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We screened the electronic records of 2,799 patients admitted in Tongji Hospital from January 10th to February 18th, 2020. There were 375 discharged patients including 201 survivors. We built a prognostic prediction model based on XGBoost machine learning algorithm and then tested 29 patients (included 3 patients from other hospital) who were cleared after February 19th. Results:The mean age of the 375 patients was 58.83 years old with 58.7% of males. Fever was the most common initial symptom (49.9%), followed by cough (13.9%), fatigue (3.7%), and dyspnea (2.1%). Our model identified three key clinical features, i.e., lactic dehydrogenase (LDH), lymphocyte and High-sensitivity C-reactive protein (hs-CRP), from a pool of more than 300 features. The clinical route is simple to check and can precisely and quickly assess the risk of death. Therefore, it is of great clinical significance. : medRxiv preprint Conclusion:The three indices-based prognostic prediction model we built is able to predict the mortality risk, and present a clinical route to the recognition of critical cases from severe cases. It can help doctors with early identification and intervention, thus potentially reducing mortality.

Objective: To observe and analyze the application effect of the combined mode of Massive Open Online Course (MOOC) microvideo during the COVID-19 epidemic period in the distance teaching practice of interns in the emergency department. Materials and Methods: The subjects of this study were 60 trainee nurses who conducted emergency nursing practice in Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 1 to February 29, 2020. At the time of the COVID-19 outbreak in Wuhan, they were divided into two groups: (1) the experimental group (combined mode of MOOC micro-video) and (2) the control group (traditional theory teaching combined with clinical practice teaching). The differences of theoretical and practical examination scores and teaching satisfaction between the two groups were compared. Results: There was no significant difference in theoretical, practical, and total examination scores between the two groups, but in terms of teaching satisfaction, the overall satisfaction, the degree of easy understanding, the evaluation of teachers and learning results in the experimental group were higher than those in the control group, with statistical difference (p < 0.05). Conclusion: Compared with the traditional teaching methods, the effect of combined mode of MOOC micro-video in emergency nursing practice is the same as that of traditional teaching methods, but the satisfaction is higher, so it is more suitable to be used in nursing practice during the COVID-19 epidemic period, so as to effectively reduce the cross-infection between doctors, nurses, and teaching staff.