Diagnostic performance of chest CT in screening patients with suspected COVID-19 infection in a Western population.
Identifieur interne : 000656 ( Main/Exploration ); précédent : 000655; suivant : 000657Diagnostic performance of chest CT in screening patients with suspected COVID-19 infection in a Western population.
Auteurs : Jasenko Krdzalic [Pays-Bas] ; Tom M H. De Jaegere [Pays-Bas] ; Robert M. Kwee [Pays-Bas]Source :
- The British journal of radiology [ 1748-880X ] ; 2020.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Betacoronavirus (MeSH), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (imagerie diagnostique), Mâle (MeSH), Pandémies (MeSH), Pneumopathie virale (imagerie diagnostique), Poumon (imagerie diagnostique), Radiographie thoracique (méthodes), Reproductibilité des résultats (MeSH), Sensibilité et spécificité (MeSH), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Tomodensitométrie (méthodes), Études prospectives (MeSH), Études rétrospectives (MeSH).
- MESH :
- imagerie diagnostique : Infections à coronavirus, Pneumopathie virale, Poumon.
- méthodes : Radiographie thoracique, Tomodensitométrie.
- Adulte, Adulte d'âge moyen, Betacoronavirus, Femelle, Humains, Mâle, Pandémies, Reproductibilité des résultats, Sensibilité et spécificité, Sujet âgé, Sujet âgé de 80 ans ou plus, Études prospectives, Études rétrospectives.
English descriptors
- KwdEn :
- Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (MeSH), Coronavirus Infections (diagnostic imaging), Female (MeSH), Humans (MeSH), Lung (diagnostic imaging), Male (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnostic imaging), Prospective Studies (MeSH), Radiography, Thoracic (methods), Reproducibility of Results (MeSH), Retrospective Studies (MeSH), Sensitivity and Specificity (MeSH), Tomography, X-Ray Computed (methods).
- MESH :
- diagnostic imaging : Coronavirus Infections, Lung, Pneumonia, Viral.
- methods : Radiography, Thoracic, Tomography, X-Ray Computed.
- Adult, Aged, Aged, 80 and over, Betacoronavirus, Female, Humans, Male, Middle Aged, Pandemics, Prospective Studies, Reproducibility of Results, Retrospective Studies, Sensitivity and Specificity.
Abstract
OBJECTIVE
To investigate the diagnostic performance of chest CT in screening patients suspected of Coronavirus disease 2019 (COVID-19) in a Western population.
METHODS
Consecutive patients who underwent chest CT because of clinical suspicion of COVID-19 were included. CT scans were prospectively evaluated by frontline general radiologists who were on duty at the time when the CT scan was performed and retrospectively assessed by a chest radiologist in an independent and blinded manner. Real-time reverse transcriptase-polymerase chain reaction was used as reference standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity and specificity of the frontline general radiologists were compared to those of the chest radiologist using the McNemar test.
RESULTS
56 patients were included. Sensitivity, specificity, PPV, and NPV for the frontline general radiologists were 89.3% [95% confidence interval (CI): 71.8%, 97.7%], 32.1% (95% CI: 15.9%, 52.4%), 56.8% (95% CI: 41.0%, 71.7%), and 75.0% (95% CI: 42.8%, 94.5%), respectively. Sensitivity, specificity, PPV, and NPV for the chest radiologist were 89.3% (95% CI: 71.8%, 97.7%), 75.0% (95% CI: 55.1%, 89.3%), 78.1% (95% CI: 60.0%, 90.7%), and 87.5% (95% CI: 67.6%, 97.3%), respectively. Sensitivity was not significantly different (
CONCLUSION
Chest CT interpreted by frontline general radiologists achieves insufficient screening performance. Although specificity of a chest radiologist appears to be significantly higher, sensitivity did not improve. A negative chest CT result does not exclude COVID-19.
ADVANCES IN KNOWLEDGE
Our study shows that chest CT interpreted by frontline general radiologists achieves insufficient diagnostic performance to use it as an independent screening tool for COVID-19. Although specificity of a chest radiologist appears to be significantly higher, sensitivity is still insufficiently high.
