astmedАстраханский медицинский журналAstrakhan medical journal1992-6499ФГБОУ ВО Астраханский ГМУ Минздрава России10.17021/1992-6499-2024-1-118-130astmed-407Research ArticleОРИГИНАЛЬНЫЕ ИССЛЕДОВАНИЯORIGINAL INVESTIGATIONSВозможности нейросетевого анализа в определении формы тяжести новой коронавирусной инфекции у детей школьного возрастаPossibilities of neural network analysis in determining the severity form of new coronavirus infection in school-age childrenПерегоедоваВ. Н.PeregoedovaV. N.

Валентина Николаевна Перегоедова, кандидат медицинских наук, доцент кафедры педиатрии лечебного и стоматологического факультетов 

г. Чита

Valentina N. Peregoedova, Cand. Sci. (Med.), Associate Professor

Chita

v.peregoedova@mail.ruБогомоловаИ. К.BogomolovaI. K.

Ирина Кимовна Богомолова, доктор медицинских наук, профессор, проректор по учебно-воспитательной работе, заведующая кафедрой педиатрии лечебного и стоматологического факультетов

г. Чита 

Irina K. Bogomolova, Dr. Sci. (Med.), Professor, Vice-Rector, Head of the Department

Chita

bogomolova_ik@mail.ruЧитинская государственная медицинская академияРоссияChita State Medical AcademyRussian Federation202411042024191118130Copyright © Перегоедова В.Н., Богомолова И.К., 20242024Перегоедова В.Н., Богомолова И.К.Peregoedova V.N., Bogomolova I.K.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.astmedj.ru/jour/article/view/407

Введение. Коронавирусная инфекция у детей протекает легче по сравнению со взрослыми, однако истинная причина патогенеза до сих пор остается неясной. Растет интерес к возможной взаимосвязи между тяжестью заболевания и биомаркерами, включая хемокины. Цель исследования: на основании определения уровня хемокинов сыворотки крови оценить возможности нейросетевого анализа в ранней диагностике формы тяжести новой коронавирусной инфекции у детей школьного возраста. Материалы и методы. Количественно определена концентрация 10 хемокинов с использованием мультиплексного анализа на проточном цитометре в 98 образцах сыворотки крови детей с коронавирусной инфекцией в возрасте 7–17 лет (медиана 13 [10; 14] лет), составившие основную исследуемую группу, и 93 здоровых детей (13 [10; 15] лет), которые набраны до пандемии COVID-19. Среди пациентов с COVID-19 выделены подгруппы наблюдения с бессимптомным течением (первая подгруппа, n = 16), легкой (вторая подгруппа, n = 54) и среднетяжелой формами болезни (третья подгруппа, n = 28). Результаты. Статистически значимые различия сывороточной концентрации между школьниками с COVID-19 и группой контроля показали девять хемокинов CCL11 (Eotaxin), CCL5 (RANTES), CCL3 (MIP-1α), CCL4 (MIP-1β), CCL20 (MIP-3α), CCL17 (TARC), CXCL11 (I-TAC), CXCL5 (ENA-78), CXCL1 (GROα). В результате исследования разработана нейронная сеть, основанная на комплексной оценке их уровнейв сыворотке крови и позволяющая определять форму тяжести COVID-19 у детей школьного возраста на момент поступления в стационар. Не наблюдалось статистически значимых различий в уровне CXCL9 (MIG) между исследуемыми группами. В результате исследования разработана нейронная сеть, основанная на комплексной оценке уровней хемокинов сыворотке крови, позволяющая определять форму тяжести COVID-19 у детей школьного возраста на момент поступления в стационар. Заключение. Измерение уровней комплекса хемокинов CCL11 (Eotaxin), CCL5 (RANTES), CCL3 (MIP-1α), CCL4 (MIP-1β), CCL20 (MIP-3α), CCL17 (TARC), CXCL11 (I-TAC), CXCL5 (ENA-78), CXCL1 (GROα) в сыворотке крови может быть полезным в диагностике формы тяжести новой коронавирусной инфекции у детей школьного возраста и дальнейшего определения стратегии лечения.

Coronavirus infection in children is milder than in adults, nevertheless the true reason of pathogenesis is still uncertain. There has been an increasing interest to possible connection between the severity of the disease and biomarkers including chemokines. Study objective. To study the possibilities of neural network analysis in early diagnostics of severity form of new coronavirus infection in school-age children depending on the plasma level of chemokines. Materials and methods. The concentration of 10 chemokines was quantified using multiplex analysis on a flow cytometer in 98 blood serum samples (main group) of school-age children (13 [10; 14] years old) divided into subgroups: first – 16 children with asymptomatic form of COVID-19, second – 54 children with mild form and third – 28 patients with moderate form of the disease. There was a group of 93 healthy children (13 [10; 15] years old) who were taken before COVID-19 pandemic. Results. Nine chemokines have shown statistically significant differences in serum concentration between school-age children with COVID-19 and the control group: CCL11 (Eotaxin), CCL5 (RANTES), CCL3 (MIP-1α), CCL4 (MIP-1β), CCL20 (MIP-3α), CCL17 (TARC), CXCL11 (I-TAC), CXCL5 (ENA-78), CXCL1 (GROα). There was no statistically significant difference in CXCL9 (MIG) levels between study groups. As a result of the study, a neural network was created based on a comprehensive assessment of the plasma levels CCL11 (Eotaxin), CCL5 (RANTES), CCL3 (MIP-1α), CCL4 (MIP-1β), CCL20 (MIP-3α), CCL17 (TARC), CXCL11 (I-TAC), CXCL5 (ENA-78), CXCL1 (GROα) that allowed to determine the severity form of COVID-19 in school-age children at the time of admission to the hospital. Conclusion. Plasma levels measurement of CCL11 (Eotaxin), CCL5 (RANTES), CCL3 (MIP-1α), CCL4 (MIP-1β), CCL20 (MIP-3α), CCL17 (TARC), CXCL11 (I-TAC), CXCL5 (ENA-78), CXCL1 (GROα) can be useful in diagnostics of severity form of new coronavirus infection in school-age children and further determining the treatment strategy.

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The authors declare that there are no conflicts of interest present.