Effects of hypertension, diabetes and coronary heart disease on COVID-19 diseases severity: a systematic review and meta-analysis
Abstract
Background
COVID-19 patients with chronic diseases such as hypertension, diabetes and coronary heart diseases is more likely to worsen, but with mixed results for COVID-19 severity. This meta-analysis is to analyze the correlation between hypertension, diabetes, coronary heart disease and COVID-19 disease severity.
Methods
Available data from PubMed, Web of Science, China National Knowledge Infrastructure Database, WanFang Database and VIP Database, were analyzed using a fixed effects model meta-analysis to derive overall odds ratios (OR) with 95% CIs. Funnel plots and Begg’s were used to assess publication bias.
Findings
Of 182 articles found following our initial search, we assessed 34 full-text articles, of which 9 articles with 1936 COVID-19 patients met all selection criteria for our meta-analysis. No significant heterogeneity between studies. There were significant correlations between COVID-19 severity and hypertension [OR=2.3 [95% CI (1.76, 3.00), P<0.01], diabetes [OR=2.67, 95% CI (1.91, 3.74), P<0.01], coronary heart disease [OR=2.85 [95% CI (1.68, 4.84), P<0.01]. Most of the studies in the funnel plot are on the upper part and few on the base part, and are roughly symmetrical left and right. Begg’s test: hypertension (Z=-0.1, P=1.0), diabetes (Z=0.73, P=0.466), coronary heart disease (Z=0.38, P=0.707), all found no publication bias.
Interpretation
Hypertension, diabetes, and coronary heart disease can affect the severity of COVID-19. It may be related to the imbalance of angiotensin-converting enzyme 2 (ACE2) and the cytokine storm induced by Glucolipid metabolic disorders (GLMD).
Funding
National Natural Science Foundation of China (No. 81830113, 81530102); Major basic and applied basic research projects of Guangdong Province of China (No. 2019B030302005); National key R & D plan “Research on modernization of traditional Chinese medicine” (No. 2018YFC1704200) and Natural Science Foundation of Guangdong Province (No. 2018A030313391)
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