Journal Logo

In View: Special Feature

Early Allograft Dysfunction and Complications in DCD Liver Transplantation: Expert Consensus Statements From the International Liver Transplantation Society

Quintini, Cristiano MD1; Muiesan, Paolo MD2; Detry, Olivier MD, PhD3; Gastaca, Mikel MD, PhD4; de Jonge, Jeroen MD, PhD5; Clavien, Pierre-Alain MD, PhD6; Del Prete, Luca MD1; Fondevila, Constantino MD, PhD7

Author Information
doi: 10.1097/TP.0000000000003877
  • Free

Abstract

INTRODUCTION

Benchmarks for liver transplantation (LT) using deceased brain donors (DBDs) have been recently defined as 1-y mortality ≤9%, graft loss ≤11%, biliary complications ≤28%, and hepatic artery thrombosis (HAT) ≤4.4%.1 Although standard DBD represents organ donation’s first choice, marginal donors represent an essential opportunity to reduce waiting list mortality. For these graft-specific outcomes, benchmarks have not been established yet.

One of the most underutilized and understudied donor population is represented by donors after circulatory death (DCD). Due to the prerecovery period of warm ischemia, grafts from these donors are considered at increased risk for adverse posttransplant primary nonfunction (PNF), early allograft dysfunction (EAD), biliary complications, and failure. Through careful consideration and optimization of donor and recipient-related characteristics, patient and graft survival at 1, 3, and 5 y are not significantly different between controlled DCD (cDCD) and DBD groups; however, EAD occurred in 39.5% of patients,2 ischemic cholangiopathy (IC) in 12%, and HAT in up to 7.7%3,4 of cDCD recipients.

As strategies are designed to expand the donor pool and new technologies are used to improve outcomes with these and other marginal livers, it is of paramount importance to accurately identify, classify, and even predict the onset of complications and adverse events.

In recognizing these priorities, the International Liver Transplantation Society (ILTS) organized a consensus conference on EAD and complications in cDCD liver transplantation.

DEVELOPMENT OF THE GUIDELINES

A total of 151 professionals from 25 countries met on January 31, 2020, during the ILTS consensus conference at the San Servolo Convention Center in Venice, Italy. The meeting’s purpose was to develop evidence-based statements about the most important aspects of cDCD liver transplantation, liver preservation, and machine perfusion. Several databases including Pubmed, Cochrane library, and Google Scholar were searched using selected keywords for every main topic. Working groups met separately and presented their findings to the entire audience for further discussion.

Liver EAD and complications in cDCD was one of the main topics discussed. The debate about EAD and complications in cDCD among a special interest group of experts resulted in a series of clinically relevant statements. The statements are formulated and graded according to the Grading of Recommendations Assessment, Development and Evaluation hierarchy of evidence, which reflects not only the level of evidence in their support but also the strength of recommendation based on the degree of agreement among experts.5

EARLY ALLOGRAFT DYSFUNCTION IN DCD LIVER TRANSPLANTATION

Early allograft function or, conversely, dysfunction defines the ability of the transplanted liver graft to support the recipient’s needs for hepatic metabolic and synthetic function in the immediate posttransplant phase. Early graft function and subsequent posttransplant survival are strongly influenced by donor factors, the pretransplant clinical condition of the recipient, and other intraoperative and perioperative events. Although important variables can be identified in each of these domains, no study has unequivocally determined their specific contributions to patient and graft survival, and very few have specifically evaluated the issue of EAD in the context of cDCD liver transplantation.2

A model to predict early allograft function is important because it allows for the stratification of risk for graft failure and the need for emergency retransplantation in the event of PNF. Additionally, a consistent definition of EAD allows for the comparison of the effects of different graft or patient interventions across different studies. The ideal EAD model or definition should be (1) simple to calculate, (2) based on objective parameters, (3) correlate with outcomes (namely graft and patient survival), (4) associated with recognizable risk factors, (5) dynamic, and (6) reproducible (ie, pass the test of external validation). Additionally, an ideal EAD model needs to take into account that early allograft function is not a “yes/no” condition but rather a continuous one.

One of the first functional definitions of EAD was introduced by Deschênes et al6 in 1998 following a large multicenter trial. In their study, the authors used bilirubin, prothrombin time), and hepatic encephalopathy as surrogate markers of graft function. Patients meeting the criteria for EAD experienced worse graft and patient survival. Other definitions of EAD followed, mostly from single-center studies and largely incorporating hepatic transaminases, bilirubin, and international normalized ratio (INR).7,8

In 2010, Olthoff et al9 introduced the most commonly used definition of EAD to date and tested it in a multicenter cohort of patients from the MELD era. Patients met the criteria for EAD based on at least 1 of the following conditions: (1) bilirubin ≥10 mg/dL on postoperative day (POD) 7, (2) INR ≥1.6 on POD7, and (3) hepatic transaminases (alanine aminotransferase [ALT] or aspartate aminotransferase [AST]) >2000 IU/mL at any point between POD0 and POD7. The use of bilirubin and INR on POD7 was chosen to minimize the impact of pretransplant cholestasis and coagulopathy on graft functional recovery, whereas AST/ALT levels were chosen as a reflection of ischemia-reperfusion injury. The authors tested the ability of this EAD definition to predict outcomes and found that patients meeting at least 1 of these EAD criteria had a >10-fold increase in risk for death within 6 mo after transplant compared with those that did not meet any criterion. On multivariate analysis, donor age and recipient MELD were found to be risk factors strongly associated with the likelihood of developing EAD. The main limitation of this study is that it was designed to validate prior EAD definitions and not to assess donor and recipient variables or the cutoff values chosen to define EAD. Other limitations include the binary nature of the definition and the necessity to wait until the end of the first posttransplant week to make a decision regarding allograft function.

