Aleksandra Klisic 1 , Aleksandra Isakovic 2 , Gordana Kocic 3 , Nebojsa Kavaric 1 , Milovan Jovanovic 1 , Elvir Zvrko 4 , Verica Skerovic 4 , Ana Ninic 5 Show Affiliations »
Abstract
INTRODUCTION/AIM: Considering the high prevalence of non-alcoholic fatty liver disease (NAFLD) in individuals with type 2 diabetes mellitus (DM2), we aimed to investigate the potential benefit of determining markers of oxidative stress, inflammation and dyslipidemia for prediction of NAFLD, as estimated with fatty liver index (FLI) in individuals with DM2. METHODS: A total of 139 individuals with DM2 (of them 49.9% females) were enrolled in cross-sectional study. Anthropometric and biochemical parameters, as well as blood pressure were obtained. A FLI was calculated. RESULTS: Multivariate logistic regression analysis showed that high density lipoprotein cholesterol (HDL-c) and malondialdehyde (MDA) were independent predictors of higher FLI [Odds ratio (OR)=0.056, p=0.029; and OR=1.105, p=0.016, respectively]. In Receiver Operating Characteristic curve analysis, the addition of fatty liver risk factors (e. g., age, gender, body height, smoking status, diabetes duration and drugs metabolized in liver) to each analysed biochemical parameter [HDL-c, non-HDL-c, high sensitivity C-reactive protein (hsCRP), MDA and advanced oxidant protein products (AOPP)] in Model 1, increased the ability to discriminate patients with and without fatty liver [Area under the curve (AUC)=0.832, AUC=0.808, AUC=0.798, AUC=0.824 and AUC=0.743, respectively]. Model 2 (which included all five examined predictors, e. g., HDL-c, non-HDL-c, hsCRP, MDA, AOPP, and fatty liver risk factors) improved discriminative abilities for fatty liver status (AUC=0.909). Even more, Model 2 had the highest sensitivity and specificity (89.3% and 87.5%, respectively) together than each predictor in Model 1. CONCLUSION: Multimarker approach, including biomarkers of oxidative stress, dyslipidemia and inflammation, could be of benefit in identifying patients with diabetes being at high risk of fatty liver disease. © Georg Thieme Verlag KG Stuttgart · New York.
INTRODUCTION/AIM: Considering the high prevalence of non-alcoholic fatty liver disease (NAFLD) in individuals with type 2 diabetes mellitus (DM2 ), we aimed to investigate the potential benefit of determining markers of oxidative stress, inflammation and dyslipidemia for prediction of NAFLD, as estimated with fatty liver index (FLI) in individuals with DM2 . METHODS: A total of 139 individuals with DM2 (of them 49.9% females) were enrolled in cross-sectional study. Anthropometric and biochemical parameters, as well as blood pressure were obtained. A FLI was calculated. RESULTS: Multivariate logistic regression analysis showed that high density lipoprotein cholesterol (HDL-c) and malondialdehyde (MDA) were independent predictors of higher FLI [Odds ratio (OR)=0.056, p=0.029; and OR=1.105, p=0.016, respectively]. In Receiver Operating Characteristic curve analysis, the addition of fatty liver risk factors (e. g., age, gender, body height, smoking status, diabetes duration and drugs metabolized in liver) to each analysed biochemical parameter [HDL-c, non-HDL-c, high sensitivity C-reactive protein (hsCRP), MDA and advanced oxidant protein products (AOPP)] in Model 1, increased the ability to discriminate patients with and without fatty liver [Area under the curve (AUC)=0.832, AUC=0.808, AUC=0.798, AUC=0.824 and AUC=0.743, respectively]. Model 2 (which included all five examined predictors, e. g., HDL-c, non-HDL-c, hsCRP, MDA, AOPP, and fatty liver risk factors) improved discriminative abilities for fatty liver status (AUC=0.909). Even more, Model 2 had the highest sensitivity and specificity (89.3% and 87.5%, respectively) together than each predictor in Model 1. CONCLUSION: Multimarker approach, including biomarkers of oxidative stress, dyslipidemia and inflammation , could be of benefit in identifying patients with diabetes being at high risk of fatty liver disease . © Georg Thieme Verlag KG Stuttgart · New York.
Entities: Chemical
Disease
Gene
Species
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Year: 2017
PMID： 28895641 DOI： 10.1055/s-0043-118667
Source DB: PubMed Journal: Exp Clin Endocrinol Diabetes ISSN： 0947-7349 Impact factor: 2.949