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      The associations between changes in hepatic steatosis and heart failure and mortality: a nationwide cohort study

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          Abstract

          Background

          Non-alcoholic fatty liver disease (NAFLD) is a well-known risk factor for cardiovascular (CV) disease (CVD) and mortality. However, whether the progression or regression of NAFLD can increase or decrease the risk of heart failure (HF) and mortality has not been fully evaluated. We investigated the association between changes in hepatic steatosis and the risks of incident HF (iHF), hospitalization for HF (hHF), and mortality including CV- or liver-related mortality.

          Methods

          Using a database from the National Health Insurance Service in Korea from January 2009 to December 2012, we analyzed 240,301 individuals who underwent health check-ups at least twice in two years. Hepatic steatosis was assessed using the fatty liver index (FLI), with an FLI ≥ 60 considered to indicate the presence of hepatic steatosis. According to FLI changes, participants were divided into four groups. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using multivariable Cox proportional hazards regression models.

          Results

          Persistent hepatic steatosis increased the risk of iHF, hHF, and mortality including CV- and liver-related mortality compared with the group that never had steatosis (all P < 0.05). Incident hepatic steatosis was associated with increased risk for iHF and mortality including CV- or liver-related mortality (all P < 0.05). Compared with persistent steatosis, regression of hepatic steatosis was associated with decreased risk for iHF, hHF, and liver-related mortality (iHF, HR [95% CI], 0.800 [0.691–0.925]; hHF, 0.645 [0.514–0.810]; liver-related mortality, 0.434 [0.223–0.846]).

          Conclusions

          FLI changes were associated with increased or decreased risk of HF outcomes and mortality.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12933-022-01725-z.

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          Most cited references52

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          The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases.

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            NAFLD: a multisystem disease.

            Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in Western countries that is predicted to become also the most frequent indication for liver transplantation by 2030. Over the last decade, it has been shown that the clinical burden of NAFLD is not only confined to liver-related morbidity and mortality, but there is now growing evidence that NAFLD is a multisystem disease, affecting extra-hepatic organs and regulatory pathways. For example, NAFLD increases risk of type 2 diabetes mellitus (T2DM), cardiovascular (CVD) and cardiac diseases, and chronic kidney disease (CKD). Although the primary liver pathology in NAFLD affects hepatic structure and function to cause morbidity and mortality from cirrhosis, liver failure and hepatocellular carcinoma, the majority of deaths among NAFLD patients are attributable to CVD. This narrative review focuses on the rapidly expanding body of clinical evidence that supports the concept of NAFLD as a multisystem disease. The review discusses the factors involved in the progression of liver disease in NAFLD and the factors linking NAFLD with other extra-hepatic chronic diseases, such as T2DM, CVD, cardiac diseases and CKD. The review will not discuss NAFLD treatments as these are discussed elsewhere in this issue of the Journal. For this review, PubMed was searched for articles using the keywords "non-alcoholic fatty liver disease" or "fatty liver" combined with "diabetes", "cardiovascular (or cardiac) disease", "cardiovascular mortality" or "chronic kidney disease" between 1990 and 2014. Articles published in languages other than English were excluded.
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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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                Author and article information

                Contributors
                jaehyeon@skku.edu
                Journal
                Cardiovasc Diabetol
                Cardiovasc Diabetol
                Cardiovascular Diabetology
                BioMed Central (London )
                1475-2840
                23 December 2022
                23 December 2022
                2022
                : 21
                : 287
                Affiliations
                [1 ]GRID grid.410886.3, ISNI 0000 0004 0647 3511, Department of Internal Medicine, CHA Bundang Medical Center, , CHA University School of Medicine, ; Seongnam, 13496 Republic of Korea
                [2 ]GRID grid.264381.a, ISNI 0000 0001 2181 989X, Sungkyunkwan University School of Medicine, ; Seoul, Republic of Korea
                [3 ]GRID grid.264381.a, ISNI 0000 0001 2181 989X, Department of Medicine, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; 81, Irwon-Ro, Gangnam-Gu, Seoul, 06351 Republic of Korea
                [4 ]GRID grid.488317.1, ISNI 0000 0004 0626 1869, Data Science Team, Hanmi Pharm. Co. Ltd, ; Seoul, Republic of Korea
                [5 ]Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences and Technology, Seoul, Republic of Korea
                Article
                1725
                10.1186/s12933-022-01725-z
                9789584
                36564787
                2ebd6d2c-344c-4123-ae9d-19fa8bf44790
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 24 August 2022
                : 12 December 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Endocrinology & Diabetes
                fatty liver index,heart failure,mortality,non-alcoholic fatty liver disease

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