The limitations of the Olthoff definition of EAD have pushed transplant professionals to incorporate new variables and pursue new models. In 2014, Pareja et al10 developed a model for the quantitative assessment of EAD (Model for Early Allograft Function [MEAF]), which incorporates bilirubin on POD3 and maximum ALT and INR between POD0 and POD3. Significant associations were found by the authors between MEAF scores and patient survival evaluated up to 1 y, as well as PNF. In 2017, Jochmans et al11 validated the model and concluded that MEAF outperforms the Olthoff definition of EAD as an independent predictor of posttransplant survival.

In 2017, Yunhua et al12 designed a dynamic model to predict early postoperative complications, including EAD. This model is based on indocyanine green retention at 15 min (ICGR15) and MELD score. These 2 parameters combined offered high sensitivity (>90%) and good specificity (>70%) in predicting early complications when compared with either MELD score or ICGR15 alone. This model was tested at a single center, but it has not yet been externally validated, as it requires performance of the ICG clearance test, which is not routinely available in many transplant centers.

In 2018, Agopian et al13 proposed the “Liver Assessment Following Transplantation Risk Score Model” (L-GrAFT) as a method to assess EAD. L-GrAFT incorporates several laboratory values (AST, INR, bilirubin, and platelet count) measured over the course of the first 10 posttransplant days. This innovative model enables clinicians to categorize patients depending on the severity of EAD and to calculate the odds of graft loss by 3 mo. This study seems to add accuracy in predicting graft outcome. The main drawback is its mathematical complexity.

In 2019, Diaz-Nieto et al14 published regarding their early predictor for the assessment of risk of EAD and PNF. This model, called “MaDiRe” (Maximum, Direction, and Reduction of liver function tests), includes AST on POD1 and the subsequent reduction rate through POD3 as well as ALT reduction through POD2. In the authors’ study, this model was able to provide an early assessment of patients at risk for 30-d graft failure and death as well as to stratify patients into risk groups. One of the advantages of this model is that it takes into consideration the dynamic changes in transaminase levels after liver transplantation. These changes are likely to reflect the graft’s ability to recover from ischemia-reperfusion injury. Another advantage is that the score can be calculated on POD3, and it can rapidly be applied to all patients on a routine basis. Limitations include the empiric as opposed to mathematical method it uses to establish cutoff values. It also has not been externally validated.

In 2020, Avolio et al15 developed the Early Allograft Failure Simplified Estimation (EASE) score that estimates, within the first 10 postoperative days, the patient’s risk for EAD in the first 3 mo post-LT. This model, created from an Italian cohort of patients and externally validated with a UK cohort, is a simplification and refinement of the L-GrAFT score. The EASE score consists of 8 variables and 17 entries and can be electronically calculated with a smartphone application. Limitations of this model include lack of validation outside Europe, where potential differences in donor and recipient characteristics could affect accuracy. Furthermore, this study excluded some recipient categories (such as HIV-positive recipients and patients with acute liver failure).

In 2021, Agopian et al externally validated the L-GrAFT score, and compared its prognostic performance with the Olthoff criteria and the MEAF score. The accuracy of the 3 scores was compared in a validation study that included 3 US centers (n = 3201) and the European Consortium for Organ Preservation (COPE, n = 222). L-GrAFT validation area under ROC (AUROC) was 0.78, significantly superior to binary EAD (AUROC 0.68, P = 0.001) and MEAF scores (AUROC 0.72, P < 0.001). In evaluating the L-GrAFT in the prospective COPE trial, the authors investigated the time to posttransplant adverse events and the need for renal replacement therapy. Interestingly, the highest tertile of L-GrAFT was significantly associated with liver allograft complications, grade IIIb and IVa Clavien-Dindo complication, postoperative length of stay and renal replacement therapy. One limitation of this study is the heterogeneity of the cohorts included.16

Current models do not take into account the use of machine perfusions for graft preservation, reconditioning, or assessment. During this same consensus conference, Martins et al17 highlighted that EAD in machine perfused grafts is likely underestimated due to lower transaminase peak after passive and active release into the perfusate. Indeed, the difference in EAD rate between machine perfusion and static cold storage preservation grafts is mainly due to the transaminase values.18 This difference might be emphasized in DCD grafts, in which high transaminases play a key role in EAD prediction. Therefore, EAD likely needs to be redefined, modeled, and validated in the setting of machine preservation.

The aforementioned models for liver EAD assessment, including how they are calculated and advantages and disadvantages associated with each, are reported in Table 1.

TABLE 1. - Summary of models for assessing early allograft dysfunction following liver transplantation, including an assessment of the advantages and disadvantages associated with each
Author, y Model N Variables included Available on Nature Simple? Objective? Associated with graft survival? Associated with patient survival? Recognized risk factors? Externally validated?
Deschenes, 19986 710 Bilirubin, PT, HE POD7 Binary Y N Y Y Y N
Olthoff 20109 “EAD” 297 Bilirubin, INR, AST, ALT POD7 Binary Y Y Y Y Y Y
Pareja, 201410 “MEAF” 200 ALT, bilirubin, INR POD3 Continuous Y Y Y Y Y Y
Agopian, 201813 “L-GrAFT” 2008 AST, bilirubin, INR, platelets POD10 Continuous N Y Y Y Y Y
Diaz-Nieto, 201914;Avolio, 202015 “MaDiRe”EASE 12992310 ALT, ASTAST, platelets, bilirubin, vascular thrombosis, PRBC transfusions, MELD, center volume POD3POD10 OrdinalContinuous YY YY YY YY NY NY
Of note, none of these models is specific to or has been validated in the DCD liver transplant population.
ALT, alanine aminotransferase; AST, aspartate aminotransferase; EAD, early allograft dysfunction; EASE, Early Allograft Failure Simplified Estimation; HE, hepatic encephalopathy; INR, international normalized ratio; L-GrAFT, Liver Assessment Following Transplantation Risk Score Model; MaDiRe, Maximum, Direction, and Reduction of liver function tests; MEAF, Model for Early Allograft Function; MELD, Model for End-stage Liver Disease; POD, postoperative day; PT, prothrombin time; PRBC, packed red blood cells.

