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Validity of fatty liver prediction scores for diagnosis of fatty liver by Fibroscan

Hepatobiliary & Pancreatic Diseases International 2024年第4期23卷 353-360页

作者： Seogsong Jeong Sun Jae Park Seong Kyun Na Sang Min Park Byung-Cheol Song Yun Hwan Oh Department of Biomedical Sciences Seoul National University Graduate SchoolSeoul 03080Korea Department of Biomedical Informatics CHA University School of MedicineCHA UniversitySeongnam 13488Korea Department of Internal Medicine Inje University College of MedicineSeoul 50834Korea Department of Family Medicine Seoul National University HospitalSeoul National University College of MedicineSeoul 03080Korea Department of Internal Medicine Jeju National University HospitalJeju National University College of MedicineJeju 63241Korea Department of Family Medicine Jeju National University HospitalJeju National University College of MedicineJeju 63241Korea Department of Family Medicine Chung-Ang University Gwangmyeong HospitalChung-Ang University College of MedicineGwangmyeong 14353Korea

Background:The Korea National Health and Nutrition Examination Survey nonalcoholic fatty liver disease(K-NAFLD)score was recently developed with the intent to operationally define nonalcoholic fatty liver disease(NAFLD).However,there remained an external validation that confirmed its diagnostic performance,especially in patients with alcohol consumption or hepatitis virus infection.Methods:Diagnostic accuracy of the K-NAFLD score was evaluated in a hospital-based cohort consisting of 1388 participants who received Fibroscan®.Multivariate-adjusted logistic regression models and the contrast estimation of receiver operating characteristic curves were used for validation of the K-NAFLD score,fatty liver index(FLI),and hepatic steatosis index(HSI).Results:K-NAFLD-moderate[adjusted odds ratio(aOR)=2.53,95%confidence interval(CI):1.13-5.65]and K-NAFLD-high(aOR=4.14,95%CI:1.69-10.13)groups showed higher risks of fatty liver compared to the K-NAFLD-low group after adjustments for demographic and clinical characteristics,and FLI-moderate and FLI-high groups revealed aORs of 2.05(95%CI:1.22-3.43)and 1.51(95%CI:0.78-2.90),respectively.In addition,the HSI was less predictive for Fibroscan®-defined fatty liver.Both K-NAFLD and FLI also demonstrated high accuracy in the prediction of fatty liver in patients with alcohol consumption and chronic hepatitis virus infection,and the adjusted area under curve values were comparable between K-NAFLD and FLI.Conclusions:Externally validation of the K-NAFLD and FLI showed that these scores may be a useful,noninvasive,and non-imaging modality for the identification of fatty liver.In addition,these scores also predicted fatty liver in patients with alcohol consumption and chronic hepatitis virus infection.

关键词： Nonalcoholic fatty liver disease Fatty liver index hepatic steatosis index

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Metabolic dysfunction-associated fatty liver disease and low muscle strength: A comment

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World Journal of Gastroenterology 2024年第17期30卷 2371-2373页

作者： Masood Muhammad Karim Amna Subhan Butt Department of Gastroenterology The Aga Khan University HospitalKarachi 74800SindhPakistan Department of Medicine Aga Khan University HospitalKarachi 74800Pakistan

The diagnosis of non-alcoholic fatty liver disease(NAFLD)and metabolic dysfunction-associated fatty liver disease only on the basis of laboratory parameter score such as hepatic steatosis index which includes liver enzymes,gender,basal metabolic index,and presence of diabetic mellitus is not sufficient to exclude other causes of deranged liver enzymes especially medications and autoimmune related liver diseases.As the guideline suggests ultrasound is the preferred first-line diagnostic procedure for imaging of NAFLD,as it provides additional diagnostic information and the combination of biomarkers/scores and transient elastography might confer additional diagnostic accuracy and evident from previous similar studies too.

关键词： Non-alcoholic fatty liver disease Metabolic dysfunction associated fatty liver disease Low muscle strength hepatic steatosis index Letter to the editor

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利用人工神经网络建立脂肪性肝病的预测新模型

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Gastroenterology Report 2021年第1期9卷 31-37,I0001,I0002页

作者： Yi-Shu Chen Dan Chen Chao Shen Ming Chen Chao-Hui Jin Cheng-Fu Xu Chao-Hui Yu You-Ming Li Department of Gastroenterology The First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhouZhejiangP.R.China Health Management Center The First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhouZhejiangP.R.China Hithink Royal Flush Information Network Co. LtdHangzhouZhejiangP.R.China

背景:人工神经网络(ANN)是以数学模型模拟神经元活动的信息处理系统,因其强大的自我学习能力和非线性信息分析能力而应用于疾病诊断,尤其适用于复杂的系统性疾病。本研究旨在借助ANN建立脂肪性肝病(FLD)的预测模型。方法:本研究纳入在... 详细信息

背景:人工神经网络(ANN)是以数学模型模拟神经元活动的信息处理系统,因其强大的自我学习能力和非线性信息分析能力而应用于疾病诊断,尤其适用于复杂的系统性疾病。本研究旨在借助ANN建立脂肪性肝病(FLD)的预测模型。方法:本研究纳入在浙江大学医学院附属第一医院进行体检的共7,396对性别和年龄匹配的受试者,并将体检报告中的各项检查指标作为可能的输入变量进行ANN模型的训练。采用ROC曲线下面积(AUROC)评估该模型对FLD的预测能力,其他评估指标包括准确性、敏感性、特异性、Cohen’s k系数、Brier评分和Hosmer-Lemeshow检验等。本研究还使用本组数据重新训练了其他FLD诊断模型,包括脂肪肝指数(FLI)和肝脂肪变性指数(HSI),并与本研究建立的ANN模型进行比较。结果:经训练,最终纳入8个变量(年龄、性别、体质指数、丙氨酸氨基转移酶、天冬氨酸氨基转移酶、尿酸、甘油三酯、空腹血糖)作为ANN诊断模型的输入节点,输出区间在0-1之间(1为存在FLD,0为不存在FLD)。取0.51作为截点值,在验证队列中,ANN模型预测FLD的AUROC为0.908(95%CI:0.901-0.915),显著高于FLI模型(0.881,95%CI:0.872-0.891;P<0.05)和HSI模型(0.885,95%CI:0.877-0.893;P<0.05)。与FLI模型和HSI模型相比,本研究建立的ANN模型呈现更高的预测准确性,与超声检查结果的一致性更好,校正能力也更强。结论:本研究建立的ANN模型对FLD具有良好的预测及诊断能力,我们期待ANN模型能在未来的临床和流行病学研究中得到广泛应用。

关键词： artificial neural network diagnostic model fatty liver disease Fatty Liver index hepatic steatosis index uric acid

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