Using patient-collected clinical samples and sera to detect and quantify the severe acute respiratory syndrome coronavirus (SARS-CoV)
Identifieur interne : 000E70 ( Pmc/Checkpoint ); précédent : 000E69; suivant : 000E71Using patient-collected clinical samples and sera to detect and quantify the severe acute respiratory syndrome coronavirus (SARS-CoV)
Auteurs : Zhongping He [République populaire de Chine] ; Hui Zhuang [République populaire de Chine] ; Chunhui Zhao [République populaire de Chine] ; Qingming Dong [République populaire de Chine] ; Guoai Peng [République populaire de Chine] ; Dominic E. Dwyer [Australie]Source :
- Virology Journal [ 1743-422X ] ; 2007.
Abstract
Severe acute respiratory syndrome (SARS) caused a large outbreak of pneumonia in Beijing, China, in 2003. Reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect and quantify SARS-CoV in 934 sera and self-collected throat washes and fecal samples from 271 patients with laboratory-confirmed SARS managed at a single institution.
SARS-CoV detection rates in sera were highest in the first 9 days of illness, whereas detection was highest in throat washes 5–14 days after onset of symptoms. The highest SARS-CoV RT-PCR rates (70.4–86.3%) and viral loads (log10 4.5–6.1) were seen in fecal samples collected 2–4 weeks after the onset of clinical illness. Fecal samples were frequently SARS-CoV RT-PCR positive beyond 40 days, and occasional sera still had SARS-CoV detected after 3 weeks of illness.
In the context of an extensive outbreak with major pressure on hospital resources, patient self-collected samples are an alternative to nasopharyngeal aspirates for laboratory confirmation of SARS-CoV infection.
Url:
DOI: 10.1186/1743-422X-4-32
PubMed: 17386116
PubMed Central: 1851004
Affiliations:
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Severe acute respiratory syndrome (SARS) caused a large outbreak of pneumonia in Beijing, China, in 2003. Reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect and quantify SARS-CoV in 934 sera and self-collected throat washes and fecal samples from 271 patients with laboratory-confirmed SARS managed at a single institution.</p>
</sec>
<sec><title>Results</title>
<p>SARS-CoV detection rates in sera were highest in the first 9 days of illness, whereas detection was highest in throat washes 5–14 days after onset of symptoms. The highest SARS-CoV RT-PCR rates (70.4–86.3%) and viral loads (log<sub>10</sub>
4.5–6.1) were seen in fecal samples collected 2–4 weeks after the onset of clinical illness. Fecal samples were frequently SARS-CoV RT-PCR positive beyond 40 days, and occasional sera still had SARS-CoV detected after 3 weeks of illness.</p>
</sec>
<sec><title>Conclusion</title>
<p>In the context of an extensive outbreak with major pressure on hospital resources, patient self-collected samples are an alternative to nasopharyngeal aspirates for laboratory confirmation of SARS-CoV infection.</p>
</sec>
</div>
</front>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Virol J</journal-id>
<journal-id journal-id-type="iso-abbrev">Virol. J</journal-id>
<journal-title-group><journal-title>Virology Journal</journal-title>
</journal-title-group>
<issn pub-type="epub">1743-422X</issn>
<publisher><publisher-name>BioMed Central</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">17386116</article-id>
<article-id pub-id-type="pmc">1851004</article-id>
<article-id pub-id-type="publisher-id">245</article-id>
<article-id pub-id-type="doi">10.1186/1743-422X-4-32</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research</subject>
</subj-group>
</article-categories>
<title-group><article-title>Using patient-collected clinical samples and sera to detect and quantify the severe acute respiratory syndrome coronavirus (SARS-CoV)</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>He</surname>
<given-names>Zhongping</given-names>
</name>
<address><email>zhongpinghe@yahoo.com</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
<xref ref-type="aff" rid="Aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zhuang</surname>
<given-names>Hui</given-names>
</name>
<address><email>zhangbmu@126.com</email>
</address>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zhao</surname>
<given-names>Chunhui</given-names>
</name>
<address><email>yabgc9329@sina.com</email>
</address>
<xref ref-type="aff" rid="Aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Dong</surname>
<given-names>Qingming</given-names>
</name>
<address><email>dqm3@sina.com</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Peng</surname>
<given-names>Guoai</given-names>
</name>
