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 investigates 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, 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.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
219
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. A nose clip was placed on the nose of each participant to avoid entry of non-filtered air in the device. Before measuring, the Aeonose was flushed with room air, guided through a carbon filter as well. During each measurement, a video was displayed to distract the participant and to reduce the chance of hyperventilation. Failed breath tests were excluded from analysis; the reason for failure was documented. Four similar Aeonose devices were used for breath analysis. A full-measurement procedure required sixteen minutes.
Maastricht University Medical Center
Maastricht, Netherlands
COVID 19 positive vs negative
Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.
Time frame: 3 months
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