Information on the incidence of EAD in the DCD liver transplant population is scarce. Croome et al19 described an EAD rate of 68% in a small cohort of 38 cDCD liver recipients transplanted between 2006 and 2011. In a larger study on 2015 cDCD liver recipients transplanted between 1998 and 2011, Lee et al demonstrated that 40% developed EAD according to the Olthoff definition. Patient and graft survival rates among cDCD recipients developing EAD were lower compared with those not developing EAD, even when patients who went on to develop nonanastomotic biliary strictures (NABS) were excluded from the authors’ analysis. The authors did not observe any correlation between EAD and subsequent development of NABS.2 Interestingly, they did find that the majority of patients meeting EAD criteria (85%) satisfied only 1 criterion among the 3 included in the definition. Although patients who met the EAD definition due to elevated transaminases experienced only a slight decrease in survival at 6 mo and 1 y, patients who met the definition due to increased INR and total bilirubin on POD7 had significantly worse graft and overall patient survival.

ILTS Guidance

  • Due to the lack of validation studies in DCD liver transplantation, the ILTS cannot recommend the use of any specific model to define EAD.

(Level of Evidence B–C; Grade of Recommendation I Strong)

  • In recognizing the limitation of current models, which do not address the multifactorial nature of EAD, the ILTS recommends that future studies investigate the interactions between donor, recipients, and perioperative factors in determining EAD in DCD liver transplantation.

(Level of Evidence B–C; Grade of Recommendation I Strong)

  • The ILTS recommends that the future models of EAD take into account the time-dependent nature of early allograft function. Specific validation among DCD liver recipients is also recommended.

(Level of Evidence B–C; Grade of Recommendation I Strong)

COMPLICATIONS OF DCD liver transplantation

Although early graft dysfunction and loss were major problems in early experiences with cDCD liver transplantation, years of experience have allowed for better donor and recipient selection, dramatically reducing the incidence of early catastrophic events. For the past 2 decades, biliary complications have been the major obstacle facing cDCD liver transplantation, even though their incidence has decreased considerably from the early 2000s.

Studies published by groups in North American and Europe in the past decade (Tables 2 and 3) suggest that complications and outcomes following cDCD liver transplantation performed with super-rapid recovery vary according to center and in relation to the risk profiles of donors and grafts. Rates of PNF and HAT are consistently low in these studies and largely in a range considered acceptable in the recent benchmark study on standard DBD liver transplantation (<4.4% HAT).1 Rates of biliary complications and nonanastomotic biliary strictures, however, are more variable.

TABLE 2. - Complications and outcomes of controlled DCD liver transplantation performed in North America using livers recovered with super-rapid recovery
Author, y Cohort Time period Study design, N Risk factors PNF (%) Biliary complications (%) NABS (%) HAT (%) Graft survival 1, 3, 5, 10 y (%) Patient survival 1, 3, 5, 10 y (%) Retransplant (%)
Mathur, 201020 UNOS, national 2001–2009 Retrospective, N = 1567 Donor age, DWIT, CIT, recipient age, MELD 78, 65, -,- 83, 78, -, - 14
Bellingham, 201121 Wisconsin, USA 1980–2008 Retrospective, N = 87 52 69, 60, 56, 43 84, 72, 68, 54 14
Foley, 201122 Wisconsin, USA 1993–2008 Retrospective, N = 87 Donor age, DWIT, BMI, MELD 2 47 34 69, -, 56, 43 84, -, 68, 54 19
Jay, 201123 UNOS, national 1996–2007 Retrospective, N = 1113 Donor age, CIT, regional sharing, recipient age, HCV, HCC, renal insufficiency 82, 71, -, - 15
Taner, 201224 Mayo, FL, USA 1998–2010 Retrospective, N = 200 Race, DWIT 3 27 12 4 81, 73, 69, - 93, 85, 81, - 11
Vanatta, 201325 Memphis, USA 2006–2011 Retrospective, N = 38 Donor age, DWIT, CIT, macrosteatosis, procurement team, donor location 3 18 8 0 92, 74, -, - 92, 80, -, - 3
Doyle, 201526 St. Louis, USA 2005–2014 Retrospective, N = 49 Donor age, DWIT 0 ABS 16, BL 14 9 0 -, -, 80, - -, -, 87, - 6
Firl, 201527 Cleveland, USA 2005–2014 Retrospective, N = 92 Donor age 7 27 7 1 83, 72, 66, - 2
Croome, 201628 UNOS, national 2003–2014 (3 eras) Retrospective, N = 3199 Donor age, CIT, recipient age, MELD, MV, HCV, earlier era Era 1: 72, 62, 55, -Era 2: 79, 69, 63, -Era 3: 85, 75, 67, - Era 1: 87, 76, 72, -Era 2: 88, 77, 73, -Era 3: 90, 88, -, -
Scalea, 201629 UNOS, national 2002–2014 Retrospective, N = 2185 Donor age, CIT, BMI 33 -, -, 61, -
Bohorquez, 20173 New Orleans, USA 2003–2015 Retrospective, N = 138, 2 groups DWIT 0 25 4 4 Early: 76, 74, -, -Late: 92, 91, -, - Early: 87, 84, -, -Late: 93, 89, -, -
Croome, 201730 Mayo, FL, USA 1998–2015 Retrospective, N = 300 27 12 2 86, 78, 73, - 92, 86, 80, -
Goldberg, 201731 National consortium 2005–2014 Retrospective, N = 744 Donor age, center volume, DWIT 22 12
Croome, 20184 3 centers, USA 2002–2016 Retrospective, N = 471 Donor age, DM, CIT, MELD, MV, ICU Donor ≥50 y: 32 Donor ≥50 y: 12 Donor ≥50 y: 2 Donor ≥50 y: 87, 76, 72, - Donor ≥50 y: 91, 84, 82, -
Kollmann, 201832 Toronto, Canada 2009–2017 Retrospective, N = 77 1 5 3 0 88, 83, 69, - 92, 85, 72, - 4
Reports have all been published within the last 10 y.
ABS, anastomotic biliary stricture; BL, bile leak; BMI, body mass index; DCD, donation after circulatory death; CIT, cold ischemia time; DWIT, donor warm ischemia time; HAT, hepatic artery thrombosis; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; ICU, intensive care unit; MELD, Model for End-stage Liver Disease; NABS, nonanastomotic biliary strictures; PNF, primary nonfunction; UNOS, United Network for Organ Sharing.

