ABSTRACT
Background/Objective: To evaluate the impact of the COVID-19 pandemic on hospital admissions and outcomes in patients admitted with acute ischemic stroke. Methods: Single-center retrospective analysis of patients admitted to the hospital with acute ischemic stroke, between December 1st, 2019 and June 30th, 2020. Outcomes were classified as none-to-minimal disability, moderate-to-severe disability, and death based on discharge disposition, and compared between two time periods: pre-COVID-19 era (December 1st, 2019 to March 11th, 2020) and COVID19 era (March 12th to June 30th, 2020). We also performed a comparative trend analysis for the equivalent period between 2019 and 2020. Results: Five hundred and seventy-five patients with a mean age (years +/- SD) of 68 +/- 16 were admitted from December 1st, 2019 to June 30th, 2020, with a clinical diagnosis of acute ischemic stroke. Of these, 255 (44.3%) patients were admitted during the COVID-19 era. We observed a 22.1% and 39.5% decline in admission for acute ischemic stroke in April and May 2020, respectively. A significantly higher percentage of patients with acute ischemic stroke received intravenous thrombolysis during the COVID-1 9 era (p = 0.020). In patients with confirmed COVID-19, we found a higher percentage of older men with preexisting comorbidities such as hyperlipidemia, coronary artery disease, and diabetes mellitus but a lower rate of atrial fibrillation. In addition, we found a treatment delay in both intravenous thrombolysis (median 94.5 min versus 38 min) and mechanical thrombectomy (median 244 min versus 86 min) in patients with confirmed COVID-19 infection. There were no differences in patients' disposition including home, short-term, and long-term facility (p = 0.60). Conclusions: We observed a reduction of hospital admissions in acute ischemic strokes and some delay in reperfusion therapy during the COVID-1 9 pandemic. Prospective studies and a larger dataset analysis are warranted.
ABSTRACT
Today, the world suffers from the rapid spread of COVID-19, which has claimed thousands of lives. Unfortunately, its treatment is yet to be developed. Nevertheless, this phenomenon can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. In this study, the early diagnosis of this disease through artificial intelligence (AI) technology is explored. AI is a revolutionizing technology that drives new research opportunities in various fields. Although this study does not provide a final solution, it highlights the most promising lines of research on AI technology for the diagnosis of COVID-19. The major contribution of this work is a discussion on the following substantial issues of AI technology for preventing the severe effects of COVID-19: (1) rapid diagnosis and detection, (2) outbreak and prediction of virus spread, and (3) potential treatments. This study profoundly investigates these controversial research topics to achieve a precise, concrete, and concise conclusion. Thus, this study provides significant recommendations on future research directions related to COVID-19.