Real-World Disparities in Remote Follow-Up of Cardiac Implantable Electronic Devices and Impact of the COVID-19 Pandemic: A Single-Center Experience.

Background Remote monitoring (RM) of cardiac implantable electronic devices has been shown to improve cardiovascular morbidity and mortality. To date, no studies have investigated disparities in use and delivery of RM. This study was performed to investigate if racial and socioeconomic disparities are present in cardiac implantable electronic device RM. Methods and Results This was a retrospective observational cohort study at a single tertiary care center in the United States. Patients who received a newly implanted cardiac implantable electronic device or device upgrade between January 2017 and December 2020 were included. Patients were classified as RM positive (RM+) when they underwent at least ≥2 remote interrogations per year during follow-up. Of all eligible patients, 2520 patients were included, and 34% were women. The mean follow-up was 25 months. Mean age was 71±14 years. Pacemakers constituted 66% of implanted devices, whereas 26% were implantable cardioverter-defibrillators, and 8% were cardiac resynchronization therapy with implantable cardioverter-defibrillators. Most patients (83%) were of European American ancestry. During follow-up, 66% of patients were classified as RM+. Patients who were younger, European American, college-educated, lived in a county with higher median household income, and were active on the hospital's patient portals were more frequently RM+. In an adjusted regression model, RM+ remained associated with the use of the online patient portal (odds ratio [OR], 2.889 [95% CI, 2.387-3.497]), presence of an implantable cardioverter-defibrillator (OR, 1.489 [95% CI, 1.207-1.835]), advanced college degree (OR, 1.244 [95% CI, 1.014-1.527]), and lastly with European American ancestry (P<0.05). During the years of the COVID-19 pandemic, the number of RM+ patients increased, whereas the association with ancestry and ethnicity decreased. Conclusions Despite being offered to all patients at implantation, significant disparities were present in cardiovascular implantable electronic device RM in this cohort. Disparities were partly reversed during COVID-19. Further studies are needed to examine health center- and patient-specific factors to overcome these barriers, and to facilitate equal opportunities to participate in RM.

Elevation of neural injury markers in patients with neurologic sequelae after hospitalization for SARS-CoV-2 infection.

Patients with SARS-CoV-2 infection (COVID-19) risk developing long-term neurologic symptoms after infection. Here, we identify biomarkers associated with neurologic sequelae one year after hospitalization for SARS-CoV-2 infection. SARS-CoV-2-positive patients were followed using post-SARS-CoV-2 online questionnaires and virtual visits. Hospitalized adults from the pre-SARS-CoV-2 era served as historical controls. 40% of hospitalized patients develop neurological sequelae in the year after recovery from acute COVID-19 infection. Age, disease severity, and COVID-19 infection itself was associated with additional risk for neurological sequelae in our cohorts. Glial fibrillary astrocytic protein (GFAP) and neurofilament light chain (NF-L) were significantly elevated in SARS-CoV-2 infection. After adjusting for age, sex, and disease severity, GFAP and NF-L remained significantly associated with longer term neurological symptoms in patients with SARS-CoV-2 infection. GFAP and NF-L warrant exploration as biomarkers for long-term neurologic complications after SARS-CoV-2 infection.

The Impact of Active Screening and Management on COVID-19 in Plateau Region of Sichuan, China.

Background: In December 2019, the cases of pneumonia of unknown etiology emerged in Wuhan, China, and rapidly spread throughout the country. The disease was later designated by the World Health Organization (WHO) as Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). Few studies have assessed the clinical characteristics of COVID-19 and control strategies used to mitigate disease spread in high-altitude plateau regions of China. Study Objective: To assess the impact of real-world strategies to control COVID-19 spread in remote plateau regions. Methods: A retrospective study was performed to assess the epidemiology of COVID-19 and strategies used to control disease spread in the high-altitude plateau of Sichuan, China from 24 January 2020 to 19 March 2020. Results: COVID-19 spread and outbreaks in Sichuan were attributed to mass gatherings. A total of 70 patients and 20 asymptomatic individuals were found in the hypoxic plateau region of Sichuan. Twelve patients were admitted after the onset of symptoms, while 58 patients and 20 asymptomatic individuals were found by active screening. The symptomatic patients included those with uncomplicated illness (16/70, 22.9%), mild pneumonia (44/70, 62.9%), and severe pneumonia (10/70, 14.3%). Most patients in the study area showed relatively mild and atypical symptoms such as low or no fever and dyspnea. The incidence of severe pneumonia, fever, dyspnea, and interstitial abnormalities identified by chest CT were all significantly lower in screened patients than those admitted after symptom onset (P < 0.05). Severe pneumonia was noted in patients with chronic conditions like hypertension, diabetes etc. as compared to less severe pneumonia in healthy subjects (P <0.05). No patients died and all were eventually discharged. Conclusion: Mass gatherings increased risk of spread of SARS-CoV-2 responsible for COVID-19. Active screening and early management have collectively contributed to reduced incidence of severe pneumonia and satisfactory prognoses of infections with COVID-19 in this hypoxic plateau region.

COVID-19 countermeasures of Chinese national athletes: Prevention, treatment, and return to play.

Under the condition of normalized epidemic, how athletes train and compete well has been in the spotlight. This article reported the symptom, hospitalization and training situation of seven confirmed cases of coronavirus-disease-2019 (COVID-19) among Chinese national teams. Moreover, the paper summarized the experience of Chinese national teams in terms of epidemic prevention and control, treatment of infection, and safe return to play. Through a scientific combination of medication and non-medical treatment, seven athletes were all discharged from the hospital. These discharged athletes underwent strict isolation and scientific training before returning to sports teams. Before returning to play, continuous monitoring of physical and mental condition was required. All seven athletes returned to play safely and performed excellently. As for hosting large-scale sporting events, the entire enclosed-loop management from immigration to competition was proposed in this paper. This study could serve as a standard of epidemic prevention and control, treatment for infection and safe return to play during competition and training around the world.

