Diagnostics of macrophage activation syndrome, depending on IL-6 initial level in patients with a novel coronavirus infection

Cover Page

Cite item

Full Text

Abstract

Introduction. The novel coronavirus infection caused by the SARS-CoV-2 remains the main problem, which is being studied by all the efforts of the global scientific community. Large clinical recourse has been accumulated that allows to conduct more effective treatment of patients, but there are still unresolved issues on the pathogenesis for development and course of the disease.

Materials and methods. The study included 163 patients admitted to the infectious diseases hospital diagnosed with “Novel coronavirus infection caused by the SARS-CoV-2”. Upon admission, all patient serum samples were quantified for IL-6 level that allowed to stratify patients into three groups: A — 55 patients with IL-6 below 5.0 pg/ml. The mean age in the group was 57.3±14.9 years, body mass index (BMI) was 28.2±5.6 kg/m2; C — 52 patients whose serum IL-6 level was in the range of 5–49 pg/ml. The average age in the group was 60.8±11.8 years, BMI — 29.6±5.5 kg/m2; C — 56 patients in whom the level of IL-6 in the blood serum ranged within 50–300 pg/ml. The average age in the group was 62.5±15.6 years, BMI — 28.8±5.6 kg/m2. Patients at admission were analysed for serum level of IL-6, IL-8, and C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH) were also determined on day 3 and 7.

Results. The minimum production of IL-6 within the range of 0.1–5 pg/ml, corresponds to the minimum changes in IL-8, CRP, and ferritin as well as LDH that was within the range of physiological values. Moderate cytokinemia, IL-6 is within the range of 5–49 pg/ml was associated with elevated ferritin and LDH not tending to decline by the end of treatment. Significant cytokinemia, the level of IL-6 within the range of 50–300 pg/ml was associated with hyperferritinemia and increased LDH. The course of COVID-19 in such patients is characterized by increased ferritin by day 3 of treatment, consistently high level of LDH, without a significant trend towards a decline in the studied markers by the end of treatment.

Conclusion. The risk of developing macrophage activation syndrome is not observed of the serum IL-6 level was below 5 pg/ml, whereas ferritin and LDH were within the range of physiological values, with no/degree I ARF. Moderate macrophage activation syndrome is characterized by increased serum IL-6 level within the range 5–49 pg/ml, a moderate increase in LDH and ferritin, as well as signs of ARF I–II degree. Severe signs are diagnosed in case of serum IL-6 level exceeded 50 pg/ml, along with significant increase in LDH and ferritin, as well as signs of II–III degree ARF.

About the authors

Svetlana A. Perepelitsa

Imannuel Kant Baltic Federal University; Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology

Author for correspondence.
Email: sveta_perepeliza@mail.ru
ORCID iD: 0000-0002-4535-9805

PhD, MD (Medicine), Associate Professor, Professor of the Department of Surgery, Leading Researcher, Laboratory of Cell Pathology in Critical Conditions, V.A. Negovsky Research Institute of General Reanimatology

