Benedek Pálma, Lázár Zsófia, Bikov András, Kunos László, Katona Gábor, Horváth Ildikó
Department of Oto-Rhino-Laryngology and Bronchology, Heim Pál Children's Hospital, 86 Üllői Str., 1089 Budapest, Hungary.
Int J Pediatr Otorhinolaryngol. 2013 Aug;77(8):1244-7. doi: 10.1016/j.ijporl.2013.04.025. Epub 2013 Jun 6.
Obstructive sleep apnoea syndrome (OSAS) is a common disorder in children, which is associated with enhanced inflammatory status. Inflammation-associated changes could be monitored by the assessment of exhaled biomarker profile. This study aimed to compare the exhaled biomarker profile in children with OSAS and habitual snorers.
Eighteen children with OSAS (8 ± 2 years, mean ± SD) and ten non-OSAS subjects with habitual snoring (9 ± 2 years) were recruited. Exhaled breath was collected from the lower airways, processed using an electronic nose (E-nose) and analyzed off-line using principal component analysis, followed by discrimination analysis and logistic regression to build a receiver operating characteristic (ROC) curve.
Exhaled biomarker pattern of OSAS patients was discriminated from that of control subjects (p = 0.03, cross-validation accuracy: 64%), ROC curve analysis (area: 0.83) showed 78% sensitivity and 70% specificity.
The altered exhaled biomarker pattern in OSAS might reflect accelerated airway and/or systemic inflammation in diseased state. Breath pattern analysis by an E-nose can serve as a new tool to monitor inflammation in children with OSAS.
阻塞性睡眠呼吸暂停综合征(OSAS)是儿童常见疾病,与炎症状态增强有关。炎症相关变化可通过评估呼出生物标志物谱进行监测。本研究旨在比较OSAS儿童与习惯性打鼾儿童的呼出生物标志物谱。
招募了18名OSAS儿童(8±2岁,均值±标准差)和10名习惯性打鼾的非OSAS受试者(9±2岁)。从下呼吸道收集呼出气体,使用电子鼻(E-nose)进行处理,并离线使用主成分分析进行分析,随后进行判别分析和逻辑回归以构建受试者工作特征(ROC)曲线。
OSAS患者的呼出生物标志物模式与对照受试者的模式不同(p = 0.03,交叉验证准确率:64%),ROC曲线分析(面积:0.83)显示敏感性为78%,特异性为70%。
OSAS中呼出生物标志物模式的改变可能反映了疾病状态下气道和/或全身炎症的加速。通过电子鼻进行呼吸模式分析可作为监测OSAS儿童炎症的新工具。