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Adverse Initial CT Findings Associated with Poor Prognosis of Coronavirus Disease.

Identifieur interne : 000953 ( Main/Exploration ); précédent : 000952; suivant : 000954

Adverse Initial CT Findings Associated with Poor Prognosis of Coronavirus Disease.

Auteurs : Youngjun Chon [Corée du Sud] ; Jin Young Kim [Corée du Sud] ; Young Joo Suh [Corée du Sud] ; Ji Yeon Lee [Corée du Sud] ; Jae Seok Park [Corée du Sud] ; Sung Min Moon [Corée du Sud] ; Mu Sook Lee [Corée du Sud] ; Jaehyuck Yi [Corée du Sud]

Source :

RBID : pubmed:32864912

Descripteurs français

English descriptors

Abstract

BACKGROUND

The predictors of poor prognosis in patients with coronavirus disease 2019 (COVID-19) using computed tomography (CT) have not been investigated in a large cohort. Therefore, the purpose of this study was to investigate the adverse initial CT features to predict poor prognosis in COVID-19.

METHODS

From February to April 2020, 281 COVID-19 patients who underwent CT at the time of admission were included. We divided the patients into the severe and non-severe disease groups. The severe group included patients with severe pneumonia or critical events. Intensive care unit admission or death were the critical events in this study. We compared the clinical and CT findings between the severe and non-severe groups and investigated the prognostic factors and critical events of the severe group using the regression analysis.

RESULTS

Among the 281 patients, 36 (12.8%) patients were in the severe group and 245 (87.2%) patients were in the non-severe group. Critical events occurred in 10 patients (3.6%). In the severe group, patients showed significantly more pneumonia with consolidation, crazy-paving appearance, pleural effusion, and higher CT scores than those in the non-severe group (all,

CONCLUSION

Pleural effusion and the extent of pneumonia on initial CT scans are associated with poor prognosis in patients with COVID-19.


DOI: 10.3346/jkms.2020.35.e316
PubMed: 32864912
PubMed Central: PMC7458853


Affiliations:


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Le document en format XML

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<term>Aged (MeSH)</term>
<term>Aged, 80 and over (MeSH)</term>
<term>Aging (MeSH)</term>
<term>Betacoronavirus (MeSH)</term>
<term>C-Reactive Protein (analysis)</term>
<term>Coronavirus Infections (diagnosis)</term>
<term>Coronavirus Infections (diagnostic imaging)</term>
<term>Coronavirus Infections (mortality)</term>
<term>Coronavirus Infections (pathology)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Intensive Care Units (MeSH)</term>
<term>Lung (diagnostic imaging)</term>
<term>Lung (pathology)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Pandemics (MeSH)</term>
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<term>Pleural Effusion (pathology)</term>
<term>Pneumonia, Viral (diagnosis)</term>
<term>Pneumonia, Viral (diagnostic imaging)</term>
<term>Pneumonia, Viral (mortality)</term>
<term>Pneumonia, Viral (pathology)</term>
<term>Prognosis (MeSH)</term>
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<term>Adulte d'âge moyen (MeSH)</term>
<term>Betacoronavirus (MeSH)</term>
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<term>Humains (MeSH)</term>
<term>Indice de gravité de la maladie (MeSH)</term>
<term>Infections à coronavirus (anatomopathologie)</term>
<term>Infections à coronavirus (diagnostic)</term>
<term>Infections à coronavirus (imagerie diagnostique)</term>
<term>Infections à coronavirus (mortalité)</term>
<term>Mâle (MeSH)</term>
<term>Pandémies (MeSH)</term>
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<term>Pneumopathie virale (diagnostic)</term>
<term>Pneumopathie virale (imagerie diagnostique)</term>
<term>Pneumopathie virale (mortalité)</term>
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<term>Poumon (imagerie diagnostique)</term>
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<term>Protéine C-réactive (analyse)</term>
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<term>Sujet âgé de 80 ans ou plus (MeSH)</term>
<term>Tomodensitométrie (MeSH)</term>
<term>Unités de soins intensifs (MeSH)</term>
<term>Vieillissement (MeSH)</term>
<term>Épanchement pleural (anatomopathologie)</term>
<term>Épanchement pleural (imagerie diagnostique)</term>
<term>Études rétrospectives (MeSH)</term>
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<term>C-Reactive Protein</term>
</keywords>
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<term>Protéine C-réactive</term>
</keywords>
<keywords scheme="MESH" qualifier="anatomopathologie" xml:lang="fr">
<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Poumon</term>
<term>Épanchement pleural</term>
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<keywords scheme="MESH" qualifier="diagnosis" xml:lang="en">
<term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
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<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
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<term>Coronavirus Infections</term>
<term>Lung</term>
<term>Pleural Effusion</term>
<term>Pneumonia, Viral</term>
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<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Poumon</term>
<term>Épanchement pleural</term>
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<keywords scheme="MESH" qualifier="mortality" xml:lang="en">
<term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
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<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
</keywords>
<keywords scheme="MESH" qualifier="pathology" xml:lang="en">
<term>Coronavirus Infections</term>
<term>Lung</term>
<term>Pleural Effusion</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" xml:lang="en">
<term>Aged</term>
<term>Aged, 80 and over</term>
<term>Aging</term>
<term>Betacoronavirus</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>Severity of Illness Index</term>
<term>Tomography, X-Ray Computed</term>
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<term>Adulte d'âge moyen</term>
<term>Betacoronavirus</term>
<term>Femelle</term>
<term>Humains</term>
<term>Indice de gravité de la maladie</term>
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<term>Pandémies</term>
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<front>
<div type="abstract" xml:lang="en">
<p>
<b>BACKGROUND</b>
</p>
<p>The predictors of poor prognosis in patients with coronavirus disease 2019 (COVID-19) using computed tomography (CT) have not been investigated in a large cohort. Therefore, the purpose of this study was to investigate the adverse initial CT features to predict poor prognosis in COVID-19.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>METHODS</b>
</p>
<p>From February to April 2020, 281 COVID-19 patients who underwent CT at the time of admission were included. We divided the patients into the severe and non-severe disease groups. The severe group included patients with severe pneumonia or critical events. Intensive care unit admission or death were the critical events in this study. We compared the clinical and CT findings between the severe and non-severe groups and investigated the prognostic factors and critical events of the severe group using the regression analysis.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>RESULTS</b>
</p>
<p>Among the 281 patients, 36 (12.8%) patients were in the severe group and 245 (87.2%) patients were in the non-severe group. Critical events occurred in 10 patients (3.6%). In the severe group, patients showed significantly more pneumonia with consolidation, crazy-paving appearance, pleural effusion, and higher CT scores than those in the non-severe group (all, </p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>CONCLUSION</b>
</p>
<p>Pleural effusion and the extent of pneumonia on initial CT scans are associated with poor prognosis in patients with COVID-19.</p>
</div>
</front>
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<Month>09</Month>
<Day>07</Day>
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<Year>2020</Year>
<Month>09</Month>
<Day>07</Day>
</DateRevised>
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<ISSN IssnType="Electronic">1598-6357</ISSN>
<JournalIssue CitedMedium="Internet">
<Volume>35</Volume>
<Issue>34</Issue>
<PubDate>
<Year>2020</Year>
<Month>Aug</Month>
<Day>31</Day>
</PubDate>
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<Title>Journal of Korean medical science</Title>
<ISOAbbreviation>J Korean Med Sci</ISOAbbreviation>
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<ArticleTitle>Adverse Initial CT Findings Associated with Poor Prognosis of Coronavirus Disease.</ArticleTitle>
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<ELocationID EIdType="doi" ValidYN="Y">10.3346/jkms.2020.35.e316</ELocationID>
<Abstract>
<AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">The predictors of poor prognosis in patients with coronavirus disease 2019 (COVID-19) using computed tomography (CT) have not been investigated in a large cohort. Therefore, the purpose of this study was to investigate the adverse initial CT features to predict poor prognosis in COVID-19.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">From February to April 2020, 281 COVID-19 patients who underwent CT at the time of admission were included. We divided the patients into the severe and non-severe disease groups. The severe group included patients with severe pneumonia or critical events. Intensive care unit admission or death were the critical events in this study. We compared the clinical and CT findings between the severe and non-severe groups and investigated the prognostic factors and critical events of the severe group using the regression analysis.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Among the 281 patients, 36 (12.8%) patients were in the severe group and 245 (87.2%) patients were in the non-severe group. Critical events occurred in 10 patients (3.6%). In the severe group, patients showed significantly more pneumonia with consolidation, crazy-paving appearance, pleural effusion, and higher CT scores than those in the non-severe group (all,
<i>P</i>
< 0.05). In the multivariate regression, pleural effusion (odds ratio [OR], 8.96; 95% confidence interval [CI], 1.81-44.42;
<i>P</i>
= 0.007), CT score > 5 (OR, 3.70; 95% CI, 1.44-9.53;
<i>P</i>
= 0.007), old age (> 77 years, OR, 9.96; 95% CI, 3.78-26.28;
<i>P</i>
< 0.001), and elevated C-reactive protein (OR, 4.15; 95% CI, 1.62-10.6;
<i>P</i>
= 0.003) were significant prognostic factors of severe disease. CT score > 5 (OR, 7.29; 95% CI, 1.37-38.68;
<i>P</i>
= 0.020), pleural effusion (OR, 5.67; 95% CI, 1.04-30.8;
<i>P</i>
= 0.045) and old age (OR, 8.6; 95% CI, 1.80-41.0;
<i>P</i>
= 0.007) were also significant predictors of critical events.</AbstractText>
<AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Pleural effusion and the extent of pneumonia on initial CT scans are associated with poor prognosis in patients with COVID-19.</AbstractText>
<CopyrightInformation>© 2020 The Korean Academy of Medical Sciences.</CopyrightInformation>
</Abstract>
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<Affiliation>Department of Radiology, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, Daegu, Korea.</Affiliation>
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