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Gas-capillary column ion mobility spectrometer (GC-IMS) analysis of exhaled volatile organic compounds (VOC) may be a noninvasive and feasible option for clinicians to diagnose respiratory tract infections (RTIs) in hospitalized individuals, according to a study published in PLoS One.
Researchers identified and recruited 71 individuals at the Royal Liverpool University Hospital in the United Kingdom to participate in a prospective study to determine the feasibility and accuracy of a portable GC-IMS to diagnose bacterial RTIs, which would assist in decreasing the inappropriate use of antibiotic therapy. In addition, the current gold standard for VOC detection is gas chromatography/mass spectrometry, but these devices have several disadvantages (eg, expensive, large, and typically laboratory-based).
Individuals were asked to inhale and then exhale into a disposable mouthpiece that was attached directly to a machine mounted on a hospital trolley and brought to their bedside for data collection to be downloaded and reviewed. Study results demonstrated test sensitivity and specificity rates of 62% (95% CI, 41%-80%) and 80% (95% CI, 64%-91%), respectively.
Limitations of this study include the small sample size, single research site, and overall exploratory nature. In addition, there was a low rate of microbiologic testing that could have caused a selection bias, as patients with confirmed viral diagnosis through laboratory services were recruited to participate in the study because of a low number of participants confirmed with viral RTIs.
The researchers concluded that the use of a portable GC-IMS instrument by clinicians to test for and diagnose bacterial RTI in hospitalized patients was an overall feasible option, with moderate accuracy (area under the curve, 0.73; 95% CI, 0.61-0.86). However, further instrument testing is needed.
Reference
Lewis JM, Savage RS, Beeching NJ, Beadsworth MBJ, Feasey N, Covington JA. Identifying volatile metabolite signatures for the diagnosis of bacterial respiratory tract infection using electronic nose technology: a pilot study. PLoS One. 2017;12(12):e0188879.
