| Literature DB >> 33906571 |
Hin Fung Tsang1,2, Wai Ming Stanley Leung1, Lawrence Wing Chi Chan2, William Chi Shing Cho3, Sze Chuen Cesar Wong2.
Abstract
Background: Nucleic acid amplification tests (NAATs) based methods such as real-time reverse transcription polymerase-chain reaction (real-time RT-PCR) are the gold standard for diagnosis of current infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The cobas® Liat® and cepheid® GeneXpert® systems are two rapid real-time RT-PCR platforms offering rapid, specimen-to-answer detection of SARS-CoV-2.Research design and methods: In this study, we compared the performance of these two systems on SARS-CoV-2 detection in 9 nasopharyngeal swab (NPS) and 70 posterior oropharyngeal saliva specimens collected from 79 patients suspected of SARS-CoV-2 infection between August 2020 and March 2021.Entities:
Keywords: COVID-19 diagnosis; Coronavirus disease-2019; POCT; SARS-CoV-2 PCR; severe acute respiratory syndrome coronavirus 2
Mesh:
Year: 2021 PMID: 33906571 PMCID: PMC8095157 DOI: 10.1080/14737159.2021.1919513
Source DB: PubMed Journal: Expert Rev Mol Diagn ISSN: 1473-7159 Impact factor: 5.225
Comparison of Cepheid Xpress SARS-CoV-2 assay and Cobas Liat SARS-CoV-2 & influenza A/B assay
| Cepheid Xpress SARS-CoV-2 assay results, n | Total | |||
|---|---|---|---|---|
| Positive | Negative | |||
| Cobas Liat SARS-CoV-2 & Influenza A/B assay results, n | Positive (NPS) | 7 | 0 | 7 |
| Positive (Saliva) | 27 | 0 | 27 | |
| Negative (NPS) | 0 | 2 | 2 | |
| Negative (Saliva) | 0 | 43 | 43 | |
| Overall | 34 | 45 | 79 | |
| Positive Percent Agreement (PPA) (95% CI) | 100% (97.7–100%) | |||
| Negative Percent Agreement (NPA) (95% CI) | 100% (97.7–100%) | |||
| Overall Percent Agreement (OPA) (95% CI) | 100% (97.7–100%) | |||
Cycle threshold (Ct) values of positive specimens obtained by Cepheid® Xpress SARS-CoV-2 assay and Cobas® Liat® SARS-CoV-2 & influenza A/B assay
| Specimen | Specimen type | Cepheid® Xpress SARS-CoV-2 assay | Cobas® Liat® SARS-CoV-2 & Influenza A/B assay | |
|---|---|---|---|---|
| E gene | N2 gene | |||
| 1 | Saliva | 25.0 | 28.3 | 23.5 |
| 2 | NPS | 16.9 | 19.2 | 15.4 |
| 3 | Saliva | 27.7 | 29.9 | 23.2 |
| 4 | NPS | 17.2 | 18.8 | 13.4 |
| 5 | Saliva | 20.3 | 21.8 | 16.0 |
| 6 | Saliva | 29.4 | 32.2 | 30.2 |
| 7 | Saliva | 18.2 | 20.6 | 16.4 |
| 8 | Saliva | 26.4 | 28.6 | 24.2 |
| 9 | Saliva | 17.4 | 19.9 | 15.9 |
| 10 | Saliva | 20.3 | 22.6 | 21.0 |
| 11 | Saliva | 0.0 | 40.6 | 33.5 |
| 12 | NPS | 35.9 | 39.2 | 29.4 |
| 13 | NPS | 33.4 | 38.2 | 34.6 |
| 14 | Saliva | 16.1 | 18.6 | 12.1 |
| 15 | Saliva | 20.1 | 21.8 | 17.8 |
| 16 | NPS | 20.3 | 22.7 | 19.7 |
| 17 | NPS | 23.7 | 25.9 | 20.1 |
| 18 | Saliva | 26.0 | 28.1 | 21.5 |
| 19 | Saliva | 27.4 | 30.2 | 32.9 |
| 20 | Saliva | 32.3 | 36.1 | 28.1 |
| 21 | Saliva | 28.3 | 30.5 | 36.6 |
| 22 | Saliva | 25.3 | 27.7 | 24.5 |
| 23 | Saliva | 24.6 | 27.7 | 24.4 |
| 24 | NPS | 20.2 | 22.3 | 17.8 |
| 25 | Saliva | 23.9 | 25.9 | 21.3 |
| 26 | Saliva | 24.9 | 27.2 | 22.8 |
| 27 | Saliva | 18.1 | 20.8 | 11.3 |
| 28 | Saliva | 26.2 | 28.5 | 22.8 |
| 29 | Saliva | 0.0 | 40.9 | 32.9 |
| 30 | Saliva | 18.3 | 20.5 | 18.5 |
| 31 | Saliva | 27.9 | 30.6 | 25.5 |
| 32 | Saliva | 29.4 | 32.3 | 27.1 |
| 33 | Saliva | 20.8 | 22.9 | 15.8 |
| 34 | Saliva | 22.6 | 25.2 | 18.9 |
NPS: nasopharyngeal swab.
The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of Cepheid Xpress SARS-CoV-2 assay and Cobas Liat SARS-CoV-2 & Influenza A/B assay on SARS-CoV-2 detection
| Positive specimens | Negative specimens | Sensitivity | Specificity | PPV | NPV | Accuracy | ||
|---|---|---|---|---|---|---|---|---|
| Cobas Liat SARS-CoV-2 & Influenza A/B assay results | Test positive | 34a | 0b | 100% | 100% | 100% | 100% | 100% |
| Test negative | 0 c | 45d | ||||||
| Cepheid Xpress SARS-CoV-2 assay results | Test positive | 34a | 0b | 100% | 100% | 100% | 100% | 100% |
| Test negative | 0 c | 45d |
Sensitivity = [a/(a + c)] x 100%; Specificity = [d/(b + d)] x 100%; PPV = [a/(a + b)] x 100%; NPV; NPV = [d/(c + d)] x 100%; accuracy = [(a + d)/(a + b + c + d)] x 100%.