ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens
Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off...
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| Language: | English |
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Taylor & Francis Group
2020-01-01
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| Series: | Emerging Microbes and Infections |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/22221751.2020.1772678 |
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| author | Tao Suo Xinjin Liu Jiangpeng Feng Ming Guo Wenjia Hu Dong Guo Hafiz Ullah Yang Yang Qiuhan Zhang Xin Wang Muhanmmad Sajid Zhixiang Huang Liping Deng Tielong Chen Fang Liu Ke Xu Yuan Liu Qi Zhang Yingle Liu Yong Xiong Guozhong Chen Ke Lan Yu Chen |
| author_facet | Tao Suo Xinjin Liu Jiangpeng Feng Ming Guo Wenjia Hu Dong Guo Hafiz Ullah Yang Yang Qiuhan Zhang Xin Wang Muhanmmad Sajid Zhixiang Huang Liping Deng Tielong Chen Fang Liu Ke Xu Yuan Liu Qi Zhang Yingle Liu Yong Xiong Guozhong Chen Ke Lan Yu Chen |
| author_sort | Tao Suo |
| collection | DOAJ |
| description | Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI: 27–55%), 100% (95% CI: 54–100%), 100%, 16% (95% CI: 13–19%), 0.6 (95% CI: 0.48–0.75) and 47% (95% CI: 33–60%) for RT-PCR to 94% (95% CI: 83–99%), 100% (95% CI: 48–100%), 100%, 63% (95% CI: 36–83%), 0.06 (95% CI: 0.02–0.18), and 95% (95% CI: 84–99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5–12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR. |
| format | Article |
| id | doaj-art-94a5cb75fbe44dc9b853b6b3b0148a9c |
| institution | DOAJ |
| issn | 2222-1751 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Emerging Microbes and Infections |
| spelling | doaj-art-94a5cb75fbe44dc9b853b6b3b0148a9c2025-08-20T03:08:32ZengTaylor & Francis GroupEmerging Microbes and Infections2222-17512020-01-01911259126810.1080/22221751.2020.1772678ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimensTao Suo0Xinjin Liu1Jiangpeng Feng2Ming Guo3Wenjia Hu4Dong Guo5Hafiz Ullah6Yang Yang7Qiuhan Zhang8Xin Wang9Muhanmmad Sajid10Zhixiang Huang11Liping Deng12Tielong Chen13Fang Liu14Ke Xu15Yuan Liu16Qi Zhang17Yingle Liu18Yong Xiong19Guozhong Chen20Ke Lan21Yu Chen22State Key Laboratory of Virology, Renmin Hospital, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaDepartment of Infectious Disease, Zhongnan Hospital, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaDepartment of Infectious Disease, Zhongnan Hospital, Wuhan University, Wuhan, People’s Republic of ChinaDepartment of Infectious Disease, Zhongnan Hospital, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaDepartment of Infectious Disease, Zhongnan Hospital, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Renmin Hospital, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Virology, Modern Virology Research Center, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of ChinaQuantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI: 27–55%), 100% (95% CI: 54–100%), 100%, 16% (95% CI: 13–19%), 0.6 (95% CI: 0.48–0.75) and 47% (95% CI: 33–60%) for RT-PCR to 94% (95% CI: 83–99%), 100% (95% CI: 48–100%), 100%, 63% (95% CI: 36–83%), 0.06 (95% CI: 0.02–0.18), and 95% (95% CI: 84–99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5–12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR.https://www.tandfonline.com/doi/10.1080/22221751.2020.1772678SARS-CoV-2droplet digital PCRRT-PCRclinical detectionfalse negative |
| spellingShingle | Tao Suo Xinjin Liu Jiangpeng Feng Ming Guo Wenjia Hu Dong Guo Hafiz Ullah Yang Yang Qiuhan Zhang Xin Wang Muhanmmad Sajid Zhixiang Huang Liping Deng Tielong Chen Fang Liu Ke Xu Yuan Liu Qi Zhang Yingle Liu Yong Xiong Guozhong Chen Ke Lan Yu Chen ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens Emerging Microbes and Infections SARS-CoV-2 droplet digital PCR RT-PCR clinical detection false negative |
| title | ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens |
| title_full | ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens |
| title_fullStr | ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens |
| title_full_unstemmed | ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens |
| title_short | ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens |
| title_sort | ddpcr a more accurate tool for sars cov 2 detection in low viral load specimens |
| topic | SARS-CoV-2 droplet digital PCR RT-PCR clinical detection false negative |
| url | https://www.tandfonline.com/doi/10.1080/22221751.2020.1772678 |
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