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      COVID-19 and Preexisting Comorbidities: Risks, Synergies, and Clinical Outcomes

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          Abstract

          Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated symptoms, named coronavirus disease 2019 (COVID-19), have rapidly spread worldwide, resulting in the declaration of a pandemic. When several countries began enacting quarantine and lockdown policies, the pandemic as it is now known truly began. While most patients have minimal symptoms, approximately 20% of verified subjects are suffering from serious medical consequences. Co-existing diseases, such as cardiovascular disease, cancer, diabetes, and others, have been shown to make patients more vulnerable to severe outcomes from COVID-19 by modulating host–viral interactions and immune responses, causing severe infection and mortality. In this review, we outline the putative signaling pathways at the interface of COVID-19 and several diseases, emphasizing the clinical and molecular implications of concurring diseases in COVID-19 clinical outcomes. As evidence is limited on co-existing diseases and COVID-19, most findings are preliminary, and further research is required for optimal management of patients with comorbidities.

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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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            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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              COVID-19: consider cytokine storm syndromes and immunosuppression

              As of March 12, 2020, coronavirus disease 2019 (COVID-19) has been confirmed in 125 048 people worldwide, carrying a mortality of approximately 3·7%, 1 compared with a mortality rate of less than 1% from influenza. There is an urgent need for effective treatment. Current focus has been on the development of novel therapeutics, including antivirals and vaccines. Accumulating evidence suggests that a subgroup of patients with severe COVID-19 might have a cytokine storm syndrome. We recommend identification and treatment of hyperinflammation using existing, approved therapies with proven safety profiles to address the immediate need to reduce the rising mortality. Current management of COVID-19 is supportive, and respiratory failure from acute respiratory distress syndrome (ARDS) is the leading cause of mortality. 2 Secondary haemophagocytic lymphohistiocytosis (sHLH) is an under-recognised, hyperinflammatory syndrome characterised by a fulminant and fatal hypercytokinaemia with multiorgan failure. In adults, sHLH is most commonly triggered by viral infections 3 and occurs in 3·7–4·3% of sepsis cases. 4 Cardinal features of sHLH include unremitting fever, cytopenias, and hyperferritinaemia; pulmonary involvement (including ARDS) occurs in approximately 50% of patients. 5 A cytokine profile resembling sHLH is associated with COVID-19 disease severity, characterised by increased interleukin (IL)-2, IL-7, granulocyte-colony stimulating factor, interferon-γ inducible protein 10, monocyte chemoattractant protein 1, macrophage inflammatory protein 1-α, and tumour necrosis factor-α. 6 Predictors of fatality from a recent retrospective, multicentre study of 150 confirmed COVID-19 cases in Wuhan, China, included elevated ferritin (mean 1297·6 ng/ml in non-survivors vs 614·0 ng/ml in survivors; p 39·4°C 49 Organomegaly None 0 Hepatomegaly or splenomegaly 23 Hepatomegaly and splenomegaly 38 Number of cytopenias * One lineage 0 Two lineages 24 Three lineages 34 Triglycerides (mmol/L) 4·0 mmol/L 64 Fibrinogen (g/L) >2·5 g/L 0 ≤2·5 g/L 30 Ferritin ng/ml 6000 ng/ml 50 Serum aspartate aminotransferase <30 IU/L 0 ≥30 IU/L 19 Haemophagocytosis on bone marrow aspirate No 0 Yes 35 Known immunosuppression † No 0 Yes 18 The Hscore 11 generates a probability for the presence of secondary HLH. HScores greater than 169 are 93% sensitive and 86% specific for HLH. Note that bone marrow haemophagocytosis is not mandatory for a diagnosis of HLH. HScores can be calculated using an online HScore calculator. 11 HLH=haemophagocytic lymphohistiocytosis. * Defined as either haemoglobin concentration of 9·2 g/dL or less (≤5·71 mmol/L), a white blood cell count of 5000 white blood cells per mm3 or less, or platelet count of 110 000 platelets per mm3 or less, or all of these criteria combined. † HIV positive or receiving longterm immunosuppressive therapy (ie, glucocorticoids, cyclosporine, azathioprine).
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                27 May 2022
                2022
                27 May 2022
                : 13
                : 890517
                Affiliations
                [1] 1Department of Bioengineering, University of Massachusetts Dartmouth , Dartmouth, MA, United States
                [2] 2Department of Electrical Engineering, University of California , Irvine, CA, United States
                [3] 3Department of Biomedical Engineering, University of California, Irvine , Irvine, CA, United States
                [4] 4Laboratory for Integrated Nano Bio Electronics Innovation, The Henry Samueli School of Engineering, University of California, Irvine , Irvine, CA, United States
                [5] 5Department of Chemical and Biomolecular Engineering, New York University , New York, NY, United States
                [6] 6Department of Medicine, Albert Einstein College of Medicine , Bronx, NY, United States
                [7] 7Institute of Parasitology, Biology Centre Czech Academy of Science , Ceske Budejovice, Czech Republic
                [8] 8Department of Neurosurgery, University Hospital Basel , Basel, Switzerland
                [9] 9Division of Hematology/Oncology, Department of Medicine, Rhode Island Hospital and Warren Alpert Medical School of Brown University , Providence, RI, United States
                Author notes

                Edited by: Milos Jesenak, Comenius University, Slovakia

                Reviewed by: Rudy Ippodrino, Ulisse BioMed S.p.A Trieste, Italy; Ahmet Cagkan Inkaya, Hacettepe University, Turkey

                *Correspondence: Steven Zanganeh, Szanganeh@ 123456umassd.edu ; Rahim Esfandiarpour, rahimes@ 123456uci.edu

                This article was submitted to Viral Immunology, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2022.890517
                9196863
                35711466
                c434ae9e-aab3-4143-861f-e1070f939faf
                Copyright © 2022 Bigdelou, Sepand, Najafikhoshnoo, Negrete, Sharaf, Ho, Sullivan, Chauhan, Etter, Shekarian, Liang, Hutter, Esfandiarpour and Zanganeh

                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
                : 06 March 2022
                : 11 April 2022
                Page count
                Figures: 2, Tables: 2, Equations: 0, References: 149, Pages: 16, Words: 8902
                Categories
                Immunology
                Review

                Immunology
                coronavirus disease 2019,covid-19,immune responses,cancer,cardiovascular disease,diabetes,treatment implications

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