| Property | Value |
|---|
|
?:abstract
|
-
BACKGROUND: Infection with SARS-CoV-2 causes corona virus disease (COVID-19). The most standard diagnostic method is reverse transcription-polymerase chain reaction (RT-PCR) on a nasopharyngeal and/or an oropharyngeal swab. The high occurrence of false-negative results due to the non-presence of SARS-CoV-2 in the oropharyngeal environment renders this sampling method not ideal. Therefore, a new sampling device is desirable. This proof-of-principle study investigated the possibility to train machine-learning classifiers with an electronic nose (Aeonose) to differentiate between COVID-19-positive and negative persons based on volatile organic compounds (VOCs) analysis. METHODS: Between April and June 2020, participants were invited for breath analysis when a swab for RT-PCR was collected. If the RT-PCR resulted negative, the presence of SARS-CoV-2-specific antibodies was checked to confirm the negative result. All participants breathed through the Aeonose for five minutes. This device contains metal-oxide sensors that change in conductivity upon reaction with VOCs in exhaled breath. These conductivity changes are input data for machine learning and used for pattern recognition. The result is a value between − 1 and + 1, indicating the infection probability. RESULTS: 219 participants were included, 57 of which COVID-19 positive. A sensitivity of 0.86 and a negative predictive value (NPV) of 0.92 were found. Adding clinical variables to machine-learning classifier via multivariate logistic regression analysis, the NPV improved to 0.96. CONCLUSIONS: The Aeonose can distinguish COVID-19 positive from negative participants based on VOC patterns in exhaled breath with a high NPV. The Aeonose might be a promising, non-invasive, and low-cost triage tool for excluding SARS-CoV-2 infection in patients elected for surgery.
|
|
is
?:annotates
of
|
|
|
?:creator
|
|
|
?:doi
|
|
|
?:doi
|
-
10.1007/s00464-020-08169-0
|
|
?:journal
|
|
|
?:license
|
|
|
?:pdf_json_files
|
-
document_parses/pdf_json/db212c0fe5d825c782071077838f2deb74fb79f7.json
|
|
?:pmc_json_files
|
-
document_parses/pmc_json/PMC7709806.xml.json
|
|
?:pmcid
|
|
|
?:pmid
|
|
|
?:pmid
|
|
|
?:publication_isRelatedTo_Disease
|
|
|
is
?:relation_isRelatedTo_publication
of
|
|
|
?:sha_id
|
|
|
?:source
|
|
|
?:title
|
-
Applying the electronic nose for pre-operative SARS-CoV-2 screening
|
|
?:type
|
|
|
?:year
|
|
![[This page as RDF]](https://research.tib.eu/covid-19/static/rdf-icon.gif){kind=icon}