Biomarkers and predictive models of early allograft dysfunction in liver transplantation - A systematic review of the literature, meta-analysis, and expert panel recommendations.
biomarker
early allograft dysfunction
lactate
liver transplantation
Journal
Clinical transplantation
ISSN: 1399-0012
Titre abrégé: Clin Transplant
Pays: Denmark
ID NLM: 8710240
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
02
01
2022
accepted:
28
02
2022
pubmed:
16
3
2022
medline:
15
12
2022
entrez:
15
3
2022
Statut:
ppublish
Résumé
Prompt identification of early allograft dysfunction (EAD) is critical to reduce morbidity and mortality in liver transplant (LT) recipients. Evaluate the evidence supporting biomarkers that can provide diagnostic and predictive value for EAD. Ovid MEDLINE, Embase, Scopus, Google Scholar, and Cochrane Central. Systematic review following PRISMA guidelines and recommendations using the GRADE approach was derived from an international expert panel. Studies that investigated biomarkers or models for predicting EAD in adult LT recipients were included for in-depth evaluation and meta-analysis. Olthoff's criteria were used as the standard reference for the diagnostic accuracy evaluation. CRD42021293838 RESULTS: Ten studies were included for the systematic review. Lactate, lactate clearance, uric acid, Factor V, HMGB-1, CRP to ALB ratio, phosphocholine, total cholesterol, and metabolomic predictive model were identified as potential early EAD predictive biomarkers. The sensitivity ranged between .39 and .92, while the specificity ranged from .63 to .90. Elevated lactate level was most indicative of EAD after adult LT (pooled diagnostic odds ratio of 7.15 (95%CI: 2.38-21.46)). The quality of evidence (QOE) for lactate as indicator was moderate according to the GRADE approach, whereas the QOE for other biomarkers was very low to low likely as consequence of study design characteristics such as single study, small sample size, and large ranges of sensitivity or specificity. Lactate is an early indicator to predict EAD after LT (Quality of Evidence: Moderate | Grade of Recommendation: Strong). Further multicenter studies and the use of machine perfusion setting should be implemented for validation.
Sections du résumé
BACKGROUND
Prompt identification of early allograft dysfunction (EAD) is critical to reduce morbidity and mortality in liver transplant (LT) recipients.
OBJECTIVES
Evaluate the evidence supporting biomarkers that can provide diagnostic and predictive value for EAD.
DATA SOURCES
Ovid MEDLINE, Embase, Scopus, Google Scholar, and Cochrane Central.
METHODS
Systematic review following PRISMA guidelines and recommendations using the GRADE approach was derived from an international expert panel. Studies that investigated biomarkers or models for predicting EAD in adult LT recipients were included for in-depth evaluation and meta-analysis. Olthoff's criteria were used as the standard reference for the diagnostic accuracy evaluation.
PROSPERO ID
CRD42021293838 RESULTS: Ten studies were included for the systematic review. Lactate, lactate clearance, uric acid, Factor V, HMGB-1, CRP to ALB ratio, phosphocholine, total cholesterol, and metabolomic predictive model were identified as potential early EAD predictive biomarkers. The sensitivity ranged between .39 and .92, while the specificity ranged from .63 to .90. Elevated lactate level was most indicative of EAD after adult LT (pooled diagnostic odds ratio of 7.15 (95%CI: 2.38-21.46)). The quality of evidence (QOE) for lactate as indicator was moderate according to the GRADE approach, whereas the QOE for other biomarkers was very low to low likely as consequence of study design characteristics such as single study, small sample size, and large ranges of sensitivity or specificity.
CONCLUSIONS
Lactate is an early indicator to predict EAD after LT (Quality of Evidence: Moderate | Grade of Recommendation: Strong). Further multicenter studies and the use of machine perfusion setting should be implemented for validation.
Substances chimiques
Biomarkers
0
Lactic Acid
33X04XA5AT
Types de publication
Systematic Review
Meta-Analysis
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e14635Investigateurs
Claus Niemann
(C)
Joerg-Matthias Pollok
(JM)
Marina Berenguer
(M)
Pascale Tinguely
(P)
Informations de copyright
© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Références
Merion RM, Schaubel DE, Dykstra DM, Freeman RB, Port FK, Wolfe RA. The survival benefit of liver transplantation. Am J Transplant. 2005;5(2):307-313.
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 Transplant. 2010;16(8):943-949.
