Elalfy Hatem, Elsherbiny Walid, Abdel Rahman Ashraf, Elhammady Dina, Shaltout Shaker Wagih, Elsamanoudy Ayman Z, El Deek Bassem
Hatem Elalfy, Walid Elsherbiny, Dina Elhammady, Shaker Wagih Shaltout, Tropical Medicine Department, Mansoura Faculty of Medicine, Mansoura University Hospital, Mansoura 35516, Egypt.
World J Hepatol. 2016 Aug 28;8(24):1028-37. doi: 10.4254/wjh.v8.i24.1028.
To build a diagnostic non-invasive model for screening of large varices in cirrhotic hepatitis C virus (HCV) patients.
This study was conducted on 124 post-HCV cirrhotic patients presenting to the clinics of the Endemic Medicine Department at Mansoura University Hospital for evaluation before HCV antiviral therapy: 78 were Child A and 46 were Child B (score ≤ 8). Inclusion criteria for patients enrolled in this study was presence of cirrhotic HCV (diagnosed by either biopsy or fulfillment of clinical basis). Exclusion criteria consisted of patients with other etiologies of liver cirrhosis, e.g., hepatitis B virus and patients with high MELD score on transplant list. All patients were subjected to full medical record, full basic investigations, endoscopy, and computed tomography (CT), and then divided into groups with no varices, small varices, or large risky varices. In addition, values of Fibrosis-4 score (FIB-4), aminotransferase-to-platelet ratio index (APRI), and platelet count/splenic diameter ratio (PC/SD) were also calculated.
Detection of large varies is a multi-factorial process, affected by many variables. Choosing binary logistic regression, dependent factors were either large or small varices while independent factors included CT variables such coronary vein diameter, portal vein (PV) diameter, lieno-renal shunt and other laboratory non-invasive variables namely FIB-4, APRI, and platelet count/splenic diameter. Receiver operating characteristic (ROC) curve was plotted to determine the accuracy of non-invasive parameters for predicting the presence of large esophageal varices and the area under the ROC curve for each one of these parameters was obtained. A model was established and the best model for prediction of large risky esophageal varices used both PC/SD and PV diameter (75% accuracy), while the logistic model equation was shown to be (PV diameter × -0.256) plus (PC/SD × -0.006) plus (8.155). Values nearing 2 or more denote large varices.
This model equation has 86.9% sensitivity and 57.1% specificity, and would be of clinical applicability with 75% accuracy.
构建一种用于筛查丙型肝炎病毒（HCV）肝硬化患者大静脉曲张的诊断非侵入性模型。
本研究对124例HCV肝硬化患者进行，这些患者前往曼苏拉大学医院地方医学科诊所进行HCV抗病毒治疗前的评估：78例为Child A级，46例为Child B级（评分≤8）。纳入本研究的患者的纳入标准为存在HCV肝硬化（通过活检或满足临床标准诊断）。排除标准包括患有其他肝硬化病因的患者，如乙型肝炎病毒患者以及移植名单上MELD评分高的患者。所有患者均接受完整的病历记录、全面的基础检查、内镜检查和计算机断层扫描（CT），然后分为无静脉曲张、小静脉曲张或大风险静脉曲张组。此外，还计算了纤维化-4评分（FIB-4）、转氨酶与血小板比值指数（APRI）以及血小板计数/脾直径比值（PC/SD）。
大静脉曲张的检测是一个多因素过程，受许多变量影响。选择二元逻辑回归，因变量为大或小静脉曲张，自变量包括CT变量，如冠状静脉直径、门静脉（PV）直径、脾肾分流以及其他实验室非侵入性变量，即FIB-4、APRI和血小板计数/脾直径。绘制受试者操作特征（ROC）曲线以确定预测大食管静脉曲张存在的非侵入性参数的准确性，并获得这些参数中每一个的ROC曲线下面积。建立了一个模型，预测大风险食管静脉曲张的最佳模型同时使用了PC/SD和PV直径（准确率75%），而逻辑模型方程显示为（PV直径× -0.256）加上（PC/SD× -0.006）加上（8.155）。值接近2或更高表示大静脉曲张。
该模型方程具有86.9%的敏感性和57.1%的特异性，准确率为75%，具有临床适用性。
