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      Impact of diabetes on COVID-19 prognosis beyond comorbidity burden: the CORONADO initiative

      research-article
      1 , , 1 , 2 , 1 , 3 , 1 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 11 , 36 , 4 , 1 , on behalf of the CORONADO investigators
      Diabetologia
      Springer Berlin Heidelberg
      Charlson index, Comorbidity, COVID-19, Death, Diabetes, Invasive mechanical ventilation, Prognosis

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Aims/hypothesis

          Diabetes has been recognised as a pejorative prognostic factor in coronavirus disease 2019 (COVID-19). Since diabetes is typically a disease of advanced age, it remains unclear whether diabetes remains a COVID-19 risk factor beyond advanced age and associated comorbidities. We designed a cohort study that considered age and comorbidities to address this question.

          Methods

          The Coronavirus SARS-CoV-2 and Diabetes Outcomes (CORONADO) initiative is a French, multicentric, cohort study of individuals with (exposed) and without diabetes (non-exposed) admitted to hospital with COVID-19, with a 1:1 matching on sex, age (±5 years), centre and admission date (10 March 2020 to 10 April 2020). Comorbidity burden was assessed by calculating the updated Charlson comorbidity index (uCCi). A predefined composite primary endpoint combining death and/or invasive mechanical ventilation (IMV), as well as these two components separately, was assessed within 7 and 28 days following hospital admission. We performed multivariable analyses to compare clinical outcomes between patients with and without diabetes.

          Results

          A total of 2210 pairs of participants (diabetes/no-diabetes) were matched on age (mean±SD 69.4±13.2/69.5±13.2 years) and sex (36.3% women). The uCCi was higher in individuals with diabetes. In unadjusted analysis, the primary composite endpoint occurred more frequently in the diabetes group by day 7 (29.0% vs 21.6% in the no-diabetes group; HR 1.43 [95% CI 1.19, 1.72], p<0.001). After multiple adjustments for age, BMI, uCCi, clinical (time between onset of COVID-19 symptoms and dyspnoea) and biological variables (eGFR, aspartate aminotransferase, white cell count, platelet count, C-reactive protein) on admission to hospital, diabetes remained associated with a higher risk of primary composite endpoint within 7 days (adjusted HR 1.42 [95% CI 1.17, 1.72], p<0.001) and 28 days (adjusted HR 1.30 [95% CI 1.09, 1.55], p=0.003), compared with individuals without diabetes. Using the same adjustment model, diabetes was associated with the risk of IMV, but not with risk of death, within 28 days of admission to hospital.

          Conclusions/interpretation

          Our results demonstrate that diabetes status was associated with a deleterious COVID-19 prognosis irrespective of age and comorbidity status.

          Trial registration

          ClinicalTrials.gov NCT04324736

          Graphical abstract

          Supplementary Information

          The online version of this article (10.1007/s00125-022-05734-1) contains peer-reviewed but unedited supplementary material.

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          Most cited references29

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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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            A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

            The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
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              Is Open Access

              OpenSAFELY: factors associated with COVID-19 death in 17 million patients

              COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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                Author and article information

