Volatolomics is gaining consideration as a viable approach to diagnose several diseases, and it also shows promising results to discriminate COVID-19 patients via breath analysis. This paper extends the study of the relationship between volatile compounds (VOCs) and COVID-19 to blood serum. Blood samples were collected from subjects recruited at the emergency department of a large public hospital. The VOCs were analyzed with a gas chromatography mass spectrometer (GC/MS). GC/MS data show that in more than 100 different VOCs, the pattern of abundances of 17 compounds identifies COVID-19 from non-COVID with an accuracy of 89% (sensitivity 94% and specificity 83%). GC/MS analysis was complemented by an array of gas sensors whose data achieved an accuracy of 89% (sensitivity 94% and specificity 80%).
Mougang, Y.k., Di Zazzo, L., Minieri, M., Capuano, R., Catini, A., Legramante, J.m., et al. (2021). Sensor array and gas chromatographic detection of the blood serum volatolomic signature of COVID-19. ISCIENCE, 24(8), 102851 [10.1016/j.isci.2021.102851].
Sensor array and gas chromatographic detection of the blood serum volatolomic signature of COVID-19
Minieri, Marilena;Capuano, Rosamaria;Catini, Alexandro;Legramante, Jacopo Maria;Paolesse, Roberto;Bernardini, Sergio;Di Natale, Corrado
2021-08-20
Abstract
Volatolomics is gaining consideration as a viable approach to diagnose several diseases, and it also shows promising results to discriminate COVID-19 patients via breath analysis. This paper extends the study of the relationship between volatile compounds (VOCs) and COVID-19 to blood serum. Blood samples were collected from subjects recruited at the emergency department of a large public hospital. The VOCs were analyzed with a gas chromatography mass spectrometer (GC/MS). GC/MS data show that in more than 100 different VOCs, the pattern of abundances of 17 compounds identifies COVID-19 from non-COVID with an accuracy of 89% (sensitivity 94% and specificity 83%). GC/MS analysis was complemented by an array of gas sensors whose data achieved an accuracy of 89% (sensitivity 94% and specificity 80%).File | Dimensione | Formato | |
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