ACS Nano. 2020 Aug 18. doi: 10.1021/acsnano.0c05657. Online ahead of print.
ABSTRACT
This article reports on a non-invasive approach in detecting and following-up individuals who are at-risk or have an existing COVID-19 infection, with a potential ability to serve as an epidemic control tool. The proposed method uses a developed breath device comprised of a nanomaterial-based hybrid sensors array with multiplexed detection capabilities that can detect disease-specific biomarkers from exhaled breath, thus enabling rapid and accurate diagnosis. An exploratory clinical study with this approach was examined in Wuhan, China during March 2020. The study cohort included 49 confirmed COVID-19 patients, 58 healthy controls and 33 non-COVID lung infection controls. When applicable, positive COVID-19 patients were sampled twice: during the active disease, and after recovery. Discriminant analysis of the obtained signals from the nanomaterial-based sensors achieved very good test discriminations between the different groups. The training and test set data exhibited, respectively, 94% and 76% accuracy in differentiating patients from controls as well as 90% and 95% accuracy in differentiating between patients with COVID-19 and patients with other lung infections. While further validation studies are needed, the results may serve as a base for technology that would lead to a reduction in number of unneeded confirmatory tests and lower the burden on the hospitals, while allowing individuals a screening solution that can be performed in PoC facilities. The proposed method can be considered as a platform that could be applied for any other disease infection with proper modifications to the artificial intelligence and would therefore be available to serve as a diagnostic tool in case of a new disease outbreak.
PMID:32808759 | DOI:10.1021/acsnano.0c05657