A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity.

BACKGROUND: Cardiovascular disease (CVD), one of the most common comorbidities of coronavirus disease 2019 (COVID-19), has been suspected to be associated with adverse outcomes in COVID-19 patients, but their correlation remains controversial. METHOD: This is a quantitative meta-analysis on the basis of adjusted effect estimates. PubMed, Web of Science, MedRxiv, Scopus, Elsevier ScienceDirect, Cochrane Library and EMBASE were searched comprehensively to obtain a complete data source up to January 7, 2021. Pooled effects (hazard ratio (HR), odds ratio (OR)) and the 95% confidence intervals (CIs) were estimated to evaluate the risk of the adverse outcomes in COVID-19 patients with CVD. Heterogeneity was assessed by Cochran's Q-statistic, I2test, and meta-regression. In addition, we also provided the prediction interval, which was helpful for assessing whether the variation across studies was clinically significant. The robustness of the results was evaluated by sensitivity analysis. Publication bias was assessed by Begg's test, Egger's test, and trim-and-fill method. RESULT: Our results revealed that COVID-19 patients with pre-existing CVD tended more to adverse outcomes on the basis of 203 eligible studies with 24,032,712 cases (pooled ORs = 1.41, 95% CIs: 1.32-1.51, prediction interval: 0.84-2.39; pooled HRs = 1.34, 95% CIs: 1.23-1.46, prediction interval: 0.82-2.21). Further subgroup analyses stratified by age, the proportion of males, study design, disease types, sample size, region and disease outcomes also showed that pre-existing CVD was significantly associated with adverse outcomes among COVID-19 patients. CONCLUSION: Our findings demonstrated that pre-existing CVD was an independent risk factor associated with adverse outcomes among COVID-19 patients.

Smoking Is Independently Associated With an Increased Risk for COVID-19 Mortality: A Systematic Review and Meta-analysis Based on Adjusted Effect Estimates.

INTRODUCTION: Smoking can cause mucociliary clearing dysfunction and poor pulmonary immunity, leading to more severe infection. We performed this study to explore the association between smoking and mortality of coronavirus disease 2019 (COVID-19) patients utilizing a quantitative meta-analysis on the basis of adjusted effect estimates. AIMS AND METHODS: We conducted a systematic search of the online databases including PubMed, Web of Science, Scopus, and Embase. Only articles reporting adjusted effect estimates on the association between smoking and the risk of mortality among COVID-19 patients in English were included. Newcastle-Ottawa scale was fitted to assess the risk of bias. A random-effects model was applied to calculate the pooled effect with the corresponding 95% confidence interval (CI). RESULTS: A total of 73 articles with 863 313 COVID-19 patients were included in this meta-analysis. Our results indicated that smoking was significantly associated with an increased risk for death in patients with COVID-19 (pooled relative risk = 1.19, 95% CI = 1.12-1.27). Sensitivity analysis indicated that our results were stable and robust. CONCLUSIONS: Smoking was independently associated with an increased risk for mortality in COVID-19 patients. IMPLICATIONS: This present study may contribute to summarizing the association between smoking and the risk of COVID-19 mortality based on adjusted effect estimates. More detailed and complete data on smoking status should be collected to more accurately estimate the effect of smoking on COVID-19 mortality.

Effect of Intraocular Pressure on Aerosol Density Generated by Noncontact Tonometer Measurement.

