Effects of hypertension, diabetes and coronary heart disease on COVID-19 diseases severity: a systematic review and meta-analysis

Summary 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)