A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity
The global prevalence of non-alcoholic fatty liver disease (NAFLD) has attained a level of 25.24%. The prevalence of NAFLD in China has exhibited an upward trajectory in parallel with the increasing incidence of obesity over the preceding decade. In order to comprehensively assess hepatic lipid depo...
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The Japan Endocrine Society
2023-10-01
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Series: | Endocrine Journal |
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Online Access: | https://www.jstage.jst.go.jp/article/endocrj/70/10/70_EJ23-0227/_html/-char/en |
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author | Jie Chen Jiang Yue Jingjing Fu Shengyun He Qianjing Liu Minglan Yang Wang Zhang Hua Xu Qing Lu Jing Ma |
author_facet | Jie Chen Jiang Yue Jingjing Fu Shengyun He Qianjing Liu Minglan Yang Wang Zhang Hua Xu Qing Lu Jing Ma |
author_sort | Jie Chen |
collection | DOAJ |
description | The global prevalence of non-alcoholic fatty liver disease (NAFLD) has attained a level of 25.24%. The prevalence of NAFLD in China has exhibited an upward trajectory in parallel with the increasing incidence of obesity over the preceding decade. In order to comprehensively assess hepatic lipid deposition in individuals with overweight or obesity, we have devised a pioneering prognostic formula that capitalizes on clinical parameters. To this end, we have conducted a cross-sectional cohort study involving 149 overweight or obese subjects. Magnetic resonance imaging proton density fat fraction (MRI-PDFF) has been employed to evaluate the extent of liver fat accumulation. Through univariate analysis, we have identified potential factors, and the definitive elements in the prediction model were selected utilizing the forward stepwise regression algorithm. The Shang Hai Steatosis Index (SHSI) incorporates alanine aminotransferase (ALT), aspartate aminotransferase (AST), fasting insulin, and 1-h postload glycaemic levels, thereby furnishing the capability to predict NAFLD with an area under the receiver operator characteristic (AUROC) of 0.87. By establishing a threshold value of 10.96, determined through Youden’s index, we have achieved a sensitivity of 69.57% and a specificity of 88.24%. The Spearman correlation coefficient between liver fat fraction ascertained by MRI-PDFF and that predicted by the SHSI equation amounts to 0.74. Consequently, the SHSI equation affords a dependable means of predicting the presence of NAFLD and liver fat accumulation within the overweight and obese population. |
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id | doaj-art-62a8bad5af4d4fcc96365c276d98a6f6 |
institution | Kabale University |
issn | 1348-4540 |
language | English |
publishDate | 2023-10-01 |
publisher | The Japan Endocrine Society |
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series | Endocrine Journal |
spelling | doaj-art-62a8bad5af4d4fcc96365c276d98a6f62025-01-22T06:19:20ZengThe Japan Endocrine SocietyEndocrine Journal1348-45402023-10-01701097798510.1507/endocrj.EJ23-0227endocrjA prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesityJie Chen0Jiang Yue1Jingjing Fu2Shengyun He3Qianjing Liu4Minglan Yang5Wang Zhang6Hua Xu7Qing Lu8Jing Ma9Department of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, ChinaThe global prevalence of non-alcoholic fatty liver disease (NAFLD) has attained a level of 25.24%. The prevalence of NAFLD in China has exhibited an upward trajectory in parallel with the increasing incidence of obesity over the preceding decade. In order to comprehensively assess hepatic lipid deposition in individuals with overweight or obesity, we have devised a pioneering prognostic formula that capitalizes on clinical parameters. To this end, we have conducted a cross-sectional cohort study involving 149 overweight or obese subjects. Magnetic resonance imaging proton density fat fraction (MRI-PDFF) has been employed to evaluate the extent of liver fat accumulation. Through univariate analysis, we have identified potential factors, and the definitive elements in the prediction model were selected utilizing the forward stepwise regression algorithm. The Shang Hai Steatosis Index (SHSI) incorporates alanine aminotransferase (ALT), aspartate aminotransferase (AST), fasting insulin, and 1-h postload glycaemic levels, thereby furnishing the capability to predict NAFLD with an area under the receiver operator characteristic (AUROC) of 0.87. By establishing a threshold value of 10.96, determined through Youden’s index, we have achieved a sensitivity of 69.57% and a specificity of 88.24%. The Spearman correlation coefficient between liver fat fraction ascertained by MRI-PDFF and that predicted by the SHSI equation amounts to 0.74. Consequently, the SHSI equation affords a dependable means of predicting the presence of NAFLD and liver fat accumulation within the overweight and obese population.https://www.jstage.jst.go.jp/article/endocrj/70/10/70_EJ23-0227/_html/-char/ennon-alcoholic fatty liver disease (nafld)magnetic resonance imaging proton density fat fraction (mri-pdff)obeseoverweight |
spellingShingle | Jie Chen Jiang Yue Jingjing Fu Shengyun He Qianjing Liu Minglan Yang Wang Zhang Hua Xu Qing Lu Jing Ma A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity Endocrine Journal non-alcoholic fatty liver disease (nafld) magnetic resonance imaging proton density fat fraction (mri-pdff) obese overweight |
title | A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity |
title_full | A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity |
title_fullStr | A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity |
title_full_unstemmed | A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity |
title_short | A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity |
title_sort | prediction model of liver fat fraction and presence of non alcoholic fatty liver disease nafld among patients with overweight or obesity |
topic | non-alcoholic fatty liver disease (nafld) magnetic resonance imaging proton density fat fraction (mri-pdff) obese overweight |
url | https://www.jstage.jst.go.jp/article/endocrj/70/10/70_EJ23-0227/_html/-char/en |
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