2022
DOI: 10.1111/1751-7915.14112
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A quantitative RT‐qLAMP for the detection of SARS‐CoV‐2 and human gene in clinical application

Abstract: Reverse transcription (RT) – loop‐mediated isothermal amplification (LAMP) assay is a rapid and one‐step method to detect SARS‐CoV‐2 in the pandemic. Quantitative estimation of the viral load of SARS‐CoV‐2 in patient samples could help physicians make decisions on clinical treatment and patient management. Here, we propose to use a quantitative LAMP (qLAMP) method to evaluate the viral load of SARS‐CoV‐2 in samples. We used threshold time (TT) values of qLAMP, the isothermal incubation time required for the fl… Show more

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Cited by 3 publications
(2 citation statements)
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“…RT-qPCR is recognised as the gold standard for COVID-19 diagnostics, due to its high sensitivity and specificity. However, because this type of assay requires a long reaction time (around 2 h), sophisticated instruments, and highly trained personnel (Babiker et al, 2020;Yu et al, 2022), diagnostics labs have not been able to fulfil the unprecedentedly high level of testing requests.…”
mentioning
confidence: 99%
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“…RT-qPCR is recognised as the gold standard for COVID-19 diagnostics, due to its high sensitivity and specificity. However, because this type of assay requires a long reaction time (around 2 h), sophisticated instruments, and highly trained personnel (Babiker et al, 2020;Yu et al, 2022), diagnostics labs have not been able to fulfil the unprecedentedly high level of testing requests.…”
mentioning
confidence: 99%
“…Different methods of detection can be used to interpret the results of RT-LAMP assays including turbidimetry, fluorescence signal or colorimetry using pH-sensitive dyes such as phenol red or neutral red (Cui et al, 2020;Huang et al, 2020;Rohaim et al, 2020;Woo et al, 2020;Alves et al, 2021;Aoki et al, 2021;Garcia-Venzor et al, 2021;Lim et al, 2021). The RT-LAMP assays developed for SARS-CoV-2 detection have shown sensitivity and specificity comparable to RT-qPCR (Baek et al, 2020;Cui et al, 2020;Ganguli et al, 2020;Huang et al, 2020;Lamb et al, 2020;Mautner et al, 2020;Mohon et al, 2020;Park et al, 2020;Rodel et al, 2020;Rohaim et al, 2020;Yan et al, 2020;Fowler et al, 2021;Garcia-Venzor et al, 2021;Lalli et al, 2021;Lim et al, 2021;Nawattanapaiboon et al, 2021;Wei et al, 2021;Marino et al, 2022;Papadakis et al, 2022;Yu et al, 2022).…”
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confidence: 99%