<address><email>pengguoai@yahoo.com.cn</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Dwyer</surname>
<given-names>Dominic E</given-names>
</name>
<address><email>dominic_dwyer@wmi.usyd.edu.au</email>
</address>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<aff id="Aff1"><label>1</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.413996.0</institution-id>
<institution>Beijing Ditan Hospital,</institution>
</institution-wrap>
Beijing, 100011 China</aff>
<aff id="Aff2"><label>2</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.24696.3f</institution-id>
<institution-id institution-id-type="ISNI">000000040369153X</institution-id>
<institution>Capital University of Medical Sciences Affiliated Beijing YouAn Hospital,</institution>
</institution-wrap>
Beijing, 100054 China</aff>
<aff id="Aff3"><label>3</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.11135.37</institution-id>
<institution-id institution-id-type="ISNI">0000000122569319</institution-id>
<institution>Department of Microbiology,</institution>
<institution>Peking University Health Science Center,</institution>
</institution-wrap>
Beijing, 100083 China</aff>
<aff id="Aff4"><label>4</label>
Centre for Infectious Diseases and Microbiology Laboratory Services, Institute of Clinical Pathology and Medical Research, Westmead, Australia</aff>
</contrib-group>
<pub-date pub-type="epub"><day>27</day>
<month>3</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>27</day>
<month>3</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="collection"><year>2007</year>
</pub-date>
<volume>4</volume>
<elocation-id>32</elocation-id>
<history><date date-type="received"><day>13</day>
<month>2</month>
<year>2006</year>
</date>
<date date-type="accepted"><day>27</day>
<month>3</month>
<year>2007</year>
</date>
</history>
<permissions><copyright-statement>© He et al; licensee BioMed Central Ltd. 2007</copyright-statement>
<license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p>
</license>
</permissions>
<abstract id="Abs1"><sec><title>Background</title>
<p>Severe acute respiratory syndrome (SARS) caused a large outbreak of pneumonia in Beijing, China, in 2003. Reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect and quantify SARS-CoV in 934 sera and self-collected throat washes and fecal samples from 271 patients with laboratory-confirmed SARS managed at a single institution.</p>
</sec>
<sec><title>Results</title>
<p>SARS-CoV detection rates in sera were highest in the first 9 days of illness, whereas detection was highest in throat washes 5–14 days after onset of symptoms. The highest SARS-CoV RT-PCR rates (70.4–86.3%) and viral loads (log<sub>10</sub>
4.5–6.1) were seen in fecal samples collected 2–4 weeks after the onset of clinical illness. Fecal samples were frequently SARS-CoV RT-PCR positive beyond 40 days, and occasional sera still had SARS-CoV detected after 3 weeks of illness.</p>
</sec>
<sec><title>Conclusion</title>
<p>In the context of an extensive outbreak with major pressure on hospital resources, patient self-collected samples are an alternative to nasopharyngeal aspirates for laboratory confirmation of SARS-CoV infection.</p>
</sec>
</abstract>
<kwd-group xml:lang="en"><title>Keywords</title>
<kwd>Fecal Sample</kwd>
<kwd>Reverse Transcriptase Polymerase Chain Reaction</kwd>
<kwd>Severe Acute Respiratory Syndrome</kwd>
<kwd>Severe Acute Respiratory Syndrome</kwd>
<kwd>Severe Acute Respiratory Syndrome Patient</kwd>
</kwd-group>
<custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2007</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>Australie</li>
<li>République populaire de Chine</li>
</country>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="He, Zhongping" sort="He, Zhongping" uniqKey="He Z" first="Zhongping" last="He">Zhongping He</name>
</noRegion>
<name sortKey="Dong, Qingming" sort="Dong, Qingming" uniqKey="Dong Q" first="Qingming" last="Dong">Qingming Dong</name>
<name sortKey="He, Zhongping" sort="He, Zhongping" uniqKey="He Z" first="Zhongping" last="He">Zhongping He</name>
<name sortKey="Peng, Guoai" sort="Peng, Guoai" uniqKey="Peng G" first="Guoai" last="Peng">Guoai Peng</name>
<name sortKey="Zhao, Chunhui" sort="Zhao, Chunhui" uniqKey="Zhao C" first="Chunhui" last="Zhao">Chunhui Zhao</name>
<name sortKey="Zhuang, Hui" sort="Zhuang, Hui" uniqKey="Zhuang H" first="Hui" last="Zhuang">Hui Zhuang</name>
</country>
<country name="Australie"><noRegion><name sortKey="Dwyer, Dominic E" sort="Dwyer, Dominic E" uniqKey="Dwyer D" first="Dominic E" last="Dwyer">Dominic E. Dwyer</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
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