Evaluation of a near-patient SARS-CoV-2 novel rapid diagnostic platform
Year: 2024
Type: article
Abstract: The goal of this study is to test a novel device and methodology based on the "Pebble" platform and real-time quantitative colorimetric loop-mediated isothermal amplification (qcLAMP) during SARS-CoV-2 detection using crude samples and extracted RNA. The new method employs an inexpensive lightweight device aimed toward rapid point-of-care testing. An extensive evaluation was performed consisting of 1,693 clinical samples across five independent clinical testing centers. Positive colorimetric results were observed within 20 minutes of testing. At a 20-minute time-to-positive cut-off, the specificity is 98.5% with a diagnostic accuracy of 91.9%, compared to qPCR assays. Our findings indicate that the SARS-CoV-2 qcLAMP diagnostic assay in conjunction with the Pebble device is ideal for point-of-care/near-patient testing.IMPORTANCEHere, we describe our analyses and validation of a novel real-time quantitative colorimetric loop-mediated isothermal amplification (qcLAMP) device, available under the name "Pebble" and associated SARS-CoV-2 diagnostic qcLAMP assay for clinical diagnostic use. The analyses were performed in five independent testing sites across Europe using clinical samples from the associated clinical sites and support the use of "pebble" and associated kit in the diagnostic environment.
Source: Microbiology Spectrum
Institutions: University College London Hospitals NHS Foundation Trust, University College London, Inserm, Sorbonne Université, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Institut Pierre Louis d‘Épidémiologie et de Santé Publique, Université Libre de Bruxelles, Aristotle University of Thessaloniki, AHEPA University Hospital, Science and Technology Park of Crete, FORTH Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, University of Crete
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
Funder: Horizon 2020 Framework Programme
Award: G6049260834
OpenAlex ID: W4403544053
