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Burn E, Duarte-Salles T, Fernandez-Bertolin S, Reyes C, Kostka K, Delmestri A, Rijnbeek P, Verhamme K, Prieto-Alhambra D. Venous or arterial thrombosis and deaths among COVID-19 cases: a European network cohort study. The Lancet Infectious Diseases 2022; 22:1142-1152. [PMID: 35576963 PMCID: PMC9106320 DOI: 10.1016/s1473-3099(22)00223-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 12/11/2022]
Abstract
Background There are few data on the incidence of thrombosis among COVID-19 cases, with most research concentrated on hospitalised patients. We aimed to estimate the incidence of venous thromboembolism, arterial thromboembolism, and death among COVID-19 cases and to assess the impact of these events on the risks of hospitalisation and death. Methods We conducted a distributed network cohort study using primary care records from the Netherlands, Italy, Spain, and the UK, and outpatient specialist records from Germany. The Spanish database was linked to hospital admissions. Participants were followed up from the date of a diagnosis of COVID-19 or positive RT-PCR test for SARS-CoV-2 (index date) for 90 days. The primary study outcomes were venous thromboembolic events, arterial thromboembolic events, and death, all over the 90 days from the index date. We estimated cumulative incidences for the study outcomes. Multistate models were used to calculate adjusted hazard ratios (HRs) for the association between venous thromboembolism or arterial thromboembolism occurrence and risks of hospitalisation or COVID-19 fatality. Findings Overall, 909 473 COVID-19 cases and 32 329 patients hospitalised with COVID-19 on or after Sept 1, 2020, were studied. The latest index dates across the databases ranged from Jan 30, 2021, to July 31, 2021. Cumulative 90-day incidence of venous thromboembolism ranged from 0·2% to 0·8% among COVID-19 cases, and up to 4·5% for those hospitalised. For arterial thromboembolism, estimates ranged from 0·1% to 0·8% among COVID-19 cases, increasing to 3·1% among those hospitalised. Case fatality ranged from 1·1% to 2·0% among patients with COVID-19, rising to 14·6% for hospitalised patients. The occurrence of venous thromboembolism in patients with COVID-19 was associated with an increased risk of death (adjusted HRs 4·42 [3·07–6·36] for those not hospitalised and 1·63 [1·39–1·90] for those hospitalised), as was the occurrence of arterial thromboembolism (3·16 [2·65–3·75] and 1·93 [1·57–2·37]). Interpretation Risks of venous thromboembolism and arterial thromboembolism were up to 1% among COVID-19 cases, and increased with age, among males, and in those who were hospitalised. Their occurrence was associated with excess mortality, underlying the importance of developing effective treatment strategies that reduce their frequency. Funding European Medicines Agency.
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Affiliation(s)
- Edward Burn
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain; Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Carlen Reyes
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Kristin Kostka
- Real World Solutions, IQVIA, Cambridge, MA, USA; The Observational Health Data Sciences and Informatics Center at The Roux Institute, Northeastern University, Portland, ME, USA
| | - Antonella Delmestri
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Katia Verhamme
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands.
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Recalde M, Pistillo A, Fernandez-Bertolin S, Roel E, Aragon M, Freisling H, Prieto-Alhambra D, Burn E, Duarte-Salles T. Body Mass Index and Risk of COVID-19 Diagnosis, Hospitalization, and Death: A Cohort Study of 2 524 926 Catalans. J Clin Endocrinol Metab 2021; 106:e5030-e5042. [PMID: 34297116 PMCID: PMC8344917 DOI: 10.1210/clinem/dgab546] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT A comprehensive understanding of the association between body mass index (BMI) and coronavirus disease 2019 (COVID-19) is still lacking. OBJECTIVE To investigate associations between BMI and risk of COVID-19 diagnosis, hospitalization with COVID-19, and death after a COVID-19 diagnosis or hospitalization (subsequent death), accounting for potential effect modification by age and sex. DESIGN Population-based cohort study. SETTING Primary care records covering >80% of the Catalan population, linked to regionwide testing, hospital, and mortality records from March to May 2020. PARTICIPANTS Adults (≥18 years) with at least 1 measurement of weight and height. MAIN OUTCOME MEASURES Hazard ratios (HR) for each outcome. RESULTS We included 2 524 926 participants. After 67 days of follow-up, 57 443 individuals were diagnosed with COVID-19, 10 862 were hospitalized with COVID-19, and 2467 had a subsequent death. BMI was positively associated with being diagnosed and hospitalized with COVID-19. Compared to a BMI of 22 kg/m2, the HR (95% CI) of a BMI of 31 kg/m2 was 1.22 (1.19-1.24) for diagnosis and 1.88 (1.75-2.03) and 2.01 (1.86-2.18) for hospitalization without and with a prior outpatient diagnosis, respectively. The association between BMI and subsequent death was J-shaped, with a modestly higher risk of death among individuals with BMIs ≤ 19 kg/m2 and a more pronounced increasing risk for BMIs ≥ 40 kg/m2. The increase in risk for COVID-19 outcomes was particularly pronounced among younger patients. CONCLUSIONS There is a monotonic association between BMI and COVID-19 diagnosis and hospitalization risks but a J-shaped relationship with mortality. More research is needed to unravel the mechanisms underlying these relationships.
