scholarly journals Validation of Fatty Liver Index as a Marker for Metabolic Dysfunction-associated Fatty Liver Disease

Author(s):  
A lum Han ◽  
Youngjon Kim

Abstract Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a new nomenclature for non-alcoholic fatty liver. Fatty liver associated with metabolic dysfunction is increasing with obesity and has become a serious socioeconomic problem. Non-invasive testing to confirm MAFLD, such as the fatty liver index (FLI), can be used as an alternative method for diagnosing steatosis when imaging modalities are not available. To date, few studies have examined the effectiveness and validity of FLI for diagnosing MAFLD. Therefore, this study analyzed the effectiveness and validity of FLI for diagnosing MAFLD.Methods: The medical records of men and women aged 19 years or older who underwent abdominal computed tomography (CT) examination at the University Hospital Health Promotion Center from March 2012 to October 2019 were reviewed retrospectively. A comparative analysis between non-continuous variables was performed using the chi-squared test. The area under receiver operating characteristic (AUROC) curve was used to verify the effectiveness of FLI as a predictive index for MAFLD. Results: Analysis of the association between MAFLD and abdominal CT revealed that the sensitivity and specificity of FLI for diagnosing MAFLD were 0.712 and 0.713, respectively. The AUROC of FLI for the prediction of MAFLD was 0.776. Conclusion: Our study verified the accuracy of FLI for predicting MAFLD using CT. Additionally, FLI can be used as a simple and cost-effective tool for screening MAFLD in clinical settings.

2021 ◽  
Author(s):  
A lum Han ◽  
Youngjon Kim

Abstract Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a new nomenclature for non-alcoholic fatty liver. Fatty liver associated with metabolic dysfunction is increasing with obesity and has become a serious socioeconomic problem. Non-invasive testing to confirm MAFLD, such as the fatty liver index (FLI), can be used as an alternative method for diagnosing steatosis when imaging modalities are not available. To date, few studies have examined the effectiveness and validity of FLI for diagnosing MAFLD. Therefore, this study analyzed the effectiveness and validity of FLI for diagnosing MAFLD.Methods: The medical records of men and women aged 19 years or older who underwent abdominal computed tomography (CT) examination at the University Hospital Health Promotion Center from March 2012 to October 2019 were reviewed retrospectively. A comparative analysis between non-continuous variables was performed using the chi-squared test. The area under receiver operating characteristic (AUROC) curve was used to verify the effectiveness of FLI as a predictive index for MAFLD. Results: Analysis of the association between MAFLD and abdominal CT revealed that the sensitivity and specificity of FLI for diagnosing MAFLD were 0.712 and 0.713, respectively. The AUROC of FLI for the prediction of MAFLD was 0.776.Conclusion: Our study verified the accuracy of FLI for predicting MAFLD using CT. Additionally, FLI can be used as a simple and cost-effective tool for screening MAFLD in clinical settings


2021 ◽  
Author(s):  
A lum Han

Abstract Aims Metabolic dysfunction-associated fatty liver disease (MAFLD) is a new nomenclature for nonalcoholic fatty liver. Along with obesity, fatty liver associated with metabolic dysfunction is increasing and has become a serious socioeconomic problem. Non-invasive testing for the confirmation of MAFLD, including the fatty liver index (FLI), can be used as an alternative method for diagnosing steatosis when imaging modalities are not available. To date, few studies have examined the effectiveness and validity of FLI for diagnosing MAFLD. Therefore, this study analyzed the effectiveness and validity of FLI for diagnosing MAFLD. Methods Medical records of men and women aged ≥ 19 years who underwent abdominal computed tomography (CT) examination at our facility between March 2012 and October 2019 were retrospectively reviewed. A comparative analysis between non-continuous variables was performed using the chi-squared test. The area under receiver operating characteristic (AUROC) curve was used to verify the effectiveness of FLI as a predictive index for MAFLD. Results Analysis of the association between MAFLD and abdominal CT revealed that the sensitivity and specificity of FLI for diagnosing MAFLD were 0.712 and 0.713, respectively. The AUROC of FLI for predicting MAFLD was 0.776. Conclusions Our study verified the accuracy of FLI for predicting MAFLD using CT. The FLI can be used as a simple and cost-effective tool for screening MAFLD in clinical settings.


