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      Long COVID-19 and Postural Orthostatic Tachycardia Syndrome- Is Dysautonomia to Be Blamed?

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          Abstract

          While the increased arrhythmic tendency during acute COVID-19 infection is recognised, the long-term cardiac electrophysiological complications are less well known. There are a high number of patients reporting ongoing symptoms post-infection, termed long COVID. A recent hypothesis is that long COVID symptoms could be attributed to dysautonomia, defined as malfunction of the autonomic nervous system (ANS). The most prevalent cardiovascular dysautonomia amongst young people is postural orthostatic tachycardia syndrome (POTS). Numerous reports have described the development of POTS as part of long COVID. Possible underlying mechanisms, although not mutually exclusive or exhaustive, include hypovolaemia, neurotropism, inflammation and autoimmunity. Treatment options for POTS and other long COVID symptoms are currently limited. Future research studies should aim to elucidate the underlying mechanisms of dysautonomia to enable the development of targeted therapies. Furthermore, it is important to educate healthcare professionals to recognise complications and conditions arising from COVID-19, such as POTS, to allow prompt diagnosis and access to early treatment.

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          Most cited references54

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          Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

          In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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            An interactive web-based dashboard to track COVID-19 in real time

            In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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              The species Severe acute respiratory syndrome-related coronavirus : classifying 2019-nCoV and naming it SARS-CoV-2

              The present outbreak of a coronavirus-associated acute respiratory disease called coronavirus disease 19 (COVID-19) is the third documented spillover of an animal coronavirus to humans in only two decades that has resulted in a major epidemic. The Coronaviridae Study Group (CSG) of the International Committee on Taxonomy of Viruses, which is responsible for developing the classification of viruses and taxon nomenclature of the family Coronaviridae, has assessed the placement of the human pathogen, tentatively named 2019-nCoV, within the Coronaviridae. Based on phylogeny, taxonomy and established practice, the CSG recognizes this virus as forming a sister clade to the prototype human and bat severe acute respiratory syndrome coronaviruses (SARS-CoVs) of the species Severe acute respiratory syndrome-related coronavirus, and designates it as SARS-CoV-2. In order to facilitate communication, the CSG proposes to use the following naming convention for individual isolates: SARS-CoV-2/host/location/isolate/date. While the full spectrum of clinical manifestations associated with SARS-CoV-2 infections in humans remains to be determined, the independent zoonotic transmission of SARS-CoV and SARS-CoV-2 highlights the need for studying viruses at the species level to complement research focused on individual pathogenic viruses of immediate significance. This will improve our understanding of virus–host interactions in an ever-changing environment and enhance our preparedness for future outbreaks.
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                Author and article information

                Contributors
                Journal
                Front Cardiovasc Med
                Front Cardiovasc Med
                Front. Cardiovasc. Med.
                Frontiers in Cardiovascular Medicine
                Frontiers Media S.A.
                2297-055X
                09 March 2022
                2022
                09 March 2022
                : 9
                : 860198
                Affiliations
                [1] 1Cambridge University Hospitals NHS Foundation Trust , Cambridge, United Kingdom
                [2] 2Physiological Laboratory, University of Cambridge , Cambridge, United Kingdom
                [3] 3Department of Biochemistry, University of Cambridge , Cambridge, United Kingdom
                [4] 4Faculty of Health and Medical Sciences, University of Surrey , Guildford, United Kingdom
                Author notes

                Edited by: Hung-Fat Tse, The University of Hong Kong, Hong Kong SAR, China

                Reviewed by: Thomas Klingenheben Klingenheben, Goethe University, Germany

                *Correspondence: Kamalan Jeevaratnam, drkamalanjeeva@ 123456gmail.com

                These authors have contributed equally to this work and share first authorship

                This article was submitted to Cardiac Rhythmology, a section of the journal Frontiers in Cardiovascular Medicine

                Article
                10.3389/fcvm.2022.860198
                8959615
                35355961
                411e20ca-f82f-4354-a6b1-da9f50dde201
                Copyright © 2022 Chadda, Blakey, Huang and Jeevaratnam.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 January 2022
                : 16 February 2022
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 54, Pages: 5, Words: 3661
                Categories
                Cardiovascular Medicine
                Mini Review

                long covid,tachycardia,postural orthostatic tachycardia syndrome,dysautonomia,arrhythmia

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