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Affiliation(s)
- Martina Recalde
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autònoma de Barcelona, Spain
| | - Andrea Pistillo
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Elena Roel
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autònoma de Barcelona, Spain
| | - Maria Aragon
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Heinz Freisling
- International Agency for Research on Cancer (IARC-WHO), 150 Cours Albert Thomas, 69008 Lyon, France
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, NDORMS, University of Oxford
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Edward Burn
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine, NDORMS, University of Oxford
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
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Duarte-Salles T, Vizcaya D, Pistillo A, Casajust P, Sena AG, Lai LYH, Prats-Uribe A, Ahmed WUR, Alshammari TM, Alghoul H, Alser O, Burn E, You SC, Areia C, Blacketer C, DuVall S, Falconer T, Fernandez-Bertolin S, Fortin S, Golozar A, Gong M, Tan EH, Huser V, Iveli P, Morales DR, Nyberg F, Posada JD, Recalde M, Roel E, Schilling LM, Shah NH, Shah K, Suchard MA, Zhang L, Zhang Y, Williams AE, Reich CG, Hripcsak G, Rijnbeek P, Ryan P, Kostka K, Prieto-Alhambra D. Thirty-Day Outcomes of Children and Adolescents With COVID-19: An International Experience. Pediatrics 2021; 148:peds.2020-042929. [PMID: 34049958 DOI: 10.1542/peds.2020-042929] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/13/2021] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children and adolescents diagnosed or hospitalized with coronavirus disease 2019 (COVID-19) and to compare them in secondary analyses with patients diagnosed with previous seasonal influenza in 2017-2018. METHODS International network cohort using real-world data from European primary care records (France, Germany, and Spain), South Korean claims and US claims, and hospital databases. We included children and adolescents diagnosed and/or hospitalized with COVID-19 at age <18 between January and June 2020. We described baseline demographics, comorbidities, symptoms, 30-day in-hospital treatments, and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome, multisystem inflammatory syndrome in children, and death. RESULTS A total of 242 158 children and adolescents diagnosed and 9769 hospitalized with COVID-19 and 2 084 180 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were more common among those hospitalized with versus diagnosed with COVID-19. Dyspnea, bronchiolitis, anosmia, and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital prevalent treatments for COVID-19 included repurposed medications (<10%) and adjunctive therapies: systemic corticosteroids (6.8%-7.6%), famotidine (9.0%-28.1%), and antithrombotics such as aspirin (2.0%-21.4%), heparin (2.2%-18.1%), and enoxaparin (2.8%-14.8%). Hospitalization was observed in 0.3% to 1.3% of the cohort diagnosed with COVID-19, with undetectable (n < 5 per database) 30-day fatality. Thirty-day outcomes including pneumonia and hypoxemia were more frequent in COVID-19 than influenza. CONCLUSIONS Despite negligible fatality, complications including hospitalization, hypoxemia, and pneumonia were more frequent in children and adolescents with COVID-19 than with influenza. Dyspnea, anosmia, and gastrointestinal symptoms could help differentiate diagnoses. A wide range of medications was used for the inpatient management of pediatric COVID-19.
