COVID-19 pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability
Objectives To assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak. Methods From March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an i...
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| Veröffentlicht in: | European radiology 2021-04, Vol.31 (4), p.1969-1977 |
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| container_end_page | 1977 |
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| container_issue | 4 |
| container_start_page | 1969 |
| container_title | European radiology |
| container_volume | 31 |
| creator | Brun, Anne Laure Gence-Breney, Alexia Trichereau, Julie Ballester, Marie Christine Vasse, Marc Chabi, Marie Laure Mellot, François Grenier, Philippe A. |
| description | Objectives
To assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak.
Methods
From March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an intermediate clinical probability of COVID-19 pneumonia underwent a chest CT scan. Two independent chest radiologists blinded to clinical information and RT-PCR results retrospectively reviewed and classified images on a 1–5 confidence level scale for COVID-19 pneumonia. Agreements between radiologists were assessed with kappa statistics. Diagnostic accuracy of chest CT compared with RT-PCR assay and patient outcomes was measured using receiver operating characteristics (ROC). Positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 pneumonia were calculated.
Results
Inter-observer agreement for highly probable (kappa: 0.83 [
p
|
| doi_str_mv | 10.1007/s00330-020-07346-y |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7532930</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2448638616</sourcerecordid><originalsourceid>FETCH-LOGICAL-c508t-4fdac1d31134756a23b9eb4e293ca520005004f30b5d546305524bec0cb1ab533</originalsourceid><addsrcrecordid>eNp9UUtv1DAQthCILgt_gAOyxAUOgXFs58EBqVoerbRSL4Wr5XidjUvWDnbSKv--U1IK7aEHy9LM95iZj5DXDD4wgPJjAuAcMsjxlVwU2fyErJjgecagEk_JCmpeZWVdiyPyIqULAKiZKJ-TI6QxVpXlivzanP08_ZKxmg7eTofgnf5EO7fv6M7pvQ9pdIZqY6aozUxDS01n00g359R5OujRWT8meuXGDgujjQeLvNFS0zvvjO7pEEOjG9e7cX5JnrW6T_bV7b8mP759Pd-cZNuz76eb421mJFRjJtqdNmzHGeOilIXOeVPbRti85kbLHLeQAKLl0MidFAUHKXPRWAOmYbqRnK_J50V3mBqcx-CIUfdqiO6g46yCdup-x7tO7cOlKiVHE0CB94tA94B2crxVNzUQopZlXVwyxL67NYvh94S3UQeXjO177W2YksqFqApeFaxA6NsH0IswRY-nULkEDgjE9NYkX1AmhpSibe8mYKBucldL7gpzV39yVzOS3vy_8h3lb9AI4AsgYcvvbfzn_YjsNcB1uGg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2503048614</pqid></control><display><type>article</type><title>COVID-19 pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Brun, Anne Laure ; Gence-Breney, Alexia ; Trichereau, Julie ; Ballester, Marie Christine ; Vasse, Marc ; Chabi, Marie Laure ; Mellot, François ; Grenier, Philippe A.</creator><creatorcontrib>Brun, Anne Laure ; Gence-Breney, Alexia ; Trichereau, Julie ; Ballester, Marie Christine ; Vasse, Marc ; Chabi, Marie Laure ; Mellot, François ; Grenier, Philippe A.</creatorcontrib><description>Objectives
To assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak.
Methods
From March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an intermediate clinical probability of COVID-19 pneumonia underwent a chest CT scan. Two independent chest radiologists blinded to clinical information and RT-PCR results retrospectively reviewed and classified images on a 1–5 confidence level scale for COVID-19 pneumonia. Agreements between radiologists were assessed with kappa statistics. Diagnostic accuracy of chest CT compared with RT-PCR assay and patient outcomes was measured using receiver operating characteristics (ROC). Positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 pneumonia were calculated.
Results
Inter-observer agreement for highly probable (kappa: 0.83 [
p
< .001]) and highly probable or probable (kappa: 0.82 [
p
< .001]) diagnosis of COVID-19 pneumonia was very good. RT-PCR tests performed in 307 patients were positive in 174 and negative in 133. The areas under the curve (AUC) were 0.94 and 0.92 respectively. With a disease prevalence of 61.2%, PPV were 95.9% and 94.3%, and NPV 84.4% and 77.1%.
