Clinical case analysis of novel coronavirus pneumonia complicated with pulmonary hypertension.

Objective: To report the clinical features of pulmonary hypertension diagnosed by echocardiography in 5 patients with novel coronavirus pneumonia (COVID-19) in order to understand the special clinical manifestations of COVID-19 and explore the possible mechanism. Method(s): The echocardiographic data and clinical characteristics of COVID-19 patients complicated with pulmonary hypertension diagnosed by echocardiography in Beijing Ditan Hospital, Capital Medical University were analyzed descriptively from February 5 to March 31, 2020. Result(s): A total of 15 patients with severe and critical COVID-19 patients underwent echocardiography. Of them, 7 patients were diagnosed with pulmonary hypertension, 5 of which were confirmed as complications of COVID-19. Among the 5 patients, 4 were female and 1 was male, aged 62-78 years;4 were with hypertension, 3 were with diabetes, and 1 was with coronary atherosclerotic heart disease. All 5 critically ill patients with COVID-19 were given ventilator-assisted breathing, 2 of which were given extracorporeal membrane oxygenation at the same time. According to echocardiography, the systolic pressure of pulmonary artery in 5 patients was 43-65 mmHg, with an average of 54 mmHg. The severity of pulmonary hypertension was graded as mild in 1 patient and moderate in 4 patients. During the follow-up, pulmonary artery systolic pressure gradually decreased to normal in 4 patients, and then ventilator and ECMO were withdrawn;1 patient died due to respiratory failure and persistent pulmonary hypertension. Conclusion(s): Patients with COVID-19 may be complicated by pulmonary hypertension, which is often found in the critical patients. Echocardiography is an important imagingdiagnostic method for pulmonary hypertension in patients with COVID-19.Copyright © 2020 by the Chinese Medical Association.

Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model

Understanding the interactions among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets, especially the role of climate change in this system is of great significance for policy makers, energy producers/consumers and relevant investors. The present paper aims to quantify the time-varying connectedness effects among the four factors by using the TVP-VAR based extensions of both time- and frequency-domain connectedness index measurements proposed by Antonakakis et al. (2020) and Ellington and Barunik (2021) [8,48]. The empirical results suggest that, firstly, the average total connectedness among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets is not so strong for the heterogenous fundamentals underlying them. Nevertheless, the time-varying total connectedness fluctuates fiercely through May 2005 to September 2021, varying from about 8% to 30% and rocket to very high levels during the global subprime mortgage crisis and the COVID-19 pandemic. Furthermore, the total connectedness mainly centers on the short-term frequency, i.e., 1–3 months. Secondly, climate change is generally the leading information contributor among the four factors, although not particularly strong, and its leading role also performs mainly on the short-term frequency (1–3 months). Thirdly, renewable energy stock market and crude oil market show tight interactions between them and they are the two major bridges of information exchanges across various time frequencies (horizons) in this system. Finally, we confirm the evidence that the primary net connectedness contributor and receiver switch frequently across different time frequencies, implying that it is extremely essential for policy makers, energy producers/consumers and investors to make time-horizon-specific regulatory, production/purchasing or investment decisions when facing the uncertain effects of climate change on the interactions among carbon emission allowance, crude oil and renewable energy stock markets. © 2022 Elsevier Ltd

Can Green Economy stocks hedge natural gas market risk? Evidence during Russia-Ukraine conflict and other crisis periods

One of the ultimate goals of the Green Economy is to move away from dependence on fossil energy, thereby achieving a sustainable development of a resource-saving and environment-friendly society. Thus, whether Green Economy stocks can hedge the risks of fossil energy markets, especially for natural gas market during recent crisis periods, is of great importance for both policy makers and portfolio managers. This paper identifies the time-varying connectedness and hedging effects of twelve NASDAQ OMX Green Economy sector stocks on NYMEX natural gas futures during three major turmoil events, i.e., European debt crisis, COVID-19 pandemic, and recent Russia-Ukraine conflict. The empirical results show that various Green Economy sector stocks can provide gratifying hedge effectiveness on the market risk of natural gas futures, and some of them can even perform similarly to gold and USD. Moreover, NASDAQ OMX Green Economy sector stocks offer better hedge effectiveness during recent Russia-Ukraine conflict than those of them in the periods of European debt crisis and COVID-19 pandemic. Finally, the Sharpe ratio results further show the important but time-varying roles of Green Economy sector stocks in hedging risks of natural gas market. © 2023 Elsevier Inc.

Construction of an emergent public health event management model in large general hospitals based on 4R crisis management theory -A case study of The First Affiliated Hospital of Xi'an Jiaotong University

Since the outbreak of a new round of COVID-19 in Xi'an on December 9, 2021, the response capability of the city's and even the province's health system to major public health emergencies has been severely tested and challenged. Faced with the rapid spread of the Delta strain and its multiple hidden transmission chains, The First Affiliated Hospital of Xi'an Jiaotong University, as the largest comprehensive tertiary hospital in Northwest China, has successfully applied the 4R crisis management theory to prevent the pandemic spread and continue the clinic work as well. Balancing of epidemic prevention and medical service with scientific, orderly and standardized procedures has been achieved. Hence, we have contributed to the "The First Affiliated Hospital of Xi'an Jiaotong University model" for controlling the epidemic and restoring normal production and life as soon as possible under the guidance and command of the National Health Commission and provincial and municipal health administrative institutions at all levels. The First Affiliated Hospital of Xi'an Jiaotong University has improved the present management system and enhanced its management level amid epidemic prevention and control. This paper aims to provide new epidemic prevention experience under the changeable environment by explaining and summarizing our theoretical basis, operation mode and practical effects of our management system.

