Abstract
The SARS-CoV-2 infection rate, as well as mortality rate, is high. There is an urgent need for a high-throughput, accurate and reliable method of diagnosing COVID-19 pneumonia. We included references from databases, such as PubMed, Cochrane Library, Web of Science, and Embase, and extracted data. Then, MetaDisc and STATA were used to establish forest plots and funnel plots for meta-analysis. We collected 14 articles and performed a systematic review. The following results were obtained: sensitivity and specificity were 0.97 (0.96 to 0.98) and 0.97 (0.96 to 0.98) respectively; PLR and NLR were 24.51 (16.63-36.12) and 0.03 (0.01 to 0.10) respectively, DOR was 975.15 (430.11-2210.88), and AUC was 0.9926. When Xpress detects SARS-CoV-2 in different samples, the heterogeneity is small and the specificity and sensitivity are extremely high. We recommend the employment of Xpert Xpress analysis in rapid screening.
Keywords: COVID-19 pneumonia; Diagnostic accuracy; SARS-CoV-2; Systemic review; Xpert Xpress.
【저자키워드】 SARS-CoV-2, COVID-19 pneumonia, Diagnostic accuracy, Systemic review, Xpert Xpress., 【초록키워드】 COVID-19, Meta-analysis, COVID-19 pneumonia, Pneumonia, SARS-COV-2 infection, systematic review, heterogeneity, databases, sensitivity, specificity, Diagnostic accuracy, Sensitivity and specificity, mortality rate, NLR, Analysis, Systemic review, AUC, employment, systemic, forest plot, Web of Science, Cochrane Library, funnel plots, article, Stata, funnel plot, forest plots, diagnosing, performed, detect, collected, were used, 【제목키워드】 Diagnostic accuracy,