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Affiliation(s)
- Talita Duarte-Salles
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | | | - Andrea Pistillo
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Paula Casajust
- Real-World Evidence, Trial Form Support, Barcelona, Spain
| | - Anthony G Sena
- Janssen Research & Development, Titusville, New Jersey.,Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Lana Yin Hui Lai
- School of Medical Sciences, University of Manchester, Manchester, United Kingdom
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
| | - Waheed-Ul-Rahman Ahmed
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences.,College of Medicine and Health, St Luke's Campus, University of Exeter, Exeter, United Kingdom
| | | | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts
| | - Edward Burn
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain.,Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
| | - Seng Chan You
- Department of Biomedical Informatics, School of Medicine, Ajou University, Suwon, South Korea
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Clair Blacketer
- Janssen Research & Development, Titusville, New Jersey.,Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Scott DuVall
- Department of Veterans Affairs, Salt Lake City, Utah.,School of Medicine, University of Utah, Salt Lake City, Utah
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, New York
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | | | - Asieh Golozar
- Regeneron Pharmaceuticals, Tarrytown, New York.,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | | | - Eng Hooi Tan
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
| | - Vojtech Huser
- Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland
| | | | - Daniel R Morales
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, United Kingdom
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jose D Posada
- Department of Medicine, School of Medicine, Stanford University, Stanford, California
| | - Martina Recalde
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain.,Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Elena Roel
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Lisa M Schilling
- Data Science to Patient Value Program, Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Nigam H Shah
- Department of Medicine, School of Medicine, Stanford University, Stanford, California
| | - Karishma Shah
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
| | - Marc A Suchard
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain.,Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Lin Zhang
- Bayer Pharmaceuticals, Sant Joan Despi, Spain.,Bayer Pharmaceuticals, Sant Joan Despi, Spain.,Real-World Evidence, Trial Form Support, Barcelona, Spain.,Real-World Evidence, Trial Form Support, Barcelona, Spain
| | - Ying Zhang
- DHC Technologies, Co, Ltd, Beijing, China
| | - Andrew E Williams
- Janssen Research & Development, Titusville, New Jersey.,Janssen Research & Development, Titusville, New Jersey
| | - Christian G Reich
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands.,Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, New York
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Patrick Ryan
- Janssen Research & Development, Titusville, New Jersey.,Department of Biomedical Informatics, Columbia University, New York, New York
| | - Kristin Kostka
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands.,Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
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Vivekanantham A, Burn E, Fernandez-Bertolin S, Aragon M, Duarte-Salles T, Prieto-Alhambra D. POS0053 RHEUMATOID ARTHRITIS AND THE RISK OF COVID-19 DIAGNOSIS, HOSPITALISATION AND DEATH: A POPULATION-BASED MULTI-STATE COHORT ANALYSIS INCLUDING 5,586,565 PEOPLE IN CATALONIA, SPAIN. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.3160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is of particular concern for people with rheumatoid arthritis (RA), with concerns that these people may be at higher risk and have poorer outcomes. However, at present the implications of COVID-19 for people with RA remain poorly understood.Objectives:To investigate the associations between rheumatoid arthritis and the risk of COVID-19 diagnosis, hospitalisation with COVID-19 and COVID-19-related death.Methods:A population-based cohort study including all individuals registered in the Information System for Research in Primary Care (SIDIAP). SIDIAP includes primary care records covering over 80% of the population of Catalonia, Spain, and was linked to region-wide SARS-CoV-2 PCR testing, hospital and mortality records. Outpatient diagnoses of COVID-19, hospitalisations with COVID-19 and deaths with COVID-19 were identified as study outcomes between 1st March and 6th May 2020. A multi-state model was used, with cause-specific Cox survival models estimated for each transition, adjusted for age and sex.Results:A total of 5,586,565 individuals were identified in SIDIAP as of the 1st March 2020, of which 16,344 had RA. RA patients were median (IQR) 63 years (52.0, 74.0) and the majority (n=11,727, 71.8%) were female. Having RA was positively associated with being diagnosed with COVID-19 (adjusted HR 1.14 (1.03 to 1.28)), with