Clinical characteristics and mechanism of COVID-19 vaccine-related myocarditis

Objective: To investigate the clinical characteristics and potential mechanism of coronavirus disease 2019 (COVID-19) vaccine-related myocarditis. Methods: We made a systematic literature retrieval based on PubMed to search for all reports on COVID-19 vaccine-related myocarditis published by August 31, 2021. A total of 29 reports involving 71 patients with myocarditis were enrolled after screening. The patients' demographic data, vaccination, clinical manifestations, biochemical and imaging results, treatments, and outcomes were extracted and summarized. The patients were divided into prior COVID (n=12) and non-prior COVID (n=59) according to their previous medical history. Results: COVID vaccine-related myocarditis was more common in men (91.5%) and after the second dose of mRNA vaccine (81.7%). The average time to onset was 3 (1, 25) days, and the main symptoms included chest pain (94.4%), fever (45.1%), myalgia (26.8%), and shortness of breath (16.9%). Abnormal troponin level was present in almost all the patients, with a common elevation of C-reactive protein. Non-steroidal anti-inflammatory drugs and colchicine were widely used in clinical treatment, and the symptoms of one-fifth of the patients were relieved after symptomatic therapy, with 1 to 2 weeks' length of hospital stay. However, the risk of vaccine-related myocarditis was significantly increased in patients with previous COVID-19 infection, which was more common after the first dose of vaccine (58.3%) other than the second dose. And the clinical symptoms and outcomes were somewhat different from those without COVID-19 infection previously. Conclusion: Myocarditis is one of the serious adverse events related to COVID-19 vaccine, with an overall relatively low incidence, mild clinical severity, and favorable prognosis. Vaccine-related myocarditis may be a combined result of primed immune system and individual susceptibility after infection with COVID-19.

Construction of the emergency command system of public health emergency in COVID-19 epidemic prevention and control background

Based on the current situation and task of fighting COVID-19, and combined with emergency management mode of public health emergencies and participation of multi-times emergency rescue practices along with the case analysis and literature review and brain-storming, we constructed a basic framework of the emergency command system of public health emergencies in COVID-19 epidemic prevention and control background. The framework contained four modules: the response mechanism, the organizational structure, the emergency capacity, and the supervisory mechanism and the advantages and key points in implementing this emergency command system was discussed. © 2021, Editorial Board of Journal of Xi'an Jiaotong University (Medical Sciences). All right reserved.

[Impact of cardiovascular metabolic diseases on COVID-19: review of recent progress].

The high comorbidity between cardiovascular and metabolic diseases (CVMD) and coronavirus disease 2019 (COVID-19) and the consequent high mortality and the potential risk of cardiovascular damage have brought great challenges to the clinical diagnosis and treatment of the condition. The latest studies found that advanced age, immune function defects, inflammatory factor storms and oxidative stress damage all potentially contribute to the high comorbidity of the two. Direct virus invasion, myocardial oxygen supply and demand imbalance and vascular endothelial and coagulation dysfunction may be important mechanisms for cardiovascular injury in COVID-19 patients. In addition, the expression level of ACE2 (the cell membrane receptor of SARS-CoV-2) in various organs and the peripheral blood not only mediates the direct invasion and damage of the organs, but also participates in regulation of the balance of systematic inflammation and oxidative stress, thus affecting the susceptibility and outcomes of the patients. Herein we review the recent research progress in the comorbidity between COVID-19 and CVMD and explore the mechanisms of cardiovascular damage caused by SARS-CoV-2, thus to provide a theoretical basis for the clinical diagnosis and treatment of COVID-19 with underlying CVMD.

GeoAI-based epidemic control with geo-social data sharing on blockchain

Epidemics especially those caused by major contagious diseases have entailed huge losses in human history. The fights have thus never stopped to prevent pandemics. Due to its acute outbreak, is generally susceptible to the population regardless of ages, so strict quarantine of the infections becomes the most effective means for the epidemic control, which has been proved in the prevention of other contagious diseases such as SARS and H1N1. The key strategy widely used to find infected and suspected patients is still the epidemiological tracking of confirmed cases. However, this may fail to identify infections especially when patients do not show any symptoms. Therefore, the approach to rapid, effective, and simple infection identification is essential to prevent the spread of a contagious disease. This paper proposes to leverage a social apps and Geospatial artificial intelligence (GeoAI) with Blockchain to effectively identify infections with privacy concern. Since people widely use social apps, a large scale of social data with geospatial information could be easily collected and kept on Blockchain with privacy preservation, which thus provides a framework of decentralized, tamper-proof, and privacy-preserved information sharing. With the support of GeoAI, which analyzes the spatial distribution of diseases from the shared data, we could study the influence factors based on spatial propagation of contagious diseases for infection identification. Since WeChat is widely used in China, we take COVID-19 as an example to use the experiments on real-life datasets demonstrate the effectiveness of our method, and provide insight into epidemic control in terms of geo-social data sharing. © 2021 IEEE.