1. Cytokine signature and COVID-19 prediction models in the two waves of pandemics.
- Author
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Cabaro S, D'Esposito V, Di Matola T, Sale S, Cennamo M, Terracciano D, Parisi V, Oriente F, Portella G, Beguinot F, Atripaldi L, Sansone M, and Formisano P
- Subjects
- Aged, Biomarkers blood, COVID-19 Testing, Case-Control Studies, Cytokines metabolism, Discriminant Analysis, Female, Humans, Interleukin-6 metabolism, Interleukin-8 metabolism, Italy epidemiology, Machine Learning, Male, Middle Aged, Pandemics, Regression Analysis, SARS-CoV-2, COVID-19 blood, COVID-19 epidemiology, Cytokines blood
- Abstract
In Europe, multiple waves of infections with SARS-CoV-2 (COVID-19) have been observed. Here, we have investigated whether common patterns of cytokines could be detected in individuals with mild and severe forms of COVID-19 in two pandemic waves, and whether machine learning approach could be useful to identify the best predictors. An increasing trend of multiple cytokines was observed in patients with mild or severe/critical symptoms of COVID-19, compared with healthy volunteers. Linear Discriminant Analysis (LDA) clearly recognized the three groups based on cytokine patterns. Classification and Regression Tree (CART) further indicated that IL-6 discriminated controls and COVID-19 patients, whilst IL-8 defined disease severity. During the second wave of pandemics, a less intense cytokine storm was observed, as compared with the first. IL-6 was the most robust predictor of infection and discriminated moderate COVID-19 patients from healthy controls, regardless of epidemic peak curve. Thus, serum cytokine patterns provide biomarkers useful for COVID-19 diagnosis and prognosis. Further definition of individual cytokines may allow to envision novel therapeutic options and pave the way to set up innovative diagnostic tools., (© 2021. The Author(s).)
- Published
- 2021
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