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Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort study
EA. Voss, A. Shoaibi, L. Yin Hui Lai, C. Blacketer, T. Alshammari, R. Makadia, K. Haynes, AG. Sena, G. Rao, S. van Sandijk, C. Fraboulet, L. Boyer, T. Le Carrour, S. Horban, DR. Morales, J. Martínez Roldán, JM. Ramírez-Anguita, MA. Mayer, M. de...
Status neindexováno Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 2018
PubMed Central
od 2018
Europe PubMed Central
od 2018
ROAD: Directory of Open Access Scholarly Resources
od 2018
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines, but with COVID-19. Our aim was to characterise the incidence rates of AESIs following SARS-CoV-2 infection in patients and compare these to historical rates in the general population. METHODS: A multi-national cohort study with data from primary care, electronic health records, and insurance claims mapped to a common data model. This study's evidence was collected between Jan 1, 2017 and the conclusion of each database (which ranged from Jul 2020 to May 2022). The 16 pre-specified prevalent AESIs were: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain- Barré syndrome, haemorrhagic stroke, non-haemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, transverse myelitis, and thrombosis with thrombocytopenia. Age-sex standardised incidence rate ratios (SIR) were estimated to compare post-COVID-19 to pre-pandemic rates in each of the databases. FINDINGS: Substantial heterogeneity by age was seen for AESI rates, with some clearly increasing with age but others following the opposite trend. Similarly, differences were also observed across databases for same health outcome and age-sex strata. All studied AESIs appeared consistently more common in the post-COVID-19 compared to the historical cohorts, with related meta-analytic SIRs ranging from 1.32 (1.05 to 1.66) for narcolepsy to 11.70 (10.10 to 13.70) for pulmonary embolism. INTERPRETATION: Our findings suggest all AESIs are more common after COVID-19 than in the general population. Thromboembolic events were particularly common, and over 10-fold more so. More research is needed to contextualise post-COVID-19 complications in the longer term. FUNDING: None.
British Heart Foundation Data Science Centre London UK
Center for Data driven Insights and Innovation University of California Health Oakland CA USA
Centre for Statistics in Medicine NDORMS University of Oxford Oxford UK
Clinical Practice Research Datalink Medicines and Healthcare Products Regulatory Agency London UK
College of Pharmacy Prince Sattam Bin Abdulaziz University Alkharj Kingdom of Saudi Arabia
Department of Biomedical Informatics Columbia University Irving Medical Center New York NY USA
Department of Biostatistics University of California Los Angeles Los Angeles CA USA
Department of Informatics Imaging and Data Sciences University of Manchester Manchester UK
Department of Medical Informatics Erasmus University Medical Center Rotterdam the Netherlands
Department of Medical Information Assistance Publique Hopitaux de Marseille Marseille France
Department of Medicine and Life Sciences Universitat Pompeu Fabra Barcelona Spain
Department of Public Health University of Southern Denmark Odense Denmark
Department of Systems Engineering School of Engineering Universidad del Norte Barranquilla Colombia
Division of Population Health and Genomics University of Dundee Dundee UK
Fundación para la Investigación e Innovación Biosanitaria en Atención Primaria Madrid Spain
Health Data Research UK London UK
Health Informatics Centre University of Dundee Dundee UK
Hospital del Mar Department of Innovation and Digital Transformation Barcelona Spain
Hospital del Mar Medical Research Institute Barcelona Spain
Hospital Universitario 12 de Octubre Madrid Spain
Instituto de Investigación Hospital 12 de Octubre Madrid Spain
Janssen Pharmaceutical Research and Development LLC Titusville NJ USA
Medaman BV Geel Flanders Belgium
New York Presbyterian Hospital New York NY USA
O'Brien Institute for Public Health Faculty of Medicine University of Calgary Alberta CA USA
Odysseus Data Services Prague Czechia
OHDSI Collaborators Observational Health Data Sciences and Informatics New York NY USA
Stanford School of Medicine Stanford University Palo Alto CA USA
University College London Institute of Health Informatics London UK
University of Colorado Anschutz Medical Campus Denver CO USA
University of Tartu Tartu Estonia
VA Informatics and Computing Infrastructure US Department of Veterans Affairs Salt Lake City UT USA
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