Biophotonics Research Unit, Gloucestershire Royal Hospital, Gloucester, UK.
Eur J Clin Invest. 2011 Jan;41(1):52-8. doi: 10.1111/j.1365-2362.2010.02376.x. Epub 2010 Sep 14.
Electronic nose (E-nose) technology has been successfully used to diagnose a number of microbial infections. We have investigated the potential use of an E-nose for the diagnosis of ventilator-associated pneumonia (VAP) by detecting micro-organisms in bronchoalveolar lavage (BAL) fluid in a prospective comparative study of E-nose analysis and microbiology.
BAL samples were collected using a blind technique from 44 patients following a minimum of 72 h mechanical ventilation. Control samples were collected from six patients mechanically ventilated on the intensive care unit (ICU) immediately following elective surgery. Quantitative microbiological culture and E-nose headspace analysis of the BAL samples were undertaken. Multivariate analysis was applied to correlate E-nose response with microbiological growth.
E-nose fingerprints correctly classified 77% of the BAL samples, with and without microbiological growth from patients not on antibiotics. Inclusion of patients on antibiotics resulted in 68% correct classification. Seventy per cent of isolates, cultured in the laboratory from the clinical samples, were accurately discriminated into four clinically significant groups.
E-nose technology can accurately discriminate between different microbial species in BAL samples from ventilated patients on ICU at risk of developing VAP with accuracy comparable with accepted microbiological techniques.
电子鼻（E-nose）技术已成功用于诊断多种微生物感染。我们通过检测支气管肺泡灌洗液（BAL）中的微生物，在一项电子鼻分析与微生物学的前瞻性对比研究中，调查了电子鼻用于诊断呼吸机相关性肺炎（VAP）的潜力。
对至少接受 72 小时机械通气的 44 名患者，采用盲法技术采集 BAL 样本。对照组采集 6 名在 ICU 接受择期手术后即刻行机械通气的患者的 BAL 样本。对 BAL 样本进行定量微生物培养和 E-nose 顶空分析。应用多元分析将 E-nose 反应与微生物生长相关联。
E-nose 指纹图谱正确分类了 77%的 BAL 样本，包括未接受抗生素治疗的患者和有微生物生长的患者。纳入接受抗生素治疗的患者后，正确分类率为 68%。从临床样本中实验室培养的 70%的分离株准确地分为四个有临床意义的组。
E-nose 技术可准确区分 ICU 机械通气患者 BAL 样本中的不同微生物种类，与公认的微生物学技术相比，其准确性相当。
