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      Clinical significance of prediabetes, undiagnosed diabetes and diagnosed diabetes on critical outcomes in COVID‐19: Integrative analysis from the Japan COVID‐19 task force

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          Abstract

          Aim

          Diabetes mellitus (DM) is a known risk factor for severe coronavirus disease 2019 (COVID‐19), but the clinical impact of undiagnosed diabetes and prediabetes in COVID‐19 are unclear particularly in Japan. We clarify the difference in clinical characteristics, including age, sex, body mass index and co‐morbidities, laboratory findings and critical outcomes, in a large Japanese COVID‐19 cohort without diabetes, with prediabetes, undiagnosed diabetes and diagnosed diabetes, and to identify associated risk factors.

          Materials and Methods

          This multicentre, retrospective cohort study used the Japan COVID‐19 Task Force database, which included data on 2430 hospitalized COVID‐19 patients from over 70 hospitals from February 2020 to October 2021. The prevalence of prediabetes, undiagnosed diabetes and diagnosed diabetes were estimated based on HbA1c levels or a clinical diabetes history. Critical outcomes were defined as the use of high‐flow oxygen, invasive positive‐pressure ventilation or extracorporeal membrane oxygenation, or death during hospitalization.

          Results

          Prediabetes, undiagnosed diabetes and diagnosed diabetes were observed in 40.9%, 10.0% and 23.0%, respectively. Similar to diagnosed diabetes, prediabetes and undiagnosed diabetes were risk factors for critical COVID‐19 outcomes (adjusted odds ratio [aOR] [95% CI]: 2.13 [1.31‐3.48] and 4.00 [2.19‐7.28], respectively). HbA1c was associated with COVID‐19 severity in prediabetes patients (aOR [95% CI]: 11.2 [3.49‐36.3]), but not other groups.

          Conclusions

          We documented the clinical characteristics and outcomes of Japanese COVID‐19 patients according to HbA1c levels or diabetes co‐morbidity. As well as undiagnosed and diagnosed diabetes, physicians should be aware of prediabetes related to COVID‐19 severity.

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          Most cited references35

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          COVID-19 and cardiovascular disease: from basic mechanisms to clinical perspectives

          Coronavirus disease 2019 (COVID-19), caused by a strain of coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic that has affected the lives of billions of individuals. Extensive studies have revealed that SARS-CoV-2 shares many biological features with SARS-CoV, the zoonotic virus that caused the 2002 outbreak of severe acute respiratory syndrome, including the system of cell entry, which is triggered by binding of the viral spike protein to angiotensin-converting enzyme 2. Clinical studies have also reported an association between COVID-19 and cardiovascular disease. Pre-existing cardiovascular disease seems to be linked with worse outcomes and increased risk of death in patients with COVID-19, whereas COVID-19 itself can also induce myocardial injury, arrhythmia, acute coronary syndrome and venous thromboembolism. Potential drug–disease interactions affecting patients with COVID-19 and comorbid cardiovascular diseases are also becoming a serious concern. In this Review, we summarize the current understanding of COVID-19 from basic mechanisms to clinical perspectives, focusing on the interaction between COVID-19 and the cardiovascular system. By combining our knowledge of the biological features of the virus with clinical findings, we can improve our understanding of the potential mechanisms underlying COVID-19, paving the way towards the development of preventative and therapeutic solutions.
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            Prediabetes: a high-risk state for diabetes development

            Prediabetes (intermediate hyperglycaemia) is a high-risk state for diabetes that is defined by glycaemic variables that are higher than normal, but lower than diabetes thresholds. 5-10% of people per year with prediabetes will progress to diabetes, with the same proportion converting back to normoglycaemia. Prevalence of prediabetes is increasing worldwide and experts have projected that more than 470 million people will have prediabetes by 2030. Prediabetes is associated with the simultaneous presence of insulin resistance and β-cell dysfunction-abnormalities that start before glucose changes are detectable. Observational evidence shows associations between prediabetes and early forms of nephropathy, chronic kidney disease, small fibre neuropathy, diabetic retinopathy, and increased risk of macrovascular disease. Multifactorial risk scores using non-invasive measures and blood-based metabolic traits, in addition to glycaemic values, could optimise estimation of diabetes risk. For prediabetic individuals, lifestyle modification is the cornerstone of diabetes prevention, with evidence of a 40-70% relative-risk reduction. Accumulating data also show potential benefits from pharmacotherapy. Copyright © 2012 Elsevier Ltd. All rights reserved.
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              Age-specific mortality and immunity patterns of SARS-CoV-2

