgical complications, the negative impact of returning to dialysis, the risks and complications associated with ESRD and exposure to immunosuppression combine to dramatically increase mortality risk after EGL. This is consistent with a previous study which reported an increased risk of death in the 60 days post graft loss, irrespective of when graft loss occurred (22). Despite the association of DCD donor type with EGL, there were no significant differences in the long-term graft survival outcomes between DCD and DBD donors, as previously reported by our center and others (6,12,15). This finding suggests that the early impact of the DCD donation American Journal of Transplantation 2015; 15: 1632–1643
on graft survival is ‘‘diluted’’ by other factors affecting graft survival later in the first year. An important finding of our study is that, despite their increased mortality risk, recipients with EGL had better longterm outcomes than patients on the transplant waiting list. Starting from an initial increased risk of 1 year mortality of more than eightfold, patient survival in the EGL group gradually reduced to equal the risk of death for all patients on the transplant waiting list at 23 months (Figure 2B). The increased mortality risk after EGL was much smaller (less than twofold) when compared to patients on the waiting list who were not transplanted, and reduced to baseline by 4 months (Figure 2C). In comparison, the relative risk of death of recipients has previously been reported to be 2.8 times higher than patients on the waiting list after transplantation, decreasing to unity (time to equal risk) by 3.5 months (23). Our results are consistent with the high mortality rate reported for patients on dialysis (24) and suggest that, in the face of lengthening kidney transplant waiting lists, increasing use of kidneys from suboptimal donors must be considered despite their predisposition to the catastrophic outcome of EGL. A caveat to this conclusion, and a limitation of this study, is the selection bias that is inherent in this comparison: it is likely that patients selected from a waiting list to receive a kidney transplant are a more optimal group (e.g. less sensitized) than those that remain on the 1641
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waiting list without being transplanted. These and other factors may have resulted in a selection bias, not quantified in our analysis, which affects the comparison between patients on the waiting list who are transplanted and those who are not. Nonetheless, our results suggest that the additional mortality risk associated with EGL is, in the long-term, less than the alternative of remaining on the transplant waiting list. While this does not justify the injudicious use of suboptimal organs, it serves to draw attention to the risks that patients on the waiting list are exposed to every time a kidney is declined for transplantation. Our findings are consistent with a previous report that demonstrated DCD kidney transplantation offers a survival benefit over those waiting for DBD grafts (25). They go further, however, and suggest that when the waiting list is considered in its entirety, use of even very suboptimal kidneys may offer a survival advantage for the population on the waiting list. In this study, 1-year graft survival after kidney retransplantation following EGL was 85.7% (compared to 90.8% after re-transplantation following late graft loss). This is consistent with previous reports on outcomes for second kidney grafts (1-year graft survival 85–89%) (26,27). Our findings, therefore, suggest that re-transplantation after EGL should be considered for selected cases. Our results suggest that EGL is more frequent after DCD and ECD kidney transplantation and is a major risk factor for patient mortality. However, long-term patient survival after EGL is still better than those remaining on the kidney transplant waiting list. Kidney re-transplantation after EGL is associated with a good outcome and should be considered.
Acknowledgments We are grateful to the NHS Blood and Transplant (NHSBT) for their help in providing the relevant data for this paper from the UK transplant registry. The study was approved by our institution’s review board as a service evaluation audit. Yining Chen was supported by the Engineering and Physical Sciences Research Council Grant EP/J017213/1.
Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
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Supporting Information Additional Supporting Information may be found in the online version of this article. Supplementary Materials and Methods
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