Conclusion
During acute COVID-19 outbreak, chest CT scan may be used for triage of patients with intermediate clinical probability with very good inter-observer agreements and diagnostic accuracy.
Key Points
• Concordances between two chest radiologists to diagnose or exclude a COVID-19 pneumonia in 319 consecutive patients with intermediate clinical probability were very good (kappa: 0.82; p < .001).
• When compared with RT-PCR results and patient outcomes, the diagnostic accuracy of CT to identify COVID-19 pneumonia was high for both radiologists (AUC: 0.94 and 0.92).
• With a disease prevalence of 61.2% in the studied population, the positive predictive values of CT for diagnosing COVID-19 pneumonia were 95.9% and 94.3% with negative predictive values of 84.4% and 77.1%.</description><identifier>ISSN: 0938-7994</identifier><identifier>ISSN: 1432-1084</identifier><identifier>EISSN: 1432-1084</identifier><identifier>DOI: 10.1007/s00330-020-07346-y</identifier><identifier>PMID: 33011877</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Accuracy ; Chest ; Clinical outcomes ; Computed tomography ; Confidence intervals ; Coronaviruses ; COVID-19 ; Diagnostic Radiology ; Diagnostic systems ; Hematology ; Human health and pathology ; Humans ; Imaging ; Internal Medicine ; Interventional Radiology ; Life Sciences ; Medical diagnosis ; Medical imaging ; Medicine ; Medicine & Public Health ; Middle Aged ; Neuroradiology ; Outbreaks ; Patients ; Pneumonia ; Polymerase chain reaction ; Population studies ; Probability ; Radiology ; Retrospective Studies ; SARS-CoV-2 ; Statistical analysis ; Tomography, X-Ray Computed ; Ultrasound ; Viral diseases</subject><ispartof>European radiology, 2021-04, Vol.31 (4), p.1969-1977</ispartof><rights>European Society of Radiology 2020</rights><rights>European Society of Radiology 2020.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c508t-4fdac1d31134756a23b9eb4e293ca520005004f30b5d546305524bec0cb1ab533</citedby><cites>FETCH-LOGICAL-c508t-4fdac1d31134756a23b9eb4e293ca520005004f30b5d546305524bec0cb1ab533</cites><orcidid>0000-0002-4447-7850</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00330-020-07346-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00330-020-07346-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,780,784,885,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33011877$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-04495796$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Brun, Anne Laure</creatorcontrib><creatorcontrib>Gence-Breney, Alexia</creatorcontrib><creatorcontrib>Trichereau, Julie</creatorcontrib><creatorcontrib>Ballester, Marie Christine</creatorcontrib><creatorcontrib>Vasse, Marc</creatorcontrib><creatorcontrib>Chabi, Marie Laure</creatorcontrib><creatorcontrib>Mellot, François</creatorcontrib><creatorcontrib>Grenier, Philippe A.</creatorcontrib><title>COVID-19 pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability</title><title>European radiology</title><addtitle>Eur Radiol</addtitle><addtitle>Eur Radiol</addtitle><description>Objectives
To assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak.
Methods
From March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an intermediate clinical probability of COVID-19 pneumonia underwent a chest CT scan. Two independent chest radiologists blinded to clinical information and RT-PCR results retrospectively reviewed and classified images on a 1–5 confidence level scale for COVID-19 pneumonia. Agreements between radiologists were assessed with kappa statistics. Diagnostic accuracy of chest CT compared with RT-PCR assay and patient outcomes was measured using receiver operating characteristics (ROC). Positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 pneumonia were calculated.
Results
Inter-observer agreement for highly probable (kappa: 0.83 [
p
< .001]) and highly probable or probable (kappa: 0.82 [
p
< .001]) diagnosis of COVID-19 pneumonia was very good. RT-PCR tests performed in 307 patients were positive in 174 and negative in 133. The areas under the curve (AUC) were 0.94 and 0.92 respectively. With a disease prevalence of 61.2%, PPV were 95.9% and 94.3%, and NPV 84.4% and 77.1%.
Conclusion
During acute COVID-19 outbreak, chest CT scan may be used for triage of patients with intermediate clinical probability with very good inter-observer agreements and diagnostic accuracy.
