Diagnosis of COVID-19 by analysis of breath with gas chromatography-ion mobility spectrometry - a feasibility study. (December 2020)

• Record Type: Journal Article
• Authors: Ruszkiewicz, Dorota M; Sanders, Daniel; O'Brien, Rachel; Hempel, Frederik; Reed, Matthew J; Riepe, Ansgar C; Bailie, Kenneth; Brodrick, Emma; Darnley, Kareen; Ellerkmann, Richard; Mueller, Oliver; Skarysz, Angelika; Truss, Michael; Wortelmann, Thomas; Yordanov, Simeon; Thomas, C.L.Paul; Schaaf, Bernhard; Eddleston, Michael
• Is Part Of: EClinicalMedicine. Volume 29/30(2020)
• Publication Date: 2020-12
• Subjects: Covid-19 diagnostics -- Breath-analysis -- Breath-testing -- Gas chromatography-ion mobility spectrometry -- GC-IMS -- Multi-variate analysis -- Aldehydes -- Ketones -- Methanol; Medicine -- Research -- Periodicals; Medical policy -- Periodicals; Clinical Medicine; Health Policy; Public Health; Medical policy; Medicine -- Research; Periodical; Electronic journals; Periodicals; 613
• DOI: 10.1016/j.eclinm.2020.100609
• Languages: English
• ISSNs: 2589-5370

Abstract

Abstract: Background: There is an urgent need to rapidly distinguish COVID-19 from other respiratory conditions, including influenza, at first-presentation. Point-of-care tests not requiring laboratory- support will speed diagnosis and protect health-care staff. We studied the feasibility of using breath-analysis to distinguish these conditions with near-patient gas chromatography-ion mobility spectrometry (GC-IMS). Methods: Independent observational prevalence studies at Edinburgh, UK, and Dortmund, Germany, recruited adult patients with possible COVID-19 at hospital presentation. Participants gave a single breath-sample for VOC analysis by GC-IMS. COVID-19 infection was identified by transcription polymerase chain reaction (RT- qPCR) of oral/nasal swabs together with clinical-review. Following correction for environmental contaminants, potential COVID-19 breath-biomarkers were identified by multi-variate analysis and comparison to GC-IMS databases. A COVID-19 breath-score based on the relative abundance of a panel of volatile organic compounds was proposed and tested against the cohort data. Findings: Ninety-eight patients were recruited, of whom 21/33 (63.6%) and 10/65 (15.4%) had COVID-19 in Edinburgh and Dortmund, respectively. Other diagnoses included asthma, COPD, bacterial pneumonia, and cardiac conditions. Multivariate analysis identified aldehydes (ethanal, octanal), ketones (acetone, butanone), and methanol that discriminated COVID-19 from other conditions. An unidentified-feature with significant predictive power for severity/death was isolated in Edinburgh, while heptanal was identified in Dortmund. Differentiation of patients with definite diagnosis (25 and 65) of COVID-19 from non-COVID-19 was possible with 80% and 81.5% accuracy in Edinburgh and Dortmund respectively (sensitivity/specificity 82.4%/75%; area-under-the-receiver- operator-characteristic [AUROC] 0.87 95% CI 0.67 to 1) and Dortmund (sensitivity / specificity 90%/80%; AUROC 0.91 95% CI 0.87 to 1). Interpretation: These two studies independently indicate that patients with COVID-19 can be rapidly distinguished from patients with other conditions at first healthcare contact. The identity of the marker compounds is consistent with COVID-19 derangement of breath-biochemistry by ketosis, gastrointestinal effects, and inflammatory processes. Development and validation of this approach may allow rapid diagnosis of COVID-19 in the coming endemic flu seasons. Funding: MR was supported by an NHS Research Scotland Career Researcher Clinician award. DMR was supported by the University of Edinburgh ref COV_29.