CovidSeniorV1, Main, Exploration, bibRecord, 000838

CT lung lesions as predictors of early death or ICU admission in COVID-19 patients.

Identifieur interne : 000838 ( Main/Exploration ); précédent : 000837; suivant : 000839

CT lung lesions as predictors of early death or ICU admission in COVID-19 patients.

Auteurs : Yvon Ruch [France] ; Charlotte Kaeuffer [France] ; Mickael Ohana [France] ; Aissam Labani [France] ; Thibaut Fabacher [France] ; Pascal Bilbault [France] ; Sabrina Kepka [France] ; Morgane Solis [France] ; Valentin Greigert [France] ; Nicolas Lefebvre [France] ; Yves Hansmann [France] ; François Danion [France]

Source :

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases [ 1469-0691 ] ; 2020.

RBID : pubmed:32717417

Descripteurs français

KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Analyse de survie (MeSH), Betacoronavirus (génétique), Betacoronavirus (pathogénicité), Femelle (MeSH), Humains (MeSH), Indice de gravité de la maladie (MeSH), Infections à coronavirus (diagnostic), Infections à coronavirus (imagerie diagnostique), Infections à coronavirus (mortalité), Infections à coronavirus (physiopathologie), Infections à coronavirus (virologie), Mâle (MeSH), Pandémies (MeSH), Pneumopathie virale (imagerie diagnostique), Pneumopathie virale (mortalité), Pneumopathie virale (physiopathologie), Pneumopathie virale (virologie), Poumon (imagerie diagnostique), Poumon (physiopathologie), Poumon (virologie), Pronostic (MeSH), RT-PCR (MeSH), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Techniques de laboratoire clinique (méthodes), Tomodensitométrie (MeSH), Unités de soins intensifs (MeSH), Études rétrospectives (MeSH).
MESH :
- diagnostic : Infections à coronavirus.
- génétique : Betacoronavirus.
- imagerie diagnostique : Infections à coronavirus, Pneumopathie virale, Poumon.
- mortalité : Infections à coronavirus, Pneumopathie virale.
- méthodes : Techniques de laboratoire clinique.
- pathogénicité : Betacoronavirus.
- physiopathologie : Infections à coronavirus, Pneumopathie virale, Poumon.
- virologie : Infections à coronavirus, Pneumopathie virale, Poumon.
- Adulte, Adulte d'âge moyen, Analyse de survie, Femelle, Humains, Indice de gravité de la maladie, Mâle, Pandémies, Pronostic, RT-PCR, Sujet âgé, Sujet âgé de 80 ans ou plus, Tomodensitométrie, Unités de soins intensifs, Études rétrospectives.

English descriptors

KwdEn :
- Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (genetics), Betacoronavirus (pathogenicity), Clinical Laboratory Techniques (methods), Coronavirus Infections (diagnosis), Coronavirus Infections (diagnostic imaging), Coronavirus Infections (mortality), Coronavirus Infections (physiopathology), Coronavirus Infections (virology), Female (MeSH), Humans (MeSH), Intensive Care Units (MeSH), Lung (diagnostic imaging), Lung (physiopathology), Lung (virology), Male (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnostic imaging), Pneumonia, Viral (mortality), Pneumonia, Viral (physiopathology), Pneumonia, Viral (virology), Prognosis (MeSH), Retrospective Studies (MeSH), Reverse Transcriptase Polymerase Chain Reaction (MeSH), Severity of Illness Index (MeSH), Survival Analysis (MeSH), Tomography, X-Ray Computed (MeSH).
MESH :
- diagnosis : Coronavirus Infections.
- diagnostic imaging : Coronavirus Infections, Lung, Pneumonia, Viral.
- genetics : Betacoronavirus.
- methods : Clinical Laboratory Techniques.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- pathogenicity : Betacoronavirus.
- physiopathology : Coronavirus Infections, Lung, Pneumonia, Viral.
- virology : Coronavirus Infections, Lung, Pneumonia, Viral.
- Adult, Aged, Aged, 80 and over, Female, Humans, Intensive Care Units, Male, Middle Aged, Pandemics, Prognosis, Retrospective Studies, Reverse Transcriptase Polymerase Chain Reaction, Severity of Illness Index, Survival Analysis, Tomography, X-Ray Computed.