Modeling Multi-Dimensional Public Opinion Process Based on Complex Network Dynamics Model in the Context of Derived Topics

With the rapid development of the Internet, the speed with which information can be updated and propagated has accelerated, resulting in wide variations in public opinion. Usually, after the occurrence of some newsworthy event, discussion topics are generated in networks that influence the formation of initial public opinion. After a period of propagation, some of these topics are further derived into new subtopics, which intertwine with the initial public opinion to form a multidimensional public opinion. This paper is concerned with the formation process of multi-dimensional public opinion in the context of derived topics. Firstly, the initial public opinion variation mechanism is introduced to reveal the formation process of derived subtopics, then Brownian motion is used to determine the subtopic propagation parameters and their propagation is studied based on complex network dynamics according to the principle of evolution. The formula of basic reproductive number is introduced to determine whether derived subtopics can form derived public opinion, thereby revealing the whole process of multi-dimensional public opinion formation. Secondly, through simulation experiments, the influences of various factors, such as the degree of information alienation, environmental forces, topic correlation coefficients, the amount of information contained in subtopics, and network topology on the formation of multi-dimensional public opinion are studied. The simulation results show that: (1) Environmental forces and the amount of information contained in subtopics are key factors affecting the formation of multi-dimensional public opinion. Among them, environmental forces have a greater impact on the number of subtopics, and the amount of information contained in subtopics determines whether the subtopic can be the key factor that forms the derived public opinion. (2) Only when the degree of information alienation reaches a certain level, will derived subtopics emerge. At the same time, the degree of information alienation has a greater impact on the number of derived subtopics, but it has a small impact on the dimensions of the final public opinion. (3) The network topology does not have much impact on the number of derived subtopics but has a greater impact on the number of individuals participating in the discussion of subtopics. The multidimensional public opinion dimension formed by the network topology with a high aggregation coefficient and small average path length is higher. Finally, a practical case verifies the rationality and effectiveness of the model proposed in this paper.

Evolutionary Game of Multi-Subjects in Live Streaming and Governance Strategies Based on Social Preference Theory during the COVID-19 Pandemic

After the outbreak of the COVID-19, offline consumption has been significantly impacted. For the sake of safety, online consumption has become the most common manner, and this has generated e-commerce, which not only breaks the spatio-temporal or regional restrictions, but also conforms to the normal economic development needs for epidemic prevention and control. However, this new business model causes problems such as the shortage of post-sales service, false publicity, and uneven quality of live streaming anchors, seriously affecting the interests of consumers. Therefore, it is urgent to strengthen the management of the chaos of live streaming. This study focuses on exploring the problems and the behavioral strategies of stakeholders in the governance process. The paper obtained online user comments by python, and used topic clustering and subject extraction methods to dig out the problems and related multiple subjects in live streaming at first. Secondly, the theory of social preference was introduced to construct an evolutionary game model among multiple subjects, and how to guide the behavioral decision-making of multiple subjects to standardize and rationalize was studied, so as to control the problem of live streaming. Finally, simulation experiments were conducted and the results demonstrated that: (1) Compared with strengthening the reciprocal preference of the government, live streaming platforms, and consumers, changing the individual’s altruistic preference is more effective in controlling the chaos of live streaming;(2) weakening the platform’s altruistic preference for anchors is conducive to creating a good live streaming environment;and (3) changing consumers’ altruistic preference or reciprocal preference is less effective in promoting the governance of the live streaming environment.

An integrative analysis identifying transcriptional features and key genes involved in COVID-19.

Aim: To elucidate the transcriptional characteristics of COVID-19. Materials & methods: We utilized an integrative approach to comprehensively analyze the transcriptional features of both COVID-19 patients and SARS-CoV-2 infected cells. Results: Widespread infiltration of immune cells was observed. We identified 233 genes that were codifferentially expressed in both bronchoalveolar lavage fluid and lung samples of COVID-19 patients. Functional analysis suggested upregulated genes were related to immune response such as neutrophil activation and antivirus response, while downregulated genes were associated with cell adhesion. Finally, we identified LCN2, STAT1 and UBE2L6 as core genes during SARS-CoV-2 infection. Conclusion: The identification of core genes involved in COVID-19 can provide us with more insights into the molecular features of COVID-19.

Assessing ACE2 expression patterns in lung tissues in the pathogenesis of COVID-19.

It has been reported that SARS-CoV-2 may use ACE2 as a receptor to gain entry into human cells, in a way similar to that of SARS-CoV. Analyzing the distribution and expression level of ACE2 may therefore help reveal underlying mechanisms of viral susceptibility and post-infection modulation. In this study, we utilized previously uploaded information on ACE2 expression in various conditions including SARS-CoA to evaluate the role of ACE2 in SARS-CoV and extrapolate that to COVID-19. We found that the expression of ACE2 in healthy populations and patients with underlying diseases was not significantly different. However, based on the elevated expression of ACE2 in cigarette smokers, we speculate that long-term smoking may be a risk factor for COVID-19. Analysis of ACE2 in SARS-CoV infected cells suggests that ACE2 is not only a receptor but is also involved in post-infection regulation, including immune response, cytokine secretion, and viral genome replication. Moreover, we constructed Protein-protein interaction (PPI) networks and identified hub genes in viral activity and cytokine secretion. Our findings may help clinicians and researchers gain more insight into the pathogenesis of SARS-CoV-2 and design therapeutic strategies for COVID-19.