Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea.
Identifieur interne : 000752 ( Main/Curation ); précédent : 000751; suivant : 000753Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea.
Auteurs : Byunggeon Park [Corée du Sud] ; Jongmin Park [Corée du Sud] ; Jae Kwang Lim [Corée du Sud] ; Kyung Min Shin [Corée du Sud] ; Jaehee Lee [Corée du Sud] ; Hyewon Seo [Corée du Sud] ; Yong Hoon Lee [Corée du Sud] ; Jun Heo [Corée du Sud] ; Won Kee Lee [Corée du Sud] ; Jin Young Kim [Corée du Sud] ; Ki Beom Kim [Corée du Sud] ; Sungjun Moon [Corée du Sud] ; Sooyoung Choi [Corée du Sud]Source :
- Korean journal of radiology [ 2005-8330 ] ; 2020.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Betacoronavirus (isolement et purification), Femelle (MeSH), Humains (MeSH), Indice de gravité de la maladie (MeSH), Infections à coronavirus (diagnostic), Infections à coronavirus (imagerie diagnostique), Infections à coronavirus (virologie), Modèles des risques proportionnels (MeSH), Mâle (MeSH), Pandémies (MeSH), Pneumopathie virale (diagnostic), Pneumopathie virale (imagerie diagnostique), Pneumopathie virale (virologie), Poumon (imagerie diagnostique), Pronostic (MeSH), Protéine C-réactive (analyse), République de Corée (MeSH), Sujet âgé (MeSH), Tomodensitométrie (MeSH), Études rétrospectives (MeSH).
- MESH :
- analyse : Protéine C-réactive.
- diagnostic : Infections à coronavirus, Pneumopathie virale.
- imagerie diagnostique : Infections à coronavirus, Pneumopathie virale, Poumon.
- isolement et purification : Betacoronavirus.
- virologie : Infections à coronavirus, Pneumopathie virale.
- Adulte, Adulte d'âge moyen, Femelle, Humains, Indice de gravité de la maladie, Modèles des risques proportionnels, Mâle, Pandémies, Pronostic, République de Corée, Sujet âgé, Tomodensitométrie, Études rétrospectives.
English descriptors
- KwdEn :
- Adult (MeSH), Aged (MeSH), Betacoronavirus (isolation & purification), C-Reactive Protein (analysis), Coronavirus Infections (diagnosis), Coronavirus Infections (diagnostic imaging), Coronavirus Infections (virology), Female (MeSH), Humans (MeSH), Lung (diagnostic imaging), Male (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnosis), Pneumonia, Viral (diagnostic imaging), Pneumonia, Viral (virology), Prognosis (MeSH), Proportional Hazards Models (MeSH), Republic of Korea (MeSH), Retrospective Studies (MeSH), Severity of Illness Index (MeSH), Tomography, X-Ray Computed (MeSH).
- MESH :
- chemical , analysis : C-Reactive Protein.
- geographic : Republic of Korea.
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- diagnostic imaging : Coronavirus Infections, Lung, Pneumonia, Viral.
- isolation & purification : Betacoronavirus.
- virology : Coronavirus Infections, Pneumonia, Viral.
- Adult, Aged, Female, Humans, Male, Middle Aged, Pandemics, Prognosis, Proportional Hazards Models, Retrospective Studies, Severity of Illness Index, Tomography, X-Ray Computed.
Abstract
OBJECTIVE
Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19.
MATERIALS AND METHODS
CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis.
RESULTS
Eighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021-42.457;
CONCLUSION
CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.
DOI: 10.3348/kjr.2020.0567
PubMed: 32767868
PubMed Central: PMC7462758
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CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea.</title><author><name sortKey="Park, Byunggeon" sort="Park, Byunggeon" uniqKey="Park B" first="Byunggeon" last="Park">Byunggeon Park</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Park, Jongmin" sort="Park, Jongmin" uniqKey="Park J" first="Jongmin" last="Park">Jongmin Park</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Lim, Jae Kwang" sort="Lim, Jae Kwang" uniqKey="Lim J" first="Jae Kwang" last="Lim">Jae Kwang Lim</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea. limjk@knu.ac.kr.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Shin, Kyung Min" sort="Shin, Kyung Min" uniqKey="Shin K" first="Kyung Min" last="Shin">Kyung Min Shin</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Lee, Jaehee" sort="Lee, Jaehee" uniqKey="Lee J" first="Jaehee" last="Lee">Jaehee Lee</name><affiliation wicri:level="1"><nlm:affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Seo, Hyewon" sort="Seo, Hyewon" uniqKey="Seo H" first="Hyewon" last="Seo">Hyewon Seo</name><affiliation wicri:level="1"><nlm:affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Lee, Yong Hoon" sort="Lee, Yong Hoon" uniqKey="Lee Y" first="Yong Hoon" last="Lee">Yong Hoon Lee</name><affiliation wicri:level="1"><nlm:affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Heo, Jun" sort="Heo, Jun" uniqKey="Heo J" first="Jun" last="Heo">Jun Heo</name><affiliation wicri:level="1"><nlm:affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Lee, Won Kee" sort="Lee, Won Kee" uniqKey="Lee W" first="Won Kee" last="Lee">Won Kee Lee</name><affiliation wicri:level="1"><nlm:affiliation>Medical Research Collaboration Center in Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Medical Research Collaboration Center in Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Kim, Jin Young" sort="Kim, Jin Young" uniqKey="Kim J" first="Jin Young" last="Kim">Jin Young Kim</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, Keimyung University Dongsan Hospital, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Keimyung University Dongsan Hospital, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Kim, Ki Beom" sort="Kim, Ki Beom" uniqKey="Kim K" first="Ki Beom" last="Kim">Ki Beom Kim</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, Daegu