Articles: sars-cov-2.
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Multicenter Study
Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study.
The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm achieves a performance equivalent to that achieved by physicians in chest radiography (CR) diagnoses with Coronavirus disease 2019 (COVID-19) pneumonia, the automatic interpretation of the CR with DL algorithms can significantly reduce the burden on clinicians and radiologists in sudden surges of suspected COVID-19 patients. The aim of this study was to evaluate the efficacy of the DL algorithm for detecting COVID-19 pneumonia on CR compared with formal radiology reports. ⋯ The area under the curve value of the DL algorithm for the detection of COVID-19 with pneumonia was 0.921. The DL algorithm demonstrated a satisfactory diagnostic performance comparable with that of formal radiology reports in the CR-based diagnosis of pneumonia in COVID-19 patients. The DL algorithm may offer fast and reliable examinations that can facilitate patient screening and isolation decisions, which can reduce the medical staff workload during COVID-19 pandemic situations.
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Frontiers in immunology · Jan 2020
ReviewSARS-CoV-2: Immune Response Elicited by Infection and Development of Vaccines and Treatments.
The World Health Organization (WHO) announced in March a pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This new infectious disease was named Coronavirus Disease 19 (COVID-19), and at October 2020, more than 39,000,000 cases of SARS-CoV-2 have been detected worldwide leading to near 1,100,000 deaths. Clinically, COVID-19 is characterized by clinical manifestations, such as fever, dry cough, headache, and in more severe cases, respiratory distress. ⋯ Moreover, monoclonal antibody therapy is also under development to neutralize the virus and prevent infection. In this article, we describe the clinical manifestations and the immunological information available about COVID-19 disease. Furthermore, we discuss current therapies under study and the development of vaccines to prevent this disease.
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An ongoing outbreak of pneumonia caused by a novel coronavirus, currently designated as the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was reported recently. However, as SARS-CoV-2 is an emerging virus, we know little about it. ⋯ We highlight bats as the potential natural reservoir and pangolins as the possible intermediate host of the virus, but their roles are waiting for further investigation. Finally, the advances in the development of chemotherapeutic options are also briefly summarized.
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Coronaviruses were first discovered in the 1960s and are named due to their crown-like shape. Sometimes, but not often, a coronavirus can infect both animals and humans. An acute respiratory disease, caused by a novel coronavirus (severe acute respiratory syndrome coronavirus-2 or SARS-CoV-2 previously known as 2019-nCoV) was identified as the cause of coronavirus disease 2019 (COVID-19) as it spread throughout China and subsequently across the globe. ⋯ The early recognition of this immunological phenotype could assist prompt recognition of patients who will progress to severe disease. Here we review the data of the immune response during COVID-19 infection. The current review summarizes our understanding of how immune dysregulation and altered cytokine networks contribute to the pathophysiology of COVID-19 patients.
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From the first report of the respiratory disease caused by SARS-Cov-2 towards the end of 2019, in Wuhan, China, to June 8, 2020, 6,931,000 people had been affected in the world, and 113,619 in Mexico, where there is a lack of literature describing the tomographic behavior of this disease throughout its evolution and its correlation with patient clinical data. ⋯ Knowing the behavior of this type of pneumonia allows becoming familiarized with the characteristic tomographic patterns, in order to aid timely detection and treatment.