TABLE 3. - Complications and outcomes of controlled DCD liver transplantation performed in Europe using livers recovered with super-rapid recovery
Author, y Cohort Time period Study design, N Risk factors PNF (%) Biliary complications (%) NABS (%) HAT (%) Graft survival 1, 3, 5, 10 y (%) Patient survival 1, 3, 5, 10 y (%) Retransplant (%)
Dubbeld, 201033 The Netherlands, national 2001–2006 Retrospective, N = 55 DWIT, CIT, RWIT, transplant center 2 24 7 74, 68, -, - 85, 80, -, - 18
DeOliveira, 201134 London, United Kingdom 2001–2010 Retrospective, N = 152 20 3 3 -, -, 78, - -, -, 80, - 1
Mallik, 201235 Cambridge, United Kingdom 2004–2010 Retrospective, N = 32 50 19 95, -, -, - 100, -, -, -
Meurisse, 201236 Leuven, Belgium 2003–2010 Retrospective, N = 30 Donor age, DWIT, CIT 0 50 33 90, 82, -, - 93, 86, -, - 3
Callaghan, 201337 United Kingdom, national 2005–2010 Retrospective, N = 352 Leading to graft loss: 6 -, 73,-, - -, 81, -, -
Detry, 201438 Liege, Belgium 2003–2012 Retrospective, N = 69 Donor age 0 20 1 1 -, 72, -, - -, 73, -, - 1
O’Neill, 201439 Medline Embase, Cochrane 1993–2011 Meta-analysis (25 studies), N = 2478 Donor age, recipient age, MELD, CIT 26 16 -, 73, -, - -, 82, -, -
Blok, 201640 Belgium and the Netherlands 2003–2007 Retrospective, N = 126 DWIT 3 6 0.8 75, -, 54, 44 88, -, 68, 56 14
Laing, 201641 Birmingham, United Kingdom 2004–2014 Retrospective, N = 234 (propensity matched, N = 187) 33 9 5 83, -, -, - 88, -, -, - 3
Kalisvaart, 201742 Rotterdam, the Netherlands 2001–2015 Retrospective, N = 115 4 34 11 -, -, 60, - -, -, 75, - 15
Schlegel, 201843 Birmingham, United Kingdom 2004–2017 Retrospective, N = 315 Donor age, donor BMI, CIT 3 29 11 7 Donor >60 y and BMI ≤25: -, -, >80, - Donor >60 y and BMI ≤25: -, -, >88, - 7
Gilbo, 201944 Leuven, Belgium 2009–2015 Retrospective, N = 78 -, 82, -, - -, 85, -, -
Taylor, 201945 United Kingdom, national 2008–2015 Retrospective, N = 953 Donor age, recipient age, recipient status, liver appearance 4 84, -, 69, - 92, -, 78, -
Hessheimer, 201946 Spain, national 2012–2016 Retrospective, N = 117 DWIT 3 31 13 3 83, 76, -, - 88, 84, -, - 9
Pitarch Martínez, 201947 Málaga, Spain 2013–2017 Retrospective, N = 25 Donor age, DWIT, CIT 0 20 12 -, 84, -, - 8
Cascales-Campos, 202048 Murcia, Spain 2014–2018 Retrospective, N = 77 Steatosis, fibrosis 1 38 6 4 73, -, -, - 79, -, -, - 6
Otero, 202049 La Coruña, Spain 2012–2018 Retrospective, N = 24 DWIT 4 30 4 4 83, -, -, - -, -, -, -
Reports have all been published within the last 10 y.
BMI, body mass index; CIT, cold ischemia time; DCD, donation after circulatory death; DWIT, donor warm ischemia time; HAT, hepatic artery thrombosis; MELD, Model for End-stage Liver Disease; NABS, nonanastomotic biliary strictures; PNF, primary nonfunction; RWIT, recipient warm ischemia time.

The most recent meta-analysis on cDCD liver transplantation describes rates of overall biliary complications and NABS of 26% and 16%, respectively, as well as 1- and 3-y graft and patient survival rates of 79% and 73% and 88% and 82%, respectively.39 Although the overall biliary complication rate meets the aforementioned DBD benchmark goal of 28%, rates of graft loss and patient death by 1 y are above benchmark limits (11% and 9%, respectively). In consideration of these facts, it appears that there is additional need for benchmark studies specific to cDCD liver transplantation.

IC could be documented by endoscopic retrograde cholangiopancreatography (ERCP), percutaneous transhepatic cholangiography, surgically placed biliary catheter, or magnetic resonance cholangiopancreatography (MRCP). The latter is of great interest because it is the only noninvasive method with high sensitivity (96%) and specificity (94%) to diagnose biliary adverse events following liver transplantation.50,51

Noncontrast MRCP cannot clearly differentiate between obstructive and nonobstructive dilatation and does not clearly visualize strictures in a nondilated biliary system, whereas contrast-enhanced MRCP is particularly helpful for identifying adverse biliary events and providing functional information. Its major drawbacks are high costs and its limited role in patients with liver dysfunction.52

An increasing number of reports have come out during the past couple of years on cDCD liver transplantation performed with postmortem normothermic regional perfusion (NRP), which restores the flow of oxygenated blood to the abdominal organs and occasionally to the thoracic organs following the declaration of death.53,54 This recovery strategy is currently permitted by law in 5 European countries (Belgium, the Netherlands, Spain, Switzerland, and the United Kingdom) and compulsory in 3 (France, Italy, and Norway).55 Reports on cDCD liver transplant performed with NRP describe consistent results in terms of biliary complications, graft loss, and patient survival, and largely meet current standards and benchmarks for DBD liver transplantation, including with respect to rates of posttransplant biliary complications (Table 4).

