A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients
Introduction: 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 prospecti...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Karger Publishers
2023-01-01
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| Series: | Cerebrovascular Diseases Extra |
| Subjects: | |
| Online Access: | https://www.karger.com/Article/FullText/529277 |
| _version_ | 1829455011802775552 |
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| author | Alexander Merkin Sofya Akinfieva Oleg N. Medvedev Rita V. Krishnamurthi Alexey Gutsaluk Ulf-Dietrich Reips Rufat Kuliev Evgeny Dinov Igor Nikiforov Nikolay Shamalov Polina Shafran Lyudmila Popova Dmitry Burenchev Valery L. Feigin |
| author_facet | Alexander Merkin Sofya Akinfieva Oleg N. Medvedev Rita V. Krishnamurthi Alexey Gutsaluk Ulf-Dietrich Reips Rufat Kuliev Evgeny Dinov Igor Nikiforov Nikolay Shamalov Polina Shafran Lyudmila Popova Dmitry Burenchev Valery L. Feigin |
| author_sort | Alexander Merkin |
| collection | DOAJ |
| description | Introduction: 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 hospitalized with COVID-19 (median age 61 years). The participants were categorized 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 hospitalization was significantly higher among patients in the severe group (2.83, 95% CI: 2.35–4.68) versus 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) versus survivors (1.31, 95% CI: 1.14–1.52) and (134, 95% CI: 130–135), respectively. Those who spent more than 2.5 h 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. |
| first_indexed | 2024-04-10T07:42:43Z |
| format | Article |
| id | doaj.art-d3f8beb506fb40dba9f08aff905dbef6 |
| institution | Directory Open Access Journal |
| issn | 1664-5456 |
| language | English |
| last_indexed | 2024-04-10T07:42:43Z |
| publishDate | 2023-01-01 |
| publisher | Karger Publishers |
| record_format | Article |
| series | Cerebrovascular Diseases Extra |
| spelling | doaj.art-d3f8beb506fb40dba9f08aff905dbef62023-02-23T11:31:01ZengKarger PublishersCerebrovascular Diseases Extra1664-54562023-01-011110.1159/000529277529277A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized PatientsAlexander Merkin0Sofya Akinfieva1Oleg N. Medvedev2https://orcid.org/0000-0002-2167-5002Rita V. Krishnamurthi3Alexey Gutsaluk4Ulf-Dietrich Reips5https://orcid.org/0000-0002-1566-4745Rufat Kuliev6Evgeny Dinov7Igor Nikiforov8Nikolay Shamalov9https://orcid.org/0000-0001-6250-0762Polina Shafran10Lyudmila Popova11https://orcid.org/0000-0002-3496-6466Dmitry Burenchev12https://orcid.org/0000-0003-2894-6255Valery L. Feigin13National Institute for Stroke and Applied Neurosciences, Faculty of Health & Environmental Sciences, AUT University, Auckland, New ZealandNational Centre for Development of Social Support and Rehabilitation, Moscow, Russian FederationSchool of Psychology, The University of Waikato, Hamilton, New ZealandNational Institute for Stroke and Applied Neurosciences, Faculty of Health & Environmental Sciences, AUT University, Auckland, New ZealandThe City Clinical Hospital Named after A.K. Eramishantsev, Moscow, Russian FederationiScience group, Department of Psychology, University of Konstanz, Konstanz, GermanyThe City Clinical Hospital Named after A.K. Eramishantsev, Moscow, Russian FederationDepartment of Psychology, Russian Peoples’ Friendship University, Moscow, Russian FederationAcademy for Postgraduate Education, Moscow, Russian FederationPirogov Russian National Research Medical University, Moscow, Russian FederationThe City Clinical Hospital Named after A.K. Eramishantsev, Moscow, Russian FederationI.M. Sechenov First Moscow State Medical University, Moscow, Russian FederationThe City Clinical Hospital Named after A.K. Eramishantsev, Moscow, Russian FederationNational Institute for Stroke and Applied Neurosciences, Faculty of Health & Environmental Sciences, AUT University, Auckland, New ZealandIntroduction: 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 hospitalized with COVID-19 (median age 61 years). The participants were categorized 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 hospitalization was significantly higher among patients in the severe group (2.83, 95% CI: 2.35–4.68) versus 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) versus survivors (1.31, 95% CI: 1.14–1.52) and (134, 95% CI: 130–135), respectively. Those who spent more than 2.5 h 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.https://www.karger.com/Article/FullText/529277stroke riskometer mobile appstrokecovid-19comorbiditypredictionseverity |
| spellingShingle | Alexander Merkin Sofya Akinfieva Oleg N. Medvedev Rita V. Krishnamurthi Alexey Gutsaluk Ulf-Dietrich Reips Rufat Kuliev Evgeny Dinov Igor Nikiforov Nikolay Shamalov Polina Shafran Lyudmila Popova Dmitry Burenchev Valery L. Feigin A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients Cerebrovascular Diseases Extra stroke riskometer mobile app stroke covid-19 comorbidity prediction severity |
| title | A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients |
| title_full | A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients |
| title_fullStr | A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients |
| title_full_unstemmed | A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients |
| title_short | A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients |
| title_sort | pilot study of application of the stroke riskometer mobile app for assessment of the course and clinical outcomes of covid 19 among hospitalized patients |
| topic | stroke riskometer mobile app stroke covid-19 comorbidity prediction severity |
| url | https://www.karger.com/Article/FullText/529277 |
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