Russian Federation, 14, A. Nevskiy str., Kaliningrad, 236041; Moscow

References

  1. Возгомент О.В., Пыков М.И., Зайцева Н.В. Новые подходы к ультразвуковой оценке размеров селезенки у детей // Ультразвуковая и функциональная диагностика. 2013. № 6. С. 56–62. [Vozgoment O.V., Pykov M.I., Zaitseva N.V. Ultrasound assessment of spleen size in children. New approaches. Ul’trazvukovaya i funktsional’naya diagnostika = Ultrasound and Functional Diagnostics, 2013, no. 6, pp. 56–62. (In Russ.)]
  2. Профилактика, диагностика и лечение новой коронавирусной инфекции (COVID-19). Временные методические рекомендации. Версия 14 (27.12. 2021). 233 с. [Prevention, diagnosis and treatment of novel coronavirus infection (COVID-19). Interim Guidelines. Version 14 (27.12.2021). 233 p. (In Russ.)]
  3. Asghar M.S., Haider Kazmi S.J., Khan N.A., Akram M., Hassan M., Rasheed U., Ahmed Khan S. Poor prognostic biochemical markers predicting fatalities caused by COVID-19: a retrospective observational study from a developing country. Cureus., 2020, vol. 12, no. 8: e9575. doi: 10.7759/cureus.9575
  4. Batur A., Kılınçer A., Ateş F., Demir N.A., Ergün R. Evaluation of systemic involvement of Coronavirus disease 2019 through spleen; size and texture analysis. Turk. J. Med. Sci., 2021, vol. 51, no. 3, pp. 972–980. doi: 10.3906/sag-2009-270
  5. Bohn M.K., Lippi G., Horvath A., Sethi S., Koch D., Ferrari M., Wang C-B., Mancini N., Steele S., Adeli K. Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC taskforce evaluation of the latest evidence. Clin. Chem. Lab. Med., 2020, vol. 58, no. 7, pp. 1037–1052. doi: 10.1515/cclm-2020-0722
  6. Carcillo J.A., Sward K., Halstead E.S., Telford R., Jimenez-Bacardi A., Shakoory B., Simon D., Hall M. A systemic inflammation mortality risk assessment contingency table for severe sepsis. Pediatr. Crit. Care Med., 2016, vol. 18, no. 2, pp. 143–150. doi: 10.1097/PCC.0000000000001029.
  7. Caricchio R., Gallucci M., Dass C., Zhang X., Gallucci S., Fleece D., Bromberg M., Criner G.J. Preliminary predictive criteria for COVID-19 cytokine storm. Ann. Rheum. Dis., 2021, vol. 80, no. 1, pp. 88–95. doi: 10.1136/annrheumdis-2020-218323
  8. Cazzola M., Bergamaschi G., Tonon L., Arbustini E., Grasso M., Vercesi E., Barosi G., Bianchi P.E., Cairo G., Arosio P. Hereditary hyperferritinemia-cataract syndrome: relationship between phenotypes and specific mutations in the iron-responsive element of ferritin light-chain mRNA. Blood, 1997, no. 90, p.814.
  9. Chen G., Wu D., Guo W., Cao Y., Huang D., Wang H., Wang T., Zhang X., Chen H., Yu H., Zhang X., Zhang M., Wu S., Song J., Chen T., Han M., Li S., Luo X., Zhao J., Ning Q. Clinical and immunological features of severe and moderate coronavirus disease 2019. J. Clin. Invest., 2020, vol. 130, no. 5, pp. 2620–2629. doi: 10.1172/JCI137244
  10. Chen Y., Klein S.L., Garibaldi B.T., Li H., Wu C., Osevala N.M., Li T., Margolick J.B., Pawelec G., Leng S.X. Aging in COVID-19: Vulnerability, immunity and intervention. Ageing Res. Rev., 2021, no. 65: 101205. doi: 10.1016/j.arr.2020.101205
  11. Cohen L.A., Gutierrez L., Weiss A., Leichtmann-Bardoogo Y., De-liang Zhang, Crooks D.R., Sougrat R., Morgenstern A., Galy B., Hentze M.W., Lazaro F.J., Rouault T.A., Meyron-Holtz E.G. Serum ferritin is derived primarily from macrophages through a nonclassical secretory pathway. Blood, 2010, vol. 116, no. 9, pp. 1574-1584. doi: 10.1182/blood-2009-11-253815
