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Diagnostic value of combined nucleic acid and antibody detection in suspected COVID-19 cases.

Identifieur interne : 000655 ( Main/Exploration ); précédent : 000654; suivant : 000656

Diagnostic value of combined nucleic acid and antibody detection in suspected COVID-19 cases.

Auteurs : H. Zeng [République populaire de Chine] ; S. Deng [République populaire de Chine] ; Z. Zhou [République populaire de Chine] ; X. Qiu [République populaire de Chine] ; X. Jia [République populaire de Chine] ; Z. Li [République populaire de Chine] ; J. Wang [République populaire de Chine] ; H. Duan [République populaire de Chine] ; L. Tu [République populaire de Chine] ; J. Wang [République populaire de Chine]

Source :

RBID : pubmed:32731151

Descripteurs français

English descriptors

Abstract

OBJECTIVES

Nucleic acid testing is the gold standard method for the diagnosis of coronavirus disease 2019 (COVID-19); however, large numbers of false-negative results have been reported. In this study, nucleic acid detection and antibody detection (IgG and IgM) were combined to improve the testing accuracy of patients with suspected COVID-19.

STUDY DESIGN

The positive rate of nucleic acid detection and antibody detection (IgG and IgM) were compared in suspected COVID-19 patients.

METHODS

A total of 71 patients with suspected COVID-19 were selected to participate in this study, which included a retrospective analysis of clinical features, imaging examination, laboratory biochemical examination and nucleic acid detection and specific antibody (IgM and IgG) detection.

RESULTS

The majority of participants with suspected COVID-19 presented with fever (67.61%) and cough (54.93%), and the imaging results showed multiple small patches and ground-glass opacity in both lungs, with less common infiltration and consolidation opacity (23.94%). Routine blood tests were mostly normal (69.01%), although only a few patients had lymphopenia (4.23%) or leucopenia (12.68%). There was no statistical difference in the double-positive rate between nucleic acid detection (46.48%) and specific antibody (IgG and IgM) detection (42.25%) (P = 0.612), both of which were also poorly consistent with each other (kappa = 0.231). The positive rate of combined nucleic acid detection and antibody detection (63.38%) was significantly increased, compared with that of nucleic acid detection (46.48%) and that of specific antibody (IgG and IgM) detection (42.25%), and the differences were statistically significant (P = 0.043 and P = 0.012, respectively).

CONCLUSIONS

Nucleic acid detection and specific antibody (IgG and IgM) detection had similar positive rates, and their combination could improve the positive rate of COVID-19 detection, which is of great significance for diagnosis and epidemic control.


DOI: 10.1016/j.puhe.2020.07.011
PubMed: 32731151
PubMed Central: PMC7351380


Affiliations:


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Le document en format XML

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<term>Adolescent (MeSH)</term>
<term>Adult (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Antibodies, Viral (isolation & purification)</term>
<term>Betacoronavirus (genetics)</term>
<term>Betacoronavirus (immunology)</term>
<term>Child (MeSH)</term>
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<term>Coronavirus Infections (epidemiology)</term>
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<term>Immunoglobulin M (isolation & purification)</term>
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<term>Middle Aged (MeSH)</term>
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<term>Pandemics (MeSH)</term>
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<term>Pneumonia, Viral (epidemiology)</term>
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<term>Retrospective Studies (MeSH)</term>
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<term>Acides nucléiques (isolement et purification)</term>
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<term>Betacoronavirus (génétique)</term>
<term>Betacoronavirus (immunologie)</term>
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<term>Humains (MeSH)</term>
<term>Immunoglobuline G (isolement et purification)</term>
<term>Immunoglobuline M (isolement et purification)</term>
<term>Infections à coronavirus (diagnostic)</term>
<term>Infections à coronavirus (épidémiologie)</term>
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<term>Pneumopathie virale (diagnostic)</term>
<term>Pneumopathie virale (épidémiologie)</term>
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<term>Nucleic Acids</term>
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<term>Pneumonia, Viral</term>
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<term>Pneumopathie virale</term>
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<term>Pneumonia, Viral</term>
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<term>Anticorps antiviraux</term>
<term>Immunoglobuline G</term>
<term>Immunoglobuline M</term>
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<term>Pneumopathie virale</term>
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<term>Adulte</term>
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<p>
<b>OBJECTIVES</b>
</p>
<p>Nucleic acid testing is the gold standard method for the diagnosis of coronavirus disease 2019 (COVID-19); however, large numbers of false-negative results have been reported. In this study, nucleic acid detection and antibody detection (IgG and IgM) were combined to improve the testing accuracy of patients with suspected COVID-19.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>STUDY DESIGN</b>
</p>
<p>The positive rate of nucleic acid detection and antibody detection (IgG and IgM) were compared in suspected COVID-19 patients.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>METHODS</b>
</p>
<p>A total of 71 patients with suspected COVID-19 were selected to participate in this study, which included a retrospective analysis of clinical features, imaging examination, laboratory biochemical examination and nucleic acid detection and specific antibody (IgM and IgG) detection.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>RESULTS</b>
</p>
<p>The majority of participants with suspected COVID-19 presented with fever (67.61%) and cough (54.93%), and the imaging results showed multiple small patches and ground-glass opacity in both lungs, with less common infiltration and consolidation opacity (23.94%). Routine blood tests were mostly normal (69.01%), although only a few patients had lymphopenia (4.23%) or leucopenia (12.68%). There was no statistical difference in the double-positive rate between nucleic acid detection (46.48%) and specific antibody (IgG and IgM) detection (42.25%) (P = 0.612), both of which were also poorly consistent with each other (kappa = 0.231). The positive rate of combined nucleic acid detection and antibody detection (63.38%) was significantly increased, compared with that of nucleic acid detection (46.48%) and that of specific antibody (IgG and IgM) detection (42.25%), and the differences were statistically significant (P = 0.043 and P = 0.012, respectively).</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>CONCLUSIONS</b>
</p>
<p>Nucleic acid detection and specific antibody (IgG and IgM) detection had similar positive rates, and their combination could improve the positive rate of COVID-19 detection, which is of great significance for diagnosis and epidemic control.</p>
</div>
</front>
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<Journal>
<ISSN IssnType="Electronic">1476-5616</ISSN>
<JournalIssue CitedMedium="Internet">
<Volume>186</Volume>
<PubDate>
<Year>2020</Year>
<Month>Sep</Month>
</PubDate>
</JournalIssue>
<Title>Public health</Title>
<ISOAbbreviation>Public Health</ISOAbbreviation>
</Journal>
<ArticleTitle>Diagnostic value of combined nucleic acid and antibody detection in suspected COVID-19 cases.</ArticleTitle>
<Pagination>
<MedlinePgn>1-5</MedlinePgn>
</Pagination>
<ELocationID EIdType="pii" ValidYN="Y">S0033-3506(20)30306-1</ELocationID>
<ELocationID EIdType="doi" ValidYN="Y">10.1016/j.puhe.2020.07.011</ELocationID>
<Abstract>
<AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">Nucleic acid testing is the gold standard method for the diagnosis of coronavirus disease 2019 (COVID-19); however, large numbers of false-negative results have been reported. In this study, nucleic acid detection and antibody detection (IgG and IgM) were combined to improve the testing accuracy of patients with suspected COVID-19.</AbstractText>
<AbstractText Label="STUDY DESIGN" NlmCategory="METHODS">The positive rate of nucleic acid detection and antibody detection (IgG and IgM) were compared in suspected COVID-19 patients.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">A total of 71 patients with suspected COVID-19 were selected to participate in this study, which included a retrospective analysis of clinical features, imaging examination, laboratory biochemical examination and nucleic acid detection and specific antibody (IgM and IgG) detection.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">The majority of participants with suspected COVID-19 presented with fever (67.61%) and cough (54.93%), and the imaging results showed multiple small patches and ground-glass opacity in both lungs, with less common infiltration and consolidation opacity (23.94%). Routine blood tests were mostly normal (69.01%), although only a few patients had lymphopenia (4.23%) or leucopenia (12.68%). There was no statistical difference in the double-positive rate between nucleic acid detection (46.48%) and specific antibody (IgG and IgM) detection (42.25%) (P = 0.612), both of which were also poorly consistent with each other (kappa = 0.231). The positive rate of combined nucleic acid detection and antibody detection (63.38%) was significantly increased, compared with that of nucleic acid detection (46.48%) and that of specific antibody (IgG and IgM) detection (42.25%), and the differences were statistically significant (P = 0.043 and P = 0.012, respectively).</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Nucleic acid detection and specific antibody (IgG and IgM) detection had similar positive rates, and their combination could improve the positive rate of COVID-19 detection, which is of great significance for diagnosis and epidemic control.</AbstractText>
