Chrome Extension
WeChat Mini Program
Use on ChatGLM

The predictive value of epicardial fat volume for clinical severity of COVID-19.

Revista portuguesa de cardiologia : orgao oficial da Sociedade Portuguesa de Cardiologia = Portuguese journal of cardiology : an official journal of the Portuguese Society of Cardiology(2022)

Cited 3|Views15
No score
Abstract
Introduction:Epicardial adipose tissue serves as a source of inflammatory cytokines and mediators. Cytokine storm is an important cause of morbidity and mortality in coronavirus disease 2019 (COVID-19). Objectives:To investigate the association between epicardial fat volume (EFV), inflammatory biomarkers and clinical severity of COVID-19. Methods:This retrospective study included 101 patients who were infected with COVID-19. Serum inflammatory biomarkers including C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and ferritin levels were measured. Computed tomography images were analyzed and semi-automated measurements for EFV were obtained. The primary composite endpoint was admission to the intensive care unit (ICU) or death. Results:The primary composite endpoint occurred in 25.1% (n=26) of patients (mean age 64.8±14.8 years, 14 male). A total of 10 patients died. EFV, CRP, PCT, ferritin and IL-6 levels were significantly higher in ICU patients. Moreover, a positive correlation was determined between EFV and CRP (r: 0.494, p<0.001), PCT (r: 0.287, p=0.005), ferritin (r: 0.265, p=0.01) and IL-6 (r: 0.311, p=0.005). On receiver operating characteristic analysis, patients with EFV >102 cm3 were more likely to have severe complications. In multivariate logistic regression analysis, EFV independently predicted admission to the ICU at a significant level (OR: 1.02, 95% CI: 1.01-1.03, p=0.025). Conclusion:EFV and serum CRP, IL-6, PCT and ferritin levels can effectively assess disease severity and predict the outcome in patients with COVID-19. EFV is an independent predictor of admission to the ICU in hospitalized COVID-19 patients.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined