Analysis of the sensitization spectrum in patients with severe allergic diseases using the ImmunoCAP ISAC method

Russian Journal of Allergy Pub Date : 2024-04-01 DOI:10.36691/rja15994

M. Lebedkina, D. Fomina, Ekaterina Nikitina, A. Dushkin, A. Chernov, Y. Yukhnovskaya, M. A. Lysenko, A. Karaulov

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Abstract

BACKGROUND: An important advance in modern allergology has been made by the introduction of allergenic molecules/components, including their detection by the ImmunoCAP ISAC method. This method is useful in patients with a complex spectrum of sensitization and severe forms of allergic diseases, where various predictors of severe course are actively searched for. AIMS: To evaluate the informativeness of component resolved diagnostic by ISAC ImmunoCAP method in patients with severe bronchial asthma (SBA) and severe atopic dermatitis (SAD MATERIALS AND METHODS: A single-center retrospective study was conducted from January to August 2023. 100 patients who were candidates for biologicals for SBA (63 patients) - group 1, SAD (20 patients) - group 2, or their combination (17 patients) - group 3 were included. Component restlved diagnostic was performed by ImmunoCAP ISAC method. Mathematical and statistical data processing was performed using Python3.10 programming language packages in IDE Visual Studio Code 1.76.1 (Universal). The following criteria were used: Student's, Gaims-Howell, Kraskell-Wallis, Dunn with Holm's correction. RESULTS: Polysensitization and high occurrence of food and fungal allergens were more frequently detected in

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使用免疫细胞分析仪 ISAC 方法分析严重过敏性疾病患者的致敏谱

背景：现代过敏学的一个重要进步是引入了过敏原分子/成分，包括使用免疫细胞分析仪 ISAC 方法检测过敏原分子/成分。这种方法适用于具有复杂致敏谱和严重过敏性疾病的患者，在这种情况下，需要积极寻找各种预测严重病程的因素。材料与方法：2023 年 1 月至 8 月进行了一项单中心回顾性研究。研究对象包括 100 名适用于 SBA（63 名患者）--第 1 组、SAD（20 名患者）--第 2 组，或这两种疾病合并使用生物制剂（17 名患者）--第 3 组的患者。采用免疫细胞分析仪（ImmunoCAP）ISAC法进行成分重排诊断。数学和统计数据的处理是在 IDE Visual Studio Code 1.76.1（通用版）中使用 Python3.10 编程语言包进行的。使用的标准如下学生、Gaims-Howell、Kraskell-Wallis、Dunn 和 Holm 校正。结果：食物和真菌过敏原的多敏性和高发生率在以下人群中更为常见

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来源期刊

Russian Journal of Allergy

CiteScore

0.50

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0.00%

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