用于预测慢性乙型肝炎和非酒精性脂肪性肝病患者NASH的无创

StephenW

Biomed Res Int. 2017;2017:8793278. doi: 10.1155/2017/8793278. Epub 2017 Mar 2.
A Noninvasive Score Model for Prediction of NASH in Patients with Chronic Hepatitis B and Nonalcoholic Fatty Liver Disease.
Liang J1, Liu F1, Wang F1, Han T1, Jing L2, Ma Z3, Gao Y2.
Author information

1    Department of Gastroenterology and Hepatology, Tianjin Third Central Hospital, Tianjin 300170, China; Tianjin Key Laboratory of Artificial Cell, Tianjin 300170, China; Artificial Cell Engineering Technology Research Center of Public Health Ministry, Tianjin 300170, China.
2    Tianjin Key Laboratory of Artificial Cell, Tianjin 300170, China; Artificial Cell Engineering Technology Research Center of Public Health Ministry, Tianjin 300170, China; Molecular Biology Laboratory, Tianjin Third Central Hospital, Tianjin 300170, China.
3    Department of Pathology, Tianjin Third Central Hospital, Tianjin 300170, China.

Abstract

Aims. To develop a noninvasive score model to predict NASH in patients with combined CHB and NAFLD. Objective and Methods. 65 CHB patients with NAFLD were divided into NASH group (34 patients) and non-NASH group (31 patients) according to the NAS score. Biochemical indexes, liver stiffness, and Controlled Attenuation Parameter (CAP) were determined. Data in the two groups were compared and subjected to multivariate analysis, to establish a score model for the prediction of NASH. Results. In the NASH group, ALT, TG, fasting blood glucose (FBG), M30 CK-18, CAP, and HBeAg positive ratio were significantly higher than in the non-NASH group (P < 0.05). Multivariate analysis showed that CK-18 M30, CAP, FBG, and HBVDNA level were independent predictors of NASH. Therefore, a new model combining CK18 M30, CAP, FBG, and HBVDNA level was established using logistic regression. The AUROC curve predicting NASH was 0.961 (95% CI: 0.920-1.00, cutoff value is 0.218), with a sensitivity of 100% and specificity of 80.6%. Conclusion. A noninvasive score model might be considered for the prediction of NASH in patients with CHB combined with NAFLD.

PMID:
    28349067
PMCID:
    PMC5352864
DOI:
    10.1155/2017/8793278

StephenW

生物研究2017; 2017：8793278。 doi：10.1155 / 2017/8793278。 Epub 2017 Mar 2。
用于预测慢性乙型肝炎和非酒精性脂肪性肝病患者NASH的无创分数模型。
梁吉1，刘F1，王F1，韩T1，京L2，马Z3，高Y2。
作者信息

1
    天津市第三中心医院消化内科，天津300170;天津市人造细胞重点实验室，天津300170;公共卫生部人工细胞工程技术研究中心，天津300170。
2
    天津市人造细胞重点实验室，天津300170;公共卫生部人工细胞工程技术研究中心，天津300170;天津市第三中心医院分子生物学实验室，天津300170。
3
    天津市第三中心医院病理科，天津300170。

抽象

目标开发非侵入性评分模型，以预测联合CHB和NAFLD患者的NASH。目的和方法。根据NAS评分，将65例NAFLD患者分为NASH组（34例）和非NASH组（31例）。测定生化指标，肝硬度和受控衰减参数（CAP）。比较两组数据进行多变量分析，建立NASH预测评分模型。结果。在NASH组，ALT，TG，空腹血糖（FBG），M30 CK-18，CAP和HBeAg阳性率均显着高于非NASH组（P <0.05）。多变量分析显示，CK-18 M30，CAP，FBG和HBVDNA水平是NASH的独立预测因子。因此，使用逻辑回归建立了CK18 M30，CAP，FBG和HBVDNA水平的新模型。预测NASH的AUROC曲线为0.961（95％CI：0.920-1.00，临界值为0.218），灵敏度为100％，特异度为80.6％。结论。可以考虑非侵入性评分模型，用于预测CHB联合NAFLD患者的NASH。

PMID：
    28349067
PMCID：
    PMC5352864
DOI：
    10.1155 / 2017/8793278