              Estimating the size of the coronavirus disease 2019 (COVID-19) pandemic and the infection severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is made challenging by inconsistencies in the available data. The number of deaths associated with COVID-19 is often used as a key indicator for the size of the epidemic, but the observed number of deaths represents only a minority of all infections1,2. In addition, the heterogeneous burdens in nursing homes and the variable reporting of deaths of older individuals can hinder direct comparisons of mortality rates and the underlying levels of transmission across countries3. Here we use age-specific COVID-19-associated death data from 45 countries and the results of 22 seroprevalence studies to investigate the consistency of infection and fatality patterns across multiple countries. We find that the age distribution of deaths in younger age groups (less than 65 years of age) is very consistent across different settings and demonstrate how these data can provide robust estimates of the share of the population that has been infected. We estimate that the infection fatality ratio is lowest among 5-9-year-old children, with a log-linear increase by age among individuals older than 30 years. Population age structures and heterogeneous burdens in nursing homes explain some but not all of the heterogeneity between countries in infection fatality ratios. Among the 45 countries included in our analysis, we estimate that approximately 5% of these populations had been infected by 1 September 2020, and that much higher transmission rates have probably occurred in a number of Latin American countries. This simple modelling framework can help countries to assess the progression of the pandemic and can be applied in any scenario for which reliable age-specific death data are available.
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                Author and article information

                Contributors
                bachibachi472000@live.jp
                Journal
                Diabetes Obes Metab
                Diabetes Obes Metab
                10.1111/(ISSN)1463-1326
                DOM
                Diabetes, Obesity & Metabolism
                Blackwell Publishing Ltd (Oxford, UK )
                1462-8902
                1463-1326
                26 September 2022
                26 September 2022
                : 10.1111/dom.14857
                Affiliations
                [ 1 ] Division of Pulmonary Medicine, Department of Medicine Keio University School of Medicine Tokyo Japan
                [ 2 ] Department of Infectious Diseases Keio University School of Medicine Tokyo Japan
                [ 3 ] Department of Clinical Medicine (Laboratory of Bioregulatory Medicine) Kitasato University School of Pharmacy Tokyo Japan
                [ 4 ] Department of Respiratory Medicine Kitasato University Kitasato Institute Hospital Tokyo Japan
                [ 5 ] Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan
                [ 6 ] Department of Genome Informatics Graduate School of Medicine, The University of Tokyo Tokyo Japan
                [ 7 ] Laboratory for Systems Genetics RIKEN Center for Integrative Medical Sciences Yokohama Japan
                [ 8 ] Medical Innovation Promotion Center Tokyo Medical and Dental University Tokyo Japan
                [ 9 ] Institute of Research Tokyo Medical and Dental University Tokyo Japan
                [ 10 ] Division of Health Medical Intelligence Human Genome Center, The Institute of Medical Science, The University of Tokyo Tokyo Japan
                [ 11 ] M&D Data Science Center Tokyo Medical and Dental University Tokyo Japan
                [ 12 ] Department of Pathology and Tumor Biology Institute for the Advanced Study of Human Biology (WPI‐ASHBi), Kyoto University Kyoto Japan
                [ 13 ] Department of Medicine, Center for Hematology and Regenerative Medicine Karolinska Institute Stockholm Sweden
                [ 14 ] Division of Gastroenterology and Hepatology, Department of Medicine Keio University School of Medicine Tokyo Japan
                Author notes
                [*] [* ] Correspondence

                Shotaro Chubachi, MD, Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, 35 Shinanomachi, Tokyo, 160‐8582, Japan.

                Email: bachibachi472000@ 123456live.jp

                Author information
                https://orcid.org/0000-0002-5046-3762
                Article
                DOM14857
                10.1111/dom.14857
                9538969
                36056760
                812acaf8-8f3c-4b37-aaa2-2f15d52c338c
                © 2022 John Wiley & Sons Ltd.

                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
                : 22 August 2022
                : 13 July 2022
                : 29 August 2022
                Page count
                Figures: 4, Tables: 3, Pages: 12, Words: 6851
                Funding
                Funded by: Japan Science and Technology Agency Core Research for Evolutional Science and Technology(JST CREST)
                Award ID: JPMJCR20H2
                Funded by: Japan Agency for Medical Research and Development , doi 10.13039/100009619;
                Award ID: JP20fk0108415
                Award ID: JP20nk0101612
                Award ID: JP21jk0210034
                Award ID: JP21km0405211
                Award ID: JP21km0405217
                Funded by: Ministry of Health, Labour and Welfare , doi 10.13039/501100003478;
                Award ID: 20CA2054
                Funded by: Mitsubishi Foundation , doi 10.13039/501100004398;
                Funded by: Takeda Science Foundation , doi 10.13039/100007449;
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                corrected-proof
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                Endocrinology & Diabetes
                covid‐19,diabetes,hyperglycaemia,prediabetes state,undiagnosed diabetes
                Endocrinology & Diabetes
                covid‐19, diabetes, hyperglycaemia, prediabetes state, undiagnosed diabetes

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