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COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute respiratory distress syndrome (ARDS) is one of the common clinical manifestations of severe COVID-19 and it is also responsible for the current shortage of ventilators worldwide. This study aims to analyze the clinical characteristics of COVID-19 ARDS patients and establish a diagnostic system based on artificial intelligence (AI) method to predict the probability of ARDS in COVID-19 patients. We collected clinical data of 659 COVID-19 patients from 11 regions in China. The clinical characteristics of the ARDS group and no-ARDS group of COVID-19 patients were elaborately compared and both traditional machine learning algorithms and deep learning-based method were used to build the prediction models. Results indicated that the median age of ARDS patients was 56.5 years old, which was significantly older than those with non-ARDS by 7.5 years. Male and patients with BMI > 25 were more likely to develop ARDS. The clinical features of ARDS patients included cough (80.3%), polypnea (59.2%), lung consolidation (53.9%), secondary bacterial infection (30.3%), and comorbidities such as hypertension (48.7%). Abnormal biochemical indicators such as lymphocyte count, CK, NLR, AST, LDH, and CRP were all strongly related to the aggravation of ARDS. Furthermore, through various AI methods for modeling and prediction effect evaluation based on the above risk factors, decision tree achieved the best AUC, accuracy, sensitivity and specificity in identifying the mild patients who were easy to develop ARDS, which undoubtedly helped to deliver proper care and optimize use of limited resources.

COVID-19 pandemic is the third zoonotic coronavirus (CoV) outbreak of the century after severe acute respiratory syndrome (SARS) in 2003 and Middle East respiratory syndrome (MERS) since 2012. Treatment options for CoVs are largely lacking. Here, we show that clofazimine, an anti-leprosy drug with a favorable safety and pharmacokinetics profile, possesses pan-coronaviral inhibitory activity, and can antagonize SARS-CoV-2 replication in multiple in vitro systems, including the human embryonic stem cell-derived cardiomyocytes and ex vivo lung cultures. The FDA-approved molecule was found to inhibit multiple steps of viral replication, suggesting multiple underlying antiviral mechanisms. In a hamster model of SARS-CoV-2 pathogenesis, prophylactic or therapeutic administration of clofazimine significantly reduced viral load in the lung and fecal viral shedding, and also prevented cytokine storm associated with viral infection. Additionally, clofazimine exhibited synergy when administered with remdesivir. Since clofazimine is orally bioavailable and has a comparatively low manufacturing cost, it is an attractive clinical candidate for outpatient treatment and remdesivir-based combinatorial therapy for hospitalized COVID-19 patients, particularly in developing countries. Taken together, our data provide evidence that clofazimine may have a role in the control of the current pandemic SARS-CoV-2, endemic MERS-CoV in the Middle East, and, possibly most importantly, emerging CoVs of the future.

The novel coronavirus SARS-CoV-2 caused an outbreak of pneumonia in Wuhan, Hubei province of China in January 2020. This study aims to investigate the effects of different temperature and time durations of virus inactivation on the results of PCR testing for SARS-CoV-2. Twelve patients at the Renmin Hospital of Wuhan University suspected of being infected with SARS-CoV-2 were selected on February 13, 2020 and throat swabs were taken. The swabs were stored at room temperature (20-25°C), then divided into aliquots and subjected to different temperature for different periods in order to inactivate the viruses (56°C for 30, 45, 60 min; 65, 70, 80°C for 10, 15, 20 min). Control aliquots were stored at room temperature for 60 min. Then all aliquots were tested in a real-time fluorescence PCR using primers against SARS-CoV-2. Regardless of inactivation temperature and time, 7 of 12 cases (58.3%) tested were positive for SARS-CoV-2 by PCR, and cycle threshold values were similar. These results suggest that virus inactivation parameters exert minimal influence on PCR test results. Inactivation at 65°C for 10 min may be sufficient to ensure safe, reliable testing.