hospitalisation with COVID-19 (HR 1.66 (1.35 to 2.04)). However, we did not find an association between RA status and the risk of worsening from outpatient diagnosis to hospitalization or death, or from hospitalization to death (see Table 1).Table 1.Estimated hazard ratios, adjusted for age and gender, for individuals with rheumatoid arthritisTransitionStudy population (RA), nTotal events (RA), nHazard Ratios(95% Confidence Intervals)From general population to diagnosed with COVID-195,586,565 (16,344)88,396 (324)1.14 (1.03 to 1.28)From general population to hospitalised with COVID-195,586,565 (16,344)10,143 (90)1.66 (1.35 to 2.04)From diagnosed with COVID-19 to hospitalised with COVID-1988,396 (324)5,946 (30)0.95 (0.66 to 1.36)From diagnosed with COVID-19 to death88,396 (324)2,295 (16)0.96 (0.58 to 1.56)From hospitalised with COVID-19 to death16,089 (120)2,602 (27)1.13 (0.77 to 1.64)Conclusion:To our knowledge, this is the largest study performed to date looking at COVID-19 outcomes in RA patients. Individuals with RA were found to have an increased risk of COVID-19 diagnosis and hospitalisation with COVID-19, compared to the general population. Further research is needed to address factors associated with this including the presence of other co-morbidities, underlying RA disease activity and the use of immunosuppressive medications.Disclosure of Interests:Arani Vivekanantham: None declared, Edward Burn: None declared, Sergio Fernandez-Bertolin: None declared, Maria Aragon: None declared, Talita Duarte-Salles: None declared, Daniel Prieto-Alhambra Grant/research support from: Dr. Prieto-Alhambra reports grants and other from AMGEN, grants, non-financial support and other from UCB Biopharma, grants from Les Laboratoires Servier, outside the submitted work; and Janssen, on behalf of IMI-funded EHDEN and EMIF consortiums, and Synapse Management Partners have supported training programmes organised by DPA’s department and open for external participants.
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Burn E, Tebé C, Fernandez-Bertolin S, Aragon M, Recalde M, Roel E, Prats-Uribe A, Prieto-Alhambra D, Duarte-Salles T. The natural history of symptomatic COVID-19 during the first wave in Catalonia. Nat Commun 2021; 12:777. [PMID: 33536436 PMCID: PMC7858639 DOI: 10.1038/s41467-021-21100-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 01/07/2021] [Indexed: 11/15/2022] Open
Abstract
The natural history of coronavirus disease 2019 (COVID-19) has yet to be fully described. Here, we use patient-level data from the Information System for Research in Primary Care (SIDIAP) to summarise COVID-19 outcomes in Catalonia, Spain. We included 5,586,521 individuals from the general population. Of these, 102,002 had an outpatient diagnosis of COVID-19, 16,901 were hospitalised with COVID-19, and 5273 died after either being diagnosed or hospitalised with COVID-19 between 1st March and 6th May 2020. Older age, being male, and having comorbidities were all generally associated with worse outcomes. These findings demonstrate the continued need to protect those at high risk of poor outcomes, particularly older people, from COVID-19 and provide appropriate care for those who develop symptomatic disease. While risks of hospitalisation and death were lower for younger populations, there is a need to limit their role in community transmission.
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Affiliation(s)
- Edward Burn
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Cristian Tebé
- Biostatistics Unit at Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet, Barcelona, Spain
- Universitat de Barcelona, Barcelona, Spain
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Maria Aragon
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Martina Recalde
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Elena Roel
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK.
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
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Duarte-Salles T, Vizcaya D, Pistillo A, Casajust P, Sena AG, Lai LYH, Prats-Uribe A, Ahmed WUR, Alshammari TM, Alghoul H, Alser O, Burn E, You SC, Areia C, Blacketer C, DuVall S, Falconer T, Fernandez-Bertolin S, Fortin S, Golozar A, Gong M, Tan EH, Huser V, Iveli P, Morales DR, Nyberg F, Posada JD, Recalde M, Roel E, Schilling LM, Shah NH, Shah K, Suchard MA, Zhang L, Zhang Y, Williams AE, Reich CG, Hripcsak G, Rijnbeek P, Ryan P, Kostka K, Prieto-Alhambra D. Baseline characteristics, management, and outcomes of 55,270 children and adolescents diagnosed with COVID-19 and 1,952,693 with influenza in France, Germany, Spain, South Korea and the United States: an international network cohort study. medRxiv 2020:2020.10.29.20222083. [PMID: 33140074 PMCID: PMC7605587 DOI: 10.1101/2020.10.29.20222083] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Objectives To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children/adolescents diagnosed or hospitalized with COVID-19. Secondly, to describe health outcomes amongst children/adolescents diagnosed with previous seasonal influenza. Design International network cohort. Setting Real-world data from European primary care records (France/Germany/Spain), South Korean claims and US claims and hospital databases. Participants Diagnosed and/or hospitalized children/adolescents with COVID-19 at age <18 between January and June 2020; diagnosed with influenza in 2017-2018. Main outcome measures Baseline demographics and comorbidities, symptoms, 30-day in-hospital treatments and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome (ARDS), multi-system inflammatory syndrome (MIS-C), and death. Results A total of 55,270 children/adolescents diagnosed and 3,693 hospitalized with COVID-19 and 1,952,693 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were all more common among those hospitalized vs diagnosed with COVID-19. The most common COVID-19 symptom was fever. Dyspnea, bronchiolitis, anosmia and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital treatments for COVID-19 included repurposed medications (<10%), and adjunctive therapies: systemic corticosteroids (6.8% to 37.6%), famotidine (9.0% to 28.1%), and antithrombotics such as aspirin (2.0% to 21.4%), heparin (2.2% to 18.1%), and enoxaparin (2.8% to 14.8%). Hospitalization was observed in 0.3% to 1.3% of the COVID-19 diagnosed cohort, with undetectable (N<5 per database) 30-day fatality. Thirty-day outcomes including pneumonia, ARDS, and MIS-C were more frequent in COVID-19 than influenza. Conclusions Despite negligible fatality, complications including pneumonia, ARDS and MIS-C were more frequent in children/adolescents with COVID-19 than with influenza. Dyspnea, anosmia and gastrointestinal symptoms could help differential diagnosis. A wide range of medications were used for the inpatient management of pediatric COVID-19.
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Affiliation(s)
- Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Andrea Pistillo
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Paula Casajust
- Real-World Evidence, Trial Form Support, Barcelona, Spain
| | - Anthony G. Sena
- Janssen Research & Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Albert Prats-Uribe
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, UK
| | - Waheed-Ul-Rahman Ahmed
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, UK
- College of Medicine and Health, University of Exeter, St Luke’s Campus, Heavitree Road, Exeter, EX1 2LU, UK
| | | | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, USA
| | - Edward Burn
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Clair Blacketer
- Janssen Research & Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Scott DuVall
- Department of Veterans Affairs, Salt Lake City, UT, US
- University of Utah School of Medicine, Salt Lake City, UT, US
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, US
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Asieh Golozar
- Regeneron Pharmaceutical, NY USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD USA
| | | | - Eng Hooi Tan
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, UK
| | - Vojtech Huser
- Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | - Daniel R. Morales
- Division of Population Health and Genomics, University of Dundee, UK
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Martina Recalde
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autònoma de Barcelona, Spain
| | - Elena Roel
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Lisa M. Schilling
- Data Science to Patient Value Program, Department of Medicine, University of Colorado Anschutz Medical Campus, US
| | | | - Karishma Shah
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, UK
| | - Marc A. Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, USA
| | - Lin Zhang
- School of Population Medicine and Public Health, Peking Union Medical College and Chinese Academy of Medical Sciences, China
- Melbourne School of Population and Global Health, The University of Melbourne, Australia
| | - Ying Zhang
- DHC Technologies Co. Ltd. Beijing, China
| | | | | | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, US
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Patrick Ryan
- Janssen Research & Development, Titusville, NJ, USA
- Department of Biomedical Informatics, Columbia University, New York, NY, US
| | | | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, UK
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7
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Burn E, You SC, Sena AG, Kostka K, Abedtash H, Abrahão MTF, Alberga A, Alghoul H, Alser O, Alshammari TM, Aragon M, Areia C, Banda JM, Cho J, Culhane AC, Davydov A, DeFalco FJ, Duarte-Salles T, DuVall S, Falconer T, Fernandez-Bertolin S, Gao W, Golozar A, Hardin J, Hripcsak G, Huser V, Jeon H, Jing Y, Jung CY, Kaas-Hansen BS, Kaduk D, Kent S, Kim Y, Kolovos S, Lane JCE, Lee H, Lynch KE, Makadia R, Matheny ME, Mehta PP, Morales DR, Natarajan K, Nyberg F, Ostropolets A, Park RW, Park J, Posada JD, Prats-Uribe A, Rao G, Reich C, Rho Y, Rijnbeek P, Schilling LM, Schuemie M, Shah NH, Shoaibi A, Song S, Spotnitz M, Suchard MA, Swerdel JN, Vizcaya D, Volpe S, Wen H, Williams AE, Yimer BB, Zhang L, Zhuk O, Prieto-Alhambra D, Ryan P. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study. Nat Commun 2020; 11:5009. [PMID: 33024121 PMCID: PMC7538555 DOI: 10.1038/s41467-020-18849-z] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 09/10/2020] [Indexed: 01/08/2023] Open
Abstract
Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.
