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电子鼻可区分未经治疗的肺结节病患者与对照者的呼出气。

An electronic nose discriminates exhaled breath of patients with untreated pulmonary sarcoidosis from controls.

机构信息

Department of Respiratory Medicine, University of Amsterdam, Amsterdam, The Netherlands.

出版信息

Respir Med. 2013 Jul;107(7):1073-8. doi: 10.1016/j.rmed.2013.03.011. Epub 2013 May 3.

Abstract

BACKGROUND

Sarcoidosis is a systemic granulomatous disease of unknown cause that affects the lungs in over 90% of cases. Breath analysis by electronic nose technology provides exhaled molecular profiles that have potential in the diagnosis of several respiratory diseases.

OBJECTIVES

We hypothesized that exhaled molecular profiling may distinguish well-characterized patients with sarcoidosis from controls. To that end we performed electronic nose measurements in untreated and treated sarcoidosis patients and in healthy controls.

METHODS

31 sarcoidosis patients (11 patients with untreated pulmonary sarcoidosis [age: 48.4 ± 9.0], 20 patients with treated pulmonary sarcoidosis [age: 49.7 ± 7.9]) and 25 healthy controls (age: 39.6 ± 14.1) participated in a cross-sectional study. Exhaled breath was collected twice using a Tedlar bag by a standardized method. Both bags were then sampled by an electronic nose (Cyranose C320), resulting in duplicate data. Statistical analysis on sensor responses was performed off-line by principal components (PC) analyses, discriminant analysis and ROC curves.

RESULTS

Breathprints from patients with untreated pulmonary sarcoidosis were discriminated from healthy controls (CVA: 83.3%; AUC 0.825). Repeated measurements confirmed those results. Patients with untreated and treated sarcoidosis could be less well discriminated (CVA 74.2%), whereas the treated sarcoidosis group was undistinguishable from controls (CVA 66.7%)

CONCLUSION

Untreated patients with active sarcoidosis can be discriminated from healthy controls. This suggests that exhaled breath analysis has potential for diagnosis and/or monitoring of sarcoidosis.

摘要

背景

结节病是一种病因不明的系统性肉芽肿性疾病,超过 90%的病例累及肺部。电子鼻技术通过分析呼气中的分子谱,为多种呼吸系统疾病的诊断提供了新的可能。

目的

我们假设电子鼻分析技术能够很好地区分特征明确的结节病患者和健康对照者。为此,我们对未经治疗和经治疗的结节病患者以及健康对照者进行了电子鼻测量。

方法

31 例结节病患者(11 例未经治疗的肺结节病患者[年龄:48.4±9.0],20 例经治疗的肺结节病患者[年龄:49.7±7.9])和 25 例健康对照者(年龄:39.6±14.1)参与了一项横断面研究。通过一种标准化方法,使用 Tedlar 袋对呼出的气体进行两次采集。然后,电子鼻(Cyranose C320)对两个袋子中的气体进行了两次采样,得到了重复的数据。通过主成分(PC)分析、判别分析和 ROC 曲线,对传感器响应的统计分析进行了离线处理。

结果

未经治疗的肺结节病患者的呼吸图谱与健康对照者相区分(CVA:83.3%;AUC 0.825)。重复测量结果证实了这一结果。未经治疗和经治疗的结节病患者的区分效果较差(CVA 74.2%),而经治疗的结节病组与对照组无法区分(CVA 66.7%)。

结论

处于活动期的未经治疗的结节病患者可以与健康对照者相区分。这表明呼出气分析可能有助于结节病的诊断和/或监测。

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