Deschênes M, Belle SH, Krom RA, Zetterman RK, Lake JR. Early allograft dysfunction after liver transplantation: a definition and predictors of outcome1. Transplantation. 1998;66(3):302-310.
Deschenes M. Early allograft dysfunction: causes, recognition, and management. Liver Transplant. 2013;19(S2):S6-S8.
Ljungqvist O, Scott M, Fearon KC. Enhanced recovery after surgery: a review. JAMA Surg. 2017;152(3):292-298.
Gustafsson U, Scott M, Schwenk W, et al. Guidelines for perioperative care in elective colonic surgery: Enhanced Recovery After Surgery (ERAS®) Society recommendations. World J Surg. 2013;37(2):259-284.
Lee DD, Croome KP, Shalev JA, et al. Early allograft dysfunction after liver transplantation: an intermediate outcome measure for targeted improvements. Ann Hepatol. 2016;15(1):53-60. https://doi.org/10.5604/16652681.1184212
Friedman BH, Wolf JH, Wang L, et al. Serum cytokine profiles associated with early allograft dysfunction in patients undergoing liver transplantation. Liver Transplant. 2012;18(2):166-176.
Li L, Wang H, Yang J, et al. Immediate postoperative low platelet counts after living donor liver transplantation predict early allograft dysfunction. Medicine. 2015;94(34)
Tsai H-I, Lo C-J, Zheng C-W, et al. A lipidomics study reveals lipid signatures associated with early allograft dysfunction in living donor liver transplantation. J Clin Med. 2019;8(1):30.
Kim DG, Lee JY, Jung YB, et al. Clinical significance of lactate clearance for the development of early allograft dysfunction and short-term prognosis in deceased donor liver transplantation. Clin Transplant. 2017;31(12):e13136.
Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. Apr 2011;64(4):383-94. https://doi.org/10.1016/j.jclinepi.2010.04.026
Murad MH, Mustafa RA, Schunemann HJ, Sultan S, Santesso N. Rating the certainty in evidence in the absence of a single estimate of effect. Evid Based Med. Jun 2017;22(3):85-87. https://doi.org/10.1136/ebmed-2017-110668
Andrews J, Guyatt G, Oxman AD, et al. GRADE guidelines: 14. Going from evidence to recommendations: the significance and presentation of recommendations. J Clin Epidemiol. 2013;66(7):719-25. https://doi.org/10.1016/j.jclinepi.2012.03.013
Andrews JC, Schunemann HJ, Oxman AD, et al. GRADE guidelines: 15. Going from evidence to recommendation-determinants of a recommendation's direction and strength. J Clin Epidemiol. 2013;66(7):726-35. https://doi.org/10.1016/j.jclinepi.2013.02.003
Golse N, Guglielmo N, El Metni A, et al. Arterial lactate concentration at the end of liver transplantation is an early predictor of primary graft dysfunction. Ann Surg. 2019;270(1):131-138.
Yang J, Wang H-Q, Yang J-Y, et al. Role of the postoperative cholesterol in early allograft dysfunction and survival after living donor liver transplantation. Hepatobiliary Pancreatic Dis Int. 2017;16(6):610-616.
Faitot F, Besch C, Battini S, et al. Impact of real-time metabolomics in liver transplantation: Graft evaluation and donor-recipient matching. J Hepatol. 2018;68(4):699-706.
Sáez de la Fuente I, Sáez de la Fuente J, Molina Collado Z, et al. Combination of arterial lactate levels and cv-aco2/da-vo2 ratio to predict early allograft dysfunction after liver transplantation. Clin Transplant. 2021:e14482.
Gorgen A, Prediger C, Prediger JE, et al. Serum factor V is a continuous biomarker of graft dysfunction and a predictor of graft loss after liver transplantation. Transplantation. 2019;103(5):944-951.
Hu LM, Tsai HI, Lee CW, Chen HM, Lee WC, Yu HP. Uric Acid as a Predictor for Early Allograft Dysfunction after Living Donor Liver Transplantation: A Prospective Observational Study. J Clin Med. 2021;10(12). https://doi.org/10.3390/jcm10122729
Park J, Lim SJ, Choi HJ, et al. Predictive utility of the C-reactive protein to albumin ratio in early allograft dysfunction in living donor liver transplantation: A retrospective observational cohort study. PLoS One. 2019;14(12):e0226369. https://doi.org/10.1371/journal.pone.0226369
Houben P, Hohenberger R, Yamanaka K, Buchler MW, Schemmer P. Evaluation of Graft Effluent High Mobility Group Box-1 (HMGB-1) for Prediction of Outcome After Liver Transplantation. Ann Transplant. 2018;23:475-480.