2016 ◽  
Vol 89 (1) ◽  
pp. 82-88 ◽  
Author(s):  
Cristina Alina Silaghi ◽  
Horatiu Silaghi ◽  
Horatiu Alexandru Colosi ◽  
Anca Elena Craciun ◽  
Anca Farcas ◽  
...  

Background and aims. We aimed to study prevalence  and the predictive factors of non-alcoholic fatty liver disease (NAFLD) defined by the fatty liver index (FLI) in type 2 diabetic patients (T2DM).Methods. Three hundred and eighty-one T2DM outpatients who regularly attended a Consulting Clinic in Cluj were retrospectivelly included. FLI, a surrogate steatosis biomarker based on body mass index (BMI), waist circumference (WC), triglycerides (TGL) and gammaglutamyl-transferase (GGT) was used to assess NAFLD in all patients. Anthropometric and biochemical parameters were measured. Hepatic steatosis (HS) was evaluated by ultrasonography.Results. NAFLD-FLI (defined as FLI >60) was correlated with HS evaluated by ultrasound (r=0.28; p<0.001). NAFLD-FLI was detected in 79% of T2DM. The prevalence of obesity in NAFLD-FLI patients was 80%. Of the patients with normal alanine aminotransferase (ALAT), 73.8 % had NAFLD. At univariate analysis, NAFLD-FLI was correlated with age (r= -0.14; p=0.007), sex (r=0.20; p<0.001), LDL cholesterol (r=0.12; p=0.032), HDL cholesterol (r = -0.13; p=0.015), ALAT (r=0.20; p<0.001) and ASAT (r=0.19; p<0.001). At multiple regression analysis, sex, ALAT and LDL-cholesterol were independent predictors of NAFLD-FLI. After logistic regression model, ALAT, LDL-cholesterol, HOMA-IR were good independent predictors of NAFLD-FLI.Conclusions. NAFLD-FLI could be useful to identify NAFLD in T2DM patients. Subjects with T2DM had a high prevalence of NADLD-FLI even with normal ALAT levels . Our findings showed that sex, ALAT, LDL cholesterol and IR were significant and independent factors associated with the presence of NAFLD in T2DM subjects.


2021 ◽  
Vol 21 (2) ◽  
pp. 56-62
Author(s):  
Seong-Won Park ◽  
A-Lum Han

Background: Many studies have been conducted to validate fatty liver index (FLI) as a marker for non-alcoholic fatty liver disease (NAFLD). However, there are insufficient data in Korea to verify the usefulness of FLI, and the results of these studies are contradictory. This study aimed to validate FLI as a marker for NAFLD in Korea. For better accuracy, computed tomography (CT) scan was used instead of ultrasound scan.Methods: A cross-sectional analysis was performed in 785 subjects who participated in a health examination. The participants were divided according to presence of NAFLD, which was determined by abdominal CT. Frequency analysis was performed on all results. The chi-square test and independent t-test were used to compare the differences between the non-NAFLD group and the NAFLD group in terms of general characteristics and blood tests. The ability of the FLI to detect (nonalcoholic) fatty liver was assessed using area under the receiver operator characteristic (AUROC) curve analysis.Results: FLI was significantly higher in the NAFLD group (42.48±27.63) than in the non-NAFLD group (22.59±20.05) (P<0.0001). The algorithm for FLI had a better AUROC of 0.696 (95% confidence interval, 0.649-0.742) than any other variable in the prediction of NAFLD.Conclusions: FLI is a marker that can be used as a simple and cost-effective tool to screen for NAFLD.


2018 ◽  
Vol 18 (2) ◽  
Author(s):  
Zahra Dehnavi ◽  
Farkhonde Razmpour ◽  
Mahmoud Belghaisi Naseri ◽  
Mohsen Nematy ◽  
Seyed Ali Alamdaran ◽  
...  

2013 ◽  
Vol 144 (5) ◽  
pp. S-125 ◽  
Author(s):  
J. Michael Estep ◽  
Nayeem Hossain ◽  
Munkhzul Otgonsuren ◽  
Elena Younossi ◽  
Heshaam M. Mir ◽  
...  

2020 ◽  
Vol 39 (2) ◽  
pp. 468-474 ◽  
Author(s):  
Nima Motamed ◽  
Amir Hossein Faraji ◽  
Mahmood Reza Khonsari ◽  
Mansooreh Maadi ◽  
Fahimeh Safarnezhad Tameshkel ◽  
...  

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