To investigate if exhaled breath patterns from persons with COVID-19 infection can be distinguished from subjects without COVID-19 infection.
ID
Bron
Aandoening
COVID-19
Ondersteuning
Onderzoeksproduct en/of interventie
Uitkomstmaten
Primaire uitkomstmaten
Is it possible to detect persons with a COVID-19 infection from exhaled air analysed with the Aeonose™?
Achtergrond van het onderzoek
Currently diagnostic tests for persons with COVID-19 infection bear several disadvantages. The standard test, RT-PCR, (reverse transcription-polymerase chain reaction) is the most frequently used and most reliable test, but still results in a high number of false negative results and it also requires a specialized lab. Therefore there is a need for a fast, highly sensitive, patient friendly test. This study is a follow up study of the feasibility study ‘’Applying the electric nose for pre-operatieve SARS-CoV-2 screening to determine the capability of the Aeonose™ in diagnosing COVID-19 from the University of Maastricht. The aim of the study is to determine the diagnostic utility of the device 'Electronic Nose' for COVID-19. Validation of the E-nose in to estimate the diagnostic accuracy of the E-nose using exhaled air in persons with COVID-19 in adults.
Doel van het onderzoek
To investigate if exhaled breath patterns from persons with COVID-19 infection can be distinguished from subjects without COVID-19 infection.
Onderzoeksopzet
Primary and secondary outcomes will be determined using the electric nose "Aenose" (with three metal oxide sensors). The research consists of a training phase (December 2020 to January 2021) and a validation phase (February 2021).
Publiek
Wetenschappelijk
Belangrijkste voorwaarden om deel te mogen nemen (Inclusiecriteria)
• Subjects with a suspicion COVID-19 infection.
• All subjects must be older than 18 years and not mentally handicapped.
Belangrijkste redenen om niet deel te kunnen nemen (Exclusiecriteria)
•subjects with dyspnea and/or use supplemental oxygen
Opzet
Deelname
Voornemen beschikbaar stellen Individuele Patiënten Data (IPD)
Toelichting
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