Phenotype Algorithms for the Identification and Characterization of Vaccine-Induced Thrombotic Thrombocytopenia in Real World Data: A Multinational Network Cohort Study

0301 basic medicine COVID-19 Vaccines /dk/atira/pure/subjectarea/asjc/3000/3004 /dk/atira/pure/subjectarea/asjc/3000/3005 610 COVID-19 name=Toxicology Thrombosis name=Pharmacology Vacunes -- Efectes secundaris Thrombocytopenia 3. Good health Fenotip Cohort Studies name=Pharmacology (medical) 03 medical and health sciences Phenotype SDG 3 - Good Health and Well-being Trombocitopènia /dk/atira/pure/subjectarea/asjc/2700/2736 Humans Original Research Article Algorithms Retrospective Studies
DOI: 10.1007/s40264-022-01187-y Publication Date: 2022-06-02T10:04:56Z
ABSTRACT
Vaccine-induced thrombotic thrombocytopenia (VITT) has been identified as a rare but serious adverse event associated with coronavirus disease 2019 (COVID-19) vaccines. In this study, we explored the pre-pandemic co-occurrence of thrombosis (TWT) using 17 observational health data sources across world. We applied multiple TWT definitions, estimated background rate TWT, characterized patients, and makeup types among patients. conducted an international network retrospective cohort study electronic records insurance claims data, estimating rates amongst persons observed from 2017 to 2019. Following principles existing VITT clinical was defined patients diagnosis embolic or arterial venous events measurement within 7 days. Six phenotypes were considered, which varied in approach taken defining real world data. Overall incidence ranged 1.62 150.65 per 100,000 person-years. Substantial heterogeneity exists by age, sex, alternative phenotypes. likely be men older age various comorbidities. Among types, most common. Our findings suggest that identifying presents substantial challenge, implementing case definitions based on results large heterogeneous patints baseline characteristics are inconsistent cases reported date.
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