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当前位置: 首页 > 技术文献 > 应用文献 > 利用电子鼻进行呼气分析过敏性鼻炎与外源性哮喘的鉴别
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利用电子鼻进行呼气分析过敏性鼻炎与外源性哮喘的鉴别

来源: Silvano Dragonieri, Vitaliano N Quaranta, PierluigiCarratu  发布日期: 2019-01-15  访问量: 120


根据呼出的挥发性有机化合物(VOC)特征,评估电子鼻是否能够区分患有或不伴有外源性哮喘的变应性鼻炎患者以及健康对照者。...
标签: cyranose320 电子鼻 鼻炎 哮喘
 
Exhaled breath profiling by electronic nose enabled discrimination of allergic rhinitis and extrinsic asthma
利用电子鼻进行呼气分析过敏性鼻炎与外源性哮喘的鉴别

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:根据呼出的挥发性有机化合物(VOC)特征,评估电子鼻是否能够区分患有或不伴有外源性哮喘的变应性鼻炎患者以及健康对照者。
方法:14例外源性哮喘和变应性鼻炎(AAR)、14例无哮喘变应性鼻炎(AR)和14例健康对照(HC)参与了一项横断面研究。通过标准化方法收集呼出的气体,并通过电子鼻(Cyranose320)进行采样。采用主成分分析法对原始数据进行简化,并采用典型判别分析法进行分析。计算了交叉验证精度(CVA)和接收机工作特性(ROC)曲线。使用之前的培训对新招募患者(7名AAR、7名AR和7名HC)进行外部验证。
模型。结果。AR患者的呼吸图聚集在AAR患者(CVA=85.7%)和HC患者(CVA=82.1%)之间。AAR的呼吸图也与HC的呼吸图分离(CVA=75.0%)。外部验证证实了上述发现。结论。电子鼻可以区分呼出的呼吸和有或没有外源性哮喘的变应性鼻炎患者,这两种疾病的特征部分重叠。这也支持了在变应性鼻炎患者中使用呼吸剖面图诊断哮喘的观点。


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