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Affiliation(s)
- Edward Burn
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
| | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | | | | | - Amanda Alberga
- Observational Health Data Sciences and Informatics Network, Alberta, Canada
| | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thamir M Alshammari
- Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia
| | - Maria Aragon
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Jaehyeong Cho
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
| | - Aedin C Culhane
- Data Science, Dana-Farber Cancer Institute. Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Alexander Davydov
- Odysseus Data Services, Inc., Cambridge, MA, USA
- Department for Microbiology, Virology and Immunology, Belarusian State Medical University, Minsk, Belarus
| | | | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Scott DuVall
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Weihua Gao
- Health Economics and Outcomes Research, AbbVie, North Chicago, IL, USA
| | - Asieh Golozar
- Pharmacoepidemiology, Regeneron, NY, USA
- Department of Epidemiology, Johns Hopkins School of Public, Baltimore, MD, USA
| | - Jill Hardin
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Vojtech Huser
- National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Hokyun Jeon
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Yonghua Jing
- Health Economics and Outcomes Research, AbbVie, North Chicago, IL, USA
| | - Chi Young Jung
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Daegu Catholic University Medical Center, Daegu, Korea
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Køge, Denmark
- NNF Centre for Protein Research, University of Copenhagen, København, Denmark
| | - Denys Kaduk
- Odysseus Data Services, Inc., Cambridge, MA, USA
- Department of Pediatrics № 2, V. N. Karazin Kharkiv National University, Kharkiv, Ukraine
| | - Seamus Kent
- Science Policy and Research, National Institute for Health and Care Excellence, London, UK
| | - Yeesuk Kim
- Department of Orthopaedic Surgery, College of Medicine, Hanyang University, Seoul, Korea
| | - Spyros Kolovos
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Jennifer C E Lane
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Hyejin Lee
- Bigdata Department, Health Insurance Review & Assessment Service, Wonju, Korea
| | - Kristine E Lynch
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | - Michael E Matheny
- GRECC, Tennessee Valley Healthcare System VA, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paras P Mehta
- College of Medicine-Tucson, University of Arizona, Tucson, AZ, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Jimyung Park
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Jose D Posada
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Gowtham Rao
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Yeunsook Rho
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lisa M Schilling
- Data Science to Patient Value Program, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Martijn Schuemie
- Janssen Research and Development, Titusville, NJ, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Nigam H Shah
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Seokyoung Song
- Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of Medicine, Gyeongsan, Korea
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | | | | | - Salvatore Volpe
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Haini Wen
- Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Andrew E Williams
- Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, USA
| | - Belay B Yimer
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Lin Zhang
- School of Public Health, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Oleg Zhuk
- Odysseus Data Services, Inc., Cambridge, MA, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK.
| | - Patrick Ryan
- Janssen Research and Development, Titusville, NJ, USA
- Columbia University, New York, NY, USA
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8
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Lane JCE, Weaver J, Kostka K, Duarte-Salles T, Abrahao MTF, Alghoul H, Alser O, Alshammari TM, Biedermann P, Banda JM, Burn E, Casajust P, Conover MM, Culhane AC, Davydov A, DuVall SL, Dymshyts D, Fernandez-Bertolin S, Fišter K, Hardin J, Hester L, Hripcsak G, Kaas-Hansen BS, Kent S, Khosla S, Kolovos S, Lambert CG, van der Lei J, Lynch KE, Makadia R, Margulis AV, Matheny ME, Mehta P, Morales DR, Morgan-Stewart H, Mosseveld M, Newby D, Nyberg F, Ostropolets A, Park RW, Prats-Uribe A, Rao GA, Reich C, Reps J, Rijnbeek P, Sathappan SMK, Schuemie M, Seager S, Sena AG, Shoaibi A, Spotnitz M, Suchard MA, Torre CO, Vizcaya D, Wen H, de Wilde M, Xie J, You SC, Zhang L, Zhuk O, Ryan P, Prieto-Alhambra D. Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study. Lancet Rheumatol 2020; 2:e698-e711. [PMID: 32864627 PMCID: PMC7442425 DOI: 10.1016/s2665-9913(20)30276-9] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis. Methods In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I 2 value was less than 0·4. Findings The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1·65 [95% CI 1·12-2·44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2·19 [95% CI 1·22-3·95]), chest pain or angina (1·15 [1·05-1·26]), and heart failure (1·22 [1·02-1·45]). Interpretation Hydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment. Funding National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Senior Research Fellowship programme, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research and Development, IQVIA, Korea Health Industry Development Institute through the Ministry of Health and Welfare Republic of Korea, Versus Arthritis, UK Medical Research Council Doctoral Training Partnership, Foundation Alfonso Martin Escudero, Innovation Fund Denmark, Novo Nordisk Foundation, Singapore Ministry of Health's National Medical Research Council Open Fund Large Collaborative Grant, VINCI, Innovative Medicines Initiative 2 Joint Undertaking, EU's Horizon 2020 research and innovation programme, and European Federation of Pharmaceutical Industries and Associations.