DOI: 10.1259/bjr.20200643
PubMed: 32808545
PubMed Central: PMC7465869
Affiliations:
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De Jaegere</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen</wicri:regionArea><wicri:noRegion>Heerlen/Sittard/Geleen</wicri:noRegion></affiliation></author><author><name sortKey="Kwee, Robert M" sort="Kwee, Robert M" uniqKey="Kwee R" first="Robert M" last="Kwee">Robert M. Kwee</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen</wicri:regionArea><wicri:noRegion>Heerlen/Sittard/Geleen</wicri:noRegion></affiliation></author></analytic><series><title level="j">The British journal of radiology</title><idno type="eISSN">1748-880X</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term><term>Aged (MeSH)</term><term>Aged, 80 and over (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>Coronavirus Infections (diagnostic imaging)</term><term>Female (MeSH)</term><term>Humans (MeSH)</term><term>Lung (diagnostic imaging)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (diagnostic imaging)</term><term>Prospective Studies (MeSH)</term><term>Radiography, Thoracic (methods)</term><term>Reproducibility of Results (MeSH)</term><term>Retrospective Studies (MeSH)</term><term>Sensitivity and Specificity (MeSH)</term><term>Tomography, X-Ray Computed (methods)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (imagerie diagnostique)</term><term>Mâle (MeSH)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (imagerie diagnostique)</term><term>Poumon (imagerie diagnostique)</term><term>Radiographie thoracique (méthodes)</term><term>Reproductibilité des résultats (MeSH)</term><term>Sensibilité et spécificité (MeSH)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term><term>Tomodensitométrie (méthodes)</term><term>Études prospectives (MeSH)</term><term>Études rétrospectives (MeSH)</term></keywords><keywords scheme="MESH" qualifier="diagnostic imaging" xml:lang="en"><term>Coronavirus Infections</term><term>Lung</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="imagerie diagnostique" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term><term>Poumon</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Radiography, Thoracic</term><term>Tomography, X-Ray Computed</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Radiographie thoracique</term><term>Tomodensitométrie</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Aged</term><term>Aged, 80 and over</term><term>Betacoronavirus</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Pandemics</term><term>Prospective Studies</term><term>Reproducibility of Results</term><term>Retrospective Studies</term><term>Sensitivity and Specificity</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Betacoronavirus</term><term>Femelle</term><term>Humains</term><term>Mâle</term><term>Pandémies</term><term>Reproductibilité des résultats</term><term>Sensibilité et spécificité</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Études prospectives</term><term>Études rétrospectives</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b></p><p>To investigate the diagnostic performance of chest CT in screening patients suspected of Coronavirus disease 2019 (COVID-19) in a Western population.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Consecutive patients who underwent chest CT because of clinical suspicion of COVID-19 were included. CT scans were prospectively evaluated by frontline general radiologists who were on duty at the time when the CT scan was performed and retrospectively assessed by a chest radiologist in an independent and blinded manner. Real-time reverse transcriptase-polymerase chain reaction was used as reference standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity and specificity of the frontline general radiologists were compared to those of the chest radiologist using the McNemar test.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>56 patients were included. Sensitivity, specificity, PPV, and NPV for the frontline general radiologists were 89.3% [95% confidence interval (CI): 71.8%, 97.7%], 32.1% (95% CI: 15.9%, 52.4%), 56.8% (95% CI: 41.0%, 71.7%), and 75.0% (95% CI: 42.8%, 94.5%), respectively. Sensitivity, specificity, PPV, and NPV for the chest radiologist were 89.3% (95% CI: 71.8%, 97.7%), 75.0% (95% CI: 55.1%, 89.3%), 78.1% (95% CI: 60.0%, 90.7%), and 87.5% (95% CI: 67.6%, 97.3%), respectively. Sensitivity was not significantly different (</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>Chest CT interpreted by frontline general radiologists achieves insufficient screening performance. Although specificity of a chest radiologist appears to be significantly higher, sensitivity did not improve. A negative chest CT result does not exclude COVID-19.</p></div><div type="abstract" xml:lang="en"><p><b>ADVANCES IN KNOWLEDGE</b></p><p>Our study shows that chest CT interpreted by frontline general radiologists achieves insufficient diagnostic performance to use it as an independent screening tool for COVID-19. Although specificity of a chest radiologist appears to be significantly higher, sensitivity is still insufficiently high.