Background: Rapid and accurate detection of SARS-CoV-2 infected individuals is crucial for taking timely measures and minimizing the risk of further SARS-CoV-2 spread. We aimed to assess the accuracy of exhaled breath analysis by electronic nose (eNose) for the discrimination between individuals with and without a SARS-CoV-2 infection.
Methods: This was a prospective real-world study of individuals presenting to public test facility for SARS-CoV-2 detection by molecular amplification tests (TMA or RT-PCR). After sampling of a combined throat/nasopharyngeal swab, breath profiles were obtained using a cloud-connected eNose. Data-analysis involved advanced signal processing and statistics based on independent t-tests followed by linear discriminant and ROC analysis. Data from the training set were tested in a validation, a replication and an asymptomatic set.
Findings: For the analysis 4510 individuals were available. In the training set (35 individuals with; 869 without SARS-CoV-2), the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.947 (CI:0.928-0.967). These results were confirmed in the validation set (0.957; CI:0.942-0.971, n=904) and externally validated in the replication set (0.937; CI:0.926-0.947, n=1948) and the asymptomatic set (0.909; CI:0.879-0.938, n=754). Selecting a cut-off value of 0.30 in the training set resulted in a sensitivity/specificity of 100/78, >99/84, 98/82% in the validation, replication and asymptomatic set, respectively.
Interpretation: eNose represents a quick and non-invasive method to reliably rule out SARS-CoV-2 infection in public health test facilities and can be used as a screening test to define who needs an additional confirmation test.
Funding: Ministry of Health, Welfare and Sport