van Oort Pouline M P, Nijsen Tamara, Weda Hans, Knobel Hugo, Dark Paul, Felton Timothy, Rattray Nicholas J W, Lawal Oluwasola, Ahmed Waqar, Portsmouth Craig, Sterk Peter J, Schultz Marcus J, Zakharkina Tetyana, Artigas Antonio, Povoa Pedro, Martin-Loeches Ignacio, Fowler Stephen J, Bos Lieuwe D J
Institute of Inflammation and Repair, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Philips Research, Eindhoven, The Netherlands.
BMC Pulm Med. 2017 Jan 3;17(1):1. doi: 10.1186/s12890-016-0353-7.
The diagnosis of ventilator-associated pneumonia (VAP) remains time-consuming and costly, the clinical tools lack specificity and a bedside test to exclude infection in suspected patients is unavailable. Breath contains hundreds to thousands of volatile organic compounds (VOCs) that result from host and microbial metabolism as well as the environment. The present study aims to use breath VOC analysis to develop a model that can discriminate between patients who have positive cultures and who have negative cultures with a high sensitivity.
METHODS/DESIGN: The Molecular Analysis of Exhaled Breath as Diagnostic Test for Ventilator-Associated Pneumonia (BreathDx) study is a multicentre observational study. Breath and bronchial lavage samples will be collected from 100 and 53 intubated and ventilated patients suspected of VAP. Breath will be analysed using Thermal Desorption - Gas Chromatography - Mass Spectrometry (TD-GC-MS). The primary endpoint is the accuracy of cross-validated prediction for positive respiratory cultures in patients that are suspected of VAP, with a sensitivity of at least 99% (high negative predictive value).
To our knowledge, BreathDx is the first study powered to investigate whether molecular analysis of breath can be used to classify suspected VAP patients with and without positive microbiological cultures with 99% sensitivity.
UKCRN ID number 19086, registered May 2015; as well as registration at www.trialregister.nl under the acronym 'BreathDx' with trial ID number NTR 6114 (retrospectively registered on 28 October 2016).
呼吸机相关性肺炎(VAP)的诊断仍然耗时且成本高昂,临床工具缺乏特异性,并且尚无用于排除疑似患者感染的床旁检测方法。呼出气体中含有数百至数千种挥发性有机化合物(VOC),这些化合物源于宿主、微生物代谢以及环境。本研究旨在利用呼出气体VOC分析开发一种模型,该模型能够以高灵敏度区分培养结果为阳性和阴性的患者。
方法/设计:呼出气体分子分析作为呼吸机相关性肺炎诊断测试(BreathDx)研究是一项多中心观察性研究。将从100名和53名疑似VAP的插管通气患者中采集呼出气体和支气管灌洗样本。呼出气体将采用热解吸-气相色谱-质谱联用仪(TD-GC-MS)进行分析。主要终点是对疑似VAP患者呼吸道培养阳性结果进行交叉验证预测的准确性,灵敏度至少为99%(高阴性预测值)。
据我们所知,BreathDx是第一项有足够样本量研究呼出气体分子分析能否用于对微生物培养结果为阳性和阴性的疑似VAP患者进行分类且灵敏度达99%的研究。
英国临床试验注册号19086,于2015年5月注册;以及在www.trialregister.nl以“BreathDx”为缩写进行注册,试验编号为NTR 6114(于2016年10月28日追溯注册)。