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32808545</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>01</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1748-880X</ISSN><JournalIssue CitedMedium="Internet"><Volume>93</Volume><Issue>1113</Issue><PubDate><Year>2020</Year><Month>Sep</Month><Day>01</Day></PubDate></JournalIssue><Title>The British journal of radiology</Title><ISOAbbreviation>Br J Radiol</ISOAbbreviation></Journal><ArticleTitle>Diagnostic performance of chest CT in screening patients with suspected COVID-19 infection in a Western population.</ArticleTitle><Pagination><MedlinePgn>20200643</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1259/bjr.20200643</ELocationID><Abstract><AbstractText Label="OBJECTIVE" NlmCategory="UNASSIGNED">To investigate the diagnostic performance of chest CT in screening patients suspected of Coronavirus disease 2019 (COVID-19) in a Western population.</AbstractText><AbstractText Label="METHODS" NlmCategory="UNASSIGNED">Consecutive patients who underwent chest CT because of clinical suspicion of COVID-19 were included. CT scans were prospectively evaluated by frontline general radiologists who were on duty at the time when the CT scan was performed and retrospectively assessed by a chest radiologist in an independent and blinded manner. Real-time reverse transcriptase-polymerase chain reaction was used as reference standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity and specificity of the frontline general radiologists were compared to those of the chest radiologist using the McNemar test.</AbstractText><AbstractText Label="RESULTS" NlmCategory="UNASSIGNED">56 patients were included. Sensitivity, specificity, PPV, and NPV for the frontline general radiologists were 89.3% [95% confidence interval (CI): 71.8%, 97.7%], 32.1% (95% CI: 15.9%, 52.4%), 56.8% (95% CI: 41.0%, 71.7%), and 75.0% (95% CI: 42.8%, 94.5%), respectively. Sensitivity, specificity, PPV, and NPV for the chest radiologist were 89.3% (95% CI: 71.8%, 97.7%), 75.0% (95% CI: 55.1%, 89.3%), 78.1% (95% CI: 60.0%, 90.7%), and 87.5% (95% CI: 67.6%, 97.3%), respectively. Sensitivity was not significantly different (<i>p</i> = 1.000), but specificity was significantly higher for the chest radiologist (<i>p</i> = 0.001).</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="UNASSIGNED">Chest CT interpreted by frontline general radiologists achieves insufficient screening performance. Although specificity of a chest radiologist appears to be significantly higher, sensitivity did not improve. A negative chest CT result does not exclude COVID-19.</AbstractText><AbstractText Label="ADVANCES IN KNOWLEDGE" NlmCategory="UNASSIGNED">Our study shows that chest CT interpreted by frontline general radiologists achieves insufficient diagnostic performance to use it as an independent screening tool for COVID-19. Although specificity of a chest radiologist appears to be significantly higher, sensitivity is still insufficiently high.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Krdzalic</LastName><ForeName>Jasenko</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>de Jaegere</LastName><ForeName>Tom M H</ForeName><Initials>TMH</Initials><AffiliationInfo><Affiliation>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kwee</LastName><ForeName>Robert M</ForeName><Initials>RM</Initials><AffiliationInfo><Affiliation>Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>08</Month><Day>18</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Br J Radiol</MedlineTA><NlmUniqueID>0373125</NlmUniqueID><ISSNLinking>0007-1285</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName><SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName></SupplMeshList><CitationSubset>AIM</CitationSubset><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="Y">Betacoronavirus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000000981" MajorTopicYN="Y">diagnostic imaging</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008168" MajorTopicYN="N">Lung</DescriptorName><QualifierName UI="Q000000981" MajorTopicYN="N">diagnostic imaging</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000000981" MajorTopicYN="Y">diagnostic imaging</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011446" MajorTopicYN="N">Prospective Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013902" MajorTopicYN="N">Radiography, Thoracic</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</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="D012680" MajorTopicYN="N">Sensitivity and Specificity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014057" MajorTopicYN="N">Tomography, X-Ray Computed</DescriptorName><QualifierName 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De Jaegere</name><name sortKey="Kwee, Robert M" sort="Kwee, Robert M" uniqKey="Kwee R" first="Robert M" last="Kwee">Robert M. Kwee</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:32808545" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a CovidSeniorV1
| This area was generated with Dilib version V0.6.37. |  |