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Gierej P, Radziszewski M, Figiel W, Grąt M. Advancements in Predictive Tools for Primary Graft Dysfunction in Liver Transplantation: A Comprehensive Review. J Clin Med 2024; 13:3762. [PMID: 38999328 PMCID: PMC11242128 DOI: 10.3390/jcm13133762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 06/20/2024] [Accepted: 06/24/2024] [Indexed: 07/14/2024] Open
Abstract
Orthotopic liver transplantation stands as the sole curative solution for end-stage liver disease. Nevertheless, the discrepancy between the demand and supply of grafts in transplant medicine greatly limits the success of this treatment. The increasing global shortage of organs necessitates the utilization of extended criteria donors (ECD) for liver transplantation, thereby increasing the risk of primary graft dysfunction (PGD). Primary graft dysfunction (PGD) encompasses early allograft dysfunction (EAD) and the more severe primary nonfunction (PNF), both of which stem from ischemia-reperfusion injury (IRI) and mitochondrial damage. Currently, the only effective treatment for PNF is secondary transplantation within the initial post-transplant week, and the occurrence of EAD suggests an elevated, albeit still uncertain, likelihood of retransplantation urgency. Nonetheless, the ongoing exploration of novel IRI mitigation strategies offers hope for future improvements in PGD outcomes. Establishing an intuitive and reliable tool to predict upcoming graft dysfunction is vital for early identification of high-risk patients and for making informed retransplantation decisions. Accurate diagnostics for PNF and EAD constitute essential initial steps in implementing future mitigation strategies. Recently, novel methods for PNF prediction have been developed, and several models for EAD assessments have been introduced. Here, we provide an overview of the currently scrutinized predictive tools for PNF and EAD evaluation strategies, accompanied by recommendations for future studies.
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Affiliation(s)
- Piotr Gierej
- Department of General Transplant and Liver Surgery, Medical University of Warsaw, 02-091 Warsaw, Poland
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Galli AM, Kothari R, Adelmann D, Holm Z, Bokoch MP, De Gasperi A, Niemann CU, Kolodzie K. Lactate concentration at the end of liver transplant: Early predictor of graft function or just one piece of the puzzle? Clin Transplant 2023; 37:e15057. [PMID: 37350743 DOI: 10.1111/ctr.15057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/05/2023] [Accepted: 06/11/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND The post-operative course after Liver Transplantation (LT) can be complicated by early allograft dysfunction (EAD), primary nonfunction (PNF) and death. A lactate concentration at the end of transplant of ≥5 mmol/L was recently proposed as a predictive marker of PNF, EAD, and mortality; this study aimed to validate these previous reports in a large single center cohort. METHODS This retrospective cohort study included adult liver transplant recipients who received grafts from deceased donors at our center between June 2012 and May 2021. Receiver operating characteristic (ROC) curves for the lactate concentration at the end of transplantation were computed to determine the AUC for PNF, EAD and mortality at 90 days. RESULTS In our cohort of 1137 cases, the AUCs for lactate to predict EAD, PNF and mortality were respectively .56 (95% confidence interval [CI]: .53-.60), .69 (95% CI: .52-.85), and .74 (95% CI: .63-.84). CONCLUSION The clinical value of lactate concentration at the end of transplantation to predict PNF, EAD and mortality at 90 days was, at best, modest, as shown by the relatively low AUCs. Our findings cannot validate previous reports that the lactate level alone is a good predictor of poor outcomes after liver transplantation.
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Affiliation(s)
- Alessandro M Galli
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
- Department of Critical Care Medicine and Anesthesia, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Rishi Kothari
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
| | - Dieter Adelmann
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
| | - Zacharias Holm
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
- University of Copenhagen, Copenhagen, Denmark
| | - Michael P Bokoch
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
| | - Andrea De Gasperi
- Division of Transplant Surgery, Department of Surgery, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Claus U Niemann
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
- Division of Transplant Surgery, Department of Surgery, University of California San Francisco, San Francisco, California, USA
| | - Kerstin Kolodzie
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California, USA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, USA
- Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, California, USA
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Wang Z, Zhang L, Li S, Xu F, Han D, Wang H, Huang T, Yin H, Lyu J. The relationship between hematocrit and serum albumin levels difference and mortality in elderly sepsis patients in intensive care units-a retrospective study based on two large database. BMC Infect Dis 2022; 22:629. [PMID: 35850582 PMCID: PMC9295343 DOI: 10.1186/s12879-022-07609-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 07/12/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sepsis still threatens the lives of more than 300 million patients annually and elderly patients with sepsis usually have a more complicated condition and a worse prognosis. Existing studies have shown that both Hematocrit (HCT) and albumin (ALB) can be used as potential predictors of sepsis, and their difference HCT-ALB has a significant capacity to diagnose infectious diseases. Currently, there is no relevant research on the relationship between HCT-ALB and the prognosis of elderly sepsis patients. Therefore, this study aims to explore the association between HCT-ALB and mortality in elderly patients with sepsis. METHODS This study was a multi-center retrospective study based on the Medical Information Mart for Intensive Care (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) in elderly patients with sepsis. The optimal HCT-ALB cut-off point for ICU mortality was calculated by the Youden Index based on the eICU-CRD dataset, and multivariate logistic regressions were conducted to explore the association between HCT-ALB and ICU/hospital mortality in the two databases. Subgroup analyses were performed for different parameters and comorbidity status. RESULTS The number of 16,127 and 3043 elderly sepsis patients were selected from two large intensive care databases (eICU-CRD and MIMIC-IV, respectively) in this study. Depending on the optimal cut-off point, patients in both eICU-CRD and MIMIC-IV were independently divided into low HCT-ALB (< 6.7) and high HCT-ALB (≥ 6.7) groups. The odds ratio (95%confidence interval) [OR (95CI%)] of the high HCT-ALB group were 1.50 (1.36,1.65) and 1.71 (1.58,1.87) for ICU and hospital mortality in the eICU-CRD database after multivariable adjustment. Similar trends in the ICU and hospital mortality [OR (95%CI) 1.41 (1.15,1.72) and 1.27 (1.07,1.51)] were observed in MIMIC-IV database. Subgroup analysis showed an interaction effect with SOFA score in the eICU-CRD database however not in MIMIC-IV dataset. CONCLUSIONS High HCT-ALB (≥ 6.7) is associated with 1.41 and 1.27 times ICU and hospital mortality risk in elderly patients with sepsis. HCT-ALB is simple and easy to obtain and is a promising clinical predictor of early risk stratification for elderly sepsis patients in ICU.
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Affiliation(s)
- Zichen Wang
- Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, People's Republic of China.,Department of Public Health, University of California, Irvine, CA, USA
| | - Luming Zhang
- Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, People's Republic of China.,Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Shaojin Li
- Department of Orthopaedics, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, People's Republic of China
| | - Fengshuo Xu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Didi Han
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Hao Wang
- Department of Statistics, Iowa State University, Ames, USA
| | - Tao Huang
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Haiyan Yin
- Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, People's Republic of China.
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China. .,Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou, Guangdong, China.
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