非酒精性脂肪性肝病无创性诊断方程的构建

冯巩; 韩海静; 齐雪; 弥曼; 田秋梅; 牛春燕

doi:10.3969/j.issn.1001-5256.2018.06.026

非酒精性脂肪性肝病无创性诊断方程的构建

DOI: 10.3969/j.issn.1001-5256.2018.06.026

1. 西安医学院
2. 西安医学院第一附属医院
3. 厦门大学附属翔安医院消化内科

基金项目:

陕西省普通高等学校优势学科建设项目(陕教位[2014]3号文件)；

详细信息

中图分类号: R575.5
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出版历程
- 收稿日期: 2018-02-06
- 出版日期: 2018-06-20

Establishment of a noninvasive diagnosis equation for nonalcoholic fatty liver disease

Xi'an Medical University

Research funding:

摘要

摘要:
目的利用与非酒精性脂肪性肝病（NAFLD）相关的常用临床及实验室指标,构建无创性诊断方程,并评估该方程对NAFLD的预测及诊断价值。方法选取2016年11月-2017年11月西安医学院第一附属医院诊断为NAFLD患者127例和健康对照者30例,记录研究对象的性别、年龄、BMI、病史、ALT、AST、GGT、尿素氮（BUN）、尿酸（UA）、血肌酐（Cr）、TC、TG、HDL、LDL、糖化血红蛋白（HBA1c）、游离脂肪酸（FFA）、空腹血糖（FPG）、空腹胰岛素（FINS）、PLT、超声检查结果和Fibro Scan的检查结果等数据。计量资料组间比较采用t检验,相关性使用Pearson相关性分析,回归方程的构建使用多元线性回归方程模型,构建受试者工作特征曲线（ROC曲线）,计算回归方程的敏感度和特异度。结果与脂肪肝相关的指标包括BMI（r=0.308,P=0.005）、ALT（r=0.379,P<0.001）、AST（r=0.318,P=0.004）、GGT（r=0.293,P=0.009）、UA（r=0.244,P=0.033）、FFA（r=0.249,P=0.030）;对Fib...
- 非酒精性脂肪性肝病 /
- 诊断 /
- 预测
Abstract:
Objective To establish a noninvasive diagnosis equation for nonalcoholic fatty liver disease (NAFLD) using related clinical and laboratory markers, and to investigate the value of this equation in the prediction and diagnosis of NAFLD. Methods A total of 127 patients who were diagnosed with NAFLD in The First Affiliated Hospital of Xi' an Medical University from November 2016 to November 2017 were enrolled, and 30 healthy individuals were enrolled as healthy controls. Related data were recorded, including sex, age, body mass index (BMI) , medical history, alanine aminotransferase (ALT) , aspartate aminotransferase (AST) , gamma-glutamyl transpeptidase (GGT) , blood urea nitrogen (BUN) , uric acid (UA) , serum creatinine (SCr) , total cholesterol (TC) , triglyceride (TG) , high-density lipoprotein (HDL) , low-density lipoprotein (LDL) , Hb Alc, free fatty acid (FFA) , fasting blood glucose (FPG) , fasting insulin (FINS) , platelet count (PLT) , and results of ultrasound examination and Fibro Scan examination. The t-test was used for comparison of continuous data between groups; the Pearson correlation analysis was performed to investigate correlation; the multiple linear regression equation model was used to establish the regression equation; the receiver operating characteristic (ROC) curve was plotted to calculate the sensitivity and specificity of this regression equation. Results The indices related to fatty liver included BMI (r = 0. 308, P = 0. 005) , ALT (r = 0. 379, P < 0. 001) , AST (r = 0. 318, P = 0. 004) , GGT (r = 0. 293, P = 0. 009) , UA (r = 0. 244, P = 0. 033) , and FFA (r = 0. 249, P =0. 030) . A multiple regression analysis was performed for controlled attenuation parameter (CAP) on Fibro Scan; the regression model of CAP had statistical significance (F = 11. 113, P < 0. 001) , and its adjusted determination coefficient R2 was 0. 274, suggesting that the variation caused by regression accounted for 27. 4% of all variations; ALT had the greatest influence on CAP (β = 0. 358, P = 0. 001) , followed by BMI (β = 0. 258, P = 0. 012) . The regression equation established was CAP = 113. 163 + 0. 252 × ALT + 6. 316 × BMI. This diagnostic equation had an area under the ROC curve of 0. 927, a sensitivity of 87. 68%, and a specificity of 90. 00%, at the cut-off value of277. 67 (P < 0. 001) , suggesting that it had high diagnostic efficiency. Conclusion Compared with current diagnosis equations, the equation established in this study has a larger area under the ROC curve and higher specificity and sensitivity. It also has a simple calculation method and strong practicability and operability and helps to screen out early NAFLD and improve the awareness of self-intervention, which can further reduce the harm and delay the progression of NAFLD in the world.
- nonalcoholic fatty liver disease /
- diagnosis /
- forecasting

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