Fatima Hospital, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Daegu Fatima Hospital, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Moon, Sungjun" sort="Moon, Sungjun" uniqKey="Moon S" first="Sungjun" last="Moon">Sungjun Moon</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, College of Medicine, Yeungnam University, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, College of Medicine, Yeungnam University, Daegu</wicri:regionArea></affiliation></author><author><name sortKey="Choi, Sooyoung" sort="Choi, Sooyoung" uniqKey="Choi S" first="Sooyoung" last="Choi">Sooyoung Choi</name><affiliation wicri:level="1"><nlm:affiliation>Department of Radiology, Yeungnam University Medical Center, Daegu, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Yeungnam University Medical Center, Daegu</wicri:regionArea></affiliation></author></analytic><series><title level="j">Korean journal of radiology</title><idno type="eISSN">2005-8330</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>Betacoronavirus (isolation & purification)</term><term>C-Reactive Protein (analysis)</term><term>Coronavirus Infections (diagnosis)</term><term>Coronavirus Infections (diagnostic imaging)</term><term>Coronavirus Infections (virology)</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 (diagnosis)</term><term>Pneumonia, Viral (diagnostic imaging)</term><term>Pneumonia, Viral (virology)</term><term>Prognosis (MeSH)</term><term>Proportional Hazards Models (MeSH)</term><term>Republic of Korea (MeSH)</term><term>Retrospective Studies (MeSH)</term><term>Severity of Illness Index (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>Betacoronavirus (isolement et purification)</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 (virologie)</term><term>Modèles des risques proportionnels (MeSH)</term><term>Mâle (MeSH)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (diagnostic)</term><term>Pneumopathie virale (imagerie diagnostique)</term><term>Pneumopathie virale (virologie)</term><term>Poumon (imagerie diagnostique)</term><term>Pronostic (MeSH)</term><term>Protéine C-réactive (analyse)</term><term>République de Corée (MeSH)</term><term>Sujet âgé (MeSH)</term><term>Tomodensitométrie (MeSH)</term><term>Études rétrospectives (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>C-Reactive Protein</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Republic of Korea</term></keywords><keywords scheme="MESH" qualifier="analyse" xml:lang="fr"><term>Protéine C-réactive</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</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="isolation & purification" xml:lang="en"><term>Betacoronavirus</term></keywords><keywords scheme="MESH" qualifier="isolement et purification" xml:lang="fr"><term>Betacoronavirus</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Aged</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Pandemics</term><term>Prognosis</term><term>Proportional Hazards Models</term><term>Retrospective Studies</term><term>Severity of Illness Index</term><term>Tomography, X-Ray Computed</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Femelle</term><term>Humains</term><term>Indice de gravité de la maladie</term><term>Modèles des risques proportionnels</term><term>Mâle</term><term>Pandémies</term><term>Pronostic</term><term>République de Corée</term><term>Sujet âgé</term><term>Tomodensitométrie</term><term>Études rétrospectives</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b></p><p>Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19.</p></div><div type="abstract" xml:lang="en"><p><b>MATERIALS AND METHODS</b></p><p>CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Eighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021-42.457; </p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">32767868</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>15</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>15</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">2005-8330</ISSN><JournalIssue CitedMedium="Internet"><Volume>21</Volume><Issue>11</Issue><PubDate><Year>2020</Year><Month>11</Month></PubDate></JournalIssue><Title>Korean journal of radiology</Title><ISOAbbreviation>Korean J Radiol</ISOAbbreviation></Journal><ArticleTitle>Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea.</ArticleTitle><Pagination><MedlinePgn>1256-1264</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3348/kjr.2020.0567</ELocationID><Abstract><AbstractText Label="OBJECTIVE">Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19.</AbstractText><AbstractText Label="MATERIALS AND METHODS">CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis.</AbstractText><AbstractText Label="RESULTS">Eighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021-42.457; <i>p</i> = 0.004), C-reactive protein (CRP) (HR, 1.080 per mg/dL; 95% CI, 1.010-1.156; <i>p</i> = 0.025), and COVID-affected lung proportion (CALP) (HR, 1.067 per percentage; 95% CI, 1.033-1.101; <i>p</i> < 0.001) were significantly associated with CEFS. CRP (HR, 1.164 per mg/dL; 95% CI, 1.006-1.347; <i>p</i> = 0.041) was independently associated with CEFS in the mild pneumonia group (n = 54). Normally aerated lung proportion (NALP) (HR, 0.872 per percentage; 95% CI, 0.794-0.957; <i>p</i> = 0.004) and NALP volume (NALPV) (HR, 1.002 per mL; 95% CI, 1.000-1.004; <i>p</i> = 0.019) were associated with a lower risk of critical events in the severe pneumonia group (n = 28).</AbstractText><AbstractText Label="CONCLUSION">CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.