Dept of Paediatric Pulmonology, Maastricht University Medical Centre, Research Institute CAPHRI, The Netherlands.
Eur Respir J. 2013 Jul;42(1):98-106. doi: 10.1183/09031936.00010712. Epub 2013 May 3.
The hypothesis was that prediction of asthma exacerbations in children is possible by profiles of exhaled volatile organic compounds (VOCs), a noninvasive measure of airway inflammation. The aims of the present study were to determine: 1) whether VOCs in exhaled breath are able to predict asthma exacerbations; and 2) the time course and chemical background of the most predictive VOCs. A prospective study was performed in 40 children with asthma over 1 year. At standard 2-month intervals, exhaled nitric oxide fraction (FeNO), VOC profiles in exhaled breath samples, lung function and symptoms were determined in a standardised way. VOC profiles were analysed by gas chromatography-time-of-flight mass spectrometry. 16 out of 40 children experienced an exacerbation. With support vector machine analysis, the most optimal model of baseline measurements versus exacerbation within patients was based on six VOCs (correct classification 96%, sensitivity 100% and specificity 93%). The model of baseline values of patients with compared to those without an exacerbation consisted of seven VOCs (correct classification 91%, sensitivity 79% and specificity 100%). FeNO and lung function were not predictive for exacerbations. This study indicates that a combination of different exhaled VOCs is able to predict exacerbations of childhood asthma.
该假说认为，通过呼出挥发性有机化合物（VOC）谱（气道炎症的非侵入性测量），可以预测儿童哮喘恶化。本研究的目的是确定：1）呼气中的 VOC 是否能够预测哮喘恶化；2）最具预测性的 VOC 的时间过程和化学背景。在为期 1 年的 40 名哮喘儿童中进行了前瞻性研究。在标准的 2 个月间隔内，以标准化的方式测定呼出气一氧化氮分数（FeNO）、呼出气样本中的 VOC 谱、肺功能和症状。通过气相色谱-飞行时间质谱分析 VOC 谱。40 名儿童中有 16 名发生了恶化。通过支持向量机分析，针对患者内恶化的基线测量与恶化之间的最佳模型基于六种 VOC（正确分类 96%，敏感性 100%，特异性 93%）。与无恶化的患者相比，患者基线值的模型由七种 VOC 组成（正确分类 91%，敏感性 79%，特异性 100%）。FeNO 和肺功能不能预测恶化。这项研究表明，不同呼出 VOC 的组合能够预测儿童哮喘的恶化。
