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Increased risk of acute stroke among patients with severe COVID‐19: a multicenter study and meta‐analysis.

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Title: Increased risk of acute stroke among patients with severe COVID‐19: a multicenter study and meta‐analysis.
Authors: Siepmann, T. (AUTHOR), Sedghi, A. (AUTHOR), Simon, E. (AUTHOR), Winzer, S. (AUTHOR), Barlinn, J. (AUTHOR), With, K. (AUTHOR), Mirow, L. (AUTHOR), Wolz, M. (AUTHOR), Gruenewald, T. (AUTHOR), Schroettner, P. (AUTHOR), Bonin, S. (AUTHOR), Pallesen, L.‐P. (AUTHOR), Rosengarten, B. (AUTHOR), Schubert, J. (AUTHOR), Lohmann, T. (AUTHOR), Machetanz, J. (AUTHOR), Spieth, P. (AUTHOR), Koch, T. (AUTHOR), Bornstein, S. (AUTHOR), Reichmann, H. (AUTHOR)
Source: European Journal of Neurology. Jan2021, Vol. 28 Issue 1, p238-247. 10p.
Subjects: COVID-19, Stroke patients
Geographic Terms: Saxony (Germany), Germany
Abstract: Background and purpose: Recent observations linked coronavirus disease 2019 (COVID‐19) to thromboembolic complications possibly mediated by increased blood coagulability and inflammatory endothelial impairment. We aimed to define the risk of acute stroke in patients with severe and non‐severe COVID‐19. Methods: We performed an observational, multicenter cohort study in four participating hospitals in Saxony, Germany to characterize consecutive patients with laboratory‐confirmed COVID‐19 who experienced acute stroke during hospitalization. Furthermore, we conducted a systematic review using PubMed/MEDLINE, Embase, Cochrane Library and bibliographies of identified papers following Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines including data from observational studies of acute stroke in COVID‐19 patients. Data were extracted by two independent reviewers and pooled with multicenter data to calculate risk ratios (RRs) and 95% confidence intervals (95% CIs) for acute stroke related to COVID‐19 severity using a random‐effects model. Between‐study heterogeneity was assessed using Cochran's Q and I2 statistics. International Prospective Register of Systematic Reviews registration number: CRD42020187194. Results: Of 165 patients hospitalized for COVID‐19 (49.1% males, median age = 67 years [57–79 years], 72.1% severe or critical) included in the multicenter study, overall stroke rate was 4.2% (95% CI: 1.9–8.7). Systematic literature search identified two observational studies involving 576 patients that were eligible for meta‐analysis. Amongst 741 pooled COVID‐19 patients, overall stroke rate was 2.9% (95% CI: 1.9–4.5). Risk of acute stroke was increased for patients with severe compared to non‐severe COVID‐19 (RR = 4.18, 95% CI: 1.7–10.25; P = 0.002) with no evidence of heterogeneity (I2 = 0%, P = 0.82). Conclusions: Synthesized analysis of data from our multicenter study and previously published cohorts indicates that severity of COVID‐19 is associated with an increased risk of acute stroke. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Increased risk of acute stroke among patients with severe COVID‐19: a multicenter study and meta‐analysis.
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Neurology%22">European Journal of Neurology</searchLink>. Jan2021, Vol. 28 Issue 1, p238-247. 10p.
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  Label: Abstract
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  Data: Background and purpose: Recent observations linked coronavirus disease 2019 (COVID‐19) to thromboembolic complications possibly mediated by increased blood coagulability and inflammatory endothelial impairment. We aimed to define the risk of acute stroke in patients with severe and non‐severe COVID‐19. Methods: We performed an observational, multicenter cohort study in four participating hospitals in Saxony, Germany to characterize consecutive patients with laboratory‐confirmed COVID‐19 who experienced acute stroke during hospitalization. Furthermore, we conducted a systematic review using PubMed/MEDLINE, Embase, Cochrane Library and bibliographies of identified papers following Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines including data from observational studies of acute stroke in COVID‐19 patients. Data were extracted by two independent reviewers and pooled with multicenter data to calculate risk ratios (RRs) and 95% confidence intervals (95% CIs) for acute stroke related to COVID‐19 severity using a random‐effects model. Between‐study heterogeneity was assessed using Cochran's Q and I2 statistics. International Prospective Register of Systematic Reviews registration number: CRD42020187194. Results: Of 165 patients hospitalized for COVID‐19 (49.1% males, median age = 67 years [57–79 years], 72.1% severe or critical) included in the multicenter study, overall stroke rate was 4.2% (95% CI: 1.9–8.7). Systematic literature search identified two observational studies involving 576 patients that were eligible for meta‐analysis. Amongst 741 pooled COVID‐19 patients, overall stroke rate was 2.9% (95% CI: 1.9–4.5). Risk of acute stroke was increased for patients with severe compared to non‐severe COVID‐19 (RR = 4.18, 95% CI: 1.7–10.25; P = 0.002) with no evidence of heterogeneity (I2 = 0%, P = 0.82). Conclusions: Synthesized analysis of data from our multicenter study and previously published cohorts indicates that severity of COVID‐19 is associated with an increased risk of acute stroke. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of European Journal of Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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