TABLE 4. - Complications and outcomes of controlled DCD liver transplantation performed using livers recovered with postmortem normothermic regional perfusion
Author, y Cohort Time period Study design, N Risk factors PNF (%) Biliary complications (%) NABS (%) HAT (%) Graft survival 1, 3, 5, 10 y (%) Patient survival 1, 3, 5, 10 y (%) Retransplant (%)
Hessheimer, 201946 Spain, national 2012–2016 Retrospective, N = 95 DWIT, AST/ALT during NRP 2 8 2 4 88, 88, -, - 93, 93, -, - 5
Ruíz, 201956 Bilbao, Spain 2015–2017 Retrospective, N = 46 DWIT, AST/ALT during NRP 0 2 0 0 100, 100, -, - 100, 100, -, - 0
Watson, 201957 Cambridge and Edinburgh, United Kingdom 2011–2017 Retrospective, N = 43 ALT during NRP 0 7 0 2 95, 85, -, - 97, 92, -, -
Otero, 202049 La Coruña, Spain 2012–2018 Retrospective, N = 41 DWIT 2 15 0 5 95, -, -, - -, -, -, -
Rojas-Peña, 201458 Michigan, USA 2000–2013 Retrospective, N = 13 DWIT 8 8 0 86, -, -, - -, -, -, -
Olivieri, 201959 Modena, Italy 2017–2019 Retrospective, N = 9 AST/ALT and lactate during NRP 0 30 0 0 100, -, -, - 100, -, -, - 0
Hagness, 201960 Oslo, Norway 2015–2017 Retrospective, N = 8 DWIT, lactate during NRP 0 25 0 (13% recurrent PSC) 0 100, -, -, - 100, -, -, - 0
Reports from Foss, 201861; Miñambres, 201762; Miñambres, 202063; Oniscu, 201464; and Rodríguez-Sanjuán, 201765 have not been included, as patients in these previous reports are largely included among other reports listed in the table. Reports from De Carlis, 2018,66 and Dondossola, 2019,67 have not been included, either, as they mix results of a small number of controlled DCD with those of an equal or greater number of uncontrolled DCD liver transplants.
ALT, alanine aminotransferase; AST, aspartate aminotransferase; DCD, donation after circulatory death; DWIT, donor warm ischemia time; HAT, hepatic artery thrombosis; NABS, nonanastomotic biliary strictures; NRP, normothermic regional perfusion; PNF, primary nonfunction; PSC, primary sclerosing cholangitis.

A multicenter international study1 identified benchmarks in liver transplantation for low-risk cases receiving DBD grafts. The cutoffs, calculated as the 75th percentile of each center’s median, were 9% and 11% for 1-y graft loss and mortality, respectively. The cutoffs were 59%, 28%, and 4.4% for grade III complications, overall biliary complications, and HAT, respectively. Interestingly, the authors used the comprehensive complication index (CCI) to define benchmark values for cumulative morbidity: the CCI was 29.6 at discharge, 34.5 at 3 mo, 37.2 at 6 mo, and 42.1 at 12 mo. However, this study did not include extended criteria donors.

Kalisvaart et al42 analyzed the total burden of complications after DBD and cDCD liver transplantation with the CCI. The authors reported a comparable complication rate during the hospital stay, but the CCI increased significantly for cDCD recipients at 6 mo after transplantation because of IC.

The potential complications after cDCD liver transplantation require a delicate balance in the donor and recipient selection. Many authors have tried to define a cDCD risk score to help liver surgeons identify acceptable donor–recipient combinations in DCD donor liver transplantation.

In 2011, Hong et al68 described the UCLA-DCD score, which takes into account the cold ischemia time plus 2 donor and 3 recipient risk factors. The authors stratified their cohort into low-risk (0–1 point), intermediate-risk (2–4 points), and high-risk (5–9 points) categories. They suggested a threshold of 4 to decline the liver because of a 0% rate of 5-y graft failure-free survival in the high-risk group. Notably, the best predictor for poor outcomes was HCV positivity combined with hepatocellular carcinoma, a variable that will have less impact in the future due to the introduction of direct-acting antiviral medications.

In 2017, the King’s College Hospital group developed the DCD-risk index (DCD-RI) from a single-center cDCD transplant cohort.69 Three recipient and 2 donor risk parameters were considered, with a total score of up to 14 points. Three risk classes were defined as low (DCD-RI <1), standard (DCD-RI 2–4), and high risk (DCD-RI >5) with a 5-y graft survival of 86%, 78%, and 34%, respectively. Interestingly, the DCD-RI score independently predicted graft loss (P < 0.001), and the DCD-RI class predicted graft survival (P < 0.001).

A third model, the UK DCD Risk Score, was developed the same year by Schlegel et al.70 This model identified 7 predictors of DCD survival considering both donor and recipient factors. The authors identified 3 groups: low risk (≤5 points), high risk (>5 to ≤10 points), and futile (>10 points). One-year graft survival was >95%, >85%, and 37%, respectively; 5-y graft survival in the futile group was 20%. The causes of graft loss in the futile group were PNF, IC, and HAT in 27%, 16%, 10% of patients, respectively. Although this score includes 2 parameters not available at organ offer (donor warm ischemia time and cold ischemia time) and does not include graft steatosis, it could be of utmost importance for donor–recipient matching and decision making regarding pretransplant graft treatment. Indeed, a patient in the futile group could be transplanted after graft reconditioning with machine perfusion, which significantly reduces the impact of IC,71 the main cause of graft loss in this graft category.