                Contributors
                Bertrand.cariou@univ-nantes.fr
                Journal
                Diabetologia
                Diabetologia
                Diabetologia
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0012-186X
                1432-0428
                15 June 2022
                : 1-14
                Affiliations
                [1 ]GRID grid.4817.a, ISNI 0000 0001 2189 0784, CHU Nantes, CNRS, Inserm, l’institut du thorax, , Nantes Université, ; Nantes, France
                [2 ]GRID grid.277151.7, ISNI 0000 0004 0472 0371, CHU Nantes, Inserm CIC 1413, Pôle Hospitalo-Universitaire 11 : Santé Publique, Clinique des données, ; Nantes, France
                [3 ]GRID grid.277151.7, ISNI 0000 0004 0472 0371, CHU Nantes, Pôle de Gérontologie Clinique, ; Nantes, France
                [4 ]GRID grid.508721.9, Service de Diabétologie, Maladies Métaboliques & Nutrition, CHU Toulouse, Institut des Maladies Métaboliques & Cardiovasculaires, UMR1297 Inserm/UT3, , Université de Toulouse, ; Toulouse, France
                [5 ]GRID grid.134996.0, ISNI 0000 0004 0593 702X, Department of Endocrinology, Diabetes Mellitus and Nutrition, , Amiens University Hospital, Amiens, France; PériTox UMR_I 01, University of Picardie Jules Verne, ; Amiens, France
                [6 ]GRID grid.411147.6, ISNI 0000 0004 0472 0283, Département de Diabétologie, , Centre Hospitalier Universitaire, ; Angers, France
                [7 ]GRID grid.477082.e, ISNI 0000 0004 0641 0297, Département de Diabétologie, , Centre Hospitalier Sud Francilien, ; Corbeil Essonne, France
                [8 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, Université Paris-Saclay, Le Kremlin-Bicêtre, ; Paris, France
                [9 ]Service endocrinologie-diabétologie-nutrition, CH Le Havre, Montivilliers, France
                [10 ]GRID grid.5842.b, ISNI 0000 0001 2171 2558, Épidémiologie Clinique, Centre de Recherche en Épidémiologie et Santé des Populations, Inserm U1018, , Université Paris-Saclay, USVQ, Université Paris-Sud, ; Villejuif, France
                [11 ]GRID grid.414007.6, ISNI 0000 0004 1798 6865, Service d’endocrinologie et maladies métaboliques, H.I.A Bégin, ; Saint-Mandé, France
                [12 ]GRID grid.411158.8, ISNI 0000 0004 0638 9213, Department of Endocrinology, Diabetology and Nutrition, , Besançon University Hospital, ; Besançon, France
                [13 ]GRID grid.413784.d, ISNI 0000 0001 2181 7253, Department of Endocrinology, Diabetology and Nutrition, Assistance Publique Hôpitaux de Paris, , Paris-Saclay University, Antoine Béclère Hospital, Clamart, Bicêtre Hospital, ; Le Kremlin-Bicêtre, France
                [14 ]GRID grid.462844.8, ISNI 0000 0001 2308 1657, Assistance Publique Hôpitaux de Paris, Département de Diabétologie, CHU La Pitié-Salpêtrière - Charles-Foix; Inserm, UMR_S 1138, Centre de Recherche des Cordeliers, Paris 06; Institute of Cardiometabolism and Nutrition ICAN, , Sorbonne Université, ; Paris, France
                [15 ]GRID grid.413780.9, ISNI 0000 0000 8715 2621, Assistance Publique Hôpitaux de Paris, Avicenne Hospital, Paris 13 University, Sorbonne Paris Cité, Department of Endocrinology, Diabetology and Nutrition, CRNH-IdF, CINFO, ; Bobigny, France
                [16 ]GRID grid.508487.6, ISNI 0000 0004 7885 7602, Paris 13 University, Sorbonne Paris Cité, UMR U557 Inserm / U11125 INRAE / CNAM / Paris13 University, Nutritional Epidemiological Research Unit, ; Bobigny, France
                [17 ]GRID grid.411535.7, ISNI 0000 0004 0638 9491, Hôpital de la Conception, Service d’Endocrinologie, Maladies Métaboliques et Nutrition, ; Marseille, France
                [18 ]GRID grid.5399.6, ISNI 0000 0001 2176 4817, Inserm, INRAE, C2VN, , Aix Marseille Univ, ; Marseille, France
                [19 ]Department of Endocrinology and Diabetology, Hospital of Pontoise, Pontoise, France
                [20 ]GRID grid.411296.9, ISNI 0000 0000 9725 279X, Département Diabète et Endocrinologie, , Hôpital Lariboisière, Assistance Publique Hôpitaux de Paris, ; Paris, France
                [21 ]GRID grid.508487.6, ISNI 0000 0004 7885 7602, Inserm UMRS 1138, , Université Paris Diderot–Paris VII, Sorbonne Paris Cité, ; Paris, France
                [22 ]GRID grid.489921.f, Centre Hospitalier Saint Joseph Saint Luc, ; Lyon, France