Abstract

OBJECTIVE

The main objective of this study was to investigate the prognostic value of early systematic chest computed tomography (CT) with quantification of lung lesions in coronavirus disease 2019 (COVID-19) patients.

METHODS

We studied 572 patients diagnosed with COVID-19 (confirmed using polymerase chain reaction) for whom a chest CT was performed at hospital admission. Visual quantification was used to classify patients as per the percentage of lung parenchyma affected by COVID-19 lesions: normal CT, 0-10%, 11-25%, 26-50%, 51-75% and >75%. The primary endpoint was severe disease, defined by death or admission to the intensive care unit in the 7 days following first admission.

RESULTS

The mean patient age was 66.0 ± 16.0 years, and 343/572 (60.0%) were men. The primary endpoint occurred in 206/572 patients (36.0%). The extent of lesions on initial CT was independently associated with prognosis (odds ratio = 2.35, 95% confidence interval 1.24-4.46; p < 0.01). Most patients with lung involvement >50% (66/95, 69.5%) developed severe disease compared to patients with lung involvement of 26-50% (70/171, 40.9%) and ≤25% (70/306, 22.9%) (p < 0.01 and p < 0.01, respectively). None of the patients with normal CT (0/14) had severe disease.

CONCLUSION

Chest CT findings at admission are associated with outcome in COVID-19 patients.

DOI: 10.1016/j.cmi.2020.07.030
PubMed: 32717417
PubMed Central: PMC7378475

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Main, to step Corpus: 000987
to stream Main, to step Curation: 000987