  12. Coster D., Wasserman A., Fisher E., Rogowski O., Zeltser D., Shapira I., Bernstein D., Meilik A., Raykhshtat E., Halpern P., Berliner S., Tsarfaty S.S., Shamir R. Using the kinetics of C-reactive protein response to improve the differential diagnosis between acute bacterial and viral infections. Infection, 2020, no. 48, pp. 241–248. doi: 10.1007/s15010-019-01383-6.
  13. Eklund C.M. Proinflammatory cytokines in CRP baseline regulation. Adv. Clin. Chem., 2009, no. 48, pp. 111–136. doi: 10.1016/s0065-2423(09)48005-3
  14. Gu J., Gong E., Zhang B., Zheng J., Gao Z., Zhong Y., Zou W., Zhan J., Wang S., Xie Z., Zhuang H., Wu B., Zhong H., Shao H., Fang W., Gao D., Pei F., Li X., He Z., Xu D., Shi X., Anderson V.M., Leong A.S.-Y. Multiple organ infection and the pathogenesis of SARS. J. Exp. Med., 2005, vol. 202, no. 3, pp. 415–424. doi: 10.1084/jem.20050828
  15. Guan W.J., Ni Z.Y., Hu Y., Liang W.H., Ou C.Q., He J.X., Liu L., Shan H., Lei C.L., Hui D.S.C., Du B., Li L.J., Zeng G., Yuen K.Y., Chen R.C., Tang C.L., Wang T., Chen P.Y., Xiang J., Li S.Y., Wang J.L., Liang Z.J., Peng Y.X., Wei L., Liu Y., Hu Y.H., Peng P., Wang J.M., Liu J.Y., Chen Z., Li G., Zheng Z.J., Qiu S.Q., Luo J., Ye C.J., Zhu S.Y., Zhong N.S. Clinical characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med., 2020, vol. 382, no. 18, pp. 1708–1720. doi: 10.1056/NEJMoa2002032
  16. Gubernatorova E.O., Gorshkova E.A., Polinova A.I., Drutskaya M.S. IL-6: relevance for immunopathology of SARS-CoV-2. Cytokine Growth Factor Rev., 2020, no. 53, pp. 13–24. doi: 10.1016/j.cytogfr.2020.05.009
  17. Henry B.M., de Oliveira M.H., Benoit S., Plebani M., Lippi G. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis. Clin. Chem. Lab. Med., 2020. vol. 58 no. 7, pp. 1021–1028. doi: 10.1515/cclm-2020-0369
  18. Honore P.M., Gutierrez B. L, Kugener L., Redant S., Attou R., Gallerani A., De Bels D. Inhibiting IL-6 in COVID-19: we are not sure. Crit. Care, 2020, vol. 24, no. 1: 463. doi: 10.1186/s13054-020-03177-x
  19. Kang S., Tanaka T., Narazaki M., Kishimoto T. Targeting interleukin-6 signaling in clinic. Immunity, 2019, vol. 50, no. 4, pp. 1007–1023. doi: 10.1016/j.immuni.2019.03.026
  20. Kernan K.F., Carcillo J.A. Hyperferritinemia and inflammation. Int. Immunol., 2017, vol. 29, no. 9, pp 401–409. doi: 10.1093/intimm/dxx031
  21. Li X., Xu S., Yu M., Wang K., Tao Y., Zhou Y., Shi J., Zhou M., Wu B., Yang Z., Zhang C., Yue J., Zhang Z., Renz H., Liu X., Xie J., Xie M., Zhao J. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J. Allergy Clin. Immunol., 2020, vol. 146, no. 1, pp. 110–118. doi: 10.1016/j.jaci.2020.04.006
  22. Lippi G., Plebani M. Laboratory abnormalities in patients with COVID-2019 infection. Clin. Chem. Lab. Med., 2020, vol. 58, no. 7, pp. 1131–1134. doi: 10.1515/cclm-2020-0198
  23. Liu Y., Yang Y., Zhang C., Huang F., Wang F., Yuan J., Wang Z., Li J., Li J., Feng C., Zhang Z., Wang L., Peng L., Chen L., Qin Y., Zhao D., Tan S., Yin L., Xu J., Zhou C., Jiang C., Liu L. Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury. Sci. China Life Sci., 2020, vol. 63, no. 3, pp. 364–374. doi: 10.1007/s11427-020-1643-8
  24. Lubell Y., Blacksell S.D., Dunachie S., Tanganuchitcharnchai A., Althaus T., Watthanaworawit W., Paris D.H., Mayxay M., Peto T.J., Dondorp A.M., White N.J., Day N.P.J., Nosten F., Newton P.N., Turner P. Performance of Creactive protein and procalcitonin to distinguish viral from bacterial and malarial causes of fever in Southeast Asia. BMC Infect. Dis., 2015, no. 15: 511. doi: 10.1186/s12879-015-1272-6
