Diagnostic Accuracy Estimates for COVID-19 Real-Time Polymerase Chain Reaction and Lateral Flow Immunoassay Tests With Bayesian Latent-Class Models
نویسندگان
چکیده
Abstract Our objective was to estimate the diagnostic accuracy of real-time polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA) tests for coronavirus disease 2019 (COVID-19), depending on time after symptom onset. Based cross-classified results RT-PCR LFIA, we used Bayesian latent-class models, which do not require a gold standard evaluation diagnostics. Data were extracted from studies that evaluated LFIA (immunoglobulin G (IgG) and/or immunoglobulin M (IgM)) assays using as reference method. The sensitivity 0.68 (95% probability interval (PrI): 0.63, 0.73). IgG/M 0.32 PrI :0.23; 0.41) first week increased steadily. It 0.75 PrI: 0.67; 0.83) 0.93 0.88; 0.97) second third weeks onset, respectively. Both had high absolute specificity, with higher point median estimates specificity narrower intervals. 0.99 0.98; 1.00). IgG/IgM 0.97 0.92, 1.00), 0.98 0.95, 1.00) 0.94, first, second, varies models provide valid efficient alternative evaluating rapidly evolving diagnostics COVID-19, under various clinical settings different risk profiles.
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ژورنال
عنوان ژورنال: American Journal of Epidemiology
سال: 2021
ISSN: ['0002-9262', '1476-6256']
DOI: https://doi.org/10.1093/aje/kwab093