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...)
Le document en format XML
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<term>Betacoronavirus (pathogenicity)</term>
<term>Clinical Decision-Making (MeSH)</term>
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<term>Coronavirus Infections (mortality)</term>
<term>Coronavirus Infections (therapy)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
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<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>
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<term>Pneumonia, Viral</term>
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<term>Pneumopathie virale</term>
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<keywords scheme="MESH" qualifier="isolation & purification" xml:lang="en"><term>Betacoronavirus</term>
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<keywords scheme="MESH" qualifier="isolement et purification" xml:lang="fr"><term>Betacoronavirus</term>
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<term>Pneumonia, Viral</term>
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<term>Pneumopathie virale</term>
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<term>Pneumonia, Viral</term>
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<term>Aged</term>
<term>Aged, 80 and over</term>
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<term>Pandémies</term>
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<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>
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<MedlineTA>Int J Med Sci</MedlineTA>
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<ISSNLinking>1449-1907</ISSNLinking>
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<MeshHeading><DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName>
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<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>
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<CoiStatement>Competing Interests: The authors have declared that no competing interest exists.</CoiStatement>
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<Day>27</Day>
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<ReferenceList><Reference><Citation>N Engl J Med. 2020 Feb 20;382(8):727-733</Citation>
<ArticleIdList><ArticleId IdType="pubmed">31978945</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>JAMA. 2020 Mar 17;323(11):1061-1069</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32031570</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Urol Int. 2014;93(3):303-10</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25139069</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Chin Med J (Engl). 2020 May 5;133(9):1015-1024</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32004165</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Med Virol. 2020 Mar 17;:</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32181903</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Lancet Oncol. 2020 Mar;21(3):335-337</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32066541</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Eur Respir J. 2020 May 14;55(5):</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32217650</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>JAMA Intern Med. 2020 Jul 1;180(7):934-943</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32167524</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Stroke Cerebrovasc Dis. 2013 Oct;22(7):e214-8</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23352682</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Lancet. 2020 Feb 15;395(10223):470-473</Citation>
<ArticleIdList><ArticleId IdType="pubmed">31986257</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Med Care. 2009 Jun;47(6):626-33</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19433995</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Diabetes Metab Res Rev. 2020 Mar 31;:e3319</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32233013</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Lancet. 2020 Mar 28;395(10229):1054-1062</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32171076</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Med Virol. 2020 Jul;92(7):791-796</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32181911</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Chronic Dis. 1987;40(5):373-83</Citation>
<ArticleIdList><ArticleId IdType="pubmed">3558716</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Eur J Cardiothorac Surg. 2018 Jan 1;53(1):235-240</Citation>
<ArticleIdList><ArticleId IdType="pubmed">29106506</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Lancet. 2020 Feb 15;395(10223):497-506</Citation>
<ArticleIdList><ArticleId IdType="pubmed">31986264</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Ann Epidemiol. 2007 Aug;17(8):584-90</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17531502</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Med Care. 1998 Jan;36(1):8-27</Citation>
<ArticleIdList><ArticleId IdType="pubmed">9431328</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Med Care. 2018 May;56(5):441-447</Citation>
<ArticleIdList><ArticleId IdType="pubmed">29578951</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Tob Induc Dis. 2020 Mar 20;18:20</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32206052</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
<affiliations><list><country><li>République populaire de Chine</li>
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<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>
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