Diagnostic accuracy of an app-guided, self-administered test for influenza among individuals presenting to general practice with influenza-like illness: study protocol

Autor: Nigel Stocks, Barry Lutz, Mark Rieder, Monica Zigman Suchsland, Monique Chilver, Philip Su, Shawna Cooper, Chunjong Park, Libby Rose Lavitt, Alex Mariakakis, Shwetak Patel, Chelsey Graham, Cynthia LeRouge
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: BMJ Open, Vol 10, Iss 11 (2020)
Druh dokumentu: article
ISSN: 2044-6055
DOI: 10.1136/bmjopen-2019-036298
Popis: Introduction Diagnostic tests for influenza in Australia are currently only authorised for use in clinical settings. At-home diagnostic testing for influenza could reduce the need for patient contact with healthcare services, which potentially could contribute to symptomatic improvement and reduced spread of influenza. We aim to determine the accuracy of an app-guided nasal self-swab combined with a lateral flow immunoassay for influenza conducted by individuals with influenza-like illness (ILI).Methods and analysis Adults (≥18 years) presenting with ILI will be recruited by general practitioners (GP) participating in Australian Sentinel Practices Research Network. Eligible participants will have a nasal swab obtained by their GP for verification of influenza A/B status using reverse transcription polymerase chain reaction (RT-PCR) test at an accredited laboratory. Participants will receive an influenza test kit and will download an app that collects self-reported symptoms and influenza risk factors, then instructs them in obtaining a low-nasal self-swab, running a QuickVue influenza A+B lateral flow immunoassay (Quidel Corporation) and interpreting the results. Participants will also interpret an enhanced image of the test strip in the app. The primary outcome will be the accuracy of participants’ test interpretation compared with the laboratory RT-PCR reference standard. Secondary analyses will include accuracy of the enhanced test strip image, accuracy of an automatic test strip reader algorithm and validation of prediction rules for influenza based on self-reported symptoms. A post-test survey will be used to obtain participant feedback on self-test procedures.Ethics and dissemination The study was approved by the Human Research and Ethic Committee (HREC) at the University of Adelaide (H-2019-116). Protocol details and any amendments will be reported to https://www.tga.gov.au/. Results will be published in the peer-reviewed literature, and shared with stakeholders in the primary care and diagnostics communities.Trial registration number Australia New Zealand Clinical Trial Registry (U1111-1237-0688).
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