The association of diabetes with COVID-19 disease severity: evidence from adjusted effect estimates.
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ABSTRACT:
SUBMITTER: Liang X
PROVIDER: S-EPMC7685958 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
The association of diabetes with COVID-19 disease severity: evidence from adjusted effect estimates.
Liang Xuan X Xu Jie J Xiao Wenwei W Shi Li L Yang Haiyan H
Hormones (Athens, Greece) 20201125 2
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Project description:ObjectiveThe aim of this study was to address the association between interstitial lung disease and the risk for severity and mortality among patients with coronavirus disease 2019 (COVID-19).MethodsThe electronic databases of PubMed, Web of Science and EMBASE were systematically searched. The pooled effect size with 95 % confidence interval (CI) was computed by a random-effects meta-analysis model. Heterogeneity test, sensitivity analysis, subgroup analysis, meta-regression analysis, Begg's test and Egger's test were performed.ResultsA total of sixteen eligible studies with 217,260 COVID-19 patients were enrolled in this meta-analysis. The findings based on adjusted effect estimates indicated that pre-existing interstitial lung disease was significantly associated with higher risk for COVID-19 severity (pooled effect = 1.34 [95 % CI: 1.16-1.55]) and mortality (pooled effect = 1.26 [95 % CI: 1.09-1.46]). Consistent results were observed in the subgroup analysis stratified by sample size, age, the percentage of male patients, study design, setting, the methods for adjustment and the factors for adjustment. The results of meta-regression demonstrated that sample size, age and region might be the potential sources of heterogeneity. Sensitivity analysis exhibited that our results were stable and robust. No publication bias was observed in Egger's test and Begg's test.ConclusionThis meta-analysis on the basis of adjusted effect estimates demonstrated that pre-existing interstitial lung disease was independently associated with significantly higher risk for COVID-19 severity and mortality.
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Project description:We investigated the association between endogenous vitamin D and the severity of COVID-19 as well as the mechanisms of action of vitamin D supplementation. Vitamin D deficiency and insufficiency were associated with increased severity and unfavourable outcome after 28 days. Vitamin D levels were negatively associated with biomarkers of COVID-19 severity. Vitamin D supplementation after challenge of mice with COVID-19 plasma led to reduced levels of TNFα, IL-6, IFNγ and MPO in the lung, as well as down-regulation of pro-inflammatory pathways as derived from RNA-seq experiments. Thus, vitamin D demonstrates a protective effect against severity and unfavorable outcome in COVID-19, possibly through attenuation of tissue-specific hyperinflammation.
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Project description:ObjectiveThis study aimed to evaluate whether there was a significant relationship between anemia and the risk for mortality among coronavirus disease 2019 (COVID-19) patients by a quantitative meta-analysis based on the adjusted effect estimates.MethodsA systematic search was conducted in electronic databases to identify all published literature. A random-effects meta-analysis model was used to estimate the pooled effect size and 95% confidence interval (CI). Heterogeneity test, Begg's test, subgroup analysis and meta-regression were performed.ResultsTwenty-three articles with 573,928 COVID-19 patients were included in the quantitative meta-analysis. There was a significant association between anemia and an elevated risk of COVID-19 mortality (pooled effect size = 1.47, 95% CI [1.30-1.67]). We observed this significant association in the further subgroup analyses by age, proportion of males, sample size, study design, region and setting. Sensitivity analysis exhibited that our results were reliable. Begg's test showed that there was no publication bias. Meta-regression indicated that the tested variables might not be the source of heterogeneity.ConclusionOur meta-analysis based on risk factors-adjusted effect estimates indicated that anemia was independently associated with a significantly elevated risk for mortality among COVID-19 patients.
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Project description:BackgroundCardiovascular 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.MethodThis 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.ResultOur 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.ConclusionOur findings demonstrated that pre-existing CVD was an independent risk factor associated with adverse outcomes among COVID-19 patients.
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2021-07-23 | GSE180557 | GEO
Project description: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.
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