<CopyrightInformation>Copyright © 2020. Published by Elsevier Ltd.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Zeng</LastName>
<ForeName>H</ForeName>
<Initials>H</Initials>
<AffiliationInfo>
<Affiliation>Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Deng</LastName>
<ForeName>S</ForeName>
<Initials>S</Initials>
<AffiliationInfo>
<Affiliation>Scientific Research Platform, The Second Clinical Medical College, Guangdong Medical University, Dongguan 523808, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Zhou</LastName>
<ForeName>Z</ForeName>
<Initials>Z</Initials>
<AffiliationInfo>
<Affiliation>Department of Radiology, Shenzhen People's Hospital, Shenzhen 518020, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Qiu</LastName>
<ForeName>X</ForeName>
<Initials>X</Initials>
<AffiliationInfo>
<Affiliation>Special Clinic Department, Southern University of Science and Technology Hospital, Shenzhen 518052, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Jia</LastName>
<ForeName>X</ForeName>
<Initials>X</Initials>
<AffiliationInfo>
<Affiliation>Department of Clinical Laboratory Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Li</LastName>
<ForeName>Z</ForeName>
<Initials>Z</Initials>
<AffiliationInfo>
<Affiliation>Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Wang</LastName>
<ForeName>J</ForeName>
<Initials>J</Initials>
<AffiliationInfo>
<Affiliation>Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Duan</LastName>
<ForeName>H</ForeName>
<Initials>H</Initials>
<AffiliationInfo>
<Affiliation>Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Tu</LastName>
<ForeName>L</ForeName>
<Initials>L</Initials>
<AffiliationInfo>
<Affiliation>Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Wang</LastName>
<ForeName>J</ForeName>
<Initials>J</Initials>
<AffiliationInfo>
<Affiliation>Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518110, China. Electronic address: wangjunli0110@163.com.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList>
<PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic">
<Year>2020</Year>
<Month>07</Month>
<Day>10</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo>
<Country>Netherlands</Country>
<MedlineTA>Public Health</MedlineTA>
<NlmUniqueID>0376507</NlmUniqueID>
<ISSNLinking>0033-3506</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList>
<Chemical>
<RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D000914">Antibodies, Viral</NameOfSubstance>
</Chemical>
<Chemical>
<RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D007074">Immunoglobulin G</NameOfSubstance>
</Chemical>
<Chemical>
<RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D007075">Immunoglobulin M</NameOfSubstance>
</Chemical>
<Chemical>
<RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D009696">Nucleic Acids</NameOfSubstance>
</Chemical>
</ChemicalList>
<SupplMeshList>
<SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName>
<SupplMeshName Type="Protocol" UI="C000657964">COVID-19 diagnostic testing</SupplMeshName>
<SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName>
</SupplMeshList>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList>
<MeshHeading>
<DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000914" MajorTopicYN="N">Antibodies, Viral</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D002675" MajorTopicYN="N">Child, Preschool</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D019411" MajorTopicYN="N">Clinical Laboratory Techniques</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D007074" MajorTopicYN="N">Immunoglobulin G</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D007075" MajorTopicYN="N">Immunoglobulin M</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D009696" MajorTopicYN="N">Nucleic Acids</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM">
<Keyword MajorTopicYN="N">IgG and IgM antibody detection</Keyword>
<Keyword MajorTopicYN="N">Novel coronavirus infection</Keyword>
<Keyword MajorTopicYN="N">Nucleic acid detection</Keyword>
<Keyword MajorTopicYN="N">Suspected cases</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData>
<History>
<PubMedPubDate PubStatus="received">
<Year>2020</Year>
<Month>04</Month>
<Day>29</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised">
<Year>2020</Year>
<Month>06</Month>
<Day>30</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted">
<Year>2020</Year>
<Month>07</Month>
<Day>06</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed">
<Year>2020</Year>
<Month>7</Month>
<Day>31</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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<PubMedPubDate PubStatus="medline">
<Year>2020</Year>
<Month>10</Month>
<Day>7</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez">
<Year>2020</Year>
<Month>7</Month>
<Day>31</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList>
<ArticleId IdType="pubmed">32731151</ArticleId>
<ArticleId IdType="pii">S0033-3506(20)30306-1</ArticleId>
<ArticleId IdType="doi">10.1016/j.puhe.2020.07.011</ArticleId>
<ArticleId IdType="pmc">PMC7351380</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations>
<list>
<country>
<li>République populaire de Chine</li>
</country>
<region>
<li>Guangdong</li>
</region>
<settlement>
<li>Shenzhen</li>
</settlement>
</list>
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<country name="République populaire de Chine">
<region name="Guangdong">
<name sortKey="Zeng, H" sort="Zeng, H" uniqKey="Zeng H" first="H" last="Zeng">H. Zeng</name>
</region>
<name sortKey="Deng, S" sort="Deng, S" uniqKey="Deng S" first="S" last="Deng">S. Deng</name>
<name sortKey="Duan, H" sort="Duan, H" uniqKey="Duan H" first="H" last="Duan">H. Duan</name>
<name sortKey="Jia, X" sort="Jia, X" uniqKey="Jia X" first="X" last="Jia">X. Jia</name>
<name sortKey="Li, Z" sort="Li, Z" uniqKey="Li Z" first="Z" last="Li">Z. Li</name>
<name sortKey="Qiu, X" sort="Qiu, X" uniqKey="Qiu X" first="X" last="Qiu">X. Qiu</name>
<name sortKey="Tu, L" sort="Tu, L" uniqKey="Tu L" first="L" last="Tu">L. Tu</name>
<name sortKey="Wang, J" sort="Wang, J" uniqKey="Wang J" first="J" last="Wang">J. Wang</name>
<name sortKey="Wang, J" sort="Wang, J" uniqKey="Wang J" first="J" last="Wang">J. Wang</name>
<name sortKey="Zhou, Z" sort="Zhou, Z" uniqKey="Zhou Z" first="Z" last="Zhou">Z. Zhou</name>
</country>
</tree>
</affiliations>
</record>

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