临床中利用电子鼻分析呼出气体以评估难控制哮喘症状
2020/02/11
摘要
背景：辨别支气管哮喘个体时，呼出气挥发性有机化合物（VOC）测定分析显示出潜优势。目前，尚无难控制哮喘的生物标志物。因此，我们的目的为在真实世界临床实践中，通过使用电子鼻（eNose）的方法，评估分析呼出气有机化合物在确定难控制哮喘个体方面的作用。
方法：此试验为横断面研究，利用电子鼻收集199位受试者（包括130位女性，年龄在6-78岁间，66%合并支气管哮喘）呼出气样本进行分析。利用来自32个传感器的电阻数据，多元聚类分析将训练组与测试组分为3个亚组。利用单因素方差分析、K-W检验及卡方检验进行组间比较。
结果：在训练组中（n = 121），确定3个亚组，其包含支气管哮喘诊断、肺功能、过去四周的症状和年龄。成对比较显示各组间与运动相关的胸闷、呼吸困难以及性别分布方面存在明显差异。这些结果表现在测试组（n = 78）中得到证实，并且训练模型将其分为3个亚组。具有较少呼吸道症状（呼吸困难和夜间觉醒）的参与者分为一组，其他具有相似症状但控制较差者，其哮喘患者分布情况差异显著。
结论：在临床中利用eNose分析呼出气VOC是一项可用于检测难控制哮喘症状的快速、无创辅助评估工具。
Human volatilome analysis using eNose to assess uncontrolled asthma in a clinical setting.
Farraia M, Cavaleiro Rufo J, Paciência I, Mendes FC, Rodolfo A, Rama T, Rocha SM, Delgado L, Brinkman P, Moreira A.
Allergy. 2020 Jan 29. doi: 10.1111/all.14207.
Abstract
BACKGROUND: Analyses of exhaled volatile organic compounds (VOCs) have shown promising results when distinguishing individuals with asthma. Currently, there are no biomarkers for uncontrolled asthma. Therefore, we aimed to assess, in a real-life clinical setting, the ability of the exhaled VOC analysis, using an electronic nose (eNose), to identify individuals with uncontrolled asthma.
METHODS: A cross-sectional study was conducted and breath samples from 199 participants (130 females, aged 6-78, 66% with asthma) were analysed using an eNose. A multivariate unsupervised cluster analysis, using the resistance data from 32 sensors, could distinguish three clusters of VOC patterns in the training and testing groups. Comparisons between the clusters were performed using the one-way ANOVA, Kruskal-Wallis, and chi-squared tests.
RESULTS: In the training set (n = 121), three different clusters covering asthma, lung function, symptoms in the previous four weeks, and age were identified. The pairwise comparisons showed significant differences with respect to chest tightness during exercise, dyspnoea, and gender. These findings were confirmed in the testing set (n = 78) where the training model identified three clusters. The participants who reported fewer respiratory symptoms (dyspnoea and night-time awakenings) were grouped into one cluster, while the others comprised participants who showed similar poor control over symptoms with the distribution of the individuals with asthma being significantly different between them.
CONCLUSIONS: In a clinical setting, the analysis of the exhaled VOC profiles using an eNose could be used as a fast and non-invasive complementary assessment tool for the detection of uncontrolled asthma symptoms.
背景：辨别支气管哮喘个体时，呼出气挥发性有机化合物（VOC）测定分析显示出潜优势。目前，尚无难控制哮喘的生物标志物。因此，我们的目的为在真实世界临床实践中，通过使用电子鼻（eNose）的方法，评估分析呼出气有机化合物在确定难控制哮喘个体方面的作用。
方法：此试验为横断面研究，利用电子鼻收集199位受试者（包括130位女性，年龄在6-78岁间，66%合并支气管哮喘）呼出气样本进行分析。利用来自32个传感器的电阻数据，多元聚类分析将训练组与测试组分为3个亚组。利用单因素方差分析、K-W检验及卡方检验进行组间比较。
结果：在训练组中（n = 121），确定3个亚组，其包含支气管哮喘诊断、肺功能、过去四周的症状和年龄。成对比较显示各组间与运动相关的胸闷、呼吸困难以及性别分布方面存在明显差异。这些结果表现在测试组（n = 78）中得到证实，并且训练模型将其分为3个亚组。具有较少呼吸道症状（呼吸困难和夜间觉醒）的参与者分为一组，其他具有相似症状但控制较差者，其哮喘患者分布情况差异显著。
结论：在临床中利用eNose分析呼出气VOC是一项可用于检测难控制哮喘症状的快速、无创辅助评估工具。
（中日友好医院呼吸与危重症医学科 张鑫 摘译 林江涛 审校）
（Allergy. 2020 Jan 29. doi: 10.1111/all.14207.）
（Allergy. 2020 Jan 29. doi: 10.1111/all.14207.）
Human volatilome analysis using eNose to assess uncontrolled asthma in a clinical setting.
Farraia M, Cavaleiro Rufo J, Paciência I, Mendes FC, Rodolfo A, Rama T, Rocha SM, Delgado L, Brinkman P, Moreira A.
Allergy. 2020 Jan 29. doi: 10.1111/all.14207.
Abstract
BACKGROUND: Analyses of exhaled volatile organic compounds (VOCs) have shown promising results when distinguishing individuals with asthma. Currently, there are no biomarkers for uncontrolled asthma. Therefore, we aimed to assess, in a real-life clinical setting, the ability of the exhaled VOC analysis, using an electronic nose (eNose), to identify individuals with uncontrolled asthma.
METHODS: A cross-sectional study was conducted and breath samples from 199 participants (130 females, aged 6-78, 66% with asthma) were analysed using an eNose. A multivariate unsupervised cluster analysis, using the resistance data from 32 sensors, could distinguish three clusters of VOC patterns in the training and testing groups. Comparisons between the clusters were performed using the one-way ANOVA, Kruskal-Wallis, and chi-squared tests.
RESULTS: In the training set (n = 121), three different clusters covering asthma, lung function, symptoms in the previous four weeks, and age were identified. The pairwise comparisons showed significant differences with respect to chest tightness during exercise, dyspnoea, and gender. These findings were confirmed in the testing set (n = 78) where the training model identified three clusters. The participants who reported fewer respiratory symptoms (dyspnoea and night-time awakenings) were grouped into one cluster, while the others comprised participants who showed similar poor control over symptoms with the distribution of the individuals with asthma being significantly different between them.
CONCLUSIONS: In a clinical setting, the analysis of the exhaled VOC profiles using an eNose could be used as a fast and non-invasive complementary assessment tool for the detection of uncontrolled asthma symptoms.
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当前气道舒张标准低估老年哮喘的存在
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高度中性粒细胞性哮喘患者血清IgE升高，OCS依赖性和IL-17/22表达升高