Key Points
• Concordances between two chest radiologists to diagnose or exclude a COVID-19 pneumonia in 319 consecutive patients with intermediate clinical probability were very good (kappa: 0.82; p < .001).
• When compared with RT-PCR results and patient outcomes, the diagnostic accuracy of CT to identify COVID-19 pneumonia was high for both radiologists (AUC: 0.94 and 0.92).
• With a disease prevalence of 61.2% in the studied population, the positive predictive values of CT for diagnosing COVID-19 pneumonia were 95.9% and 94.3% with negative predictive values of 84.4% and 77.1%.</description><subject>Accuracy</subject><subject>Chest</subject><subject>Clinical outcomes</subject><subject>Computed tomography</subject><subject>Confidence intervals</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Diagnostic Radiology</subject><subject>Diagnostic systems</subject><subject>Hematology</subject><subject>Human health and pathology</subject><subject>Humans</subject><subject>Imaging</subject><subject>Internal Medicine</subject><subject>Interventional Radiology</subject><subject>Life Sciences</subject><subject>Medical diagnosis</subject><subject>Medical imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Neuroradiology</subject><subject>Outbreaks</subject><subject>Patients</subject><subject>Pneumonia</subject><subject>Polymerase chain reaction</subject><subject>Population studies</subject><subject>Probability</subject><subject>Radiology</subject><subject>Retrospective Studies</subject><subject>SARS-CoV-2</subject><subject>Statistical analysis</subject><subject>Tomography, X-Ray Computed</subject><subject>Ultrasound</subject><subject>Viral diseases</subject><issn>0938-7994</issn><issn>1432-1084</issn><issn>1432-1084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9UUtv1DAQthCILgt_gAOyxAUOgXFs58EBqVoerbRSL4Wr5XidjUvWDnbSKv--U1IK7aEHy9LM95iZj5DXDD4wgPJjAuAcMsjxlVwU2fyErJjgecagEk_JCmpeZWVdiyPyIqULAKiZKJ-TI6QxVpXlivzanP08_ZKxmg7eTofgnf5EO7fv6M7pvQ9pdIZqY6aozUxDS01n00g359R5OujRWT8meuXGDgujjQeLvNFS0zvvjO7pEEOjG9e7cX5JnrW6T_bV7b8mP759Pd-cZNuz76eb421mJFRjJtqdNmzHGeOilIXOeVPbRti85kbLHLeQAKLl0MidFAUHKXPRWAOmYbqRnK_J50V3mBqcx-CIUfdqiO6g46yCdup-x7tO7cOlKiVHE0CB94tA94B2crxVNzUQopZlXVwyxL67NYvh94S3UQeXjO177W2YksqFqApeFaxA6NsH0IswRY-nULkEDgjE9NYkX1AmhpSibe8mYKBucldL7gpzV39yVzOS3vy_8h3lb9AI4AsgYcvvbfzn_YjsNcB1uGg</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Brun, Anne Laure</creator><creator>Gence-Breney, Alexia</creator><creator>Trichereau, Julie</creator><creator>Ballester, Marie Christine</creator><creator>Vasse, Marc</creator><creator>Chabi, Marie Laure</creator><creator>Mellot, François</creator><creator>Grenier, Philippe A.</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><general>Springer 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pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability</title><author>Brun, Anne Laure ; Gence-Breney, Alexia ; Trichereau, Julie ; Ballester, Marie Christine ; Vasse, Marc ; Chabi, Marie Laure ; Mellot, François ; Grenier, Philippe A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c508t-4fdac1d31134756a23b9eb4e293ca520005004f30b5d546305524bec0cb1ab533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Chest</topic><topic>Clinical outcomes</topic><topic>Computed tomography</topic><topic>Confidence intervals</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Diagnostic Radiology</topic><topic>Diagnostic systems</topic><topic>Hematology</topic><topic>Human health and pathology</topic><topic>Humans</topic><topic>Imaging</topic><topic>Internal Medicine</topic><topic>Interventional Radiology</topic><topic>Life Sciences</topic><topic>Medical diagnosis</topic><topic>Medical imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Neuroradiology</topic><topic>Outbreaks</topic><topic>Patients</topic><topic>Pneumonia</topic><topic>Polymerase chain reaction</topic><topic>Population studies</topic><topic>Probability</topic><topic>Radiology</topic><topic>Retrospective Studies</topic><topic>SARS-CoV-2</topic><topic>Statistical analysis</topic><topic>Tomography, X-Ray Computed</topic><topic>Ultrasound</topic><topic>Viral diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Brun, Anne