Name (Synonyms) | Correlation |
---|
Name (Synonyms) | Correlation | |
---|---|---|
D045169 | Severe Acute Respiratory Syndrome NIH | 0.07 |
D018352 | Coronavirus Infections NIH | 0.06 |
Name (Synonyms) | Correlation |
---|
There are 2 clinical trials
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.
Description: Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.
Measure: COVID 19 positive vs negative Time: 3 monthsCorona Virus Disease (COVID-19), spread worldwide and has become an emergency of major international concern. In March 2020, the WHO declared the COVID-19 outbreak a global pandemic. Accurate and fast diagnosis is crucial in managing the pandemic. Current diagnostic approaches raise several difficulties: they are time-consuming, expensive, invasive, and most important lacking high sensitivity. The gold standard diagnostic test for COVID-19, reverse transcription polymerase chain reaction (RT-PCR), is highly dependent on adequate deep sampling of the swab in the naso- and oropharynx. A new diagnostic test that can correctly and rapidly identify infected patients and asymptomatic carriers is urgently required to prevent further virus transmission and thus reduce mortality rates. Aim: This proof-of-principle study aims to investigate if an electronic nose (Aeonose) can distinguish individuals with antibodies from individuals without antibodies against COVID-19 based on analysis of volatile organic compounds (VOCs). Methods: between April and July 2020, persons undergoing RT-PCR and a serology test for COVID-19 were recruited at Maastricht UMC+ for breath analysis. All participants had to breathe through the Aeonose for five consecutive minutes. The VOC pattern in their exhaled breath was then linked to the matching RT-PCR and serological test results.
Description: Ability of the electronic nose (Aeonose) to distinguish individuals with antibodies from individuals without antibodies against COVID-19 based on analysis of volatile organic compounds (VOCs).
Measure: COVID-19 antibodies vs COVID-19 negative Time: 3 months