Value Of The Prediction Of Post-hepatectomy Liver Failure By Parameters Of Liver Fibrosis

Background:Post hepatectomy liver failure(PHLF)is one of the most common complication following the hepatic resection,which is one of the major cause of hepatectomy related mortality.In recent years,several methods are used to estimate liver function,Including routine blood examinations and indocyanine green clearance test.hepatic fibrosis biomarkers have been shown to predict Post-hepatectomy liver failure accurately.Methods:This study Included 60 patients who underwent hepatic-resection surgery in the First Affiliated Hospital of Zhejiang University.And we analyzed the data of the patients retrospectively while identified whether they suffered Post-hepatectomy liver failure.And all patients were underwent indocyanine green clearance test and had complete clinical data and laboratory examination.Chi-square test,independent sample t-test,Logistic regression analyze and ROC curve analysis were used to analyze the data.Results:Among the 60 patients who underwent hepatic-resection surgery,Post-hepatectomy liver failure occurred in 21 patients.Chi-square test and independent samples T test found indocyanine green 15 minutes retention rate(P = 0.024),the international standardization ratio(P = 0.015),plasma albumin(P = 0.004),FIB4 index(P = 0.049)and intraoperative blood loss(P = 0.014)exist significant differences between the two groups.Logistic regression analysis was used to analyze the four measures and found that plasma albumin(OR 0.851,95%Cl 0.752-0.963),FIB4 index(OR 1.540,95%Cl 1.030-2.304)were independent risk factors for post hepatectomy liver failure.The accuracy of the model combining with plasma albumin and FIB4 index for the prediction of Post hepatectomy liver failure is higher(0.811,95%Cl 0.689-0.900).Conclusion:The FIB4 index have predictive value for the prediction of Post-hepatectomy liver failure.FIB4 and plasma albumin are independent risk factors of Post-hepatectomy liver failure.The multivariate logistic regression model can effectively estimate the risk of Post-hepatectomy liver failure.