Metadata about: Background: Whether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex. Methods: We performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data (≥10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses. Results: Of the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >~5 in >60-65 vs. <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR=1.73, [95%CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ~2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19. Conclusions: Despite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be used to inform objective decisions on COVID-19 testing, clinical management, and workforce planning.

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http://ns.inria.fr/covid19/graph/entityfishing	12
http://ns.inria.fr/covid19/graph/articles	3

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