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      American College of Rheumatology Clinical Guidance for Multisystem Inflammatory Syndrome in Children Associated With SARS–CoV‐2 and Hyperinflammation in Pediatric COVID‐19: Version 3

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          Abstract

          Objective

          To provide guidance on the management of Multisystem Inflammatory Syndrome in Children (MIS‐C), a condition characterized by fever, inflammation, and multiorgan dysfunction that manifests late in the course of SARS–CoV‐2 infection. Recommendations are also provided for children with hyperinflammation during COVID‐19, the acute, infectious phase of SARS–CoV‐2 infection.

          Methods

          The Task Force is composed of 9 pediatric rheumatologists and 2 adult rheumatologists, 2 pediatric cardiologists, 2 pediatric infectious disease specialists, and 1 pediatric critical care physician. Preliminary statements addressing clinical questions related to MIS‐C and hyperinflammation in COVID‐19 were developed based on evidence reports. Consensus was built through a modified Delphi process that involved anonymous voting and webinar discussion. A 9‐point scale was used to determine the appropriateness of each statement (median scores of 1–3 for inappropriate, 4–6 for uncertain, and 7–9 for appropriate). Consensus was rated as low, moderate, or high based on dispersion of the votes. Approved guidance statements were those that were classified as appropriate with moderate or high levels of consensus, which were prespecified before voting.

          Results

          The guidance was approved in June 2020 and updated in November 2020 and October 2021, and consists of 41 final guidance statements accompanied by flow diagrams depicting the diagnostic pathway for MIS‐C and recommendations for initial immunomodulatory treatment of MIS‐C.

          Conclusion

          Our understanding of SARS–CoV‐2–related syndromes in the pediatric population continues to evolve. This guidance document reflects currently available evidence coupled with expert opinion, and will be revised as further evidence becomes available.

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          Most cited references137

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

            Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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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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                Author and article information

                Contributors
                Lauren.Henderson@childrens.harvard.edu
                Journal
                Arthritis Rheumatol
                Arthritis Rheumatol
                10.1002/(ISSN)2326-5205
                ART
                Arthritis & Rheumatology (Hoboken, N.j.)
                John Wiley and Sons Inc. (Hoboken )
                2326-5191
                2326-5205
                03 February 2022
                April 2022
                03 February 2022
                : 74
                : 4 ( doiID: 10.1002/art.v74.4 )
                : e1-e20
                Affiliations
                [ 1 ] Boston Children's Hospital and Harvard Medical School Boston Massachusetts
                [ 2 ] Children’s Hospital of Philadelphia and University of Pennsylvania Perelman School of Medicine
                [ 3 ] Morgan Stanley Children’s Hospital and Columbia University New York New York
                [ 4 ] Joseph M. Sanzari Children’s Hospital at Hackensack University Medical Center and Hackensack Meridian School of Medicine Hackensack New Jersey
                [ 5 ] University of Pittsburgh School of Medicine Pittsburgh Pennsylvania
                [ 6 ] Cincinnati Children’s Hospital Medical Center and University of Cincinnati College of Medicine Cincinnati Ohio
                [ 7 ] Johns Hopkins University School of Medicine Baltimore Maryland
                [ 8 ] University of California San Diego and Rady Children’s Hospital San Diego California
                [ 9 ] The Hospital for Sick Children and University of Toronto Toronto Ontario Canada
                [ 10 ] University of Alabama at Birmingham Birmingham
                [ 11 ] American College of Rheumatology Atlanta Georgia
                [ 12 ] University of Texas Southwestern Medical Center Dallas
                Author notes
                [*] [* ] Address correspondence to Lauren A. Henderson, MD, MMSc, Karp Family Research Building, 10th Floor, 1 Blackfan Circle, Boston, MA 02115. Email: Lauren.Henderson@ 123456childrens.harvard.edu .

                Author information
                https://orcid.org/0000-0003-0242-4029
                https://orcid.org/0000-0001-8452-9937
                https://orcid.org/0000-0001-6532-8478
                https://orcid.org/0000-0002-4603-7963
                https://orcid.org/0000-0001-5923-7051
                https://orcid.org/0000-0003-2361-725X
                https://orcid.org/0000-0001-7695-2022
                https://orcid.org/0000-0002-9005-1690
                Article
                ART42062
                10.1002/art.42062
                9011620
                35118829
                6c50e036-1a05-49de-8daf-04e49b797ebe
                © 2022 American College of Rheumatology

                This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

                History
                : 13 December 2021
                : 22 December 2021
                Page count
                Figures: 2, Tables: 7, Pages: 20, Words: 17442
                Categories
                Special
                Online‐Only Special Article
                Custom metadata
                2.0
                April 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.4 mode:remove_FC converted:15.04.2022

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