All these are prognostic models with the aim to identify the most accurate risk factors related to graft loss and survival. They are useful also in reporting data allowing comparison between series. However, these models include intraoperative or postoperative variables, which make EAD a descriptive and prognostic event but not preventable. Future studies should be focused on defining risks before transplant to prevent complication and to evaluate potential futility, also considering the spreading of future technologies applied to DCD donors such as NRP and machine preservation.

ILTS Guidance

The ILTS suggests that unique benchmarks for best achievable outcomes in DCD liver transplantation be established. It is recommended that these benchmarks are specific for organ recovery method and preservation modality used.

(Level of Evidence B–C; Grade of Recommendation IIa Moderate)

SUMMARY

The statements of this ILTS Working Group of experts are summarized in Table 5, where they have also been classified according to the Grading of Recommendations Assessment, Development, and Evaluation system.5 Overall, the level of evidence supporting these statements is low, and it is clear that there is ample opportunity in the near future to devise more clear and consistent means for capturing and categorizing posttransplant DCD liver allograft function. Doing so is critical not only to help compare outcomes across studies and guide clinical decision making but also to implement new strategies and technologies to maximize allograft function and outcomes.

TABLE 5. - Summary of the consensus statements on early allograft dysfunction and complications in DCD liver transplantation
ILS guidance Level of evidencea Gradeb
Due to the lack of validation studies in DCD liver transplantation, the ILTS cannot recommend the use of any specific model to define EAD. B–C I
In recognizing the limitation of current models, which do not address the multifactorial nature of EAD, the ILTS recommends that future studies investigate the interactions between donor, recipients, and perioperative factors in determining EAD in DCD liver transplantation. B–C I
The ILTS recommends that the future models of EAD take into account the time-dependent nature of early allograft function. Specific validation among DCD liver recipients is also recommended. B–C I
The ILTS suggests that unique benchmarks for best achievable outcomes in DCD liver transplantation be established. It is recommended that these benchmarks are specific for organ recovery method and preservation modality used. B–C IIa
aLevel of evidence: A—consistent high level of evidence from well-performed and high-quality studies or systematic reviews; B—moderate/low level of evidence from studies or systematic reviews with few important limitations; C—very low level of evidence from studies with serious flaws (only expert opinion or standards of care).
bGrade: I—strong agreement to do; IIa—moderate agreement to do; IIb—weak agreement to do; III—agreement not to do.
DCD, donation after circulatory death; EAD, early allograft dysfunction; ILTS, International Liver Transplantation Society.

