Effects of Cancer, Coronary Artery Disease and other Comorbidities on COVID-19 Related Mortality: A Meta-analysis and Meta-regression

2020 ◽  
Vol 03 (04) ◽  
Author(s):  
Shon Shmushkevich ◽  
Massimo Baudo ◽  
Nagla Abdel Karim ◽  
Mahmoud Morsi ◽  
Mariam Khobsa ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Meta Analysis ◽  
Meta Regression ◽  
Artery Disease ◽  
Related Mortality

Increased Peripheral Blood Visfatin Concentrations May Be a Risk Marker of Coronary Artery Disease: A Meta-Analysis of Observational Studies

Angiology ◽  
2018 ◽  
Vol 69 (9) ◽  
pp. 825-834 ◽  
Author(s):  
Fuling Yu ◽  
Jianwei Li ◽  
Qilei Huang ◽  
Hongbin Cai
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Peripheral Blood ◽  
Observational Studies ◽  
Meta Analysis ◽  
Density Lipoprotein ◽  
Risk Marker ◽  
Regression Analyses ◽  
Meta Regression ◽  
Artery Disease

A comprehensive quantitative evaluation of the relationship between peripheral blood visfatin concentrations and coronary artery disease (CAD) is lacking. This study is the first attempt to quantify this relationship via a meta-analysis of published observational studies in terms of weighted mean difference (WMD). Literature retrieval, article selection, and data extraction were conducted. Heterogeneity was inspected using both subgroup and meta-regression analyses. In total, 15 articles involving 1053 CAD cases and 714 controls were included. Overall, peripheral blood visfatin concentrations were significantly higher in CAD cases than in controls (WMD: 4.72 ng/mL; 95% confidence interval [CI]: 2.97-6.47; P < .001), with significant heterogeneity and publication bias. Six studies were theoretically missing based on filled funnel plot, and considering the impact of these missing studies still detected a significant overall mean difference in visfatin (WMD: 2.82 ng/mL; 95% CI: 2.22-3.58; P < .001; number of studies: 21). Subgroup and meta-regression analyses indicated age, body mass index, race, diabetes, systolic blood pressure, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol were identified as possible causes of heterogeneity. In conclusion, our findings suggest that increased peripheral blood visfatin concentrations may be a risk marker of CAD.

scholarly journals Discrimination capability of pretest probability of stable coronary artery disease: a systematic review and meta-analysis suggesting how to improve validation procedures

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e047677
Author(s):  
Pierpaolo Mincarone ◽  
Antonella Bodini ◽  
Maria Rosaria Tumolo ◽  
Federico Vozzi ◽  
Silvia Rocchiccioli ◽  
...  
Keyword(s):  
Systematic Review ◽  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Quality Assessment ◽  
Meta Analysis ◽  
Stable Coronary Artery Disease ◽  
First Line ◽  
Discrimination Capability ◽  
Artery Disease

ObjectiveExternally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness.DesignSystematic review and meta-analysis.Data sourcesGlobal Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020.Eligibility criteriaWe included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability.MethodsEligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed.Results27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I2 >90% for most analyses and not significant meta-regression results undermined relevant interpretations. A detailed discussion of individual results was then carried out.ConclusionsWe recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management.PROSPERO registration numberCRD42019139388.

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