Comparative evaluation of ten lateral flow immunoassays to detect SARS-CoV-2 antibodies
收藏DataCite Commons2026-03-16 更新2026-04-25 收录
下载链接:
https://datadryad.org/dataset/doi:10.5061/dryad.brv15dv8h
下载链接
链接失效反馈官方服务:
资源简介:
Background: Rapid mobilisation from industry and academia following the
outbreak of the novel coronavirus, severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2), led to the development and availability of
SARS-CoV-2 lateral flow immunoassays (LFAs). High-quality LFAs are
urgently needed at the point of care to add to currently available
diagnostic tools. In this study, we provide evaluation data for ten LFAs
suitable for use at the point of care. Methods: COVID-19 positive patients
(N=45), confirmed by reverse transcription – quantitative polymerase chain
reaction (RT-qPCR), were recruited through the International Severe Acute
Respiratory and Emerging Infection Consortium - Coronavirus Clinical
Characterisation Consortium (ISARIC4C) study. Sera collected from patients
with influenza A (N=20), tuberculosis (N=5), individuals with previous
flavivirus exposure (N=21), and healthy sera (N=4), collected
pre-pandemic, were used as negative controls. Ten LFAs manufactured or
distributed by ASBT Holdings Ltd, Cellex, Fortress Diagnostics, Nantong
Egens Biotechnology, Mologic, NG Biotech, Nal von Minden, and Suzhou Herui
BioMed Co. were evaluated. Results: Compared to RT-qPCR, sensitivity of
LFAs ranged from 87.0-95.7%. Specificity against pre-pandemic controls
ranged between 92.0-100%. Compared to IgG ELISA, sensitivity and
specificity ranged between 90.5-100% and 93.2-100%, respectively.
Percentage agreement between LFAs and IgG ELISA ranged from 89.6-92.7%.
Inter-test agreement between LFAs and IgG ELISA ranged between
kappa=0.792-0.854. Conclusions: LFAs may serve as a useful tool for rapid
confirmation of ongoing or previous infection in conjunction with clinical
suspicion of COVID-19 in patients attending hospital. Impartial validation
prior to commercial sale provides users with data that can inform best use
settings.
提供机构:
Dryad
创建时间:
2021-01-28