</AbstractText><CopyrightInformation>Copyright © 2020 The Korean Society of Radiology.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y" EqualContrib="Y"><LastName>Park</LastName><ForeName>Byunggeon</ForeName><Initials>B</Initials><Identifier Source="ORCID">0000-0002-5807-9271</Identifier><AffiliationInfo><Affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y" EqualContrib="Y"><LastName>Park</LastName><ForeName>Jongmin</ForeName><Initials>J</Initials><Identifier Source="ORCID">0000-0001-9240-4181</Identifier><AffiliationInfo><Affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lim</LastName><ForeName>Jae Kwang</ForeName><Initials>JK</Initials><Identifier Source="ORCID">0000-0002-1299-9996</Identifier><AffiliationInfo><Affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea. limjk@knu.ac.kr.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shin</LastName><ForeName>Kyung Min</ForeName><Initials>KM</Initials><Identifier Source="ORCID">0000-0003-4109-0228</Identifier><AffiliationInfo><Affiliation>Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lee</LastName><ForeName>Jaehee</ForeName><Initials>J</Initials><Identifier Source="ORCID">0000-0001-8111-7320</Identifier><AffiliationInfo><Affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Seo</LastName><ForeName>Hyewon</ForeName><Initials>H</Initials><Identifier Source="ORCID">0000-0003-0533-8863</Identifier><AffiliationInfo><Affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lee</LastName><ForeName>Yong Hoon</ForeName><Initials>YH</Initials><Identifier Source="ORCID">0000-0001-5972-2866</Identifier><AffiliationInfo><Affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Heo</LastName><ForeName>Jun</ForeName><Initials>J</Initials><Identifier Source="ORCID">0000-0003-3180-1655</Identifier><AffiliationInfo><Affiliation>Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lee</LastName><ForeName>Won Kee</ForeName><Initials>WK</Initials><Identifier Source="ORCID">0000-0003-4217-5792</Identifier><AffiliationInfo><Affiliation>Medical Research Collaboration Center in Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kim</LastName><ForeName>Jin Young</ForeName><Initials>JY</Initials><Identifier Source="ORCID">0000-0001-6714-8358</Identifier><AffiliationInfo><Affiliation>Department of Radiology, Keimyung University Dongsan Hospital, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kim</LastName><ForeName>Ki Beom</ForeName><Initials>KB</Initials><Identifier Source="ORCID">0000-0003-4508-6058</Identifier><AffiliationInfo><Affiliation>Department of Radiology, Daegu Fatima Hospital, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Moon</LastName><ForeName>Sungjun</ForeName><Initials>S</Initials><Identifier Source="ORCID">0000-0002-3920-7004</Identifier><AffiliationInfo><Affiliation>Department of Radiology, College of Medicine, Yeungnam University, Daegu, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Choi</LastName><ForeName>Sooyoung</ForeName><Initials>S</Initials><Identifier Source="ORCID">0000-0003-1313-1002</Identifier><AffiliationInfo><Affiliation>Department of Radiology, Yeungnam University Medical Center, Daegu, Korea.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><Agency>Daegu Metropolitan City</Agency><Country>International</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>08</Month><Day>04</Day></ArticleDate></Article><MedlineJournalInfo><Country>Korea (South)</Country><MedlineTA>Korean J Radiol</MedlineTA><NlmUniqueID>100956096</NlmUniqueID><ISSNLinking>1229-6929</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>9007-41-4</RegistryNumber><NameOfSubstance UI="D002097">C-Reactive Protein</NameOfSubstance></Chemical></ChemicalList><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</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="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName><QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D002097" MajorTopicYN="N">C-Reactive Protein</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName><QualifierName UI="Q000000981" MajorTopicYN="N">diagnostic imaging</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="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="Q000175" MajorTopicYN="Y">diagnosis</QualifierName><QualifierName UI="Q000000981" MajorTopicYN="N">diagnostic imaging</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011379" MajorTopicYN="N">Prognosis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016016" MajorTopicYN="N">Proportional Hazards Models</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D056910" MajorTopicYN="N" Type="Geographic">Republic of Korea</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012720" MajorTopicYN="N">Severity of Illness Index</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014057" MajorTopicYN="Y">Tomography, X-Ray Computed</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Coronavirus disease</Keyword><Keyword MajorTopicYN="Y">Prognostic implication</Keyword><Keyword MajorTopicYN="Y">Severe acute respiratory syndrome coronavirus 2</Keyword><Keyword MajorTopicYN="Y">Volumetric quantitative analysis</Keyword></KeywordList><CoiStatement>The authors have no potential conflicts of interest to disclose.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>06</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>06</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="pmc-release"><Year>2020</Year><Month>11</Month><Day>01</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>8</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>9</Month><Day>17</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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