Le document en format XML

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<country xml:lang="fr">France</country>
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<author><name sortKey="Solis, Morgane" sort="Solis, Morgane" uniqKey="Solis M" first="Morgane" last="Solis">Morgane Solis</name>
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<country xml:lang="fr">France</country>
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<author><name sortKey="Greigert, Valentin" sort="Greigert, Valentin" uniqKey="Greigert V" first="Valentin" last="Greigert">Valentin Greigert</name>
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<country xml:lang="fr">France</country>
<wicri:regionArea>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg</wicri:regionArea>
<placeName><region type="region">Grand Est</region>
<region type="old region">Alsace (région administrative)</region>
<settlement type="city">Strasbourg</settlement>
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<author><name sortKey="Lefebvre, Nicolas" sort="Lefebvre, Nicolas" uniqKey="Lefebvre N" first="Nicolas" last="Lefebvre">Nicolas Lefebvre</name>
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<country xml:lang="fr">France</country>
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<author><name sortKey="Hansmann, Yves" sort="Hansmann, Yves" uniqKey="Hansmann Y" first="Yves" last="Hansmann">Yves Hansmann</name>
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<author><name sortKey="Danion, Francois" sort="Danion, Francois" uniqKey="Danion F" first="François" last="Danion">François Danion</name>
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<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 (genetics)</term>
<term>Betacoronavirus (pathogenicity)</term>
<term>Clinical Laboratory Techniques (methods)</term>
<term>Coronavirus Infections (diagnosis)</term>
<term>Coronavirus Infections (diagnostic imaging)</term>
<term>Coronavirus Infections (mortality)</term>
<term>Coronavirus Infections (physiopathology)</term>
<term>Coronavirus Infections (virology)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Intensive Care Units (MeSH)</term>
<term>Lung (diagnostic imaging)</term>
<term>Lung (physiopathology)</term>
<term>Lung (virology)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Pandemics (MeSH)</term>
<term>Pneumonia, Viral (diagnostic imaging)</term>
<term>Pneumonia, Viral (mortality)</term>
<term>Pneumonia, Viral (physiopathology)</term>
<term>Pneumonia, Viral (virology)</term>
<term>Prognosis (MeSH)</term>
<term>Retrospective Studies (MeSH)</term>
<term>Reverse Transcriptase Polymerase Chain Reaction (MeSH)</term>
<term>Severity of Illness Index (MeSH)</term>
<term>Survival Analysis (MeSH)</term>
<term>Tomography, X-Ray Computed (MeSH)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Analyse de survie (MeSH)</term>
<term>Betacoronavirus (génétique)</term>
<term>Betacoronavirus (pathogénicité)</term>
<term>Femelle (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Indice de gravité de la maladie (MeSH)</term>
<term>Infections à coronavirus (diagnostic)</term>
<term>Infections à coronavirus (imagerie diagnostique)</term>
<term>Infections à coronavirus (mortalité)</term>
<term>Infections à coronavirus (physiopathologie)</term>
<term>Infections à coronavirus (virologie)</term>
<term>Mâle (MeSH)</term>
<term>Pandémies (MeSH)</term>
<term>Pneumopathie virale (imagerie diagnostique)</term>
<term>Pneumopathie virale (mortalité)</term>
<term>Pneumopathie virale (physiopathologie)</term>
<term>Pneumopathie virale (virologie)</term>
<term>Poumon (imagerie diagnostique)</term>
<term>Poumon (physiopathologie)</term>
<term>Poumon (virologie)</term>
<term>Pronostic (MeSH)</term>
<term>RT-PCR (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
<term>Sujet âgé de 80 ans ou plus (MeSH)</term>
<term>Techniques de laboratoire clinique (méthodes)</term>
<term>Tomodensitométrie (MeSH)</term>
<term>Unités de soins intensifs (MeSH)</term>
<term>Études rétrospectives (MeSH)</term>
</keywords>
<keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Coronavirus Infections</term>
</keywords>
<keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Infections à coronavirus</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="genetics" xml:lang="en"><term>Betacoronavirus</term>
</keywords>
<keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Betacoronavirus</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>Clinical Laboratory Techniques</term>
</keywords>
<keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
</keywords>
<keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Techniques de laboratoire clinique</term>
</keywords>
<keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>Betacoronavirus</term>
</keywords>
<keywords scheme="MESH" qualifier="pathogénicité" xml:lang="fr"><term>Betacoronavirus</term>
</keywords>
<keywords scheme="MESH" qualifier="physiopathologie" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Poumon</term>
</keywords>
<keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Coronavirus Infections</term>
<term>Lung</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Poumon</term>
</keywords>
<keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term>
<term>Lung</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
<term>Female</term>
<term>Humans</term>
<term>Intensive Care Units</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pandemics</term>
<term>Prognosis</term>
<term>Retrospective Studies</term>
<term>Reverse Transcriptase Polymerase Chain Reaction</term>
<term>Severity of Illness Index</term>
<term>Survival Analysis</term>
<term>Tomography, X-Ray Computed</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Analyse de survie</term>
