The Relationship of COVID-19 Severity with Cardiovascular Disease and Its Traditional Risk Factors: A Systematic Review and Meta-Analysis
Kunihiro Matsushita,
Ning Ding,
Minghao Kou,
Xiao Hu,
Mengkun Chen,
Yumin Gao,
Yasuyuki Honda,
Di Zhao,
David Dowdy,
Yejin Mok,
Junichi Ishigami,
Lawrence J. Appel
Affiliations
Kunihiro Matsushita
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Ning Ding
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Minghao Kou
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Xiao Hu
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Mengkun Chen
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Yumin Gao
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Yasuyuki Honda
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Di Zhao
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
David Dowdy
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore
Yejin Mok
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Junichi Ishigami
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
Lawrence J. Appel
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore; Welch Center for Prevention, Epidemiology, and Clinical Research
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 versus <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 informative for predicting the risk of severe COVID-19.
