ArticleBiomedicines2023
Evaluation of a Commercial Point-of-Care RT-LAMP Assay for Rapid Detection of SARS-CoV-2.
Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The goal of this study was to evaluate the performance of a commercial reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay (Detect COVID-19 Test) in the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A total of 202 human respiratory and viral culture specimens were tested retrospectively. The performance of the Detect COVID-19 Test was comparable to that of commercial real-time polymerase chain reaction assays (sensitivity: 93.42%; specificity: 100%), and better than that of the rapid antigen test (sensitivity: 48.00%; specificity: 100%) for specimens with threshold cycle (Ct) values of less than 30. The Beta, Delta, and Omicron variants of concern were successfully detected. With their simplicity of use and good assay sensitivity, point-of-care RT-LAMP assays may be a viable option for SARS-CoV-2 testing at home, or in regions without sophisticated laboratory facilities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.