Takahashi K, Jafri SR, Safwan M, Abouljoud MS, Nagai S. Peri-transplant lactate levels and delayed lactate clearance as predictive factors for poor outcomes after liver transplantation: A propensity score-matched study. Clin Transplant. 2019;33(7):e13613. https://doi.org/10.1111/ctr.13613
Cortes M, Pareja E, Garcia-Canaveras JC, et al. Metabolomics discloses donor liver biomarkers associated with early allograft dysfunction. J Hepatol. 2014;61(3):564-74. https://doi.org/10.1016/j.jhep.2014.04.023
De Gasperi A, Mazza E, Corti A, et al. Lactate blood levels in the perioperative period of orthotopic liver transplantation. Int J Clin Lab Res. 1997;27(2):123-128.
Wu J-F, Wu R-Y, Chen J, Ou-Yang B, Chen M-Y, Guan X-D. Early lactate clearance as a reliable predictor of initial poor graft function after orthotopic liver transplantation. Hepatobiliary Pancreatic Dis Int. 2011;10(6):587-592.
Nishimura A, Hakamada K, Narumi S, et al. Intraoperative blood lactate level as an early predictor of initial graft function in human living donor liver transplantation. Elsevier; 2004:2246-2248.
Zhang Z, Tang Y, Zhao Q, et al. Association of perfusion characteristics and posttransplant liver function in ischemia-free liver transplantation. Liver Transplant. 2020;26(11):1441-1454.
Andersen LW, Mackenhauer J, Roberts JC, Berg KM, Cocchi MN, Donnino MW. Etiology and therapeutic approach to elevated lactate levels. Elsevier; 2013:1127-1140.
Nichol A, Bailey M, Egi M, et al. Dynamic lactate indices as predictors of outcome in critically ill patients. Crit Care. 2011/10/20 2011;15(5):R242. https://doi.org/10.1186/cc10497
Rabinowitz JD, Enerbäck S. Lactate: the ugly duckling of energy metabolism. Nat Metab. 2020;2(7):566-571. https://doi.org/10.1038/s42255-020-0243-4
Pareja E, Cortes M, Hervás D, et al. A score model for the continuous grading of early allograft dysfunction severity. Liver Transplant. 2015;21(1):38-46.
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(5):436-444.
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(12):e204095-e204095.
Richards JA, Sherif AE, Butler AJ, et al. Model for early allograft function is predictive of early graft loss in donation after circulatory death liver transplantation. Clin Transplant. 2020;34(8):e13982.
Dutkowski P, Guarrera JV, de Jonge J, Martins PN, Porte RJ, Clavien PA. Evolving Trends in Machine Perfusion for Liver Transplantation. Gastroenterology. 2019;156(6):1542-1547. https://doi.org/10.1053/j.gastro.2018.12.037
Yeh H, Uygun K. Increasing Donor Liver Utilization Through Machine Perfusion. Hepatology. 2019;70(1):431-433. https://doi.org/10.1002/hep.30523
Czigany Z, Tacke F, Lurje G. Evolving Trends in Machine Liver Perfusion: Comments on Clinical End Points and Selection Criteria. Gastroenterology. 2019;157(4):1166-1167. https://doi.org/10.1053/j.gastro.2019.02.051
Quintini C, Martins PN, Shah S, et al. Implementing an innovated preservation technology: The American Society of Transplant Surgeons' (ASTS) Standards Committee White Paper on Ex Situ Liver Machine Perfusion. Am J Transplant. 2018;18(8):1865-1874. https://doi.org/10.1111/ajt.14945
Mergental H, Laing RW, Kirkham AJ, et al. Transplantation of discarded livers following viability testing with normothermic machine perfusion. Nat Commun. 2020;11(1):2939. https://doi.org/10.1038/s41467-020-16251-3
van Leeuwen OB, de Vries Y, Fujiyoshi M, et al. Transplantation of High-risk Donor Livers After Ex Situ Resuscitation and Assessment Using Combined Hypo- and Normothermic Machine Perfusion: A Prospective Clinical Trial. Ann Surg. 2019;270(5):906-914. https://doi.org/10.1097/SLA.0000000000003540
Watson CJE, Kosmoliaptsis V, Pley C, et al. Observations on the ex situ perfusion of livers for transplantation. Am J Transplant. 2018;18(8):2005-2020. https://doi.org/10.1111/ajt.14687