185 Stroke and COVID Population: A Health Equity Analysis

Abstract

OBJECTIVES/GOALS: Observational studies suggest unequal effects of COVID-19 on the population of the U.S. distinguished by race and ethnicity. Our primary research question: what are the demographic differences among patients identified with concurrent ischemic stroke and COVID-19 positivity? METHODS/STUDY POPULATION: The National Covid Cohort Collaboration (N3C) data was used to identify patients with concurrent COVID-19 and stroke, operationally defined as those with a COVID diagnosis and inpatient admission for ischemic stroke 1 week before or 6 weeks after their COVID diagnosis. The data was further age restricted (18-65 years) and a categorical variable was created representing payer plans (Medicaid, Medicare, Other insurance). Data on patients race/ethnicity, comorbidities, treatments administered (Remdesivir and ECMO) and insurance information was analyzed using various exploratory data methods and visualizations. Logistic regression was implemented to model the relationship between variables (dependent/independent) in the cohorts. Model complexity was analyzed using the F test of significance. RESULTS/ANTICIPATED RESULTS: Taken as a whole, the data contained over 7 billion rows and around 6.4 million persons (~ 2.15 million of whom were COVID+). The main cohort of individuals with concurrent COVID positivity and ischemic stroke made up around 0.29% of the original COVID+ group, and the payer plan sub-cohort consists of around 29.26% of our main cohort. Black/African American (AA) and the Hispanic/Latino any Race have younger distributions (median ~ 65 years), while the White Non-Hispanic group has the oldest distribution (median ~ 70 years). Black/AA had the highest average number of comorbidities per patient (4.49), compared to white non-Hispanic (3.39) and Asian non-Hispanic (2.59). In our analysis, Medicaid patients had lower odds of obtaining ECMO (p < .01), there was no significant difference in Remdesivir treatment. DISCUSSION/SIGNIFICANCE: We found the N3C data to be useful in studying a distinct group of patients, and exploring COVID-19 and ischemic stroke treatment across patients’ race/ethnicity identities and insurance status. Our exploratory analysis provides a foundation for further insight into demographic trends and discrepancies in apportionment of treatment.