                [23 ]GRID grid.412220.7, ISNI 0000 0001 2177 138X, Département d’Endocrinologie, Diabétologie et Nutrition, , Hôpitaux Universitaires de Strasbourg, ; Strasbourg, France
                [24 ]GRID grid.460749.8, ISNI 0000 0004 0634 6424, Unité de Diabétologie, Endocrinologie et Nutrition, , Centre Hospitalier de Gonesse, ; Gonesse, France
                [25 ]Service de Diabétologie, Pitié-Salpêtrière, Paris, France
                [26 ]GRID grid.121334.6, ISNI 0000 0001 2097 0141, Department of Endocrinology-Diabetology-Nutrition, CHU Montpellier, , University of Montpellier, ; Montpellier, France
                [27 ]GRID grid.121334.6, ISNI 0000 0001 2097 0141, PhyMedExp, CHU Montpellier, Inserm, CNRS, , University of Montpellier, ; Montpellier, France
                [28 ]GRID grid.7849.2, ISNI 0000 0001 2150 7757, Centre du Diabète DIAB-eCARE, Hospices Civils de Lyon et Laboratoire CarMeN, Inserm, INRA, INSA, , Université Claude Bernard Lyon 1, ; Lyon, France
                [29 ]GRID grid.484642.8, ISNI 0000 0001 0807 394X, Société Francophone du Diabète (SFD), ; Paris, France
                [30 ]GRID grid.410463.4, ISNI 0000 0004 0471 8845, Department of Diabetology, Endocrinology, , Metabolism and Nutrition Lille University Hospital, ; Lille, France
                [31 ]GRID grid.452394.d, European Genomic Institute of Diabetes, , University School of Medicine, ; Lille, France
                [32 ]GRID grid.412370.3, ISNI 0000 0004 1937 1100, Assistance Publique Hôpitaux de Paris, Saint-Antoine Hospital, Reference Center of Rare Diseases of Insulin Secretion and Insulin Sensitivity (PRISIS), Department of Endocrinology, ; Paris, France
                [33 ]GRID grid.462844.8, ISNI 0000 0001 2308 1657, Inserm UMRS 938, Saint-Antoine Research Center, , Sorbonne University, ; Paris, France
                [34 ]GRID grid.492689.8, ISNI 0000 0004 0640 1948, Service d’Endocrinologie, Diabétologie et Nutrition, , Hôpital Nord Franche-Comté, ; Trévenans, France
                [35 ]GRID grid.11166.31, ISNI 0000 0001 2160 6368, Clinical Investigation Centre CIC1402, , University of Poitiers, Inserm, CHU Poitiers, ; Poitiers, France
                [36 ]Fondation Francophone pour la Recherche sur le Diabète (FFRD), Paris, France
                Author information
                https://orcid.org/0000-0002-1580-8040
                https://orcid.org/0000-0001-6027-9486
                https://orcid.org/0000-0002-2224-2014
                https://orcid.org/0000-0002-0581-7592
                https://orcid.org/0000-0001-6240-8253
                https://orcid.org/0000-0001-7348-7161
                https://orcid.org/0000-0002-8785-3385
                https://orcid.org/0000-0001-9101-5002
                https://orcid.org/0000-0003-3687-5522
                https://orcid.org/0000-0002-9540-8222
                https://orcid.org/0000-0002-0696-974X
                https://orcid.org/0000-0003-1862-4252
                https://orcid.org/0000-0002-5362-3813
                https://orcid.org/0000-0001-7110-6994
                Article
                5734
                10.1007/s00125-022-05734-1
                9197674
                35701673
                7a241fbc-42e9-403b-ac1c-166159c02821
                © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 18 November 2021
                : 6 April 2022
                Funding
                Funded by: the Fondation Francophone de Recherche sur le Diabète (FFRD), supported by Novo Nordisk, Merck Sharpe Dome (MSD), Abbott, AstraZeneca, Lilly and FFD (Fédération Française des Diabétiques) – CORONADO initiative emergency grant
                Funded by: The CORONADO control leg of the study was supported by a grant from the French Ministry of Health
                Award ID: PHRC COVID-19-20-0138
                Funded by: Société Francophone du Diabète (SFD) – CORONADO initiative emergency grant
                Funded by: Fonds de dotation du CHU de Nantes (CORONADO project: Sanofi, Air Liquid Healthcare, Novo Nordisk, NHC, Allergan, Lifescan)
                Categories
                Article

                Endocrinology & Diabetes
                charlson index,comorbidity,covid-19,death,diabetes,invasive mechanical ventilation,prognosis

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