This meta-analysis demonstrates suboptimal sensitivity and specificity of serologic-based diagnostic testing for SARS-CoV-2 and suggests that antibody testing alone, in its current form, is unlikely to be an adequate solution to the difficulties posed by COVID-19 and in guiding future policy decisions regarding social distancing and reopening of the economy worldwide. 7532, 4045830, ATTAIN COMMAND CATHETER, 2520, 2520. The sensitivity, specificity, and accuracy for IgM antibodies was 80%, 96% and 95% (95% CI, 92-96). The pooled sensitivity, specificity, and diagnostic accuracy for IgG was 81%, 97%, and 93% (95% CI, 91-95), respectively. Five studies (n=1,166 individual tests) met inclusion criteria. A bivariate model was used to compute pooled sensitivity, specificity, positive/negative likelihood ratio (LR), diagnostic odds ratio (OR), and summary receiver operating characteristic curve (SROC) with corresponding 95% confidence intervals (CIs). Full-text observational studies that reported IgG or IgM diagnostic yield and used nucleic acid amplification tests (NAATs) of respiratory tract specimens, as a the reference standard in English language were included. Electronic searches were performed using Medline (PubMed), EMBASE, and Cochrane Library. ![]() The aim of this study was to perform a structured systematic review and meta-analysis to evaluate the diagnostic characteristics of serological-based COVID-19 testing. Considering this, a proper understanding of serologic-based diagnostic testing characteristics is critical. These types have a version value of 1, 2, 3. Serologic testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) promises to assist in assessing exposure to and confirming the diagnosis of coronavirus disease 2019 (COVID-19), and to provide a roadmap for reopening countries worldwide. There are four different basic types of UUIDs: time-based, DCE security, name-based, and randomly generated UUIDs.
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