Prognosis models for severe and critical COVID-19 based on the Charlson and Elixhauser comorbidity indices.
Identifieur interne : 000321 ( Main/Exploration ); précédent : 000320; suivant : 000322Prognosis models for severe and critical COVID-19 based on the Charlson and Elixhauser comorbidity indices.
Auteurs : Wei Zhou [République populaire de Chine] ; Xiaoyi Qin [République populaire de Chine] ; Xiang Hu [République populaire de Chine] ; Yingru Lu [République populaire de Chine] ; Jingye Pan [République populaire de Chine]Source :
- International journal of medical sciences [ 1449-1907 ] ; 2020.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Appréciation des risques (méthodes), Betacoronavirus (isolement et purification), Betacoronavirus (pathogénicité), Comorbidité (MeSH), Durée du séjour (statistiques et données numériques), Femelle (MeSH), Humains (MeSH), Indice de gravité de la maladie (MeSH), Infections à coronavirus (diagnostic), Infections à coronavirus (mortalité), Infections à coronavirus (thérapie), Infections à coronavirus (virologie), Maladie grave (mortalité), Modèles statistiques (MeSH), Mortalité hospitalière (MeSH), Mâle (MeSH), Pandémies (MeSH), Pneumopathie virale (diagnostic), Pneumopathie virale (mortalité), Pneumopathie virale (thérapie), Pneumopathie virale (virologie), Prise de décision clinique (MeSH), Pronostic (MeSH), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Études rétrospectives (MeSH).
- MESH :
- diagnostic : Infections à coronavirus, Pneumopathie virale.
- isolement et purification : Betacoronavirus.
- mortalité : Infections à coronavirus, Maladie grave, Pneumopathie virale.
- méthodes : Appréciation des risques.
- pathogénicité : Betacoronavirus.
- statistiques et données numériques : Durée du séjour.
- thérapie : Infections à coronavirus, Pneumopathie virale.
- virologie : Infections à coronavirus, Pneumopathie virale.
- Adulte, Adulte d'âge moyen, Comorbidité, Femelle, Humains, Indice de gravité de la maladie, Modèles statistiques, Mortalité hospitalière, Mâle, Pandémies, Prise de décision clinique, Pronostic, Sujet âgé, Sujet âgé de 80 ans ou plus, Études rétrospectives.
English descriptors
- KwdEn :
- Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (isolation & purification), Betacoronavirus (pathogenicity), Clinical Decision-Making (MeSH), Comorbidity (MeSH), Coronavirus Infections (diagnosis), Coronavirus Infections (mortality), Coronavirus Infections (therapy), Coronavirus Infections (virology), Critical Illness (mortality), Female (MeSH), Hospital Mortality (MeSH), Humans (MeSH), Length of Stay (statistics & numerical data), Male (MeSH), Middle Aged (MeSH), Models, Statistical (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnosis), Pneumonia, Viral (mortality), Pneumonia, Viral (therapy), Pneumonia, Viral (virology), Prognosis (MeSH), Retrospective Studies (MeSH), Risk Assessment (methods), Severity of Illness Index (MeSH).
- MESH :
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- isolation & purification : Betacoronavirus.
- methods : Risk Assessment.
- mortality : Coronavirus Infections, Critical Illness, Pneumonia, Viral.
- pathogenicity : Betacoronavirus.
- statistics & numerical data : Length of Stay.
- therapy : Coronavirus Infections, Pneumonia, Viral.
- virology : Coronavirus Infections, Pneumonia, Viral.
- Adult, Aged, Aged, 80 and over, Clinical Decision-Making, Comorbidity, Female, Hospital Mortality, Humans, Male, Middle Aged, Models, Statistical, Pandemics, Prognosis, Retrospective Studies, Severity of Illness Index.
Abstract
Background: Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. Material and Methods: We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. Results: The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, P = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, P = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, P = 0.001, 95%CI 5.687-581.399; OR 71.500, P = 0.001, 95%CI 5.689-898.642; and OR 19.556, P = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, P = 0.001, 95%CI 3.565-127.672; OR 13.000, P = 0.009, 95%CI 1.921-87.990; OR 11.333, P = 0.008, 95%CI 1.859-69.080, respectively). Conclusions: This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.
