Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials)

Abstract

Background: According to WHO, as of March 31, 2021, 127 877 462 confirmed cases of the new COVID-19 coronavirus infection were registered in the world, including 2 796 561 deaths (WHO Coronavirus Disease). COVID-19 is characterized by a wide range of clinical manifestations, from asymptomatic to a rapid progression to severe and extremely severe. Predictive biomarkers for the early detection of high-risk individuals have become a matter of great medical urgency. Aims: Search for the predictors of a cytokine storm in patients with COVID-19 infection and creation of a risk scale of this complication for practical applications. Methods: The study included 458 patients with confirmed COVID-19 infection with signs of viral lung lesions according to the computer tomography data. The patients were divided into 2 groups: those with a stable course of moderate severity (100 patients) and those with progressive moderate, severe and extremely severe course (358 patients). Results: It has been established that the main risk factors for the development of a cytokine storm in COVID-19 patients are the following: interleukin-6 concentration 23 pg/ ml, dynamics of the index on the NEWS scale 0, ferritin concentration 485 ng/ml, D-dimer concentration 2.1, C-reactive protein concentration 50 mg/l, number of lymphocytes in the blood 0.72109/l, age 40 years. The cytokine storm incidence correlates with an increase in the number of risk factors. For the practical testing the scale was applied in 3 groups. In patients of the first group (01 factor) almost no cytokine storm risk was found, in the second group (2 -3 factors) the probability of the storm was 55% (increase by 35.5 times), in the third group (4 risk factors) it reached 96% (increase by 718 times). Conclusion: The diagnostic and monitoring criteria of a cytokine storm have been established in patients with COVID-19 infection. The developed prognostic scale allows identification of patients at high risk of developing a cytokine storm so that early anti-inflammatory therapy could be started.