We found that approximately 10.58% HBsAg carriers (without IVDU and HRSB) were coinfected with HDV, which is twofold of what has been estimated before. We also noted a substantially higher HDV prevalence in the IVDU and HRSB population. Our study highlights the need for increased focus on the routine HDV screening and rigorous implementation of HBV vaccine programme.

The novel coronavirus disease (COVID-19) has become a global health crisis since its first appearance in Wuhan, China. Current epidemiological studies suggest that COVID-19 affects older patients with multiple comorbidities, such as hypertension, obesity, and chronic lung diseases. The differences in the incidence and severity of COVID-19 are likely to be multifaceted, depending on various biological, social, and economical factors. Specifically, the socioeconomic differences and psychological impact of COVID-19 affecting males and females are essential in pandemic mitigation and preparedness. Previous clinical studies have shown that females are less susceptible to acquire viral infections and reduced cytokine production. Female patients have a higher macrophage and neutrophil activity as well as antibody production and response. Furthermore, in-vivo studies of the angiotensin-converting enzyme 2 (ACE2) showed higher expression in the kidneys of male than female patients, which may explain the differences in susceptibility and progression of COVID-19 between male and female patients. However, it remains unknown whether the expression of ACE2 differs in the lungs of male or female patients. Disparities in healthcare access and socioeconomic status between ethnic groups may influence COVID-19 rates. Ethnic groups often have higher levels of medical comorbidities and lower socioeconomic status, which may increase their risk of contracting COVID-19 through weak cell-mediated immunity. In this article, we examine the current literature on the gender and racial differences among COVID-19 patients and further examine the possible biological mechanisms underlying these differences.

The ongoing pandemic of Coronavirus disease-2019 (COVID-19) has spread over 200 countries worldwide, affecting >2 million people and >120,000 deaths. COVID-19 is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The most common symptoms include cough, shortness of breath, and fever. However, gastrointestinal manifestations of COVID-19 are increasingly being recognized. Herein, we report a case of COVID-19 who presented with acute pancreatitis (AP) without any other risk factors.

The severe acute respiratory syndrome coronavirus−2 (SARS-CoV-2) has been recently identified as the culprit of the highly infectious, outbreak named coronavirus disease 2019 (COVID-19) in China. Now declared a public health emergency, this pandemic is present in more than 200 countries with over 14 million cases and 600,000 deaths as of July 18, 2020. Primarily transmitted through the respiratory tract, the most common clinical presentations of symptomatic individuals infected with SARS-CoV-2 include fever, dyspnea, cough, fatigue, and sore throat. In advanced cases, patients may rapidly develop respiratory failure with acute respiratory distress syndrome, and even progress to death. While it is known that COVID-19 manifests similarly to the 2003 Severe Acute Respiratory Syndrome (SARS) and the 2012 Middle East Respiratory Syndrome (MERS), primarily affecting the pulmonary system, the impact of the disease extends far beyond the respiratory system and affects other organs of the body. The literature regarding the extrapulmonary manifestations (cardiovascular, renal, hepatic, gastrointestinal, ocular, dermatologic, and neurological) of COVID-19 is scant. Herein, we provide a comprehensive review of the organ-specific clinical manifestations of COVID-19, to increase awareness about the various organs affected by SARS-CoV-2 and to provide a brief insight into the similarities and differences in the clinical manifestations of COVID-19 and the earlier SARS and MERS.

