Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials)
Anna Yu. Anisenkova , Svetlana V. Apalko , Zakhar P. Asaulenko , Alexander N. Bogdanov , Dmitry A. Vologzhanin , Evgenii Y. Garbuzov , Oleg S. Glotov , Tatyana A. Kamilova , Olga A. Klitsenko , Evdokiia M. Minina , Sergei V. Mosenko , Dmitry N. Khobotnikov , Sergey G. Sсherbak
Journal of Clinical Practice ›› 2021, Vol. 12 ›› Issue (1) : 5 -15.
Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials)
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 <0.72×109/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 (0–1 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.
COVID-19 infection / cytokine storm / early diagnosis and monitoring
| [1] |
Chen G, Wu D, Guo W, et al. Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest. 2020;130(5):2620–2629. doi: 10.1172/JCI137244 |
| [2] |
Wiersinga WJ, Rhodes A, Cheng AC, et al. Pathophysiology, transmission, diagnosis, and treatment of Coronavirus Disease 2019 (COVID-19): a review. JAMA. 2020;324(8):782–793. doi: 10.1016/j.jiph.2020.09.008 |
| [3] |
Caso F, Costa L, Ruscitti P, et al. Could Sars-coronavirus-2 trigger autoimmune and/or autoinflammatory mechanisms in genetically predisposed subjects? Autoimmun Rev. 2020;19(5):102524. doi: 10.1016/j.autrev.2020.102524 |
| [4] |
Zachariah P, Johnson CL, Halabi KC, et al. Epidemiology, clinical features, and disease severity in patients with coronavirus disease 2019 (COVID-19) in a children’s hospital in New York City, New York. JAMA Pediatr. 2020;174(10):e202430. doi: 10.1001/jamapediatrics.2020.2430 |
| [5] |
Временные методические рекомендации «Профилактика, диагностика и лечение новой коронавирусной инфекции (COVID-19)» Версия 10 (08.02.2021). [Temporary guidelines of the Ministry of Health of the Russian Federation «Prevention, diagnosis and treatment of new coronavirus infection (COVID-19)». Version 10 (08.02.2021). (In Russ).] |
| [6] |
Royal College of Physicians. NEWS2 and deterioration in COVID-19. Available from: https://www.rcplondon.ac.uk/news/news2-and-deterioration-covid-19 |
| [7] |
Asafu-Adjei JK, Sampson AR. Covariate adjusted classification trees. Biostatistics. 2018;19(1):42–53. doi: 10.1093/biostatistics/kxx015 |
| [8] |
Jutzeler CR, Bourguignon L, Weis CV, et al. Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 2020;37:101825. doi: 10.1016/j.tmaid.2020.101825 |
| [9] |
Профилактика инфекционных болезней. Лабораторная диагностика COVID-19. Методические рекомендации MP 3.1.0169-20 (в редакции МР 3.1.0174-20 «Изменения № 1 в МР 3.1.0170-20 «Лабораторная диагностика COVID-19», утвержденных Роспотребнадзором 30.04.2020). Государственное санитарно-эпидемиологическое нормирование Российской Федерации, 2020. [Prevention of infectious diseases. Laboratory diagnostics of COVID-19. Methodological recommendations MP 3.1.0169-20 (as amended by MP 3.1.0174-20 «Amendments No. 1 to MP 3.1.0170-20 «Laboratory diagnostics of COVID-19», approved by Rospotrebnadzor on 30.04.2020). State sanitary and epidemiological regulation of the Russian Federation; 2020. (In Russ).] |
| [10] |
Kivela P. Paradigm shift for COVID-19 response: identifying high-risk individuals and treating inflammation. West J Emerg Med. 2020;21(3):473–476. doi: 10.5811/westjem.2020.3.47520 |
| [11] |
Caricchio R, Gallucci M, Dass C, et al. Preliminary predictive criteria for COVID-19 cytokine storm. Ann Rheum Dis. 2021;80(1):88–95. doi: 10.1136/annrheumdis-2020-218323 |
| [12] |
Moore J, June C. Cytokine release syndrome in severe COVID-19. Science. 2020;368(6490):473–474. doi: 10.1126/science.abb8925 |
| [13] |
Lippi G, Plebani M. Laboratory abnormalities in patients with COVID-2019 infection. Clin Chem Lab Med. 2020;58(7):1131–1134. doi: 10.1515/cclm-2020-0198 |
Anisenkova A.Y., Apalko S.V., Asaulenko Z.P., Bogdanov A.N., Vologzhanin D.A., Garbuzov E.Y., Glotov O.S., Kamilova T.A., Klitsenko O.A., Minina E.M., Mosenko S.V., Khobotnikov D.N., Sсherbak S.G.
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