Abstract 42: Epidemiological Surveillance of the Impact of the Covid-19 Pandemic on Stroke Care Using Artificial Intelligence

Abstract

Background: The degree to which the COVID-19 pandemic has affected systems of care, in particular those for time-sensitive conditions such as stroke, remains poorly quantified. We sought to evaluate the impact of COVID-19 in the overall screening for acute stroke utilizing a commercial clinical artificial intelligence (AI) platform. Methods: Data were derived from the Viz Platform, an AI application designed to optimize the workflow of acute stroke patients. Neuroimaging data on suspected stroke patients across 97 hospitals in 20 US states were collected in real-time and retrospectively analyzed with the number of patients undergoing imaging screening serving as a surrogate for the amount of stroke care. The main outcome measures were the number of CTA, CTP, Large vessel occlusions (LVOs) (defined according to the automated software detection), and severe strokes on CTP (defined as those with hypoperfusion volumes>70mL) normalized as number of patients per day per hospital. Data from the pre-pandemic (November 4, 2019 to February 29, 2020) and pandemic (March 1 to May 10, 2020) periods were compared at national and state levels. Correlations were made between the inter-period changes in imaging screening, stroke hospitalizations, and thrombectomy procedures using state-specific sampling. Results: A total of 23,223 patients were included. The incidence of LVO on CTA and severe strokes on CTP were 11.2%(n=2,602) and 14.7%(n=1,229/8,328), respectively. There were significant declines in the overall number of CTAs (-22.8%;1.39 to 1.07 patients/day/hospital,p<0.001) and CTPs (-26.1%;0.50 to 0.37 patients/day/hospital,p<0.001) as well as in the incidence of LVO (-17.1%;0.15 to 0.13 patients/day/hospital,p<0.001) and severe strokes on CTP (-16.7%;0.12 to 0.10 patients/day/hospital, p<0.005). The sampled cohort showed similar declines in the rates of LVOs versus thrombectomy (18.8%vs.19.5%, p=0.9) and CSC hospitalizations (18.8%vs.11.0%, p=0.4). Conclusions: A significant decline in stroke imaging screening has occurred during the COVID-19 pandemic. This underscores the broader application of AI neuroimaging platforms for the real-time monitoring of stroke systems of care.