Prediction of Graft Survival Post-liver Transplantation by L-GrAFT Risk Score Model, EASE Score, MEAF Scoring, and EAD

Shirui Chen, Tielong Wang, Tao Luo, Shujiao He, Changjun Huang, Zehua Jia, Liqiang Zhan, Dongping Wang, Xiaofeng Zhu, Zhiyong Guo, Xiaoshun He

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: Early allograft dysfunction (EAD) is correlated with poor patient or graft survival in liver transplantation. However, the power of distinct definitions of EAD in prediction of graft survival is unclear. Methods: This retrospective, single-center study reviewed data of 677 recipients undergoing orthotopic liver transplant between July 2015 and June 2020. The following EAD definitions were compared: liver graft assessment following transplantation (L-GrAFT) risk score model, early allograft failure simplified estimation score (EASE), model for early allograft function (MEAF) scoring, and Olthoff criteria. Risk factors for L-GrAFT7 high risk group were evaluated with univariate and multivariable logistic regression analysis. Results: L-GrAFT7 had a satisfied C-statistic of 0.87 in predicting a 3-month graft survival which significantly outperformed MEAF (C-statistic = 0.78, P = 0.01) and EAD (C-statistic = 0.75, P < 0.001), respectively. L-GrAFT10, EASE was similar to L-GrAFT7, and they had no statistical significance in predicting survival. Laboratory model for end-stage liver disease score and cold ischemia time are risk factors of L-GrAFT7 high-risk group. Conclusion: L-GrAFT7 risk score is capable for better predicting the 3-month graft survival than the MEAF and EAD in a Chinese cohort, which might standardize assessment of early graft function and serve as a surrogate endpoint in clinical trial.

Original languageEnglish (US)
Article number753056
JournalFrontiers in Surgery
Volume8
DOIs
StatePublished - Nov 19 2021

Keywords

  • graft survival
  • machine perfusion
  • orthotopic liver transplantation
  • patient survivability
  • risk factor
  • risk prediction model

ASJC Scopus subject areas

  • Surgery

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