Hospital Outcomes among COVID-19 Hospitalizations with Acute Ischemic Stroke: Cross-Sectional Study Results from California State Inpatient Database.
Muni RubensAnshul SaxenaVenkataraghavan RamamoorthyMd Ashfaq AhmedZhenwei ZhangPeter McGranaghanEmir VeledarMichael McDermottFelipe De Los Rios La RosaPublished in: Brain sciences (2022)
Coronavirus disease 2019 (COVID-19) could be a risk factor for acute ischemic stroke (AIS) due to the altered coagulation process and hyperinflammation. This study examined the risk factors, clinical profile, and hospital outcomes of COVID-19 hospitalizations with AIS. This study was a retrospective analysis of data from California State Inpatient Database (SID) during 2019 and 2020. COVID-19 hospitalizations with age ≥ 18 years during 2020 and a historical cohort without COVID-19 from 2019 were included in the analysis. The primary outcomes studied were in-hospital mortality and discharge to destinations other than home. There were 91,420 COVID-19 hospitalizations, of which, 1027 (1.1%) had AIS. The historical control cohort included 58,083 AIS hospitalizations without COVID-19. Conditional logistic regression analysis showed that the odds of in-hospital mortality, discharge to destinations other than home, DVT, pulmonary embolism, septic shock, and mechanical ventilation were significantly higher among COVID-19 hospitalizations with AIS, compared to those without AIS. The odds of in-hospital mortality, DVT, pulmonary embolism, septic shock, mechanical ventilation, and respiratory failure were significantly higher among COVID-19 hospitalizations with AIS, compared to AIS hospitalizations without COVID-19. Although the prevalence of AIS was low among COVID-19 hospitalizations, it was associated with higher mortality and greater rates of discharges to destinations other than home.
Keyphrases
- coronavirus disease
- sars cov
- pulmonary embolism
- mechanical ventilation
- acute ischemic stroke
- respiratory syndrome coronavirus
- risk factors
- healthcare
- septic shock
- respiratory failure
- intensive care unit
- machine learning
- emergency department
- extracorporeal membrane oxygenation
- adverse drug
- adipose tissue
- artificial intelligence