ABSTRACT
Dieulafoy's lesion [DL] is a rare but important cause of gastrointestinal [GI] bleeding, accountingfor up to 6% of the cases of nonvariceal bleeding in the upper GI tract and 1-2% of all GIhemorrhages. Mortality rates are similar to those of other causes for GI bleeding. Following ourstrategy, an expert endoscopist with a skilled assistant should have a high rate of successful DL diagnosis when an obscured GI lesion is suspected. In our seven case study, we thinkit was feasible to use high?definition Fujinon intelligent chromoendoscopy to diagnose DL. Isoamyl 2 cyanoacrylate [Amcrylate] was effective and safe for treating DL as well as wereother strategies, including ethanolamine oleate, band ligation, and nebutyle 2 cyanoacrylate. Surgical wedge resection of the lesion should be considered as a therapeutic option if endoscopic therapy fails
ABSTRACT
Objective and aim :Hepatitis C virus [HCV] can cause both acute and chronic hepatitis. Antiviral therapy is thecornerstone for the treatment of chronic HCV infection once diagnosis is confirmed by PCR. Thegoal of antiviral therapy is to eradicate HCV RNA or attain sustained virological response [SVR]. In many countries worldwide, including Egypt, HCV infection is treated with a combination of pegylated interferon [and ribavirin [RBV]. Liver fibrosis/cirrhosis stage influences theresponse to pegylated interferon [and RBV. Even with new oral the rapies such as Sovaldimany patients have to continue to be on combination regimens of interferon/RBV or RBV alone. In the current study, we aimed to use data mining analysis to determine sonographic picturesthat can successfully predict SVR in HCV-4 patients before the antiviral therapy
Methods: Eighty-two patients were enrolled in this study and they underwent two-dimensional ultrasound examination before the antiviral therapy. The sonographic data obtained were analyzed with Rapidminer version 4.6 to create a decision tree algorithm for the prediction of SVR
Results: The absence of significant liver fibrosis was a predictive parameter of SVR mainly in those patients without a sonographic picture of cirrhosis. The resulting tree yielded an accuracy, sensitivity, and specificity of 85.82 +/- 10.79, 68.75, and 96.00%, respectively, upon 10-foldcross-validation
Conclusion: In the current study we used decision tree algorithm, one of the most important computational methods and tools for data analysis and predictive modeling in applied medicine, to predict SVR in HCV-infected patients. Two-dimensional ultrasound can give predictive information regarding the treatment outcome before interferon therapy for HCV-4