Identification of breath-prints for the COPD detection associated with smoking and household air pollution by electronic nose

電子鼻識別吸煙和家庭空氣污染相關的COPD檢測呼吸圖譜

Maribel Rodríguez-Aguilar、Lorena Díaz de León-Martínez、Patricia Gorocica-Rosete、Ireri Thirión-Romero
Omar Ornelas-Rebolledo、Rogelio Flores-Ramírez
Published:February 12, 2020DOI:https://doi.org/10.1016/j.rmed.2020.105901

Highlights
•The breathprint of COPD is associated with the disease and not its causality.
•PCA, CDA and SVM showed a separation between COPD and healthy subjects.
•The study showed a high sensitivity of 100% and specificity of 97.8%.

•慢性阻塞性肺病的呼吸印記與疾病有關，而不是其因果關系。
•PCA、CDA和SVM顯示慢性阻塞性肺病患者和健康人之間存在分離。
•該研究顯示100%的高靈敏度和97.8%的特異性。

Abstract
Purpose
The analysis of breath-print, has been proposed as an attractive alternative to investigate possible biomarkers of Chronic Obstructive Pulmonary Disease (COPD). The aim of the present study was to discriminate between healthy subjects, patients with COPD associated with smoking (COPD-S) and patients with COPD associated with household air pollution (COPD-HAP).

呼吸印記分析被認為是研究慢性阻塞性肺疾病（COPD）可能的生物標志物的一種有吸引力的方法。本研究旨在區分健康受試者、與吸煙相關的COPD患者（COPD-S）和與家庭空氣污染相關的COPD患者（COPD-HAP）。

Methods
A cross-sectional study of 294 participants was conducted, 88 with smoking associated COPD, 28 associated with HAP and 178 healthy subjects. Breath-print analysis was performed by using the Cyranose 320 electronic nose. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA) and Support Vector Machine (SVM) and the test's diagnostic power by means of ROC (Receiver Operating Characteristic) curves.

對294名受試者、88名吸煙相關性COPD患者、28名HAP患者和178名健康受試者進行了橫斷面研究。用Cyranose 320電子鼻進行呼吸印記分析。采用主成分分析（PCA）、典型判別分析（CDA）和支持向量機（SVM）對各組數據進行評價，并用ROC曲線對測試數據進行診斷。

Results
The results indicated that the breath-print of patients with COPD is different from the one of healthy subjects explaining a variability of 93.8% with a correct prediction of 97.8% and correct classification of 100%,also positive and negative predictive value of 96.5 and 100% respectively. Furthermore, the breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference.

結果表明，COPD患者的呼吸紋與健康人不同，其變異性為93.8%，預測正確率為97.8%，分類正確率為100%，陽性預測值為96.5%，陰性預測值為100%。此外，COPD-S患者和COPD-HAP患者呼出氣的呼吸紋沒有任何差異。

Conclusions
The breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference, which demonstrates that the breath-print is related to the disease and not to causality. With these results, the analysis of the breath-print of COPD is proposed as an alternative for a screening method in future clinical applications.

COPD-S和COPD-HAP患者呼出氣的呼吸紋無明顯差異，說明呼吸紋與疾病有關，與病因無關。根據這些結果，對COPD患者的呼吸紋進行分析，為今后的臨床應用提供了一種篩選方法。

Keywords：COPD，Exhaled breath，Burning biomass fuel，Smoking，Electronic nose

關鍵詞：慢性阻塞性肺病，呼氣，燃燒生物質燃料，吸煙，電子鼻