ABSTRACT
The COVID-19 pandemic has received extensive media coverage, with a vast variety of claims made about different aspects of the virus. In order to track these claims, we present COVID-19 Claim Radar(1), a system that automatically extracts claims relating to COVID-19 in news articles. We provide a comprehensive structured view of such claims, with rich attributes (such as claimers and their affiliations) and associated knowledge elements (such as events, relations and entities). Further, we use this knowledge to identify inter-claim connections such as equivalent, supporting, or refuting relations, with shared structural evidence like claimers, similar centroid events and arguments. In order to consolidate claim structures at the corpus-level, we leverage Wikidata(2) as the hub to merge coreferential knowledge elements, and apply machine translation to aggregate claims from news articles in multiple languages. The system provides users with a comprehensive exposure to COVID-19 related claims, their associated knowledge elements, and related connections to other claims. The system is publicly available on GitHub(3) and DockerHub(4), with complete documentation(5).
ABSTRACT
Based on the complex network analysis technology, the core drugs and their compatibility rules of traditional Chinese medicine for the prevention of viral respiratory infectious diseases were excavated, and the core prescriptions of traditional Chinese medicine for the prevention of viral respiratory infectious diseases were analyzed. Firstly, the standard database of prescriptions for viral respiratory infectious diseases is constructed by combining the relevant theories of traditional Chinese medicine and database. Secondly, at the micro level, the weighted correlation network of traditional Chinese medicine prescriptions for three typical diseases COVID-19, H1N1 and SARS is constructed, and at the macro level, the weighted correlation network of traditional Chinese medicine prescriptions for viral respiratory infectious diseases is constructed. Then use Python3.6 software to analyze the node strength and compatibility of the data, use Gephi9.2 software to visualize the data, and draw a schematic diagram of complex network data analysis. By using the relevant theoretical knowledge of complex network, statistics and pharmacology, this paper studies and analyzes the weighted association network of traditional Chinese medicine prescriptions of single disease and multiple diseases from the aspects of structure and function. dig out the broad-spectrum core prescription of traditional Chinese medicine for the prevention of viral respiratory infectious diseases, and provide data reference for the active prevention of viral respiratory infectious diseases. So as to provide more scientific ideas and basis for TCM experts in formulating preventive prescriptions for traditional Chinese medicine.
ABSTRACT
Objective: To analyse the clinical history, laboratory tests and pathological data of a patient who suffered from novel coronavirus pneumonia(COVID-19) and provide reference for the clinical treatment of similar cases. Methods: Data of clinical manifestation, laboratory examination, bronchoscopy, echocardiography and cardiopulmonary pathological results were retrospectively reviewed in a case of COVID-19 with rapid exacerbation from mild to critical condition. Results: This patient hospitalized at day 9 post 2019 novel coronavirus(2019-nCoV) infection, experienced progressive deterioration from mild to severe at day 12, severe to critical at day 18 and underwent extracorporeal membrane oxygenation(ECMO) and continuous renal replacement therapy(CRRT) as well as heart lung transplantation during day 28-45 post infection, and died at the second day post heart and lung transplantation. The patient had suffered from hypertension for 8 years. At the early stage of the disease, his symptoms were mild and the inflammatory indices increased and the lymphocyte count decreased continuously. The patient's condition exacerbated rapidly with multi-organ infections, and eventually developed pulmonary hemorrhage and consolidation, pulmonary hypertension, right heart failure, malignant ventricular arrhythmias, liver dysfunction, etc. His clinical manifestations could not be improved despite viral RNAs test results became negative. The patient underwent lung and heart transplantation and finally died of multi organ failure at the second day post lung and heart transplantation. Pathological examination indicated massive mucus, dark red secretions and blood clots in bronchus. The pathological changes were mainly diffused pulmonary hemorrhagic injuries and necrosis, fibrosis, small vessel disease with cardiac edema and lymphocyte infiltration. Conclusions: The clinical course of severe COVID-19 can exacerbate rapidly from mild to critical with lung, liver and heart injuries.