The growing popularity of medical and recreational consumption of cannabis, especially among the youth, raises immediate concerns regarding its safety and long-terms effects. The cardiovascular effects of cannabis are not well known. Cannabis consumption has been shown to cause arrhythmia including ventricular tachycardia, and potentially sudden death, and to increase the risk of myocardial infarction (MI). These effects appear to be compounded by cigarette smoking and precipitated by excessive physical activity, especially during the first few hours of consumption. Cannabinoids, or the active compounds of cannabis, have been shown to have heterogeneous effects on central and peripheral circulation. Acute cannabis consumption has been shown to cause an increase in blood pressure, specifically systolic blood pressure (SBP), and orthostatic hypotension. Cannabis use has been reported to increase risk of ischemic stroke, particularly in the healthy young patients. The endocannabinoid system (ECS) is currently considered as a promising therapeutic target in the management of several disease conditions. Synthetic cannabinoids (SCs) are being increasingly investigated for their therapeutic effects; however, the value of their benefits over possible complications remains controversial. Despite the considerable research in this field, the benefits of cannabis and its synthetic derivatives remains questionable even in the face of an increasingly tolerating attitude towards recreational consumption and promotion of the therapeutic complications. More efforts are needed to increase awareness among the public, especially youth, about the cardiovascular risks associated with cannabis use and to disseminate the accumulated knowledge regarding its ill effects.

The month of December 2019 became a critical part of the time of humanity when the first case of coronavirus disease 2019 was reported in the Wuhan, Hubei Province in China. As of April 13th, 2020, there have been approximately 1.9 million cases and 199,000 deaths across the world, which were associated with COVID-19. The COVID-19 is the seventh coronavirus to be identified to infect humans. In the past, Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome were the two coronaviruses that infected humans with a high fatality, particularly among the elderly. Fatalities due to COVID-19 are higher in patients older than 50 years of age or those with multimorbid conditions. The COVID-19 is mainly transmitted through respiratory droplets, with the most common symptoms being high fever, cough, myalgia, atypical symptoms included sputum production, headache, hemoptysis and diarrhea. However, the incubation period can range from 2 to 14 days without any symptoms. It is particularly true with gastrointestinal (GI) symptoms in which patients can still shed the virus even after pulmonary symptoms have resolved. Given the high percentage of COVID-19 patients that present with GI symptoms (e.g., nausea and diarrhea), screening patients for GI symptoms remain essential. Recently, cases of fecal-oral transmission of COVID-19 have been confirmed in the USA and China, indicating that the virus can replicate in both the respiratory and digestive tract. Moreover, the epidemiology, clinical characteristics, diagnostic procedures, treatments and prevention of the gastrointestinal manifestations of COVID-19 remain to be elucidated.

Artificial neural networks (ANNs) are powerful tools for data analysis and are particularly suitable for modeling relationships between variables for best prediction of an outcome. While these models can be used to answer many important research questions, their utility has been critically limited because the interpretation of the "black box" model is difficult. Clinical investigators usually employ ANN models to predict the clinical outcomes or to make a diagnosis; the model however is difficult to interpret for clinicians. To address this important shortcoming of neural network modeling methods, we describe several methods to help subject-matter audiences (e.g., clinicians, medical policy makers) understand neural network models. Garson's algorithm describes the relative magnitude of the importance of a descriptor (predictor) in its connection with outcome variables by dissecting the model weights. The Lek's profile method explores the relationship of the outcome variable and a predictor of interest, while holding other predictors at constant values (e.g., minimum, 20th quartile, maximum). While Lek's profile was developed specifically for neural networks, partial dependence plot is a more generic version that visualize the relationship between an outcome and one or two predictors. Finally, the local interpretable model-agnostic explanations (LIME) method can show the predictions of any classification or regression, by approximating it locally with an interpretable model. R code for the implementations of these methods is shown by using example data fitted with a standard, feed-forward neural network model. We offer codes and step-by-step description on how to use these tools to facilitate better understanding of ANN.

Introduction: Gastrointestinal (GI) symptoms are increasingly being recognized in coronavirus disease 2019 (COVID-19). It is unclear if the presence of GI symptoms is associated with poor outcomes in COVID-19. We aim to assess if GI symptoms could be used for prognostication in hospitalized patients with COVID-19. Methods: We retrospectively analyzed patients admitted to a tertiary medical center in Brooklyn,