  25. Machhi J., Herskovitz J., Senan A.M., Dutta D., Nath B., Oleynikov M.D., Blomberg W.R., Meigs D.D., Hasan M., Patel M., Kline P., Chang R.C., Chang L., Gendelman H.E., Kevadiya B.D. The natural history, pathobiology, and clinical manifestations of SARS-CoV-2 infections. J. Neuroimmune Pharmacol., 2020, vol. 15, no. 3, pp. 359–386. doi: 10.1007/s11481-020-09944-5
  26. Maeda T., Obata R., Rizk D.D., Kuno T. The Association of interleukin-6 value, interleukin inhibitors and outcomes of patients with COVID-19 in New York City. J. Med. Virol., 2021, vol. 93, no. 1, pp. 463-471. doi: 10.1002/jmv.26365
  27. Martinez-Outschoorn U.E., Prisco M., Ertel A. Ketones and lactate increase cancer cell “stemness,” driving recurrence, metastasis and poor clinical outcome in breast cancer: achieving personalized medicine via metabolo-genomics. Cell. Cycle, 2011, vol. 10, no. 8, pp. 1271–1286. doi: 10.4161/cc.10.8.15330.
  28. McFadyen J., Kiefer J., Loseff-Silver J., Braig D., Potempa L.A., Eisenhardt S.U., Peter K. Dissociation of C-reactive protein localizes and amplifies inflammation: Evidence for a direct biological role of CRP and its conformational changes. Front. Immunol., 2018, no. 9: 1351. doi: 10.3389/fimmu.2018.01351
  29. Mehta P., McAuley D.F., Brown M., Sanchez E., Tattersall R.S., Manson J.J. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet, 2020, vol. 395, no. 10229, pp. 1033–1034. doi: 10.1016/S0140-6736(20)30628-0
  30. Onur S.T., Altın S., Sokucu S.N., Fikri B.İ., Barça T., Bolat E., Toptaş M. Could ferritin level be an indicator of COVID-19 disease mortality? J. Med. Virol., 2021, vol. 93, no. 3, pp. 1672–1677. doi: 10.1002/jmv.26543
  31. Rajab I.M., Hart P.C., Potempa L.A. How C-reactive protein structural isoforms with distinctive bioactivities affect disease progression. Front. Immunol., 2020, no. 11: 2126. doi: 10.3389/fimmu.2020.02126
  32. Ramasamy S., Subbian S. Critical determinants of cytokine storm and type i interferon response in COVID-19 pathogenesis. Clin. Microbiol. Rev., 2021, vol. 34, no. 3: e00299-20. doi: 10.1128/CMR.00299-20
  33. Recalcati S., Invernizzi P., Arosio P., Cairo G. New functions for an iron storage protein: the role of ferritin in immunity and autoimmunity. J. Autoimmun., 2008. vol. 30, no. 1–2, pp. 84–89. doi: 10.1016/j.jaut.2007.11.003
  34. Sette А., Crotty S. Adaptive immunity to SARS-CoV-2 and COVID-19. Cell, 2021, vol. 184, no. 4, pp. 861–880. doi: 10.1016/ j.cell.2021.01.007
  35. Shrive A.K., Cheetham G.M.T., Holden D., Myles D.A.A., Turnell W.G., Volanakis J.E., Pepys M.B., Bloomer A.C., Greenhough T.J. Three-dimensional structure of human C-reactive protein. Nat. Struct. Biol., 1996, vol. 3, no. 4, pp. 346–354. doi: 10.1038/nsb0496-346
  36. Solis-Garcia Del Pozo J., Galindo M.F., Nava E., Jordan J. A systematic review on the efficacy and safety of IL-6 modulatory drugs in the treatment of COVID-19 patients. Eur. Rev. Med. Pharmacol. Sci., 2020, vol. 24, no. 13, pp. 7475–7484. doi: 10.26355/eurrev_202007_21916
  37. Soy M., Keser G., Atagündüz P., Tabak F., Atagündüz I., Kayhan S. Cytokine storm in COVID-19: pathogenesis and overview of anti-inflammatory agents used in treatment. Clin. Rheumatol., 2020, vol. 39, no. 7, pp. 2085–2094. doi: 10.1007/s10067-020-05190-5