DOI: 10.7150/ijms.50007
PubMed: 32922189
PubMed Central: PMC7484649
Affiliations:
Links toward previous steps (curation, corpus...)
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last="Lu">Yingru Lu</name><affiliation wicri:level="1"><nlm:affiliation>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang</wicri:regionArea><wicri:noRegion>Zhejiang</wicri:noRegion></affiliation></author><author><name sortKey="Pan, Jingye" sort="Pan, Jingye" uniqKey="Pan J" first="Jingye" last="Pan">Jingye Pan</name><affiliation wicri:level="1"><nlm:affiliation>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 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wicri:level="1"><nlm:affiliation>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang</wicri:regionArea><wicri:noRegion>Zhejiang</wicri:noRegion></affiliation></author><author><name sortKey="Qin, Xiaoyi" sort="Qin, Xiaoyi" uniqKey="Qin X" first="Xiaoyi" last="Qin">Xiaoyi Qin</name><affiliation wicri:level="1"><nlm:affiliation>Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 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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 (isolation & purification)</term><term>Betacoronavirus (pathogenicity)</term><term>Clinical Decision-Making (MeSH)</term><term>Comorbidity (MeSH)</term><term>Coronavirus Infections (diagnosis)</term><term>Coronavirus Infections (mortality)</term><term>Coronavirus Infections (therapy)</term><term>Coronavirus Infections (virology)</term><term>Critical Illness (mortality)</term><term>Female (MeSH)</term><term>Hospital Mortality (MeSH)</term><term>Humans (MeSH)</term><term>Length of Stay (statistics & numerical data)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Models, Statistical (MeSH)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (diagnosis)</term><term>Pneumonia, Viral (mortality)</term><term>Pneumonia, Viral (therapy)</term><term>Pneumonia, Viral (virology)</term><term>Prognosis (MeSH)</term><term>Retrospective Studies (MeSH)</term><term>Risk Assessment (methods)</term><term>Severity of Illness Index (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Appréciation des risques (méthodes)</term><term>Betacoronavirus (isolement et purification)</term><term>Betacoronavirus (pathogénicité)</term><term>Comorbidité (MeSH)</term><term>Durée du séjour (statistiques et données numériques)</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 (mortalité)</term><term>Infections à coronavirus (thérapie)</term><term>Infections à coronavirus (virologie)</term><term>Maladie grave (mortalité)</term><term>Modèles statistiques (MeSH)</term><term>Mortalité hospitalière (MeSH)</term><term>Mâle (MeSH)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (diagnostic)</term><term>Pneumopathie virale (mortalité)</term><term>Pneumopathie virale (thérapie)</term><term>Pneumopathie virale (virologie)</term><term>Prise de décision clinique (MeSH)</term><term>Pronostic (MeSH)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term><term>Études rétrospectives (MeSH)</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="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="methods" xml:lang="en"><term>Risk Assessment</term></keywords><keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term><term>Critical Illness</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à coronavirus</term><term>Maladie grave</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Appréciation des risques</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="statistics & numerical data" xml:lang="en"><term>Length of Stay</term></keywords><keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Durée du séjour</term></keywords><keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="thérapie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</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>Aged, 80 and over</term><term>Clinical Decision-Making</term><term>Comorbidity</term><term>Female</term><term>Hospital Mortality</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Models, Statistical</term><term>Pandemics</term><term>Prognosis</term><term>Retrospective Studies</term><term>Severity of Illness Index</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Comorbidité</term><term>Femelle</term><term>Humains</term><term>Indice de gravité de la maladie</term><term>Modèles statistiques</term><term>Mortalité hospitalière</term><term>Mâle</term><term>Pandémies</term><term>Prise de décision clinique</term><term>Pronostic</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Études rétrospectives</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><b>Background</b>: Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. <b>Material and Methods</b>: We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. <b>Results</b>: The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, <i>P</i> = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, <i>P</i> = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, <i>P</i> = 0.001, 95%CI 5.687-581.399; OR 71.500, <i>P</i> = 0.001, 95%CI 5.689-898.642; and OR 19.556, <i>P</i> = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, <i>P</i> = 0.001, 95%CI 3.565-127.672; OR 13.000, <i>P</i> = 0.009, 95%CI 1.921-87.990; OR 11.333, <i>P</i> = 0.008, 95%CI 1.859-69.080, respectively). <b>Conclusions</b>: This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32922189</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>22</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>22</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1449-1907</ISSN><JournalIssue CitedMedium="Internet"><Volume>17</Volume><Issue>15</Issue><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>International journal of medical sciences</Title><ISOAbbreviation>Int J Med Sci</ISOAbbreviation></Journal><ArticleTitle>Prognosis models for severe and critical COVID-19 based on the Charlson and Elixhauser comorbidity indices.