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Data for Identifying volatile metabolite signatures for the diagnosis of bacterial respiratory tract infection using electronic nose technology : a pilot study
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Lewis, Joseph M., Savage, Richard S., Beeching, Nicholas J., Beadsworth, Mike B. J., Feasey, Nicholas and Covington, James A. (2017) Data for Identifying volatile metabolite signatures for the diagnosis of bacterial respiratory tract infection using electronic nose technology : a pilot study. [Dataset]
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Official URL: http://doi.org/10.5281/zenodo.1053769
Abstract
Objectives New point of care diagnostics are urgently needed to reduce the over-prescription of antimicrobials for bacterial respiratory tract infection (RTI). We performed a pilot cross sectional study to assess the feasibility of gas-capillary column ion mobility spectrometer (GC-IMS), for the analysis of volatile organic compounds (VOC) in exhaled breath to diagnose bacterial RTI in hospital inpatients. Methods 71 patients were prospectively recruited from the Acute Medical Unit of the Royal Liverpool University Hospital between March and May 2016 and classified as confirmed or probable bacterial or viral RTI on the basis of microbiologic, biochemical and radiologic testing. Breath samples were collected at the patient’s bedside directly into the electronic nose device, which recorded a VOC spectrum for each sample. Sparse principal component analysis and sparse logistic regression were used to develop a diagnostic model to classify VOC spectra as being caused by bacterial or non-bacterial RTI. Results Summary area under the receiver operator characteristic curve was 0.73 (95% CI 0.61–0.86), summary sensitivity and specificity were 62% (95% CI 41–80%) and 80% (95% CI 64–91%) respectively (p = 0.00147). Conclusions GC-IMS analysis of exhaled VOC for the diagnosis of bacterial RTI shows promise in this pilot study and further trials are warranted to assess this technique.
| Item Type: | Dataset | |||||||||||||||
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| Subjects: | R Medicine > RC Internal medicine | |||||||||||||||
| Divisions: | Faculty of Science > Engineering Faculty of Science > Statistics |
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| SWORD Depositor: | Library Publications Router | |||||||||||||||
| Library of Congress Subject Headings (LCSH): | Respiratory infections -- Diagnosis, Respiratory infections -- Microbiology, Anti-infective agents | |||||||||||||||
| Journal or Publication Title: | PLoS One | |||||||||||||||
| Publisher: | University of Warwick / Public Library of Science | |||||||||||||||
| ISSN: | 1932-6203 | |||||||||||||||
| Official Date: | 18 December 2017 | |||||||||||||||
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| Date of first compliant deposit: | 20 December 2017 | |||||||||||||||
| Volume: | 12 | |||||||||||||||
| Number: | 12 | |||||||||||||||
| Article Number: | e0188879 | |||||||||||||||
| DOI: | 10.1371/journal.pone.0188879 | |||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||
| Publication Status: | Published | |||||||||||||||
| Access rights to Published version: | Open Access | |||||||||||||||
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