REFERENCES

1. Muller X, Marcon F, Sapisochin G, et al. Defining benchmarks in liver transplantation: a multicenter outcome analysis determining best achievable results. Ann Surg. 2018;267:419–425.
2. Lee DD, Singh A, Burns JM, et al. Early allograft dysfunction in liver transplantation with donation after cardiac death donors results in inferior survival. Liver Transpl. 2014;20:1447–1453.
3. Bohorquez H, Seal JB, Cohen AJ, et al. Safety and outcomes in 100 consecutive donation after circulatory death liver transplants using a protocol that includes thrombolytic therapy. Am J Transplant. 2017;17:2155–2164.
4. Croome KP, Mathur AK, Lee DD, et al. Outcomes of donation after circulatory death liver grafts from donors 50 years or older: a multicenter analysis. Transplantation. 2018;102:1108–1114.
5. Atkins D, Eccles M, Flottorp S, et al.; GRADE Working Group. Systems for grading the quality of evidence and the strength of recommendations I: critical appraisal of existing approaches The GRADE Working Group. BMC Health Serv Res. 2004;4:38.
6. Deschênes M, Belle SH, Krom RA, et al. Early allograft dysfunction after liver transplantation: a definition and predictors of outcome. National Institute of Diabetes and Digestive and Kidney Diseases Liver Transplantation Database. Transplantation. 1998;66:302–310.
7. Nanashima A, Pillay P, Verran DJ, et al. Analysis of initial poor graft function after orthotopic liver transplantation: experience of an australian single liver transplantation center. Transplant Proc. 2002;34:1231–1235.
8. Ben-Ari Z, Weiss-Schmilovitz H, Sulkes J, et al. Serum cholestasis markers as predictors of early outcome after liver transplantation. Clin Transplant. 2004;18:130–136.
9. Olthoff KM, Kulik L, Samstein B, et al. Validation of a current definition of early allograft dysfunction in liver transplant recipients and analysis of risk factors. Liver Transpl. 2010;16:943–949.
10. Pareja E, Cortes M, Hervás D, et al. A score model for the continuous grading of early allograft dysfunction severity. Liver Transpl. 2015;21:38–46.
11. Jochmans I, Fieuws S, Monbaliu D, et al. “Model for Early Allograft Function” outperforms “Early Allograft Dysfunction” as a predictor of transplant survival. Transplantation. 2017;101:e258–e264.
12. Yunhua T, Weiqiang J, Maogen C, et al. The combination of indocyanine green clearance test and model for end-stage liver disease score predicts early graft outcome after liver transplantation. J Clin Monit Comput. 2018;32:471–479.
13. Agopian VG, Harlander-Locke MP, Markovic D, et al. Evaluation of early allograft function using the liver graft assessment following transplantation risk score model. JAMA Surg. 2018;153:436–444.
14. Diaz-Nieto R, Lykoudis P, Robertson F, et al. A simple scoring model for predicting early graft failure and postoperative mortality after liver transplantation. Ann Hepatol. 2019;18:902–912.
15. Avolio AW, Franco A, Schlegel A, et al. Development and validation of a comprehensive model to estimate early allograft failure among patients requiring early liver retransplant. JAMA Surg. 2020;155:e204095.
16. Agopian VG, Markovic D, Klintmalm GB, et al. Multicenter validation of the liver graft assessment following transplantation (L-GrAFT) score for assessment of early allograft dysfunction. J Hepatol. 2021;74:881–892.
17. Martins PN, Rizzari MD, Ghinolfi D, et al.; ILTS Special Interest Group “DCD, Preservation and Machine Perfusion”. Design, analysis, and pitfalls of clinical trials using ex situ liver machine perfusion: the International Liver Transplantation Society Consensus Guidelines. Transplantation. 2021;105:796–815.
18. Nasralla D, Coussios CC, Mergental H, et al.; Consortium for Organ Preservation in Europe. A randomized trial of normothermic preservation in liver transplantation. Nature. 2018;557:50–56.
19. Croome KP, Wall W, Quan D, et al. Evaluation of the updated definition of early allograft dysfunction in donation after brain death and donation after cardiac death liver allografts. Hepatobiliary Pancreat Dis Int. 2012;11:372–376.
20. Mathur AK, Heimbach J, Steffick DE, et al. Donation after cardiac death liver transplantation: predictors of outcome. Am J Transplant. 2010;10:2512–2519.
21. Bellingham JM, Santhanakrishnan C, Neidlinger N, et al. Donation after cardiac death: a 29-year experience. Surgery. 2011;150:692–702.
22. Foley DP, Fernandez LA, Leverson G, et al. Biliary complications after liver transplantation from donation after cardiac death donors: an analysis of risk factors and long-term outcomes from a single center. Ann Surg. 2011;253:817–825.
23. Jay C, Ladner D, Wang E, et al. A comprehensive risk assessment of mortality following donation after cardiac death liver transplant - an analysis of the national registry. J Hepatol. 2011;55:808–813.
24. Taner CB, Bulatao IG, Willingham DL, et al. Events in procurement as risk factors for ischemic cholangiopathy in liver transplantation using donation after cardiac death donors. Liver Transpl. 2012;18:100–111.
25. Vanatta JM, Dean AG, Hathaway DK, et al. Liver transplant using donors after cardiac death: a single-center approach providing outcomes comparable to donation after brain death. Exp Clin Transplant. 2013;11:154–163.
26. Doyle MB, Collins K, Vachharajani N, et al. Outcomes using grafts from donors after cardiac death. J Am Coll Surg. 2015;221:142–152.
27. Firl DJ, Hashimoto K, O’Rourke C, et al. Impact of donor age in liver transplantation from donation after circulatory death donors: a decade of experience at Cleveland clinic. Liver Transpl. 2015;21:1494–1503.
28. Croome KP, Lee DD, Keaveny AP, et al. Improving national results in liver transplantation using grafts from donation after cardiac death donors. Transplantation. 2016;100:2640–2647.
29. Scalea JR, Redfield RR, Foley DP. Liver transplant outcomes using ideal donation after circulatory death livers are superior to using older donation after brain death donor livers. Liver Transpl. 2016;22:1197–1204.
30. Croome KP, Lee DD, Perry DK, et al. Comparison of longterm outcomes and quality of life in recipients of donation after cardiac death liver grafts with a propensity-matched cohort. Liver Transpl. 2017;23:342–351.
31. Goldberg DS, Karp SJ, McCauley ME, et al. Interpreting outcomes in DCDD liver transplantation: first report of the multicenter IDOL Consortium. Transplantation. 2017;101:1067–1073.
32. Kollmann D, Sapisochin G, Goldaracena N, et al. Expanding the donor pool: donation after circulatory death and living liver donation do not compromise the results of liver transplantation. Liver Transpl. 2018;24:779–789.
33. Dubbeld J, Hoekstra H, Farid W, et al. Similar liver transplantation survival with selected cardiac death donors and brain death donors. Br J Surg. 2010;97:744–753.
34. DeOliveira ML, Jassem W, Valente R, et al. Biliary complications after liver transplantation using grafts from donors after cardiac death: results from a matched control study in a single large volume center. Ann Surg. 2011;254:716–722.
35. Mallik M, Callaghan CJ, Hope M, et al. Comparison of liver transplantation outcomes from adult split liver and circulatory death donors. Br J Surg. 2012;99:839–847.
36. Meurisse N, Vanden Bussche S, Jochmans I, et al. Outcomes of liver transplantations using donations after circulatory death: a single-center experience. Transplant Proc. 2012;44:2868–2873.
37. Callaghan CJ, Charman SC, Muiesan P, et al.; UK Liver Transplant Audit. Outcomes of transplantation of livers from donation after circulatory death donors in the UK: a cohort study. BMJ Open. 2013;3:e003287.
