COVID-19抗炎治疗有效性的临床、实验室和仪器预测指标

I. Sukhomlinova, I. Bakulin, M. Kabanov
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引用次数: 1

摘要

背景:抗炎治疗是中重度COVID-19病因治疗的主要方法。抗炎治疗中使用的药物,特别是地塞米松、olokizumab、tocilizumab和baricitinib,实际上仍然是在标签外模式下处方的。当然,他们的使用是合理的俄罗斯和国际临床指南,实践经验,专家意见。然而,主治医生的意见,基于对每个病人的风险/收益比的评估,是决定抗炎治疗药物的基础。确定中度和重度COVID-19抗炎治疗有效性的临床和实验室预测因素,将有助于在确定抗炎治疗期间发生不良后果的风险群体时进行决策过程,并根据已确定的标准确定抗炎治疗的最佳药物。目的:比较抗细胞因子药物(tocilizumab、olokizumab、baricitinib、地塞米松)对中重度COVID-19患者预防性抗炎治疗的疗效,以确定抗炎治疗结果的临床、实验室和仪器预测指标。材料与方法:回顾性分析包括Lenexpo网站在内的战争退伍军人医院229例需要各种抗炎治疗的重型和中度COVID-19疾病。结果:该研究确定了中重度COVID-19抗炎治疗有效性的主要(显著影响结果)和其他(显著)预测因素。主要包括:氧支持水平、出现临床表现的时间、c反应蛋白、d -二聚体水平。其他但重要的因素包括:根据计算机断层扫描数据对肺组织的损伤程度,伴随病理的存在和补偿程度,伴随病理的治疗,以及临床血液检查中白细胞和中性粒细胞的水平。结论:额外的氧支持是抗炎治疗有效性的主要预测指标,如果有指示,尽早给予氧支持可以显著增加中重度COVID-19患者获得有利结果的机会。重要的预后指标还包括c反应蛋白和d -二聚体。合并疾病的存在以及计算机断层扫描数据显示的肺损伤程度是显著因素;然而,为了预测抗炎治疗的结果,它们应该与其他临床和实验室数据以及患者的客观状态进行比较。
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Clinical, laboratory and instrumental predictors of the effectiveness of anti-inflammatory therapy in COVID-19
BACKGROUND: Anti-inflammatory therapy is a leading method of pathogenetic treatment of moderate and severe forms of COVID-19. The drugs used during anti-inflammatory therapy, in particular, dexamethasone, olokizumab, tocilizumab, and baricitinib, are still actually prescribed in off-label mode. Of course, their use is justified by the Russian and international clinical guidelines, practical experience, expert opinions. However, the opinion of an attending physician, based on the assessment of the risk/benefit ratio for each patient, is fundamental in determining a drug for anti-inflammatory therapy. Determination of clinical and laboratory predictors of anti-inflammatory therapy effectiveness in moderate and severe forms of COVID-19 will facilitate a decision-making process when identifying risk groups for developing an adverse outcome during anti-inflammatory therapy, as well as determining an optimal drug for an anti-inflammatory therapy, taking into account the identified criteria. AIM: To compare the effectiveness of preemptive anti-inflammatory therapy with anticytokine drugs (tocilizumab, olokizumab, baricitinib, dexamethasone) in the patients with moderate and severe COVID-19 to identify clinical, laboratory and instrumental predictors of anti-inflammatory therapy outcome. MATERIALS AND METHODS: A retrospective analysis of 229 cases of severe and moderate COVID-19 disease requiring various types of anti-inflammatory therapy at the Hospital of War Veterans, including the Lenexpo site. RESULTS: The study has identified the main (significantly affecting the outcome) and additional (significant) predictors of the effectiveness of anti-inflammatory therapy in moderate and severe forms of COVID-19. The main ones include: the level of oxygen support, the period from the onset of clinical manifestations, the level of C-reactive protein, D-dimer. The additional, but significant factors include: the amount of damage to the lung tissue according to the computed tomography data, the presence and degree of compensation of concomitant pathology, the presence of therapy for concomitant pathology, as well as the level of leukocytes and neutrophils in the clinical blood test. CONCLUSIONS: The presence of additional oxygen support is a leading predictor of the effectiveness of an anti-inflammatory therapy, and its administration as early as possible, if indicated, can significantly increase the chances of a favorable outcome for a patient with moderate to severe COVID-19. Important prognostic markers also include C-reactive protein and D-dimer. The presence of concomitant diseases in anamnesis, as well as the degree of lung damage according to computer tomography data, are significant factors; however, they should be compared with other clinical and laboratory data and the objective status of the patient in order to predict the outcome of an anti-inflammatory therapy.
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