Cordas dos Santos, David M.; Liu, Lian; Gerisch, Melvin; Hellmuth, Johannes C.; von Bergwelt-Baildon, Michael; Kunz, Wolfgang G.; Theurich, Sebastian (2022): Risk Stratification Based on a Pattern of Immunometabolic Host Factors Is Superior to Body Mass Index—Based Prediction of COVID-19-Associated Respiratory Failure. Nutrients, 14 (20): 4280. ISSN 2072-6643
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Abstract
Overweight and obesity are associated with chronic low-grade inflammation and represent risk factors for various diseases, including COVID-19. However, most published studies on COVID-19 defined obesity by the body mass index (BMI), which does not encounter adipose tissue distribution, thus neglecting immunometabolic high-risk patterns. Therefore, we comprehensively analyzed baseline anthropometry (BMI, waist-to-height-ratio (WtHR), visceral (VAT), epicardial (EAT), subcutaneous (SAT) adipose tissue masses and liver fat, inflammation markers (CRP, ferritin, interleukin-6), and immunonutritional scores (CRP-to-albumin ratio (CAR), modified Glasgow prognostic score, neutrophile-to-lymphocyte ratio, prognostic nutritional index)) in 58 consecutive COVID-19 patients of the early pandemic phase with regard to the necessity of invasive mechanical ventilation (IMV). Here, metabolically high-risk adipose tissues represented by increased VAT, liver fat, and WtHR strongly correlated with higher levels of inflammation, pathologic immunonutritional scores, and the need for IMV. In contrast, the prognostic value of BMI was inferior and absent with regard to SAT. Multivariable logistic regression analysis identified an optimized IMV risk prediction model employing liver fat, WtHR, and CAR. In summary, we suggest an immunometabolically risk-adjusted model to predict COVID-19-induced respiratory failure better than BMI-based stratification, which warrants prospective validation.
Doc-Type: | Article (LMU Hospital) |
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Organisational unit (Faculties): | 07 Medicine > Medical Center of the University of Munich > Medical Clinic and Outpatient Clinic III (Oncology) |
DFG subject classification of scientific disciplines: | Life sciences |
Date Deposited: | 14. Mar 2023 11:10 |
Last Modified: | 07. Dec 2023 12:15 |
URI: | https://oa-fund.ub.uni-muenchen.de/id/eprint/263 |
DFG: | Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 491502892 |