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      Diabetes and metabolic syndrome as risk factors for COVID-19

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          Abstract

          Background and aims

          Clinical evidence exists that patients with diabetes are at higher risk for Coronavirus disease 2019 (COVID-19). We investigated the physiological origins of this clinical observation linking diabetes with severity and adverse outcome of COVID-19.

          Methods

          Publication mining was applied to reveal common physiological contexts in which diabetes and COVID-19 have been investigated simultaneously. Overall, we have acquired 1,121,078 publications from PubMed in the time span between 01 and 01-2000 and 17-04-2020, and extracted knowledge graphs interconnecting the topics related to diabetes and COVID-19.

          Results

          The Data Mining revealed three pathophysiological pathways linking diabetes and COVID-19. The first pathway indicates a higher risk for COVID-19 because of an upregulation of Angiotensin-converting enzyme 2. The other two important physiological links between diabetes and COVID-19 are liver dysfunction and chronic systemic inflammation. A deep network analysis has suggested clinical biomarkers predicting the higher risk: Hypertension, elevated serum Alanine aminotransferase, high Interleukin-6, and low Lymphocytes count.

          Conclusions

          The revealed biomarkers can be applied directly in clinical practice. For newly infected patients, the medical history needs to be checked for evidence of a long-term, chronic dysregulation of these biomarkers. In particular, patients with diabetes, but also those with prediabetic state, deserve special attention.

          Highlights

          • Three pathophysiological pathways linking diabetes and Coronavirus disease 2019 (COVID-19) were revealed by Data Mining.

          • Diabetics with upregulated Angiotensin-converting enzyme 2 could be of higher risk for COVID-19.

          • Liver dysfunction with chronically increased serum Alanine aminotransferase indicates adverse outcome of COVID-19.

          • Clinical biomarkers for chronic inflammation, in particular Interleukin-6, predict the severity of COVID-19.

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          Most cited references 33

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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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            Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

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              Is Open Access

              Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation

              Structure of the nCoV trimeric spike The World Health Organization has declared the outbreak of a novel coronavirus (2019-nCoV) to be a public health emergency of international concern. The virus binds to host cells through its trimeric spike glycoprotein, making this protein a key target for potential therapies and diagnostics. Wrapp et al. determined a 3.5-angstrom-resolution structure of the 2019-nCoV trimeric spike protein by cryo–electron microscopy. Using biophysical assays, the authors show that this protein binds at least 10 times more tightly than the corresponding spike protein of severe acute respiratory syndrome (SARS)–CoV to their common host cell receptor. They also tested three antibodies known to bind to the SARS-CoV spike protein but did not detect binding to the 2019-nCoV spike protein. These studies provide valuable information to guide the development of medical counter-measures for 2019-nCoV. Science, this issue p. 1260
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                Author and article information

                Contributors
                Journal
                Diabetes Metab Syndr
                Diabetes Metab Syndr
                Diabetes & Metabolic Syndrome
                Diabetes India. Published by Elsevier Ltd.
                1871-4021
                1878-0334
                8 May 2020
                8 May 2020
                Affiliations
                [a ]Faculty of Medicine, University of Maribor, SI-2000, Maribor, Slovenia
                [b ]Faculty of Natural Sciences and Mathematics, University of Maribor, SI-2000, Maribor, Slovenia
                [c ]Faculty of Education, University of Maribor, SI-2000, Maribor, Slovenia
                [d ]Faculty of Electrical Engineering and Computer Science, University of Maribor, SI-2000, Maribor, Slovenia
                Author notes
                []Corresponding author. Faculty of Medicine, University of Maribor, SI-2000, Maribor, Slovenia. marko.marhl@ 123456um.si
                [1]

                Correspondence for the methods of data mining.

                Article
                S1871-4021(20)30132-6
                10.1016/j.dsx.2020.05.013
                7205616
                © 2020 Diabetes India. Published by Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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