Epidemiology and Infectious DiseasesEpidemiology and Infectious DiseasesЭпидемиология и инфекционные болезни3034-20073034-2015Eco-Vector10961210.17816/EID109612Original study articlesОригинальные исследованияResearch ArticleA method for predicting the effectiveness of glucocorticoid therapy in patients with moderate COVID-19 based on simple clinical and laboratory dataСпособ прогнозирования эффективности глюкокортикоидной терапии у пациентов со среднетяжёлым течением COVID-19 на основе простых клинических и лабораторных данныхhttps://orcid.org/0000-0001-7889-60527115-2713EfremovDmitry O.ЕфремовДмитрий Олегович
Russian Federation

начальник инфекционного центра филиала №1 ФГБУ «Национальный медицинский исследовательский центр высоких медицинских технологий имени А. А. Вишневского» Минобороны России

Efremov-d24@mail.ruhttps://orcid.org/0000-0002-0544-41674233-2046BeloborodovVladimir B.БелобородовВладимир Борисович
Russian Federation

MD, Dr. Sci. (Med.), Professor

д.м.н., профессор

belvb1070@mail.ruBranch No. 1 of the National Medical Research Center for High Medical TechnologiesФилиал № 1 Национального медицинского исследовательского центра высоких медицинских технологий имени А.А. ВишневскогоRussian Medical Academy of Continuous Professional EducationРоссийская медицинская академия непрерывного профессионального образования090920222710202227275880408202206092022Copyright ©; 2022, Eco-vectorCopyright ©; 2022, ООО "Эко-вектор"2022Eco-vectorООО "Эко-вектор"https://rjeid.com/1560-9529/article/view/109612

BACKGROUND: In patients hospitalized with coronavirus infection (COVID-19), methods for predicting the effectiveness of anti-inflammatory therapy have important practical implications for optimizing treatment and outcomes. To date, several indicators of COVID-19 patients (age, comorbidities, and laboratory criteria for the intensity of inflammation) have been identified to indicate a high probability of a severe course and a risk of an adverse outcome. However, the problem of predicting the effectiveness of anti-inflammatory therapy in patients with moderate COVID-19 is not well understood.

AIM: This study aimed to develop a predictive model to determine the effectiveness/failure of anti-inflammatory therapy with glucocorticosteroids (GCS) in patients with moderate COVID-19 to improve the treatment outcomes of hospitalized patients.

MATERIALS AND METHODS: This study retrospectively analyzed electronic medical record data of all patients admitted consecutively from October 1, 2020, to January 31, 2021. The study included 71 patients with probable (clinically confirmed) and confirmed (laboratory) COVID-19 of moderate course, with characteristic changes in the lungs according to computed tomography of the chest organs (CT-CCT). Given the severity of the course, all study patients were prescribed GCS in accordance with the current version of the Interim Guidelines of the Ministry of Health of the Russian Federation.

RESULTS: A total of 71 patients were studied, and 53 (74.7%) of them did not require an escalation of anti-inflammatory therapy, which is regarded as an effective use of corticosteroids as an anti-inflammatory therapy (group 1). In the remaining 18 patients, the use of corticosteroids for an average of 5.5 (3–6) days did not have a definite clinical effect and required the additional use of monoclonal antibodies (MCA) to interleukin-6 (IL-6) or to its receptor (group 2). Using logistic regression analysis and receiver operating characteristic analysis, a mathematical model was developed and evaluated to predict the outcome of anti-inflammatory corticosteroid therapy in patients with moderate COVID-19. As risk factors, indicators that had significant differences in the studied groups before GCS initiation were selected: number of lymphocytes, platelets, and body temperature. The quality of the constructed model is assessed as very good, and the optimal cutoff point is 0.697. The sensitivity index of the model is 81.1%, and the specificity index is 72.2%.

CONCLUSIONS: The mathematical model makes it possible to predict the effectiveness of GCS therapy according to the number of lymphocytes, platelets, and body temperature. The mathematical model is adequate and has a high sensitivity and specificity.

Обоснование. У пациентов, госпитализированных с коронавирусной инфекцией (COVID-19), способы прогнозирования эффективности противовоспалительной терапии имеют важное практическое значение для оптимизации лечения и исходов. К настоящему времени выявлен ряд показателей у пациентов с COVID-19 (возраст, сопутствующая патология, лабораторные критерии интенсивности воспаления), указывающих на высокую вероятность тяжёлого течения и риска неблагоприятного исхода. Однако проблема прогнозирования эффективности противовоспалительной терапии у пациентов со среднетяжёлым течением COVID-19 изучена недостаточно.

Цель исследования — разработать прогностическую модель для определения эффективности/неэффективности противовоспалительной терапии глюкокортикоидами (ГКС) у пациентов со среднетяжёлым течением COVID-19 для улучшения результатов лечения госпитализированных пациентов.

Материалы и методы. Проведён ретроспективный анализ данных электронных историй болезни всех пациентов, поступивших в инфекционный центр последовательно с 1 октября 2020 г. по 31 января 2021 г. В исследование включён 71 пациент с вероятным (клинически подтверждённым) и подтверждённым (лабораторно) случаем COVID-19 среднетяжёлого течения с характерными изменениями в лёгких по данным компьютерной томографии органов грудной клетки. С учётом тяжести течения заболевания всем пациентам выборки назначены ГКС в соответствии с актуальной версией временных методических рекомендаций Министерства здравоохранения Российской Федерации.

Результаты. Всего изучен 71 пациент, у 53 (74,7%) эскалация противовоспалительной терапии не потребовалась, что расценено как эффективное применение ГКС в качестве противовоспалительной терапии (группа 1). У остальных 18 пациентов применение ГКС в течение в среднем 5,5 (от 3 до 6) суток не имело определённого клинического эффекта и потребовало дополнительного применения моноклональных антител к интерлейкину-6 или его рецептору (группа 2). С помощью логистического регрессионного анализа и ROC-анализа проведена разработка и оценка математической модели, позволяющей прогнозировать исход противовоспалительной терапии ГКС у пациентов со среднетяжёлым течением COVID-19. В качестве факторов риска были выбраны показатели, имевшие достоверные различия в изученных группах перед назначением ГКС: количество лимфоцитов, тромбоцитов и температура тела. Качество построенной модели оценивается как очень хорошее, оптимальная точка отсечения — 0,697. Показатель чувствительности модели — 81,1%, специфичности — 72,2%.

Заключение. Математическая модель позволяет прогнозировать эффективность терапии ГКС по количеству лимфоцитов, тромбоцитов и уровню температуры тела. Математическая модель адекватна, имеет высокий показатель чувствительности и специфичности.

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