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Affiliation(s)
- Jennifer C E Lane
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - James Weaver
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Talita Duarte-Salles
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thamir M Alshammari
- Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia
| | | | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Edward Burn
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK.,Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Paula Casajust
- Real-World Evidence, Trial Form Support, Barcelona, Spain
| | | | - Aedin C Culhane
- Department of Data Sciences, Dana-Farber Cancer Institute, Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Alexander Davydov
- Medical Ontology Solutions, Odysseus Data Services, Cambridge MA, USA
| | - Scott L DuVall
- Western Institute for Biomedical Research, Department of Veterans Affairs, Salt Lake City, UT, USA.,Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Dmitry Dymshyts
- Medical Ontology Solutions, Odysseus Data Services, Cambridge MA, USA
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Kristina Fišter
- School of Medicine, Andrija Štampar School of Public Health, University of Zagreb, Zagreb, Croatia
| | - Jill Hardin
- Janssen Research and Development, Titusville, NJ, USA
| | - Laura Hester
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.,New York-Presbyterian Hospital, New York, NY, USA
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark.,NNF Centre for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Seamus Kent
- National Institute for Health and Care Excellence, London, UK
| | - Sajan Khosla
- Real World Science and Digital, AstraZeneca, Cambridge, UK
| | - Spyros Kolovos
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Christophe G Lambert
- Department of Internal Medicine, Center for Global Health and Division of Translational Informatics, Albuquerque, NM, USA
| | - Johan van der Lei
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Kristine E Lynch
- Western Institute for Biomedical Research, Department of Veterans Affairs, Salt Lake City, UT, USA.,Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Michael E Matheny
- Geriatrics Research Education and Clinical Care Center, Tennessee Valley Healthcare System VA, Nashville, TN, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paras Mehta
- College of Medicine, University of Arizona, Tucson, AZ, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, UK
| | | | - Mees Mosseveld
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon-si Gyeonggi-do, South Korea
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Gowtham A Rao
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Jenna Reps
- Janssen Research and Development, Titusville, NJ, USA
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | | | | | | | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA.,Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Marc A Suchard
- Department of Biomathematics and Department of Human Genetics, David Geffen School of Medicine at UCLA, and Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | | | | | - Haini Wen
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Marcel de Wilde
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Junqing Xie
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon-si Gyeonggi-do, South Korea
| | - Lin Zhang
- School of Population Medicine and Public Health, Peking Union Medical College/Chinese Academy of Medical Sciences, Beijing, China.,Melbourne School of Population and Global Health, University of Melbourne, VIC, Australia
| | - Oleg Zhuk
- Medical Ontology Solutions, Odysseus Data Services, Cambridge MA, USA
| | - Patrick Ryan
- Janssen Research and Development, Titusville, NJ, USA.,Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK.,Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
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Cabrera-Bean M, Pereira Dos Santos VJ, Roso-Llorach A, Fernandez-Bertolin S, Vidal J, Violan C. Autoencoders for health improvement by compressing the set of patient features. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2020:5917-5920. [PMID: 33019321 DOI: 10.1109/embc44109.2020.9176209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
A challenge to solve when analyzing multimorbidity patterns in elderly people is the management of a high number of characteristics associated with each patient. The main variables to study multimorbidity are diseases, however other variables should be considered to better classify the people included in each pattern. Age, sex, social class and medication are frequently used in the typing of each multimorbidity pattern. Subsequently the cardinality of the set of features that characterize a patient is very high and normally, the set is compressed to obtain a patient vector of new variables whose dimension is noticeably smaller than that of the initial set. To minimize the loss of information by compression, traditionally Principal Component Analysis (PCA) based projection techniques have been used, which although they are generally a good option, the projection is linear, which somehow reduces its flexibility and limits the performance. As an alternative to the PCA based techniques, in this paper, it is proposed to use autoencoders, and it is shown the improvement in the obtained multimorbidity patterns from the compressed database, when the registered data on about a million patients (5 years' follow-up) are processed. This work demonstrates that autoencoders retain a larger amount of information in each pattern and results are more consistent with clinical experience than other approaches frequently found in the literature.Clinical relevance- From an epidemiological perspective, the contribution is relevant, since it allows for a more precise analysis of multimorbidity patterns, leading to better approaches to patient health strategies.
