Correlations and Algorithmization of Cytokine Status Analysis of Patients with Coronary Heart Disease in the Early Recovery Period After COVID-19

V. A. Negrebetskiy, S. N. Gontarev, V. A. Ivanov
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Abstract

The purpose of research is study of correlations and algorithmization of cytokine status analysis of patients with coronary heart disease in the early recovery period after COVID-19.Methods. Cytokine status was studied in 40 patients with coronary heart disease 3-4 weeks after recovery from COVID19. The control consisted of 38 patients with coronary heart disease without COVID-19. The level of cytokines in the blood was determined on the device "Becton Dickinson FACS Canto 2 (USA)". Correlation and regression analysis were used in statistical analysis.Results. Reliable moderate correlations were established between IL-6 and IL-2, IL-3, respectively, r = 0,35 and r = 0,33; IL-17 with IL-2 and IL-6 – r = 0,28 and r = 0,63, respectively; TNF-α and IFN-γ with IL-6 – r = 0,42 and r = 0,39. At the same time, the greatest association, according to the values of the correlation coefficients, among the studied interleukins in patients with coronary heart disease during the convalescence period is characteristic of IL-6. However, IL-17 also had a significant number of correlations with the cytokines under consideration. All this indicates a high association of IL-6, IL-17 and IFN-γ with other cytokines during the recovery period of patients with coronary heart disease after COVID-19 and their priority participation in the development and recovery of these patients. To identify the most informative blood cytokines, an algorithm for analyzing the cytokine status has been developed, which provides for the development of uncorrected and adjusted mathematical models by gender and age of patients with coronary heart disease who have undergone COVID-19. It was found that the greatest effect on recovery 3-4 weeks after COVID-19 in patients with coronary heart disease has the level of IL-17 in the blood (OR = 1,792, p = 0,0021) in an uncorrected and adjusted by gender and age model (OR = 1,708, p = 0,0012).Conclusion. The established correlations, algorithms and models created are proposed to be used in assessing thedynamics of recovery of patients with coronary heart disease after COVID-19.
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COVID-19 后早期恢复期冠心病患者细胞因子状态分析的相关性和算法分析
研究目的是研究 COVID-19 后早期恢复期冠心病患者细胞因子状态分析的相关性和算法。对 40 名冠心病患者在 COVID-19 后 3-4 周恢复期的细胞因子状态进行了研究。对照组包括 38 名未服用 COVID-19 的冠心病患者。血液中细胞因子的水平通过 "Becton Dickinson FACS Canto 2(美国)"设备测定。统计分析采用了相关分析和回归分析。IL-6与IL-2、IL-3之间建立了可靠的中度相关性,分别为r = 0.35和r = 0.33;IL-17与IL-2和IL-6之间的相关性分别为r = 0.28和r = 0.63;TNF-α和IFN-γ与IL-6之间的相关性分别为r = 0.42和r = 0.39。同时,根据相关系数值,在冠心病患者康复期的白细胞介素中,IL-6 的相关性最大。不过,IL-17 与所研究的细胞因子也有大量相关性。所有这些都表明,IL-6、IL-17 和 IFN-γ 与 COVID-19 后冠心病患者康复期的其他细胞因子高度相关,它们优先参与了这些患者的发展和康复。为了确定最有参考价值的血液细胞因子,我们开发了一种分析细胞因子状态的算法,该算法可根据接受 COVID-19 治疗的冠心病患者的性别和年龄,建立未经校正和调整的数学模型。研究发现,在未校正和按性别和年龄调整的模型中(OR = 1,708, p = 0,0012),血液中 IL-17 的水平对冠心病患者 COVID-19 后 3-4 周的恢复影响最大(OR = 1,792, p = 0,0021)。建议将已建立的相关性、算法和模型用于评估 COVID-19 后冠心病患者的恢复动态。
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