Peripheral artery disease independently associated with significantly higher risk for COVID-19 mortality: Evidence based on adjusted effect estimates.

OBJECTIVE: To investigate the influence of peripheral artery disease (PAD) on the risk of mortality among coronavirus disease 2019 (COVID-19) patients based on adjusted effect estimates. METHODS: Systematic searches were performed through electronic databases. A random-effect model was applied to calculate the pooled effect and corresponding 95% confidence interval (CI). Inconsistency index (I2) was used to evaluate the heterogeneity across studies. Sensitivity analysis, subgroup analysis, and Begg's test were all implemented. RESULTS: On the basis of 16 eligible studies with 142,832 COVID-19 patients, the meta-analysis showed that PAD significantly increased the risk for mortality among COVID-19 patients (pooled effect = 1.29, 95% CI: 1.10-1.51). The significant association was also observed in the subgroup analysis stratified by hospitalized patients, mean age ≥ 60 years, Europe and North America. Sensitivity analysis verified the robustness of our findings. Begg's test (P = 0.15) showed there was no potential publication bias. CONCLUSIONS: COVID-19 patients with PAD may have a greater risk of mortality. Clinicians and nursing staff are supposed to identify and monitor these high-risk patients in a timely manner and provide appropriate clinical treatment for them.

Significant association between HIV infection and increased risk of COVID-19 mortality: a meta-analysis based on adjusted effect estimates.

To investigate the relationship between human immunodeficiency virus (HIV) infection and the risk of mortality among coronavirus disease 2019 (COVID-19) patients based on adjusted effect estimate by a quantitative meta-analysis. A random-effects model was used to estimate the pooled effect size (ES) with corresponding 95% confidence interval (CI). I2 statistic, sensitivity analysis, Begg's test, meta-regression and subgroup analyses were also conducted. This meta-analysis presented that HIV infection was associated with a significantly higher risk of COVID-19 mortality based on 40 studies reporting risk factors-adjusted effects with 131,907,981 cases (pooled ES 1.43, 95% CI 1.25-1.63). Subgroup analyses by male proportion and setting yielded consistent results on the significant association between HIV infection and the increased risk of COVID-19 mortality. Allowing for the existence of heterogeneity, further meta-regression and subgroup analyses were conducted to seek the possible source of heterogeneity. None of factors might be possible reasons for heterogeneity in the further analyses. Sensitivity analysis indicated the robustness of this meta-analysis. The Begg's test manifested that there was no publication bias (P = 0.2734). Our findings demonstrated that HIV infection was independently associated with a significantly increased risk of mortality in COVID-19 patients. Further well-designed studies based on prospective study estimates are warranted to confirm our findings.

Systematic Analysis of Coronavirus Disease 2019 (COVID-19) Receptor ACE2 in Malignant Tumors: Pan-Cancer Analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) was first detected in patients with pneumonia in December 2019 in China and it spread rapidly to the rest of the world becoming a global pandemic. Several observational studies have reported that cancer is a risk factor for COVID-19. On the other hand, ACE2, a receptor for the SARS-CoV-2 virus, was found to be aberrantly expressed in many tumors. However, the characterization of aberrant ACE2 expression in malignant tumors has not been elucidated. Here, we conducted a systematic analysis of the ACE2 expression profile across 31 types of tumors. METHODS: Distribution of ACE2 expression was analyzed using the GTEx, CCLE, TCGA pan-cancer databases. We evaluated the effect of ACE2 on clinical prognosis using the Kaplan-Meier survival plot and COX regression analysis. Correlation between ACE2 and immune infiltration levels was investigated in various cancer types. Additionally, the correlation between ACE2 and immune neoantigen, TMB, microsatellite instability, Mismatch Repair Genes (MMRs), HLA gene members, and DNA Methyltransferase (DNMT) was investigated. The frequency of ACE2 gene mutation in various tumors was analyzed. Functional enrichment analysis was conducted in various cancer types using the GSEA method. RESULTS: In normal tissues, ACE2 was highly expressed in almost all 31 organs tested. In cancer cell lines, the expression level of ACE2 was low to medium. Although aberrant expression was observed in most cancer types, high expression of ACE2 was not linked to OS, DFS, RFS, and DFI in most tumors in TCGA pan-cancer data. We found that ACE2 expression was significantly correlated with the infiltrating levels of macrophages and dendritic cells, CD4+ T cells, CD8+ T cells, and B cells in multiple tumors. A positive correlation between ACE2 expression and immune neoantigen, TMB, and microsatellite instability was found in multiple cancers. GSEA analysis which was carried out to determine the effect of ACE2 on tumors indicated that several cancer-associated pathways and immune-related pathways were hyperactivated in the high ACE2 expression group of most tumors. CONCLUSION: These findings suggest that ACE2 is not correlated with prognosis in most cancer types. However, elevated ACE2 is significantly correlated with immune infiltrating levels, including those of CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and DCs in multiple cancers, especially in lung and breast cancer patients. These findings suggest that ACE2 may affect the tumor environment in cancer patients with COVID-19.

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.