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肝性脑病风险因素分析及诊断模型的建立。

Risk Factor Analysis of Hepatic Encephalopathy and the Establishment of Diagnostic Model.

机构信息

Department of Hepatology, The Affiliated Hospital of Northwest University for Nationalities, The Second People's Hospital of Gansu Province, China.

出版信息

Biomed Res Int. 2022 Jul 19;2022:3475325. doi: 10.1155/2022/3475325. eCollection 2022.

Abstract

To identify laboratory diagnostic indicators of hepatic encephalopathy (HE), the present study established a HE diagnostic model to explore the diagnostic value of serum homocysteine, lactic acid, procalcitonin, and bile acid levels in HE identification. 371 patients with liver cirrhosis were selected as research objects, who were admitted to the Department of Hepatic Diseases, Affiliated Hospital of Northwest Minzu University from August 2019 to August 2020. The Spearman correlation results indicated that between lactic acid, procalcitonin, bile acid, serum homocysteine, and HE, the coefficients were -0.15, 0.41, 0.29, and -0.19, respectively. Univariate and multivariate analysis methods were adopted for inpatient analysis to identify the influencing factors of HE occurrence, and the diagnosis of the HE identification model was subsequently constructed. The univariate logistic regression showed that risk of developing HE increased as bile acid level ( = 0.00434) and serum homocysteine ( = 0.058) increased. Multivariate logistic regression diagnostic model of bile acid level and serum homocysteine revealed that the AUC value of the area under the ROC curve was 0.7201, indicating that the diagnostic model produced a satisfactory evaluation effect. The model formula referred logistic () = -2.4544 + 0.0117 bile acid levels + 0.0198 serum homocysteine. In this study, the HE diagnostic model was established using logistic regression analysis, which could benefit patients in early HE differential diagnosis. Particularly, combined detection of serum homocysteine and bile acid levels was considered to be more significant.

摘要

为了确定肝性脑病(HE)的实验室诊断指标,本研究建立了一个 HE 诊断模型,以探讨血清同型半胱氨酸、乳酸、降钙素原和胆汁酸水平在 HE 识别中的诊断价值。选择 2019 年 8 月至 2020 年 8 月西北民族大学附属医院肝病科收治的 371 例肝硬化患者作为研究对象。Spearman 相关性分析结果表明,乳酸、降钙素原、胆汁酸、血清同型半胱氨酸与 HE 之间的系数分别为-0.15、0.41、0.29 和-0.19。采用单因素和多因素分析方法对内住院患者进行分析,确定 HE 发生的影响因素,构建 HE 识别模型的诊断。单因素逻辑回归显示,随着胆汁酸水平( = 0.00434)和血清同型半胱氨酸( = 0.058)的增加,发生 HE 的风险增加。胆汁酸水平和血清同型半胱氨酸的多因素逻辑回归诊断模型显示,ROC 曲线下面积的 AUC 值为 0.7201,表明该诊断模型产生了令人满意的评价效果。模型公式参考逻辑()=-2.4544+0.0117×胆汁酸水平+0.0198×血清同型半胱氨酸。在这项研究中,使用逻辑回归分析建立了 HE 诊断模型,这可以使患者受益于早期 HE 鉴别诊断。特别是,联合检测血清同型半胱氨酸和胆汁酸水平被认为更有意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24e6/9325620/9b58d702deb7/BMRI2022-3475325.001.jpg

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