![]() One invalid BinaxNOW result was identified. Twelve false-positive BinaxNOW results (out of 2,308 tests) were observed in all 12, the test bands were faint but otherwise normal and were noted by both readers. By cycle threshold ( C T) value cutoff, sensitivity in all subgroups combined ( n = 292 RT-PCR-positive individuals) was 99.3% with C T values of ≤25, 95.8% with C T values of ≤30, and 81.2% with C T values of ≤35. BinaxNOW had 96.5% (95% confidence interval, 90.0 to 99.3) sensitivity and 100% (95% CI, 98.6 to 100.0) specificity in adults within 7 days of symptoms and 84.6% (95% CI, 65.1 to 95.6) sensitivity and 100% (95% CI, 94.5 to 100.0) specificity in children within 7 days of symptoms. Of 2,482 participants, 1,380 adults and 928 children had paired RT-PCR/BinaxNOW results and complete symptom data. The paired RT-PCR result was the reference for sensitivity and specificity calculations. Positive BinaxNOW results were reported to patients by phone, and they were instructed to isolate pending RT-PCR results. Positive BinaxNOW results were scored as faint, medium, or strong. One individual performed testing and official result reporting for each test, but most tests had a second independent reading to assess interoperator agreement. BinaxNOW testing was performed in a testing pod with temperature/humidity monitoring. Dual AN swabs were collected from symptomatic and asymptomatic children (≤18 years of age) and adults. Individuals presenting for molecular testing in two of seven lanes were offered the opportunity to also receive BinaxNOW testing. We evaluated the Abbott BinaxNOW COVID-19 Ag card in a high-throughput, drive-through, free community testing site in Massachusetts using anterior nasal (AN) swab reverse transcriptase PCR (RT-PCR) for clinical testing. Deployment of an Ag RDT requires an understanding of its operational and performance characteristics under real-world conditions and in relevant subpopulations. 221.Rapid diagnostic tests (RDTs) for SARS-CoV-2 antigens (Ag) that can be performed at point of care (POC) can supplement molecular testing and help mitigate the COVID-19 pandemic. (From Mausner JS, Kramer S: Mausner and Bahn Epidemiology: An Introductory Text. Relationship between disease prevalence and predictive value in a test with 95% sensitivity and 85% specificity. ![]() The figure below depicts the relationship between disease prevalence and predictive value in a test with 95% sensitivity and 95% specificity: When considering predictive values of diagnostic or screening tests, recognize the influence of the prevalence of the disease. Conversely, increased prevalence results in decreased negative predictive value. Using the same test in a population with a higher prevalence increases positive predictive value. Now let's calculate the predictive values: We maintain the same sensitivity and specificity because these are characteristics of this test. Prevalence of Disease= \(\dfrac \times 100\)
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