摘要Background:Primary non-function(PNF)and early allograft failure(EAF)after liver transplantation(LT)seriously affect patient outcomes.In clinical practice,effective prognostic tools for early identifying recip-ients at high risk of PNF and EAF were urgently needed.Recently,the Model for Early Allograft Function(MEAF),PNF score by King's College(King-PNF)and Balance-and-Risk-Lactate(BAR-Lac)score were de-veloped to assess the risks of PNF and EAF.This study aimed to externally validate and compare the prognostic performance of these three scores for predicting PNF and EAF.Methods:A retrospective study included 720 patients with primary LT between January 2015 and De-cember 2020.MEAF,King-PNF and BAR-Lac scores were compared using receiver operating characteristic(ROC)and the net reclassification improvement(NRI)and integrated discrimination improvement(IDI)analyses.Results:Of all 720 patients,28(3.9％)developed PNF and 67(9.3％)developed EAF in 3 months.The overall early allograft dysfunction(EAD)rate was 39.0％.The 3-month patient mortality was 8.6％while 1-year graft-failure-free survival was 89.2％.The median MEAF,King-PNF and BAR-Lac scores were 5.0(3.5-6.3),-2.1(-2.6 to-1.2),and 5.0(2.0-11.0),respectively.For predicting PNF,MEAF and King-PNF scores had excellent area under curves(AUCs)of 0.872 and 0.891,superior to BAR-Lac(AUC=0.830).The NRI and IDI analyses confirmed that King-PNF score had the best performance in predicting PNF while MEAF served as a better predictor of EAD.The EAF risk curve and 1-year graft-failure-free survival curve showed that King-PNF was superior to MEAF and BAR-Lac scores for stratifying the risk of EAF.Conclusions:MEAF,King-PNF and BAR-Lac were validated as practical and effective risk assessment tools of PNF.King-PNF score outperformed MEAF and BAR-Lac in predicting PNF and EAF within 6 months.BAR-Lac score had a huge advantage in the prediction for PNF without post-transplant variables.Proper use of these scores will help early identify PNF,standardize grading of EAF and reasonably select clinical endpoints in relative studies.