Laure</creatorcontrib><creatorcontrib>Gence-Breney, Alexia</creatorcontrib><creatorcontrib>Trichereau, Julie</creatorcontrib><creatorcontrib>Ballester, Marie Christine</creatorcontrib><creatorcontrib>Vasse, Marc</creatorcontrib><creatorcontrib>Chabi, Marie Laure</creatorcontrib><creatorcontrib>Mellot, François</creatorcontrib><creatorcontrib>Grenier, Philippe A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium 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Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>European radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Brun, Anne Laure</au><au>Gence-Breney, Alexia</au><au>Trichereau, Julie</au><au>Ballester, Marie Christine</au><au>Vasse, Marc</au><au>Chabi, Marie Laure</au><au>Mellot, François</au><au>Grenier, Philippe A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>COVID-19 pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability</atitle><jtitle>European radiology</jtitle><stitle>Eur Radiol</stitle><addtitle>Eur Radiol</addtitle><date>2021-04-01</date><risdate>2021</risdate><volume>31</volume><issue>4</issue><spage>1969</spage><epage>1977</epage><pages>1969-1977</pages><issn>0938-7994</issn><issn>1432-1084</issn><eissn>1432-1084</eissn><abstract>Objectives
To assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak.
Methods
From March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an intermediate clinical probability of COVID-19 pneumonia underwent a chest CT scan. Two independent chest radiologists blinded to clinical information and RT-PCR results retrospectively reviewed and classified images on a 1–5 confidence level scale for COVID-19 pneumonia. Agreements between radiologists were assessed with kappa statistics. Diagnostic accuracy of chest CT compared with RT-PCR assay and patient outcomes was measured using receiver operating characteristics (ROC). Positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 pneumonia were calculated.
Results
Inter-observer agreement for highly probable (kappa: 0.83 [
p
< .001]) and highly probable or probable (kappa: 0.82 [
p
< .001]) diagnosis of COVID-19 pneumonia was very good. RT-PCR tests performed in 307 patients were positive in 174 and negative in 133. The areas under the curve (AUC) were 0.94 and 0.92 respectively. With a disease prevalence of 61.2%, PPV were 95.9% and 94.3%, and NPV 84.4% and 77.1%.
Conclusion
During acute COVID-19 outbreak, chest CT scan may be used for triage of patients with intermediate clinical probability with very good inter-observer agreements and diagnostic accuracy.
Key Points
• Concordances between two chest radiologists to diagnose or exclude a COVID-19 pneumonia in 319 consecutive patients with intermediate clinical probability were very good (kappa: 0.82; p < .001).
• When compared with RT-PCR results and patient outcomes, the diagnostic accuracy of CT to identify COVID-19 pneumonia was high for both radiologists (AUC: 0.94 and 0.92).
• With a disease prevalence of 61.2% in the studied population, the positive predictive values of CT for diagnosing COVID-19 pneumonia were 95.9% and 94.3% with negative predictive values of 84.4% and 77.1%.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>33011877</pmid><doi>10.1007/s00330-020-07346-y</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-4447-7850</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | European radiology, 2021-04, Vol.31 (4), p.1969-1977 |
| issn | 0938-7994 1432-1084 1432-1084 |
| language | eng |
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| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Accuracy Chest Clinical outcomes Computed tomography Confidence intervals Coronaviruses COVID-19 Diagnostic Radiology Diagnostic systems Hematology Human health and pathology Humans Imaging Internal Medicine Interventional Radiology Life Sciences Medical diagnosis Medical imaging Medicine Medicine & Public Health Middle Aged Neuroradiology Outbreaks Patients Pneumonia Polymerase chain reaction Population studies Probability Radiology Retrospective Studies SARS-CoV-2 Statistical analysis Tomography, X-Ray Computed Ultrasound Viral diseases |
| title | COVID-19 pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability |
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