BACKGROUNDThe prevalence of hepatitis C virus (HCV) in Egypt is quite high, and the combined oral direct-acting antiviral agents (DAAs) may have impressive results.OBJECTIVETo assess the cardiovascular effects of DAAs in patients with HCV.METHODSA total of 170 patients with HCV were divided into 2 groups: first group (100 patients) received triple combination therapy (pegylated interferon alfa, sofosbuvir, and ribavirin, whereas the second group (70 patients) received dual combination therapy (sofosbuvir and simeprevir). Group 1 patients were followed up for 1 year more than 3 visits, whereas group 2 patients were followed up for 6 months more than 2 visits; and the end point of the study was the development of a major cardiovascular event (eg, congestive heart failure, echocardiographic evidence of left ventricular dysfunction, occurrence of significant arrhythmias, or acute coronary syndrome). The following parameters were accomplished: medical history and clinical examination, electrocardiogram, echo-Doppler study, and laboratory investigations.RESULTSNo significant differences were found between the 2 study groups regarding demographic criteria. None of the both group patients had developed any major cardiac event. No significant changes were observed regarding ST-T wave abnormalities, arrhythmias, or QT interval. None of the both group patients developed echocardiographic regional wall motion abnormalities at baseline or at study end. Systolic function parameters showed minute nonsignificant changes over study visits. Diastolic function parameters showed nonsignificant changes between baseline and 6-month and 12-month visits.CONCLUSIONSThe DAAs used in combination regimen with interferon or used orally in combination do not significantly affect the cardio-vascular system.

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The therapeutic outcomes of EPLBD for removal of large bile duct stones are better than those of ES with comparable complication rate. EPLBD is also recommended for removal of large CBD stone in patients with an underlying coagulopathy or need for anticoagulation following endoscopic retrograde cholangiopancreaticography.

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Currently, a new coronavirus(COVID-19) has affected millions of people worldwide. For this reason, it's not sufficient that radiologists can slow down the virus spreading manually. Convolutional Neural Networks (CNNs) can be utilized as a tool to aid radiologists in diagnosing COVID-19 images, which consequently can save efforts and time. In this work, a dataset of CT images of confirmed and negative COVID-19 was used for the screening of COVID-19. Some preprocessing operations were applied to enhance the COVID-19 CT images which aim at including only the Area of Interest (AOI). This was accomplished in three stages. First, a conversion of the CT images to the binary scale was performed by applying a global threshold algorithm. Then, the median filter algorithm was applied to remove random noise. Then, we include only the ROI (the lung) and exclude other parts of the images. Finally, we applied VGGNet 19 to extract features from the preprocessed CT images, which is a popular CNN architecture, trained previously on ImageNet. The proposed pipeline showed high performance by achieving 98.31%, 100%, 98.19% and 98.64% of accuracy, recall, precision and f1-score, respectively. To the best of our knowledge, these results are the best published on this dataset when compared to a set of recently published works. Also, the proposed model overcomes several popular CNNs architectures.