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Impact of diabetes status and other factors on risk for thrombotic and thromboembolic events: A multicenter, retrospective analysis using the Cerner Real-World DataTM de-identified COVID-19 cohort 

Presenter:

Erin Tallon

Date:

05-05-2022

Time:

3:30PM-4:00PM

Location:

Zoom

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a proinflammatory condition that can impact the cardiovascular and cerebrovascular systems, thereby increasing risk for thrombotic and thromboembolic events (TTE). However, little is known about the impact of diabetes status on risk for TTEs during SARS-CoV-2 infection. In this US-based, multicenter retrospective cohort study, we analyze the impact of diabetes status (i.e., diabetes present vs. diabetes absent; Type 1 diabetes versus Type 2 diabetes), race and ethnicity, sex, and other factors on risk for TTEs in adults with suspected and confirmed COVID-19 infection. After using multivariate imputation by chained equations to impute missing data and logistic mixed models to adjust for patient clustering within health systems, we examined risk factors associated with TTE of any type and TTE subtypes (e.g., myocardial infarction) across the entire cohort, as well as risk factors associated with TTE of any type in the subset of individuals with diabetes. This study demonstrates the usefulness of Cerner’s HealtheDataLab data science ecosystem and de-identified COVID-19 patient cohort for investigating health outcomes related to SARS-CoV-2 infection.

Please contact Robert Sanders (sandersrl@missouri.edu) for Zoom information.