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Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units
Although numerous studies have evaluated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using cycle threshold (Ct) values as a surrogate of viral ribonucleic acid (RNA) load, few studies have used standardized, quantitative methods. We validated a quantitative SARS-CoV-2 digi...
| Autores principales: | , , , , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9494499/ https://www.ncbi.nlm.nih.gov/pubmed/36221269 http://dx.doi.org/10.1093/ofid/ofac490 |
| _version_ | 1784793808213377024 |
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| author | Hijano, Diego R Gu, Zhengming Brazelton, Jessica Zhu, Haiqing Suganda, Sri Glasgow, Heather L Darji, Himani Tang, Li Fabrizio, Thomas P Allison, Kim J Allen, E Kaitlynn Gaur, Aditya H Wolf, Joshua Thomas, Paul G Webby, Richard J Hayden, Randall T |
| author_facet | Hijano, Diego R Gu, Zhengming Brazelton, Jessica Zhu, Haiqing Suganda, Sri Glasgow, Heather L Darji, Himani Tang, Li Fabrizio, Thomas P Allison, Kim J Allen, E Kaitlynn Gaur, Aditya H Wolf, Joshua Thomas, Paul G Webby, Richard J Hayden, Randall T |
| author_sort | Hijano, Diego R |
| collection | PubMed |
| description | Although numerous studies have evaluated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using cycle threshold (Ct) values as a surrogate of viral ribonucleic acid (RNA) load, few studies have used standardized, quantitative methods. We validated a quantitative SARS-CoV-2 digital polymerase chain reaction assay normalized to World Health Organization International Units and correlated viral RNA load with symptoms and disease severity. |
| format | Online Article Text |
| id | pubmed-9494499 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Oxford University Press |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-94944992022-09-27 Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units Hijano, Diego R Gu, Zhengming Brazelton, Jessica Zhu, Haiqing Suganda, Sri Glasgow, Heather L Darji, Himani Tang, Li Fabrizio, Thomas P Allison, Kim J Allen, E Kaitlynn Gaur, Aditya H Wolf, Joshua Thomas, Paul G Webby, Richard J Hayden, Randall T Open Forum Infect Dis Brief Report Although numerous studies have evaluated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using cycle threshold (Ct) values as a surrogate of viral ribonucleic acid (RNA) load, few studies have used standardized, quantitative methods. We validated a quantitative SARS-CoV-2 digital polymerase chain reaction assay normalized to World Health Organization International Units and correlated viral RNA load with symptoms and disease severity. Oxford University Press 2022-09-21 /pmc/articles/PMC9494499/ /pubmed/36221269 http://dx.doi.org/10.1093/ofid/ofac490 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
| spellingShingle | Brief Report Hijano, Diego R Gu, Zhengming Brazelton, Jessica Zhu, Haiqing Suganda, Sri Glasgow, Heather L Darji, Himani Tang, Li Fabrizio, Thomas P Allison, Kim J Allen, E Kaitlynn Gaur, Aditya H Wolf, Joshua Thomas, Paul G Webby, Richard J Hayden, Randall T Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units |
| title | Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units |
| title_full | Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units |
| title_fullStr | Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units |
| title_full_unstemmed | Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units |
| title_short | Prediction of Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Quantitative Digital Polymerase Chain Reaction Normalized to International Units |
| title_sort | prediction of symptomatic severe acute respiratory syndrome coronavirus 2 infection by quantitative digital polymerase chain reaction normalized to international units |
| topic | Brief Report |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9494499/ https://www.ncbi.nlm.nih.gov/pubmed/36221269 http://dx.doi.org/10.1093/ofid/ofac490 |
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