To analyze the effects of co-morbidities established as stroke risk factors in the setting of coronavirus disease 2019 (COVID-19).

Given the protean sequelae of COVID-19 and its emerging interplay on chronic disease states, the effects of well-established stroke risk factors must be analyzed in this context.

We conducted a retrospective analysis on 29 patients who presented with acute stroke and were found to be COVID-19 positive from 3/2020 through 8/2021. Information was collected on demographic variables, medical history, and pertinent clinical parameters. Stroke outcomes were assessed via the following: binarized modified Rankin scale score (mRSS) on discharge (4-6: poor outcome vs 0-3: good outcome [ref]), and whether mortality resulted. A series of logistic regression models adjusted for age, gender, body mass index, presence of diabetes mellitus (DM), presence of hyperlipidemia, prior history of coronary artery disease and/or cerebrovascular disease, and mean arterial pressure at admission were run to assess the association of these parameters with stroke outcomes in a cohort of COVID-19 positive stroke patients. All analyses were conducted using SAS Studio OnDemand for Academics (SAS Institute Inc., Cary, NC).

Among 29 COVID-19 patients (mean age 63.6 + 13.4 years, 65.5% males), tested clinical parameters were not shown to be significantly associated with stroke outcomes across a series of logistic regression models. Regarding mortality, presence of DM showed 5.89 times the odds of mortality (OR: 5.89; 95% CI: 0.67, 52.47; p-value: 0.11). When assessing for binarized mRSS at discharge, presence of DM showed 2.97 times the odds of a poor outcome (OR: 2.97, 95% CI: 0.27, 32.58; p-value: 0.37).

Analysis via adjusted logistic regression models revealed a statistically insignificant positive association between DM and both outcomes: worse mRSS and mortality. Further research is needed with larger patient cohorts and employing matched controls without COVID.