The initial search included 1683 articles of which 6 articles were selected.
4 studies compared cases of patients presenting severe or non-severe cerebrovascular disease with a sample of 1829 confirmed Covid-19 patients (553, 30.2% being severe cases). A total of 29 patients (2.6%) had a history of cerebrovascular disease or stroke.
Two studies including 202 patients (100, 49.5% being non-survivors) compared the rate of cerebrovascular disease in Covid-19 patients who did not survive vs. survived, with 19 or 9.4% classified as non-survivors.
In the four studies on severity, only one study by Wang et al. individually had a significant OR for cerebrovascular disease and COVID-19 severity. However, in pooled analysis, cerebrovascular disease was found to be associated with a statistically significant increased risk of a severe form of COVID-19 (OR: 2.55 (95% CI: 1.18 to 5.51), I^2 = 29%, Cochran’s Q, p = 0.24).
Although heterogeneity was low, a leaveone-out sensitivity analysis was still performed. Only excluding the study by Wang et al. significantly altered the results of the analysis and appeared to be the source of heterogeneity (OR: 1.88 (95% CI: 0.828 to 4.29), I^2 = 0%, Cochran’s Q, p = 0.90). In the limited pooled analysis of mortality studies, a non-significant trend was found when evaluating association of cerebrovascular disease and enhanced risk of mortality in COVID-19 patients (OR: 2.33 (95% CI: 0.77 to 7.04), I^2 = 30%, Cochran’s Q, p = 0.23). In the meta-regression analysis, a non-significant trend was observed between mean age of patients with severe COVID-19 and log odds of cerebrovascular disease and COVID-19 severity (correlation coefficient 0.1582, 95% CI: 0.0575 to 0.3740, p = 0.15). Limited studies prevented a meta-regression for mortality.
Good review methodology but limited number of studies with small samples.
Systematic review of the literature. Databases used : Pubmed, Embase and Cochrane.
Inclusion criteria :
- Studies reporting a history of cerebrovascular disease in covid-19 patients.
- Studies reporting interesting outcomes.
Data reviewed by the same authors. Disagreements resolved by consensus.
Given the limited number of studies, no assessment of bias or publication bias.
The statistical analysis was performed using MetaXL, software version 5.3 (EpiGearInternational Pty Ltd, Sunrise Beach, Australia), in the inverse variance model.
To assess the impact of mean age in severe covid-19 patients on the association between the cerebrovascular disease and the severity of COVID-19, a random effect meta-regression using log OR was used. The study was conducted in accordance with the Declaration of Helsinki and local legislation.
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