PRECIS: Aerosols generated by a noncontact tonometer (NCT) were quantified. There was a positive correlation between aerosols and intraocular pressure (IOP), and the concentration of aerosols beside the air jet port was the highest. PURPOSE: To investigate the effects of IOP on the aerosol density generated during the use of an NCT and provide references and suggestions for daily protection of ophthalmic medical staff during the coronavirus disease-19 (COVID-19) outbreak. OBJECTIVE AND METHODS: This cross-sectional clinical trial included 214 eyes of 140 patients from a hospital in Wenzhou city, Zhejiang Province. All subjects' IOPs were measured by an NCT (39 eyes with low IOP, 90 eyes with normal IOP, 37 eyes with moderately high IOP, and 48 eyes with very high IOP) between March 7 and June 17, 2020. The density of particulate matter (PM) 2.5 and PM10 generated during the process of IOP measurement with an NCT was analyzed. IOP values were recorded simultaneously. The aerosols generated during different IOP measurements were plotted in scatter plots. RESULTS: PM2.5 was generated more at the air jet port of the tonometer during the process of IOP measurement (H=2.731, P=0.019). Larger quantities of PM2.5 and PM10 were generated when the IOP was higher, and these differences were statistically significant (PM2.5: H=119.476, P<0.001; PM10: H=160.801, P<0.001). Linear correlation analysis with one variable demonstrated that IOP had significantly positive correlations with PM2.5 (r=0.756, P<0.001) and PM10 (r=0.864, P<0.001). CONCLUSIONS: Aerosols can be generated while using an NCT to measure IOP, and aerosols and IOP are positively correlated. Patients with moderately high IOP or very high IOP tend to generate more aerosols during the IOP measurement. The concentration of aerosols beside the air jet port was the highest.

Elevated interleukin-6 and adverse outcomes in COVID-19 patients: a meta-analysis based on adjusted effect estimates.

This study aimed to evaluate the association of interleukin-6 (IL-6) level with the poor outcomes in coronavirus disease 2019 (COVID-19) patients by utilizing a meta-analysis based on adjusted effect estimates. We searched the keywords from PubMed, Web of Science, and EMBASE on August 14, 2020. The pooled effects and 95% confidence interval (95% CI) were estimated by Stata 11.2. Subgroup analysis and meta-regression were performed to explore the source of heterogeneity. Sensitivity analysis was implemented to assess the stability of the results. Begg's test and Egger's test were conducted to assess the publication bias. Sixteen articles with 8752 COVID-19 patients were finally included in the meta-analysis. The results based on random-effects model indicated that elevated value of IL-6 was significantly associated with adverse outcomes in patients with COVID-19 (pooled effect = 1.21, 95% CI 1.13-1.31, I2 = 90.7%). Subgroup analysis stratified by disease outcomes showed consistent results (severe: pooled effect = 1.18, 95% CI 1.05-1.31; ICU (intensive care unit) admission: pooled effect = 1.90, 95% CI 1.04-3.47; death: pooled effect = 3.57, 95% CI 2.10-6.07). Meta-regression indicated that study design was a source of heterogeneity. Publication bias was existent in our analysis (Begg's test: P = 0.007; Egger's test: P < 0.001). In conclusion, the elevated IL-6 level is an independent risk factor associated with adverse outcomes in patients with COVID-19.

The Association of Cerebrovascular Disease with Adverse Outcomes in COVID-19 Patients: A Meta-Analysis Based on Adjusted Effect Estimates.

OBJECTIVE: The aim of this study was to address the association between cerebrovascular disease and adverse outcomes in coronavirus disease 2019 (COVID-19) patients by using a quantitative meta-analysis based on adjusted effect estimates. METHOD: A systematic search was performed in PubMed, Web of Science, and EMBASE up to August 10th, 2020. The adjusted effect estimates were extracted and pooled to evaluate the risk of the unfavorable outcomes in COVID-19 patients with cerebrovascular disease. Subgroup analysis and meta-regression were also carried out. RESULTS: There were 12 studies with 10,304 patients included in our meta-analysis. A significant trend was observed when evaluating the association between cerebrovascular disease and adverse outcomes (pooled effect = 2.05, 95% confidence interval (CI): 1.34-3.16). In addition, the pooled effects showed that patients with a history of cerebrovascular disease had more likelihood to progress fatal outcomes than patients without a history of cerebrovascular disease (pooled effect = 1.78, 95% CI: 1.04-3.07). CONCLUSION: This study for the first time indicated that cerebrovascular disease was an independent risk factor for predicting the adverse outcomes, particularly fatal outcomes, in COVID-19 patients on the basis of adjusted effect estimates. Well-designed studies with larger sample size are needed for further verification.