1. 超声结合血清学指标对自身免疫性肝病相关肝硬化的预测价值.
- Author
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冯斯奕, 涂海斌, 陈丽红, 张菊珍, and 彭素妤
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COMPLEMENT (Immunology) , *LOGISTIC regression analysis , *GOLGI apparatus , *SHEAR waves , *LIVER biopsy - Abstract
Objective: To construct a prediction model about the autoimmune liver disease (AILD) related cirrhosis based on two-dimensional shear wave elasticity (2D-SWE), ultrasound and serological indexes, and to evaluate the predicting effciency. Objective To construct a prediction model about the autoimmune liver disease (AILD) related cirrhosis based on two-dimensional shear wave elasticity (2D-SWE), ultrasound and serological indexes, and to evaluate the predicting effciency. Methods: Patients with AILD confirmed by liver biopsy with liver ultrasound, 2D-SWE and serological examination were collected from 2019.01 to 2022.05. Patients were divided into cirrhotic and non-cirrhotic groups. Independent risk factors for the AILD related cirrhosis were selected by multivariate logistic regression analysis, and a nomogram model (AILDC) of the AILD related cirrhosis was constructed. The internal was validated on the model by Bootstrap method, and the Receiver Operating Charateristic curve, calibration curve and clinical decision curve were drew to evaluate the differentiation degree, calibration degree and the clinical net benefit of the model. Results: A total of 255 patients, 45 had liver cirrhosis. Multivariate logistic regression analysis showed that liver stiffness (OR:1.322,95%CI:1.186-1.474), spleen thickness> 4 cm (OR: 5.154,95%CI: 1.943-13.674), complement C4(OR:0.001,95%CI:0.000-0.674), and the Golgi apparatus protein-73 (OR: 1.014,95% CI: 1.0 0 2-1.027) were all independent predictors of AILD related cirrhosis. The optimal cut-off for AILDC was 80, sensitivity 84.4%, specificity 78.6%, the area under curve(AUC) was 0.866. The optimal cutoff value for AILD liver stiffness was 10 Kpa, with the sensitivity of 71.1%, and the specificity of 85.2%, and an AUC of 0.803. Compared with other non-invasive indicators, AILDC has a higher net reclassification index, comprehensive discriminant improvement index, and clinical decision curve. Conclusions: The AILDC has better predictive efficacy than other noninvasive indices, and worth further promotion in clinical practice. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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