Development and validation of a prediction model based on comorbidities to estimate the risk of in-hospital death in patients with COVID-19.

Background: Most existing prognostic models of COVID-19 require imaging manifestations and laboratory results as predictors, which are only available in the post-hospitalization period. Therefore, we aimed to develop and validate a prognostic model to assess the in-hospital death risk in COVID-19 patients using routinely available predictors at hospital admission. Methods: We conducted a retrospective cohort study of patients with COVID-19 using the Healthcare Cost and Utilization Project State Inpatient Database in 2020. Patients hospitalized in Eastern United States (Florida, Michigan, Kentucky, and Maryland) were included in the training set, and those hospitalized in Western United States (Nevada) were included in the validation set. Discrimination, calibration, and clinical utility were evaluated to assess the model's performance. Results: A total of 17 954 in-hospital deaths occurred in the training set (n = 168 137), and 1,352 in-hospital deaths occurred in the validation set (n = 12 577). The final prediction model included 15 variables readily available at hospital admission, including age, sex, and 13 comorbidities. This prediction model showed moderate discrimination with an area under the curve (AUC) of 0.726 (95% confidence interval [CI]: 0.722-0.729) and good calibration (Brier score = 0.090, slope = 1, intercept = 0) in the training set; a similar predictive ability was observed in the validation set. Conclusion: An easy-to-use prognostic model based on predictors readily available at hospital admission was developed and validated for the early identification of COVID-19 patients with a high risk of in-hospital death. This model can be a clinical decision-support tool to triage patients and optimize resource allocation.

Visualization of the interaction of water aerosol and nanofiber mesh.

Face masks play a critical role in reducing the transmission risk of COVID-19 and other respiratory diseases. Masks made with nanofibers have drawn increasingly more attention because of their higher filtration efficiency, better comfort, and lower pressure drop. However, the interactions and consequences of the nanofibers and microwater droplets remain unclear. In this work, the evolution of fibers made of polymers with different contact angles, diameters, and mesh sizes under water aerosol exposure is systematically visualized. The images show that capillarity is very strong compared with the elasticity of the nanofiber. The nanofibers coalesce irreversibly during the droplet capture stage as well as the subsequent liquid evaporation stage. The fiber coalescence significantly reduces the effective fiber length for capturing aerosols. The nanofiber mesh that undergoes multiple droplet capture/evaporation cycles exhibits a fiber coalescing fraction of 40%-58%. The hydrophobic and orthogonally woven fibers can reduce the capillary forces and decrease the fiber coalescing fraction. This finding is expected to assist the proper design, fabrication, and use of face masks with nanofibers. It also provides direct visual evidence on the necessity to replace face masks frequently, especially in cold environments.

Active components in Ephedra sinica stapf disrupt the interaction between ACE2 and SARS-CoV-2 RBD: Potent COVID-19 therapeutic agents.

ETHNOPHARMACOLOGICAL RELEVANCE: Ephedra sinica Stapf is a widely used folk medicine in Asia to treat lung diseases, such as cold, cough and asthma. Many efforts have revealed that some traditional Chinese medicine (TCM) prescriptions containing Ephedra sinica could effectively alleviate the symptoms and prevent the fatal deterioration of COVID-19. AIM OF THE STUDY: The present study aims to discover active compounds in Ephedra sinica disrupting the interaction between angiotensin-converting enzyme 2 (ACE2) and the SARS-CoV-2 spike protein receptor-binding domain (SARS-CoV-2 RBD) to inhibit SARS-CoV-2 virus infection. MATERIALS AND METHODS: The ethanol extracts of Ephedra sinica were prepared. Activity guided isolation of constituents was carried out by measuring the inhibitory activity on ACE2-RBD interaction. The structures of active compounds were identified by HPLC-Q-TOF-MS/MS and NMR. To testify the contribution of main components for the inhibitory activity, different samples were prepared by components knock-out strategy. The mechanism of compounds inhibiting protein-protein interaction (PPI) was explored by competition inhibition assays, surface plasmon resonance (SPR) assays and molecular docking. SARS-CoV-2 S protein-pseudoviruses were used to observe the viropexis effect in cells. RESULTS: Ephedra sinica extracts (ESE) could effectively inhibit the interaction between ACE2 and SARS-CoV-2 RBD (IC50 = 95.01 µg/mL). Three active compounds, 4,6-dihydroxyquinoline-2-carboxylic acid, 4-hydroxyquinoline-2-carboxylic acid and 4-hydroxy-6-methoxyquinoline-2-carboxylic acid were identified to inhibit ACE2-RBD interaction (IC50 = 0.58 µM, 0.07 µM and 0.15 µM respectively). And knock-out the three components could eliminate the inhibitory activity of ESE. Molecular docking calculations indicated that the hydrogen bond was the major intermolecular force. Finally, our results also showed that these compounds could inhibit the infectivity of SARS-CoV-2 S protein-pseudoviruses to 293T-ACE2 (IC50 = 0.44-1.09 µM) and Calu-3 cells. CONCLUSION: These findings suggested that quinoline-2-carboxylic acids in Ephedra sinica could be considered as potential therapeutic agents for COVID-19. Further, this study provided some justification for the ethnomedicinal use of Ephedra sinica for COVID-19.

Feasibility of Yiqi Fumai lyophilized injection in treatment of novel coronary pneumonia (COVID-19) patients combined with cardiovascular disease

As the rapid outbreak of epidemic novel coronavirus pneumonia (COVID-19) in China, National Health Commission of People's Republic of china and National Administration of Traditional Chinese Medicine have launched different programs of diagnosis and treatment. Currently, combining the clinical characteristics of critically patients, the syndrome differentiation of traditional Chinese medicine maintain that Qi-Yin deficiency is one of the main syndrome types, and Shengmai Powder is the main alternative Chinese traditional medicine. Yiqi Fumai lyophilized Injection (YQFM) is a modern preparation derived from Shengmai Powder. In the present study, we explored the potential pathological process of COVID-19. Meanwhile, the pharmacological effects as well as the possibility of clinical application of YQFM for the treatment of COVID-19 patients with cardiovascular diseases were also evaluated. This review will provide evidences for clinicians and patients in the treatment of COVID-19 using Chinese traditional treatment.

Feasibility of Shengmai powder in convalescent patients with novel coronavirus pneumonia

As the number of discharged patients with novel coronavirus pneumonia (COVID-19) increased, TCM treatment received more attention. Some COVID-19 diagnosis and treatment plans issued by national health commission and local government recorded the syndrome differentiation and classification of TCM in the convalescent period and the treatment prescriptions. The clinical characteristics and TCM classification of convalescent period were also reported in recent literatures. Deficiency of Qi and Yin is the main syndrome in recovery period, and the Shengmai Powder (SMS) is the representative prescription. This paper reviews the studies of SMS in the treatment of deficiency of Qi and Yin, pulmonary fibrosis and vascular endothelial cell injury. The feasibility of SMS for the discharged patients with COVID-19 was discussed. This review will provide reference for clinical doctors and patients in the recovery period of TCM treatment.