AUTHOR=Vu Luan D. , Christofferson Rebecca C. , O’Neal Hollis R. , Hamer Diana , Phan Anh T. Q. , Vance Katie M. , Turner E. A. , Kumar Avinash , Yola Ibrahim Musa , Lim Natalie , Ogden Beverly , Cormier Stephania A. TITLE=Predicting severe COVID-19 using readily available admission indicators: SpO2/FiO2 ratio, comorbidity index, and gender JOURNAL=Experimental Biology and Medicine VOLUME=249 YEAR=2024 URL=https://www.ebm-journal.org/journals/experimental-biology-and-medicine/articles/10.3389/ebm.2024.10193 DOI=10.3389/ebm.2024.10193 ISSN=1535-3699 ABSTRACT=

The focus of this study was to identify risk factors for severe and critical COVID-19, evaluate local respiratory immune responses to SARS-CoV-2 infection, and develop a prognostic tool for COVID-19 severity using accessible early indicators. Using nasopharyngeal swab samples from hospitalized patients with COVID-19 of varying severity during the first wave of the pandemic from March to May 2020 in Louisiana, we evaluated the association between COVID-19 severity and viral load, respiratory immune mediators, and demographic/clinical factors. We found that the SpO2/FiO2 ratio at triage, total comorbidity burden (represented by Charlson Comorbidity Index), and gender were significantly associated with COVID-19 severity. Using these early significant indicators, we developed a prognostic tool for COVID-19 severity that is simple and convenient. Additionally, our study demonstrated that elevated levels of respiratory immune mediators, including IL-10, IL-6, MCP-1, and MCP-3, were significantly associated with COVID-19 severity. We also found that viral load at the time of admission was associated with disease severity. Our findings highlight the feasibility and importance of evaluating the humoral component of local mucosal immune responses and viral load at the infected site using convenient nasopharyngeal swab samples, which could be an effective method to understand the relationship between viral infection and immune responses at the early stages of infection. Our proposed prognostic tool has the potential to be useful for COVID-19 management in clinical settings, as it utilizes accessible and easy-to-collect variables at the time of admission.