  38. Tonial C.T., Garcia P.C.R., Schweitzer L.C., Costa C.A.D., Bruno F., Fiori H.H., Einloft P.R., Garcia R.B., Piva J.P. Cardiac dysfunction at echocardiogram and ferritin as early markers of severity in pediatric sepsis. J. Pediatr. (Rio J.), 2017, vol. 93, no. 3, pp. 301–307. doi: 10.1016/j.jped.2016.08.006
  39. Vigushin D.M., Pepys M.B., Hawkins P.N. Metabolic and scintigraphic studies of radioiodinated human C-reactive protein in health and disease. J. Clin. Invest., 1993, vol. 91, no. 4, pp. 1351–1357. doi: 10.1172/JCI116336
  40. Wang G., Wu C., Zhang Q., Wu F., Yu B., Lv J., Li Y., Li T., Zhang S., Wu C., Wu G., Zhong Y. C reactive protein level may predict the risk of COVID-19 aggravation. Open Forum Infect. Dis., 2020, vol. 7, no. 5: ofaa153. doi: 10.1093/ofid/ofaa153
  41. Wang L. C-reactive protein levels in the early stage of COVID-19. Med. Maladies Infect., 2020, vol. 50, no. 4, pp. 332–334. doi: 10.1016/j.medmal.2020.03.007
  42. Weatherhead J.E., Clark E.H., Vogel T.P., Atmar R.L., Kulkarni P.A. Inflammatory syndromes associated with SARS-CoV-2 infection: dysregulation of the immune response across the age spectrum. J. Clin. Invest., 2020, vol. 130, no. 12, pp. 6194–6197. doi: 10.1172/JCI145301.
  43. Wu Y., Potempa L.A., Kebir D.E., Filep J.G. C-reactive protein and inflammation: conformational changes affect function. Biol. Chem., 2015, vol. 396, no. 11, pp. 1181–1197. doi: 10.1515/hsz-2015-0149
  44. Xu X., Chang X.N., Pan H.X., Su H., Huang B., Yang M., Luo D.J., Weng M.X., Ma L., Nie X. Pathological changes of the spleen in ten patients with coronavirus disease 2019(COVID-19) by postmortem needle autopsy. Zhonghua Bing Li Xue Za Zhi., 2020, vol. 49, no. 6, pp. 576–582. doi: 10.3760/cma.j.cn112151-20200401-00278
  45. Xu Z., Shi L., Wang Y., Zhang J., Huang L., Zhang C., Liu S., Zhao P., Liu H., Zhu L., Tai Y., Bai C., Gao T., Song J., XiaP., Dong J., Zhao J., Wang F.-S. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir. Med., 2020, vol. 8, no. 4, pp. 420–422. doi: 10.1016/S2213-2600(20)30076-X
  46. Yang X., Yu Y., Xu J., Shu H., Xia J., Liu H., Wu Y., Zhang L., Yu Z., Fang M., Yu T., Wang Y., Pan S., Zou X., Yuan S., Shang Y. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir. Med., 2020, vol. 8, no. 5, pp. 475–481. doi: 10.1016/S2213-2600(20)30079-5
  47. Yao X., Li T., He Z., Ping Y., Liu H., Yu S., Mou H., Wang L., Zhang H., Fu W., Luo T., Liu F., Guo Q.N., Chen C., Xiao H.L., Guo H.T., Lin S., Xiang D.F., Shi Y., Pan G.Q., Li Q.R., Huang X., Cui Y., Liu X.Z., Tang W., Pan P.F., Huang X.Q., Ding Y.Q., Bian X.W. A pathological report of three COVID-19 cases. Zhonghua Bing Li Xue Za Zhi., 2020, vol. 49, no. 5, pp. 411–417. doi: 10.3760/cma.j.cn112151-20200312-00193
  48. Yi K., Rong Y., Wang C., Huang L., Wang F. COVID-19: advance in laboratory diagnostic strategy and technology. Mol. Cell Biochem., 2021, vol. 476, no. 3, pp. 1421–1438. doi: 10.1007/s11010-020-04004-1
  49. Zhang T., Chen H., Liang S., Chen D., Zheng C., Zeng C., Zhang H., Liu Z. A non-invasive laboratory panel as a diagnostic and prognostic biomarker for thrombotic microangiopathy: development and application in a Chinese cohort study. PLoS One, 2014, vol. 9, no. 11: e111992. doi: 10.1371/journal.pone.0111992
  50. Zhou F., Yu T., Du R., Fan G., Liu Y., Liu Z., Xiang J., Wang Y., Song B., Gu X., Guan L., Wei Y., Li H., Wu X., Xu J., Tu S., Zhang Y., Chen H., Cao B. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet, 2020, vol. 395, no. 10229, pp. 1054–1062. doi: 10.1016/S0140-6736(20)30566-3

