基于血清Betatrophin水平的非酒精性脂肪肝列线图预测模型的建立与分析

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摘要目的通过分析非酒精性脂肪肝（NAFLD）发生的相关危险因素，建立基于血清Betatrophin水平的列线图评价模型，并评价其预测的准确性。方法选取2017年1月~2018年4月秦皇岛市第一医院收治的NAFLD患者180例作为NAFLD组，另选取同期门诊体检肝脏脂肪含量（LF）正常（LF＜9.15%）的体检者72例，作为对照组。单因素分析NAFLD发生的相关因素，并将有统计学意义的指标纳入多因素Logistic回归模型，分析NAFLD发生的危险因素。根据回归分析结果建立列线图预测模型。利用受试者工作特征曲线（ROC）及Hosmer-Lemeshow检验评价模型预测效能。结果多因素分析显示，Betatrophin、三酰甘油（TG）、天冬氨酸氨基转移酶（AST）是NAFLD发生的危险因素，高密度脂蛋白（HDL）是NAFLD发生的保护因素（P < 0.05）。利用R软件成功建立了预测NAFLD发生的列线图预测模型。Hosmer-Lemeshow检验结果显示，该模型预测效能为85.71%，模型拟合良好（P ＜ 0.05）。预测NAFLD发生的曲线下面积（AUC）为0.877，特异性为88.68%，敏感性为82.98%。结论基于血清Betatrophin水平的NAFLD发生风险的列线图预测模型具有良好的特异性和敏感性，模型拟合良好，临床价值较高。

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	高福来谢长顺张利利

关键词 ：非酒精性脂肪肝, Betatrophin, 危险因素, 列线图模型

Abstract：Objective To establish a nomogram predictive model by analyzing the risk factors of nonalcoholic fatty liver disease (NAFLD), and to establish a nomogram model based on serum Betatrophin level, and evaluate the accuracy of prediction. Methods From January 2017 to April 2018, 180 patients with NAFLD admitted to the First Hospital of Qinhuangdao were selected as the NAFLD group, and 72 patients with normal liver fat content (LF < 9.15%) were selected as control group. Univariate analysis of factors associated with NAFLD, statistically significant indicators were included in the multivariate Logistic regression model, and the risk factors for the NAFLD were analyzed. Based on the results of the regression analysis, a preoperative model was established. The receiver operating characteristic curve (ROC) and the Hosmer-Lemeshow test were used to evaluate the model prediction performance. Results Multivariate analysis showed that Betatrophin, triglyceride (TG) and aspartate aminotransferase (AST) were risk factors for NAFLD, and high-density lipoprotein (HDL) was a protective factor for NAFLD (P < 0.05). The nomogram prediction model for predicting the occurrence of NAFLD was successfully established by using R software. The Hosmer-Lemeshow test showed that the model had a predicted performance of 85.71% and the model fit well (P < 0.05). The area under the curve (AUC) for predicting the occurrence of NAFLD was 0.877, the specificity was 88.68%, and the sensitivity was 82.98%. Conclusion The nomogram prediction model based on the serum Betatrophin level of NAFLD has good specificity and sensitivity. The model is well fitted and has high clinical value.

Key words： Nonalcoholic fatty liver disease Betatrophin Risk factors Nomogram model

基金资助:河北省秦皇岛市科技支撑项目（201602A144）。

通讯作者: 张利利（1985.1-），女，硕士；研究方向：肝脏疾病。

作者简介: 高福来（1982.2-），男，硕生；研究方向：肝脏疾病及溃疡性结肠炎。

引用本文:

高福来谢长顺张利利. 基于血清Betatrophin水平的非酒精性脂肪肝列线图预测模型的建立与分析[J]. 中国医药导报, 2019, 16(10): 103-106,119.
GAO Fulai XIE Changshun ZHANG Lili. Establishment and analysis of a nonalcoholic fatty liver disease nomogram prediction model based on serum Betatrophin level. 中国医药导报, 2019, 16(10): 103-106,119.

链接本文:

http://www.yiyaodaobao.com.cn/CN/ 或 http://www.yiyaodaobao.com.cn/CN/Y2019/V16/I10/103

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