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Burn E, You SC, Sena A, Kostka K, Abedtash H, Abrahao MTF, Alberga A, Alghoul H, Alser O, Alshammari TM, Aragon M, Areia C, Banda JM, Cho J, Culhane AC, Davydov A, DeFalco FJ, Duarte-Salles T, DuVall SL, Falconer T, Fernandez-Bertolin S, Gao W, Golozar A, Hardin J, Hripcsak G, Huser V, Jeon H, Jing Y, Jung CY, Kaas-Hansen BS, Kaduk D, Kent S, Kim Y, Kolovos S, Lane J, Lee H, Lynch KE, Makadia R, Matheny ME, Mehta P, Morales DR, Natarajan K, Nyberg F, Ostropolets A, Park RW, Park J, Posada JD, Prats-Uribe A, Rao GA, Reich C, Rho Y, Rijnbeek P, Schilling LM, Schuemie M, Shah NH, Shoaibi A, Song S, Spotnitz M, Suchard MA, Swerdel J, Vizcaya D, Volpe S, Wen H, Williams AE, Yimer BB, Zhang L, Zhuk O, Prieto-Alhambra D, Ryan P. Deep phenotyping of 34,128 patients hospitalised with COVID-19 and a comparison with 81,596 influenza patients in America, Europe and Asia: an international network study. medRxiv 2020. [PMID: 32511443 DOI: 10.1101/2020.04.22.20074336] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background In this study we phenotyped individuals hospitalised with coronavirus disease 2019 (COVID-19) in depth, summarising entire medical histories, including medications, as captured in routinely collected data drawn from databases across three continents. We then compared individuals hospitalised with COVID-19 to those previously hospitalised with influenza. Methods We report demographics, previously recorded conditions and medication use of patients hospitalised with COVID-19 in the US (Columbia University Irving Medical Center [CUIMC], Premier Healthcare Database [PHD], UCHealth System Health Data Compass Database [UC HDC], and the Department of Veterans Affairs [VA OMOP]), in South Korea (Health Insurance Review & Assessment [HIRA]), and Spain (The Information System for Research in Primary Care [SIDIAP] and HM Hospitales [HM]). These patients were then compared with patients hospitalised with influenza in 2014-19. Results 34,128 (US: 8,362, South Korea: 7,341, Spain: 18,425) individuals hospitalised with COVID-19 were included. Between 4,811 (HM) and 11,643 (CUIMC) unique aggregate characteristics were extracted per patient, with all summarised in an accompanying interactive website (http://evidence.ohdsi.org/Covid19CharacterizationHospitalization/). Patients were majority male in the US (CUIMC: 52%, PHD: 52%, UC HDC: 54%, VA OMOP: 94%,) and Spain (SIDIAP: 54%, HM: 60%), but were predominantly female in South Korea (HIRA: 60%). Age profiles varied across data sources. Prevalence of asthma ranged from 4% to 15%, diabetes from 13% to 43%, and hypertensive disorder from 24% to 70% across data sources. Between 14% and 33% were taking drugs acting on the renin-angiotensin system in the 30 days prior to hospitalisation. Compared to 81,596 individuals hospitalised with influenza in 2014-19, patients admitted with COVID-19 were more typically male, younger, and healthier, with fewer comorbidities and lower medication use. Conclusions We provide a detailed characterisation of patients hospitalised with COVID-19. Protecting groups known to be vulnerable to influenza is a useful starting point to minimize the number of hospital admissions needed for COVID-19. However, such strategies will also likely need to be broadened so as to reflect the particular characteristics of individuals hospitalised with COVID-19.
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