Exhaled breath profiling by electronic nose enabled discrimination of allergic rhinitis and extrinsic asthma
利用電子鼻進行呼氣分析過敏性鼻炎與外源性哮喘的鑒別
Silvano Dragonieri, Vitaliano N Quaranta, Pierluigi Carratu, Teresa Ranieri & Onofrio Resta
To cite this article: Silvano Dragonieri, Vitaliano N Quaranta, Pierluigi Carratu, Teresa Ranieri &
Onofrio Resta (2018): Exhaled breath profiling by electronic nose enabled discrimination of allergic
rhinitis and extrinsic asthma, Biomarkers, DOI: 10.1080/1354750X.2018.1508307
To link to this article: https://doi.org/10.1080/1354750X.2018.1508307
Abstract
Aim:To assess whether an e-nose could discriminate between subjects affected by allergic rhinitis with and without concomitant extrinsic asthma, as well as from healthy controls, in terms of exhaled VOC-profile.
METHODS. 14 patients with Extrinsic Asthma and Allergic Rhinitis (AAR), 14 patients with Allergic Rhinitis without asthma (AR) and 14 healthy controls (HC) participated in a crosssectional study. Exhaled breath was collected by a standardized method and sampled by an e-nose (Cyranose 320). Raw data were reduced by Principal component analysis and analysed by canonical discriminant analysis. Cross-validation accuracy (CVA) and Receiver Operating Characteristic(ROC)-curves were calculated. External validation in newly recruited patients (7 AAR, 7 AR and 7 HC) was tested using the previous training
model. RESULTS. Breathprints of patients with AR clustered from those with AAR (CVA = 85.7%), as well as HC (CVA = 82.1%). Breathprints from AAR were also separated from those of HC (CVA = 75.0%). External validation confirmed the above findings. CONCLUSIONS. An e-nose can discriminate exhaled breath from subjects with allergic rhinitis with and without extrinsic asthma, which represent two different diseases with partly overlapping features. This supports the view of using breath profiling to diagnose asthma also in patients with allergic rhinitis.
目的：根據(jù)呼出的揮發(fā)性有機化合物(VOC)特征，評估電子鼻是否能夠區(qū)分患有或不伴有外源性哮喘的變應性鼻炎患者以及健康對照者。
方法：14例外源性哮喘和變應性鼻炎(AAR)、14例無哮喘變應性鼻炎(AR)和14例健康對照(HC)參與了一項橫斷面研究。通過標準化方法收集呼出的氣體，并通過電子鼻(Cyranose320)進行采樣。采用主成分分析法對原始數(shù)據(jù)進行簡化，并采用典型判別分析法進行分析。計算了交叉驗證精度(CVA)和接收機工作特性(ROC)曲線。使用之前的培訓對新招募患者(7名AAR、7名AR和7名HC)進行外部驗證。
模型。結(jié)果。AR患者的呼吸圖聚集在AAR患者(CVA=85.7%)和HC患者(CVA=82.1%)之間。AAR的呼吸圖也與HC的呼吸圖分離(CVA=75.0%)。外部驗證證實了上述發(fā)現(xiàn)。結(jié)論。電子鼻可以區(qū)分呼出的呼吸和有或沒有外源性哮喘的變應性鼻炎患者，這兩種疾病的特征部分重疊。這也支持了在變應性鼻炎患者中使用呼吸剖面圖診斷哮喘的觀點。