</ArticleTitle><Pagination><MedlinePgn>2257-2263</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.7150/ijms.50007</ELocationID><Abstract><AbstractText><b>Background</b>: Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. <b>Material and Methods</b>: We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. <b>Results</b>: The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, <i>P</i> = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, <i>P</i> = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, <i>P</i> = 0.001, 95%CI 5.687-581.399; OR 71.500, <i>P</i> = 0.001, 95%CI 5.689-898.642; and OR 19.556, <i>P</i> = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, <i>P</i> = 0.001, 95%CI 3.565-127.672; OR 13.000, <i>P</i> = 0.009, 95%CI 1.921-87.990; OR 11.333, <i>P</i> = 0.008, 95%CI 1.859-69.080, respectively). <b>Conclusions</b>: This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.</AbstractText><CopyrightInformation>© The author(s).</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhou</LastName><ForeName>Wei</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Qin</LastName><ForeName>Xiaoyi</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hu</LastName><ForeName>Xiang</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lu</LastName><ForeName>Yingru</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pan</LastName><ForeName>Jingye</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.</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>25</Day></ArticleDate></Article><MedlineJournalInfo><Country>Australia</Country><MedlineTA>Int J Med Sci</MedlineTA><NlmUniqueID>101213954</NlmUniqueID><ISSNLinking>1449-1907</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>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="Q000302" MajorTopicYN="N">isolation & purification</QualifierName><QualifierName UI="Q000472" MajorTopicYN="N">pathogenicity</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000066491" MajorTopicYN="N">Clinical Decision-Making</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015897" MajorTopicYN="Y">Comorbidity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName><QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName><QualifierName UI="Q000628" MajorTopicYN="N">therapy</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016638" MajorTopicYN="N">Critical Illness</DescriptorName><QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017052" MajorTopicYN="N">Hospital Mortality</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007902" MajorTopicYN="N">Length of Stay</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015233" MajorTopicYN="Y">Models, Statistical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName><QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName><QualifierName UI="Q000628" MajorTopicYN="N">therapy</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="D018570" MajorTopicYN="N">Risk Assessment</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012720" MajorTopicYN="Y">Severity of Illness Index</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Charlson comorbidity index</Keyword><Keyword MajorTopicYN="N">Corona Virus Disease</Keyword><Keyword MajorTopicYN="N">Elixhauser comorbidity index</Keyword><Keyword MajorTopicYN="N">comorbidity</Keyword><Keyword MajorTopicYN="N">length of stay</Keyword><Keyword MajorTopicYN="N">outcome</Keyword></KeywordList><CoiStatement>Competing Interests: The authors have declared that no competing interest exists.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>06</Month><Day>27</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>08</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>9</Month><Day>14</Day><Hour>5</Hour><Minute>49</Minute></PubMedPubDate><PubMedPubDate 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IdType="pubmed">32206052</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Zhou, Wei" sort="Zhou, Wei" uniqKey="Zhou W" first="Wei" last="Zhou">Wei Zhou</name></noRegion><name sortKey="Hu, Xiang" sort="Hu, Xiang" uniqKey="Hu X" first="Xiang" last="Hu">Xiang Hu</name><name sortKey="Lu, Yingru" sort="Lu, Yingru" uniqKey="Lu Y" first="Yingru" last="Lu">Yingru Lu</name><name sortKey="Pan, Jingye" sort="Pan, Jingye" uniqKey="Pan J" first="Jingye" last="Pan">Jingye Pan</name><name sortKey="Qin, Xiaoyi" sort="Qin, Xiaoyi" uniqKey="Qin X" first="Xiaoyi" last="Qin">Xiaoyi Qin</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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