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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

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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
Subjects: R Medicine > RC Internal medicine
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Faculty of Science, Engineering and Medicine > Science > Statistics
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, Warwick Manufacturing Group
ISSN: 1932-6203
Official Date: 18 December 2017
Dates:
DateEvent
18 December 2017Published
14 November 2017Accepted
Volume: 12
Number: 12
Article Number: e0188879
DOI: 10.1371/journal.pone.0188879
Status: Peer Reviewed
Publication Status: Published
Media of Output (format): .mea .xlsx
Access rights to Published version: Open Access
Copyright Holders: University of Warwick
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDUniversity of Warwickhttp://dx.doi.org/10.13039/501100000741
UNSPECIFIED[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
EP/M027503/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
109105Z/15/AWellcome Trusthttp://dx.doi.org/10.13039/100004440
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Contributors:
ContributionNameContributor ID
UNSPECIFIEDMotta, AndreaUNSPECIFIED

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