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Figure 1. Investigation of serum IL-6 level at admission to the hospital. Note. *р < 0.05 — statistically significant differences between groups A, B and C; #p < 0.05 — statistically significant differences between groups A and B; •p < 0.05 — statistically significant differences between groups B and C.

Download (46KB)
Indexing metadata
3. Figure 2. Investigation of serum IL-8 level at admission to the hospital. Note. *р < 0.05 — statistically significant differences between groups.

Download (34KB)
Indexing metadata
4. Figure 3. Investigation of serum CRP level during course of treatment. Note. *р < 0.05 — statistically significant differences in the group at the stages of treatment; ♦p < 0.05 — statistically significant difference between groups A and C.

Download (47KB)
Indexing metadata
5. Figure 4. Investigation of serum ferritin and LDH level during course of treatment. Note. *р < 0.05 — statistically significant differences in the group at the stages of treatment; ♦p < 0.05 — statistically significant difference between groups A and C; #p < 0.05 — statistically significant differences between groups A and B.

Download (83KB)
Indexing metadata

Copyright (c) 2022 Perepelitsa S.A.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Согласие на обработку персональных данных с помощью сервиса «Яндекс.Метрика»

1. Я (далее – «Пользователь» или «Субъект персональных данных»), осуществляя использование сайта https://journals.rcsi.science/ (далее – «Сайт»), подтверждая свою полную дееспособность даю согласие на обработку персональных данных с использованием средств автоматизации Оператору - федеральному государственному бюджетному учреждению «Российский центр научной информации» (РЦНИ), далее – «Оператор», расположенному по адресу: 119991, г. Москва, Ленинский просп., д.32А, со следующими условиями.

2. Категории обрабатываемых данных: файлы «cookies» (куки-файлы). Файлы «cookie» – это небольшой текстовый файл, который веб-сервер может хранить в браузере Пользователя. Данные файлы веб-сервер загружает на устройство Пользователя при посещении им Сайта. При каждом следующем посещении Пользователем Сайта «cookie» файлы отправляются на Сайт Оператора. Данные файлы позволяют Сайту распознавать устройство Пользователя. Содержимое такого файла может как относиться, так и не относиться к персональным данным, в зависимости от того, содержит ли такой файл персональные данные или содержит обезличенные технические данные.

3. Цель обработки персональных данных: анализ пользовательской активности с помощью сервиса «Яндекс.Метрика».

4. Категории субъектов персональных данных: все Пользователи Сайта, которые дали согласие на обработку файлов «cookie».

5. Способы обработки: сбор, запись, систематизация, накопление, хранение, уточнение (обновление, изменение), извлечение, использование, передача (доступ, предоставление), блокирование, удаление, уничтожение персональных данных.

6. Срок обработки и хранения: до получения от Субъекта персональных данных требования о прекращении обработки/отзыва согласия.

7. Способ отзыва: заявление об отзыве в письменном виде путём его направления на адрес электронной почты Оператора: info@rcsi.science или путем письменного обращения по юридическому адресу: 119991, г. Москва, Ленинский просп., д.32А

8. Субъект персональных данных вправе запретить своему оборудованию прием этих данных или ограничить прием этих данных. При отказе от получения таких данных или при ограничении приема данных некоторые функции Сайта могут работать некорректно. Субъект персональных данных обязуется сам настроить свое оборудование таким способом, чтобы оно обеспечивало адекватный его желаниям режим работы и уровень защиты данных файлов «cookie», Оператор не предоставляет технологических и правовых консультаций на темы подобного характера.

9. Порядок уничтожения персональных данных при достижении цели их обработки или при наступлении иных законных оснований определяется Оператором в соответствии с законодательством Российской Федерации.

10. Я согласен/согласна квалифицировать в качестве своей простой электронной подписи под настоящим Согласием и под Политикой обработки персональных данных выполнение мною следующего действия на сайте: https://journals.rcsi.science/ нажатие мною на интерфейсе с текстом: «Сайт использует сервис «Яндекс.Метрика» (который использует файлы «cookie») на элемент с текстом «Принять и продолжить».