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      Favorable effect of sodium–glucose cotransporter 2 inhibitor, dapagliflozin, on non‐alcoholic fatty liver disease compared with pioglitazone

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          Abstract

          Aims/Introduction

          Sodium–glucose cotransporter 2 inhibitors, as well as thiazolidines, suppress nonalcoholic fatty liver disease (NAFLD); however, few comparative studies have been reported. Dapagliflozin has shown non‐inferiority compared with pioglitazone for glycemic control, and superiority regarding weight reduction in patients with type 2 diabetes. We carried out a secondary analysis for the favorable effects of sodium–glucose cotransporter inhibitors for NAFLD.

          Materials and Methods

          In this multicenter, open‐label, prospective, randomized, parallel‐group comparison trial, patients taking pioglitazone for ≥12 weeks were randomly switched to dapagliflozin or continued pioglitazone for a further 24 weeks. The fatty liver index (FLI), consisting of body mass index, triglycerides, waist circumference and γ‐glutamyl transpeptidase, was used for the evaluation of NAFLD.

          Results

          A total of 53 participants with NAFLD (27 dapagliflozin; 26 pioglitazone) were included in this analysis. FLI decreased significantly in the dapagliflozin group (48.7 ± 23.4 to 42.1 ± 23.9) compared with the pioglitazone group (49.0 ± 26.1 to 51.1 ± 25.8; P < 0.01). Multiple linear regression analysis showed that the changes in FLI had a significantly positive correlation with changes in glycated hemoglobin ( P = 0.03) and insulin level ( P < 0.01) in the dapagliflozin group.

          Conclusion

          Dapagliflozin might be more beneficial than pioglitazone in patients with NAFLD. Improvements in FLI would be closely related to glycemic control.

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          Most cited references23

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          Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection.

          Liver biopsy remains the gold standard in the assessment of severity of liver disease. Noninvasive tests have gained popularity to predict histology in view of the associated risks of biopsy. However, many models include tests not readily available, and there are limited data from patients with HIV/hepatitis C virus (HCV) coinfection. We aimed to develop a model using routine tests to predict liver fibrosis in patients with HIV/HCV coinfection. A retrospective analysis of liver histology was performed in 832 patients. Liver fibrosis was assessed via Ishak score; patients were categorized as 0-1, 2-3, or 4-6 and were randomly assigned to training (n = 555) or validation (n = 277) sets. Multivariate logistic regression analysis revealed that platelet count (PLT), age, AST, and INR were significantly associated with fibrosis. Additional analysis revealed PLT, age, AST, and ALT as an alternative model. Based on this, a simple index (FIB-4) was developed: age ([yr] x AST [U/L]) / ((PLT [10(9)/L]) x (ALT [U/L])(1/2)). The AUROC of the index was 0.765 for differentiation between Ishak stage 0-3 and 4-6. At a cutoff of 3.25 had a positive predictive value of 65% and a specificity of 97%. Using these cutoffs, 87% of the 198 patients with FIB-4 values outside 1.45-3.25 would be correctly classified, and liver biopsy could be avoided in 71% of the validation group. In conclusion, noninvasive tests can accurately predict hepatic fibrosis and may reduce the need for liver biopsy in the majority of HIV/HCV-coinfected patients.
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            The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population

            Background Fatty liver (FL) is the most frequent liver disease in Western countries. We used data from the Dionysos Nutrition & Liver Study to develop a simple algorithm for the prediction of FL in the general population. Methods 216 subjects with and 280 without suspected liver disease were studied. FL was diagnosed by ultrasonography and alcohol intake was assessed using a 7-day diary. Bootstrapped stepwise logistic regression was used to identify potential predictors of FL among 13 variables of interest [gender, age, ethanol intake, alanine transaminase, aspartate transaminase, gamma-glutamyl-transferase (GGT), body mass index (BMI), waist circumference, sum of 4 skinfolds, glucose, insulin, triglycerides, and cholesterol]. Potential predictors were entered into stepwise logistic regression models with the aim of obtaining the most simple and accurate algorithm for the prediction of FL. Results An algorithm based on BMI, waist circumference, triglycerides and GGT had an accuracy of 0.84 (95%CI 0.81–0.87) in detecting FL. We used this algorithm to develop the "fatty liver index" (FLI), which varies between 0 and 100. A FLI < 30 (negative likelihood ratio = 0.2) rules out and a FLI ≥ 60 (positive likelihood ratio = 4.3) rules in fatty liver. Conclusion FLI is simple to obtain and may help physicians select subjects for liver ultrasonography and intensified lifestyle counseling, and researchers to select patients for epidemiologic studies. Validation of FLI in external populations is needed before it can be employed for these purposes.
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              Pioglitazone, Vitamin E, or Placebo for Nonalcoholic Steatohepatitis

              New England Journal of Medicine, 362(18), 1675-1685
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                Author and article information

                Contributors
                hmiyoshi@med.hokudai.ac.jp
                Journal
                J Diabetes Investig
                J Diabetes Investig
                10.1111/(ISSN)2040-1124
                JDI
                Journal of Diabetes Investigation
                John Wiley and Sons Inc. (Hoboken )
                2040-1116
                2040-1124
                02 December 2020
                July 2021
                : 12
                : 7 ( doiID: 10.1111/jdi.v12.7 )
                : 1272-1277
                Affiliations
                [ 1 ] Department of Rheumatology, Endocrinology and Nephrology Faculty of Medicine and Graduate School of Medicine Hokkaido University Sapporo Japan
                [ 2 ] Clinical Research and Medical Innovation Center Hokkaido University Hospital Sapporo Japan
                [ 3 ] Diabetes Center Manda Memorial Hospital Sapporo Japan
                [ 4 ] Kurihara Clinic Sapporo Japan
                [ 5 ] Aoki Clinic Sapporo Japan
                [ 6 ] Division of Diabetes and Obesity Faculty of Medicine and Graduate School of Medicine Hokkaido University Sapporo Japan
                Author notes
                [*] [* ] Correspondence

                Hideaki Miyoshi

                Tel.: +81‐11‐706‐8192

                Fax: +81‐11‐706‐8194

                E‐mail address: hmiyoshi@ 123456med.hokudai.ac.jp

                Author information
                https://orcid.org/0000-0002-3131-0832
                https://orcid.org/0000-0002-8192-0006
                https://orcid.org/0000-0001-5766-6047
                https://orcid.org/0000-0001-6089-2395
                https://orcid.org/0000-0002-3313-6946
                https://orcid.org/0000-0003-0713-221X
                https://orcid.org/0000-0003-1870-6688
                https://orcid.org/0000-0002-5909-3243
                Article
                JDI13457
                10.1111/jdi.13457
                8264405
                33131199
                3d6244af-eff5-47b9-a8ff-92c7324f515e
                © 2020 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 21 October 2020
                : 10 September 2020
                : 30 October 2020
                Page count
                Figures: 3, Tables: 3, Pages: 6, Words: 3978
                Categories
                Original Article
                Articles
                Clinical Science and Care
                Custom metadata
                2.0
                July 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.4 mode:remove_FC converted:08.07.2021

                fatty liver,sodium–glucose cotransporter 2 inhibitor,type 2 diabetes

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