Human volatilome analysis using eNose to assess uncontrolled asthma in a clinical setting
使用電子鼻進行人體揮發物分析以評估臨床環境中無法控制的哮喘
Mariana Farraia João Cavaleiro Rufo Inês Paciência Francisca Castro Mendes Ana Rodolfo
Tiago Rama Sílvia M. Rocha Luís Delgado Paul Brinkman André Moreira
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.
對呼出的揮發性有機化合物(VOCs)的分析顯示，在鑒別哮喘患者時，有很好的結果。目前，還沒有哮喘失控的生物標志物。因此，我們的目的是在現實的臨床環境中，評估呼出的揮發性有機物分析能力，使用電子鼻(eNose)來識別哮喘患者。
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 m*riate 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.
進行了一項橫斷面研究，并使用電子鼻分析了199名參與者(130名女性，年齡6-78歲，66%患有哮喘)的呼吸樣本。利用32個傳感器的電阻數據進行多變量無監督聚類分析，可以區分訓練組和測試組的3組VOC模式。利用ANOVA、Kruskal-Wallis和卡方檢驗對聚類結果進行比較。
Results
In the training set (n = 121), three different clusters covering asthma, lung function, symptoms in the previous 4 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.
在訓練集(n=121)中，確定了三個不同的集群，涵蓋哮喘、肺功能、前4周的癥狀和年齡。兩組比較顯示，在運動時胸悶、呼吸困難和性別方面存在顯著差異。這些發現在測試集中得到了證實(n=78)，其中訓練模型確定了三個集群。報告較少呼吸癥狀(呼吸困難和夜間覺醒)的受試者被分為一組，而其他受試者則表現出對癥狀的類似不良控制，哮喘患者的分布在他們之間存在顯著差異。
Conclusions
In a clinical setting, the analysis of the exhaled VOC profiles using an eNose could be used as a fast and noninvasive complementary assessment tool for the detection of uncontrolled asthma symptoms.
在臨床環境中，使用電子鼻分析呼出的VOC分布可以作為一種快速、無創的輔助評估工具，用于檢測不受控制的哮喘癥狀。
