Selected article for: "optimal sensitivity and ROC curve"
Author: Abrishami, Alireza; Eslami, Vahid; Baharvand, Zahra; Khalili, Nastaran; Saghamanesh, Somayeh; Zarei, Ehsan; Sanei-Taheri, Morteza
Title: Epicardial Adipose Tissue, Inflammatory Biomarkers and COVID-19: Is There a Possible Relationship?
  • Cord-id: l34yjxk1
  • Document date: 2020_11_10
    • ID: l34yjxk1
    Snippet: Background & Aims Adipose tissue is a biologically active organ with pro-immunogenic properties. We aimed to evaluate the prognostic value of epicardial adipose tissue (EAT) in COVID-19 and its correlation with other inflammatory biomarkers. Material and Methods One-hundred patients with COVID-19 were enrolled. C-reactive protein (CRP), lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-CRP ratio (LCR), and platelet-to-lymphocyte ratio (PLR) were evaluated on admiss
    Document: Background & Aims Adipose tissue is a biologically active organ with pro-immunogenic properties. We aimed to evaluate the prognostic value of epicardial adipose tissue (EAT) in COVID-19 and its correlation with other inflammatory biomarkers. Material and Methods One-hundred patients with COVID-19 were enrolled. C-reactive protein (CRP), lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-CRP ratio (LCR), and platelet-to-lymphocyte ratio (PLR) were evaluated on admission. EAT volume and density were measured by computed tomography. Patients were followed until death or discharge. Univariate and multivariate analysis was performed and ROC curve analysis was used to assess the ability of inflammatory markers in predicting survival. The relationship between EAT and other inflammatory markers was also investigated. Results The mean ± SD age of patients was 55.5 ± 15.2 years old; 68% were male. Univariate analysis revealed that increased lung involvement, blood urea nitrogen, LDH and NLR, and decreased platelet count were significantly associated with death. After adjustment, LDH was independently predictive of death (OR= 1.013, p-value= 0.03). Among inflammatory markers, LCR had the best ability for predicting survival with 79.7% sensitivity and 64.3% specificity at an optimal cut-off value of 20.8 (AUC=0.744, 95% CI= 0.612 - 0.876, p-value= 0.004). EAT volume demonstrated positive correlation with NLR and PLR (p=0.001 and 0.01), and a negative correlation with LCR (p=0.02). EAT density was significantly different between decedents and survivors (p=0.008). Conclusion Routine laboratory tests that represent status of inflammation can be used as cost-effective prognostic markers of COVID-19. Also, the significant association between EAT volume and other inflammatory biomarkers might explain the more severe disease in obese patients.

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