<term>Femelle</term>
<term>Humains</term>
<term>Indice de gravité de la maladie</term>
<term>Mâle</term>
<term>Pandémies</term>
<term>Pronostic</term>
<term>RT-PCR</term>
<term>Sujet âgé</term>
<term>Sujet âgé de 80 ans ou plus</term>
<term>Tomodensitométrie</term>
<term>Unités de soins intensifs</term>
<term>Études rétrospectives</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b>
</p>
<p>The main objective of this study was to investigate the prognostic value of early systematic chest computed tomography (CT) with quantification of lung lesions in coronavirus disease 2019 (COVID-19) patients.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>We studied 572 patients diagnosed with COVID-19 (confirmed using polymerase chain reaction) for whom a chest CT was performed at hospital admission. Visual quantification was used to classify patients as per the percentage of lung parenchyma affected by COVID-19 lesions: normal CT, 0-10%, 11-25%, 26-50%, 51-75% and >75%. The primary endpoint was severe disease, defined by death or admission to the intensive care unit in the 7 days following first admission.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>The mean patient age was 66.0 ± 16.0 years, and 343/572 (60.0%) were men. The primary endpoint occurred in 206/572 patients (36.0%). The extent of lesions on initial CT was independently associated with prognosis (odds ratio = 2.35, 95% confidence interval 1.24-4.46; p < 0.01). Most patients with lung involvement >50% (66/95, 69.5%) developed severe disease compared to patients with lung involvement of 26-50% (70/171, 40.9%) and ≤25% (70/306, 22.9%) (p < 0.01 and p < 0.01, respectively). None of the patients with normal CT (0/14) had severe disease.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSION</b>
</p>
<p>Chest CT findings at admission are associated with outcome in COVID-19 patients.</p>
</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32717417</PMID>
<DateCompleted><Year>2020</Year>
<Month>09</Month>
<Day>29</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>09</Month>
<Day>29</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1469-0691</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>26</Volume>
<Issue>10</Issue>
<PubDate><Year>2020</Year>
<Month>Oct</Month>
</PubDate>
</JournalIssue>
<Title>Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases</Title>
<ISOAbbreviation>Clin Microbiol Infect</ISOAbbreviation>
</Journal>
<ArticleTitle>CT lung lesions as predictors of early death or ICU admission in COVID-19 patients.</ArticleTitle>
<Pagination><MedlinePgn>1417.e5-1417.e8</MedlinePgn>
</Pagination>
<ELocationID EIdType="pii" ValidYN="Y">S1198-743X(20)30438-9</ELocationID>
<ELocationID EIdType="doi" ValidYN="Y">10.1016/j.cmi.2020.07.030</ELocationID>
<Abstract><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">The main objective of this study was to investigate the prognostic value of early systematic chest computed tomography (CT) with quantification of lung lesions in coronavirus disease 2019 (COVID-19) patients.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We studied 572 patients diagnosed with COVID-19 (confirmed using polymerase chain reaction) for whom a chest CT was performed at hospital admission. Visual quantification was used to classify patients as per the percentage of lung parenchyma affected by COVID-19 lesions: normal CT, 0-10%, 11-25%, 26-50%, 51-75% and >75%. The primary endpoint was severe disease, defined by death or admission to the intensive care unit in the 7 days following first admission.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">The mean patient age was 66.0 ± 16.0 years, and 343/572 (60.0%) were men. The primary endpoint occurred in 206/572 patients (36.0%). The extent of lesions on initial CT was independently associated with prognosis (odds ratio = 2.35, 95% confidence interval 1.24-4.46; p < 0.01). Most patients with lung involvement >50% (66/95, 69.5%) developed severe disease compared to patients with lung involvement of 26-50% (70/171, 40.9%) and ≤25% (70/306, 22.9%) (p < 0.01 and p < 0.01, respectively). None of the patients with normal CT (0/14) had severe disease.</AbstractText>
<AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Chest CT findings at admission are associated with outcome in COVID-19 patients.</AbstractText>
<CopyrightInformation>Copyright © 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ruch</LastName>
<ForeName>Yvon</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg, France. Electronic address: yvon.ruch@chru-strasbourg.fr.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Kaeuffer</LastName>
<ForeName>Charlotte</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ohana</LastName>
<ForeName>Mickael</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Department of Radiology, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Labani</LastName>
<ForeName>Aissam</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Department of Radiology, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Fabacher</LastName>
<ForeName>Thibaut</ForeName>
<Initials>T</Initials>
<AffiliationInfo><Affiliation>Department of Biostatistics, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Bilbault</LastName>
<ForeName>Pascal</ForeName>
<Initials>P</Initials>
<AffiliationInfo><Affiliation>Department of Emergency Medicine, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Kepka</LastName>
<ForeName>Sabrina</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Department of Emergency Medicine, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Solis</LastName>
<ForeName>Morgane</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Department of Virology, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Greigert</LastName>
<ForeName>Valentin</ForeName>
<Initials>V</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Lefebvre</LastName>
<ForeName>Nicolas</ForeName>
<Initials>N</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hansmann</LastName>
<ForeName>Yves</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Danion</LastName>
<ForeName>François</ForeName>
<Initials>F</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Disease, Strasbourg University Hospital, Strasbourg, France.</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>24</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>Clin Microbiol Infect</MedlineTA>
<NlmUniqueID>9516420</NlmUniqueID>
<ISSNLinking>1198-743X</ISSNLinking>
</MedlineJournalInfo>
<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="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="N">Betacoronavirus</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
<QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D019411" MajorTopicYN="N">Clinical Laboratory Techniques</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName>
<QualifierName UI="Q000000981" MajorTopicYN="Y">diagnostic imaging</QualifierName>
<QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName>
<QualifierName UI="Q000503" MajorTopicYN="N">physiopathology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007362" MajorTopicYN="N">Intensive Care Units</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008168" MajorTopicYN="N">Lung</DescriptorName>
<QualifierName UI="Q000000981" MajorTopicYN="Y">diagnostic imaging</QualifierName>
<QualifierName UI="Q000503" MajorTopicYN="N">physiopathology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</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>
<QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName>
<QualifierName UI="Q000503" MajorTopicYN="N">physiopathology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011379" MajorTopicYN="N">Prognosis</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D020133" MajorTopicYN="N">Reverse Transcriptase Polymerase Chain Reaction</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012720" MajorTopicYN="N">Severity of Illness Index</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016019" MajorTopicYN="N">Survival Analysis</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D014057" MajorTopicYN="N">Tomography, X-Ray Computed</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword>
<Keyword MajorTopicYN="N">Computed tomography</Keyword>
<Keyword MajorTopicYN="N">Coronavirus</Keyword>
<Keyword MajorTopicYN="N">Ground-glass opacities</Keyword>
<Keyword MajorTopicYN="N">Visual quantification</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year>
<Month>05</Month>
<Day>15</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2020</Year>
<Month>07</Month>
<Day>16</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>07</Month>
<Day>19</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2020</Year>
<Month>7</Month>
<Day>28</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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<PubMedPubDate PubStatus="medline"><Year>2020</Year>
<Month>9</Month>
<Day>30</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2020</Year>
<Month>7</Month>
<Day>28</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">32717417</ArticleId>
<ArticleId IdType="pii">S1198-743X(20)30438-9</ArticleId>
<ArticleId IdType="doi">10.1016/j.cmi.2020.07.030</ArticleId>
<ArticleId IdType="pmc">PMC7378475</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations><list><country><li>France</li>
</country>
<region><li>Alsace (région administrative)</li>
<li>Grand Est</li>
</region>
<settlement><li>Strasbourg</li>
</settlement>
</list>
<tree><country name="France"><region name="Grand Est"><name sortKey="Ruch, Yvon" sort="Ruch, Yvon" uniqKey="Ruch Y" first="Yvon" last="Ruch">Yvon Ruch</name>
</region>
<name sortKey="Bilbault, Pascal" sort="Bilbault, Pascal" uniqKey="Bilbault P" first="Pascal" last="Bilbault">Pascal Bilbault</name>
<name sortKey="Danion, Francois" sort="Danion, Francois" uniqKey="Danion F" first="François" last="Danion">François Danion</name>
<name sortKey="Fabacher, Thibaut" sort="Fabacher, Thibaut" uniqKey="Fabacher T" first="Thibaut" last="Fabacher">Thibaut Fabacher</name>
<name sortKey="Greigert, Valentin" sort="Greigert, Valentin" uniqKey="Greigert V" first="Valentin" last="Greigert">Valentin Greigert</name>
<name sortKey="Hansmann, Yves" sort="Hansmann, Yves" uniqKey="Hansmann Y" first="Yves" last="Hansmann">Yves Hansmann</name>
<name sortKey="Kaeuffer, Charlotte" sort="Kaeuffer, Charlotte" uniqKey="Kaeuffer C" first="Charlotte" last="Kaeuffer">Charlotte Kaeuffer</name>
<name sortKey="Kepka, Sabrina" sort="Kepka, Sabrina" uniqKey="Kepka S" first="Sabrina" last="Kepka">Sabrina Kepka</name>
<name sortKey="Labani, Aissam" sort="Labani, Aissam" uniqKey="Labani A" first="Aissam" last="Labani">Aissam Labani</name>
<name sortKey="Lefebvre, Nicolas" sort="Lefebvre, Nicolas" uniqKey="Lefebvre N" first="Nicolas" last="Lefebvre">Nicolas Lefebvre</name>
<name sortKey="Ohana, Mickael" sort="Ohana, Mickael" uniqKey="Ohana M" first="Mickael" last="Ohana">Mickael Ohana</name>
<name sortKey="Solis, Morgane" sort="Solis, Morgane" uniqKey="Solis M" first="Morgane" last="Solis">Morgane Solis</name>
</country>
</tree>
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Serveur d'exploration sur la COVID chez les séniors

CT lung lesions as predictors of early death or ICU admission in COVID-19 patients.

CT lung lesions as predictors of early death or ICU admission in COVID-19 patients.

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