ArticleClinical epidemiology2022
Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS.
Article in Clinical epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Introducing an Expanded Value Framework in Health Technology Assessment of Vaccines.Journal of market access & health policy · 2026Article
- Expanding the OMOP Common Data Model to Support Perinatal Research in Network Studies.Pharmacoepidemiology and drug safety · 2025Article
- Extensive benchmarking of a method that estimates external model performance from limited statistical characteristics.NPJ digital medicine · 2025Article
- CohortDiagnostics: Phenotype evaluation across a network of observational data sources using population-level characterization.PloS one · 2025Article
- The necessity of validity diagnostics when drawing causal inferences from observational data: lessons from a multi-database evaluation of the risk of non-infectious uveitis among patients exposed to RemicadeBMC medical research methodology · 2024Article
- Country-report pattern corrections of new cases allow accurate 2-week predictions of COVID-19 evolution with the Gompertz model.Scientific reports · 2024Article
- Incidence of mental health diagnoses during the COVID-19 pandemic: a multinational network study.Epidemiology and psychiatric sciences · 2024Article
- OHDSI Standardized Vocabularies-a large-scale centralized reference ontology for international data harmonization.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Semi-supervised ROC analysis for reliable and streamlined evaluation of phenotyping algorithms.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- 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.EClinicalMedicine · 2023Article
- Integrating real-world data from Brazil and Pakistan into the OMOP common data model and standardized health analytics framework to characterize COVID-19 in the Global South.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Clinical and temporal characterization of COVID-19 subgroups using patient vector embeddings of electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Transforming the Information System for Research in Primary Care (SIDIAP) in Catalonia to the OMOP Common Data Model and Its Use for COVID-19 Research.Clinical epidemiology · 2023Article
- Natural Language Processing for Improved Characterization of COVID-19 Symptoms: Observational Study of 350,000 Patients in a Large Integrated Health Care System.JMIR public health and surveillance · 2022Observational
- Data Resource Profile: The Integrated Primary Care Information (IPCI) database, The Netherlands.International journal of epidemiology · 2022Article
- Transforming and evaluating the UK Biobank to the OMOP Common Data Model for COVID-19 research and beyond.Journal of the American Medical Informatics Association : JAMIA · 2022Observational
- Data standards and standardization: The shortest plank of bucket for the COVID-19 containment.The Lancet regional health. Western Pacific · 2022Review
- Establishment of an International Evidence Sharing Network Through Common Data Model for Cardiovascular Research.Korean circulation journal · 2022Review
- Characteristics and outcomes of COVID-19 patients with COPD from the United States, South Korea, and Europe.Wellcome open research · 2022Article
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Abstract
Purpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Patients and Methods: We conducted a descriptive retrospective database 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. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.