A pilot study of application of the Stroke Riskometer mobile app for assessment of the course and clinical outcomes of COVID-19 among hospitalised patients
Permanent link to Research Commons versionhttps://hdl.handle.net/10289/15506
Early determination of COVID-19 severity and health outcomes could facilitate better treatment of patients. Different methods and tools have been developed for predicting outcomes of COVID-19, but they are difficult to use in routine clinical practice. Methods: We conducted a prospective cohort study of inpatients aged 20-92 years, diagnosed with COVID-19 to determine whether their individual 5-year absolute risk of stroke at the time of hospital admission predicts the course of COVID-19 severity and mortality. The risk of stroke was determined by the Stroke Riskometer mobile application. Results: We examined 385 patients hospitalised with COVID-19 (median age 61 years). The participants were categorised based on COVID-19 severity: 271 (70.4%) to the “Not severe” and 114 (29.6%) to the “Severe” groups. The median risk of stroke the next day after hospitalisation was significantly higher among patients in the Severe group (2.83 [95% CI 2.35-4.68]) vs the Not severe group (1.11 [95% CI 1.00–1.29]). The median risk of stroke and median systolic blood pressure (SBP) were significantly higher among non-survivors (12.04 [95% CI 2.73-21.19]) and (150 [95% CI 140-170]) vs survivors (1.31 [95% CI 1.14-1.52]), 134 [95% CI 130-135]), respectively. Those who spent more than 2.5 hours a week on physical activity were 3.1 times more likely to survive from COVID-19. Those who consumed more than one standard alcohol drink a day, or suffered with atrial fibrillation, or had poor memory were 2.5, 2.3, and 2.6 times more likely not to survive from COVID-19, respectively. Conclusions: High risk of stroke, physical inactivity, alcohol intake, high SBP, and atrial fibrillation are associated with severity and mortality of COVID-19. Our findings suggest that the Stroke Riskometer app could be used as a simple predictive tool of COVID-19 severity and mortality.
This is an author’s accepted version of an article published in the journal: Cerebrovascular Diseases Extra. © 2023 The Authors. Published by S. Karger AG, Basel. This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission.