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 r...
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Eco-vector
2021
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oai:doaj.org-article:edbcf24a5b4c4822bd2d72c974def3ec2021-11-30T18:15:21ZMajor predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials)2220-30952618-862710.17816/clinpract63552https://doaj.org/article/edbcf24a5b4c4822bd2d72c974def3ec2021-03-01T00:00:00Zhttps://journals.eco-vector.com/clinpractice/article/viewFile/63552/pdfhttps://doaj.org/toc/2220-3095https://doaj.org/toc/2618-8627Background: 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.Anna Yu. AnisenkovaSvetlana V. ApalkoZakhar P. AsaulenkoAlexander N. BogdanovDmitry A. VologzhaninEvgenii Y. GarbuzovOleg S. GlotovTatyana A. KamilovaOlga A. KlitsenkoEvdokiia M. MininaSergei V. MosenkoDmitry N. KhobotnikovSergey G. SсherbakEco-vectorarticlecovid-19 infectioncytokine stormearly diagnosis and monitoringMedicineRRUКлиническая практика , Vol 12, Iss 1, Pp 5-15 (2021) |
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covid-19 infection cytokine storm early diagnosis and monitoring Medicine R |
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covid-19 infection cytokine storm early diagnosis and monitoring Medicine R 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 Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials) |
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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. |
format |
article |
author |
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 |
author_facet |
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 |
author_sort |
Anna Yu. Anisenkova |
title |
Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials) |
title_short |
Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials) |
title_full |
Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials) |
title_fullStr |
Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials) |
title_full_unstemmed |
Major predictive risk factors for а cytokine storm in COVID-19 patients (a retrospective clinical trials) |
title_sort |
major predictive risk factors for а cytokine storm in covid-19 patients (a retrospective clinical trials) |
publisher |
Eco-vector |
publishDate |
2021 |
url |
https://doaj.org/article/edbcf24a5b4c4822bd2d72c974def3ec |
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