    38. Detry O, Deroover A, Meurisse N, et al. Donor age as a risk factor in donation after circulatory death liver transplantation in a controlled withdrawal protocol programme. Br J Surg. 2014;101:784–792.
    39. O’Neill S, Roebuck A, Khoo E, et al. A meta-analysis and meta-regression of outcomes including biliary complications in donation after cardiac death liver transplantation. Transpl Int. 2014;27:1159–1174.
    40. Blok JJ, Detry O, Putter H, et al.; Eurotransplant Liver Intestine Advisory Committee. Longterm results of liver transplantation from donation after circulatory death. Liver Transpl. 2016;22:1107–1114.
    41. Laing RW, Scalera I, Isaac J, et al. Liver transplantation using grafts from donors after circulatory death: a propensity score-matched Study from a single center. Am J Transplant. 2016;16:1795–1804.
    42. Kalisvaart M, de Haan JE, Polak WG, et al. Comparison of postoperative outcomes between donation after circulatory death and donation after brain death liver transplantation using the comprehensive complication index. Ann Surg. 2017;266:772–778.
    43. Schlegel A, Scalera I, Perera MTPR, et al. Impact of donor age in donation after circulatory death liver transplantation: is the cutoff “60” still of relevance? Liver Transpl. 2018;24:352–362.
    44. Gilbo N, Jochmans I, Jacobs-Tulleneers-Thevissen D, et al. Survival of patients with liver transplants donated after euthanasia, circulatory death, or brain death at a single center in Belgium. JAMA. 2019;322:78–80.
    45. Taylor R, Allen E, Richards JA, et al.; Liver Advisory Group to NHS Blood and Transplant. Survival advantage for patients accepting the offer of a circulatory death liver transplant. J Hepatol. 2019;70:855–865.
    46. Hessheimer AJ, Coll E, Torres F, et al. Normothermic regional perfusion vs. super-rapid recovery in controlled donation after circulatory death liver transplantation. J Hepatol. 2019;70:658–665.
    47. Pitarch Martínez M, Sánchez Pérez B, León Díaz FJ, et al. Donation after cardiac death in liver transplantation: an additional source of organs with similar results to donation after brain death. Transplant Proc. 2019;51:4–8.
    48. Cascales-Campos PA, Ferreras D, Alconchel F, et al. Controlled donation after circulatory death up to 80 years for liver transplantation: pushing the limit again. Am J Transplant. 2020;20:204–212.
    49. Otero A, Vázquez MA, Suárez F, et al. Results in liver transplantation using grafts from donors after controlled circulatory death: a single-center experience comparing donor grafts harvested after controlled circulatory death to those harvested after brain death. Clin Transplant. 2020;34:e13763.
    50. Jorgensen JE, Waljee AK, Volk ML, et al. Is MRCP equivalent to ERCP for diagnosing biliary obstruction in orthotopic liver transplant recipients? A meta-analysis. Gastrointest Endosc. 2011;73:955–962.
    51. Xu YB, Min ZG, Jiang HX, et al. Diagnostic value of magnetic resonance cholangiopancreatography for biliary complications in orthotopic liver transplantation: a meta-analysis. Transplant Proc. 2013;45:2341–2346.
    52. Boraschi P, Donati F. Postoperative biliary adverse events following orthotopic liver transplantation: assessment with magnetic resonance cholangiography. World J Gastroenterol. 2014;20:11080–11094.
    53. Fondevila C, Hessheimer AJ, Ruiz A, et al. Liver transplant using donors after unexpected cardiac death: novel preservation protocol and acceptance criteria. Am J Transplant. 2007;7:1849–1855.
    54. Hessheimer AJ, García-Valdecasas JC, Fondevila C. Abdominal regional in-situ perfusion in donation after circulatory determination of death donors. Curr Opin Organ Transplant. 2016;21:322–328.
    55. Lomero M, Gardiner D, Coll E, et al.; European Committee on Organ Transplantation of the Council of Europe (CD-P-TO). Donation after circulatory death today: an updated overview of the European landscape. Transpl Int. 2020;33:76–88.
    56. Ruiz P, Gastaca M, Bustamante FJ, et al. Favorable outcomes after liver transplantation with normothermic regional perfusion from donors after circulatory death: a single-center experience. Transplantation. 2019;103:938–943.
    57. Watson CJE, Hunt F, Messer S, et al. In situ normothermic perfusion of livers in controlled circulatory death donation may prevent ischemic cholangiopathy and improve graft survival. Am J Transplant. 2019;19:1745–1758.
    58. Rojas-Peña A, Sall LE, Gravel MT, et al. Donation after circulatory determination of death: the University of Michigan experience with extracorporeal support. Transplantation. 2014;98:328–334.
    59. Olivieri T, Magistri P, Guidetti C, et al. University of Modena experience with liver grafts from donation after circulatory death: what really matters in organ selection? Transplant Proc. 2019;51:2967–2970.
    60. Hagness M, Foss S, Sørensen DW, et al. Liver transplant after normothermic regional perfusion from controlled donors after circulatory death: the Norwegian experience. Transplant Proc. 2019;51:475–478.
    61. Foss S, Nordheim E, Sørensen DW, et al. First Scandinavian protocol for controlled donation after circulatory death using normothermic regional perfusion. Transplant Direct. 2018;4:e366.
    62. Miñambres E, Suberviola B, Dominguez-Gil B, et al. Improving the outcomes of organs obtained from controlled donation after circulatory death donors using abdominal normothermic regional perfusion. Am J Transplant. 2017;17:2165–2172.
    63. Miñambres E, Ruiz P, Ballesteros MA, et al. Combined lung and liver procurement in controlled donation after circulatory death using normothermic abdominal perfusion. Initial experience in two Spanish centers. Am J Transplant. 2020;20:231–240.
    64. Oniscu GC, Randle LV, Muiesan P, et al. In situ normothermic regional perfusion for controlled donation after circulatory death—the United Kingdom experience. Am J Transplant. 2014;14:2846–2854.
    65. Rodríguez-Sanjuán JC, Ruiz N, Miñambres E, et al. Liver transplant from controlled cardiac death donors using normothermic regional perfusion: comparison with liver transplants from brain dead donors. Transplant Proc. 2019;51:12–19.
    66. De Carlis R, Di Sandro S, Lauterio A, et al. Liver grafts from donors after circulatory death on regional perfusion with extended warm ischemia compared with donors after brain death. Liver Transpl. 2018;24:1523–1535.
    67. Dondossola D, Lonati C, Zanella A, et al. Preliminary experience with hypothermic oxygenated machine perfusion in an Italian liver transplant center. Transplant Proc. 2019;51:111–116.
    68. Hong JC, Yersiz H, Kositamongkol P, et al. Liver transplantation using organ donation after cardiac death: a clinical predictive index for graft failure-free survival. Arch Surg. 2011;146:1017–1023.
    69. Khorsandi SE, Giorgakis E, Vilca-Melendez H, et al. Developing a donation after cardiac death risk index for adult and pediatric liver transplantation. World J Transplant. 2017;7:203–212.
    70. Schlegel A, Kalisvaart M, Scalera I, et al. The UK DCD Risk Score: a new proposal to define futility in donation-after-circulatory-death liver transplantation. J Hepatol. 2018;68:456–464.
    71. van Rijn R, Schurink IJ, de Vries Y, et al. Hypothermic machine perfusion in liver transplantation—a randomized trial. N Engl J Med. 2021;384:1391–1401.
    Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.