Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Real world data 330 Clinical Sciences OMOP CDM 610 Infectious and parasitic diseases RC109-216 613 real world evidence Article OHDSI SDG 3 - Good Health and Well-being Clinical Research open science Clinical Epidemiology Aetiology Original Research ohdsi Prevention name=Epidemiology omop cdm 004 Descriptive epidemiology 3. Good health real world data Infectious Diseases Good Health and Well Being /dk/atira/pure/subjectarea/asjc/2700/2713 Public Health and Health Services Real world evidence Open science descriptive epidemiology 2.4 Surveillance and distribution
DOI: 10.2147/clep.s323292 Publication Date: 2022-03-21T16:00:13Z
ABSTRACT
Abstract Background: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Methods: We conducted a descriptive cohort study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub [4]. Findings: We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts, and are available in an interactive website: https://data.ohdsi.org/Covid19CharacterizationCharybdis/. Interpretation: CHARYBDIS findings provide benchmarks that contribute to our understanding of COVID-19 progression, management and evolution over time. This can enable timely assessment of real-world outcomes of preventative and therapeutic options as they are introduced in clinical practice.
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