CovidChloroV1, Main, Exploration, bibRecord, 000187

Risk Factors for Mortality in Patients with COVID-19 in New York City.

Identifieur interne : 000187 ( Main/Exploration ); précédent : 000186; suivant : 000188

Risk Factors for Mortality in Patients with COVID-19 in New York City.

Auteurs : Takahisa Mikami [États-Unis] ; Hirotaka Miyashita [États-Unis] ; Takayuki Yamada [États-Unis] ; Matthew Harrington [États-Unis] ; Daniel Steinberg [États-Unis] ; Andrew Dunn [États-Unis] ; Evan Siau [États-Unis]

Source :

Journal of general internal medicine [ 1525-1497 ] ; 2021.

RBID : pubmed:32607928

Descripteurs français

KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Comorbidité (MeSH), Estimation de Kaplan-Meier (MeSH), Facteurs de risque (MeSH), Facteurs sexuels (MeSH), Facteurs âges (MeSH), Femelle (MeSH), Hospitalisation (statistiques et données numériques), Humains (MeSH), Modèles des risques proportionnels (MeSH), Mortalité hospitalière (MeSH), Mâle (MeSH), New York (ville) (épidémiologie), Pandémies (MeSH), Soins ambulatoires (statistiques et données numériques), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Études cas-témoins (MeSH), Études rétrospectives (MeSH).
MESH :
- statistiques et données numériques : Hospitalisation, Soins ambulatoires.
- épidémiologie : New York (ville).
- Adulte, Adulte d'âge moyen, Comorbidité, Estimation de Kaplan-Meier, Facteurs de risque, Facteurs sexuels, Facteurs âges, Femelle, Humains, Modèles des risques proportionnels, Mortalité hospitalière, Mâle, Pandémies, Sujet âgé, Sujet âgé de 80 ans ou plus, Études cas-témoins, Études rétrospectives.

English descriptors

KwdEn :
- Adult (MeSH), Age Factors (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Ambulatory Care (statistics & numerical data), COVID-19 (mortality), Case-Control Studies (MeSH), Comorbidity (MeSH), Female (MeSH), Hospital Mortality (MeSH), Hospitalization (statistics & numerical data), Humans (MeSH), Kaplan-Meier Estimate (MeSH), Male (MeSH), Middle Aged (MeSH), New York City (epidemiology), Pandemics (MeSH), Proportional Hazards Models (MeSH), Retrospective Studies (MeSH), Risk Factors (MeSH), SARS-CoV-2 (MeSH), Sex Factors (MeSH).
MESH :
- geographic , epidemiology : New York City.
- mortality : COVID-19.
- statistics & numerical data : Ambulatory Care, Hospitalization.
- Adult, Age Factors, Aged, Aged, 80 and over, Case-Control Studies, Comorbidity, Female, Hospital Mortality, Humans, Kaplan-Meier Estimate, Male, Middle Aged, Pandemics, Proportional Hazards Models, Retrospective Studies, Risk Factors, SARS-CoV-2, Sex Factors.

Abstract

BACKGROUND

New York City emerged as an epicenter of the coronavirus disease 2019 (COVID-19) pandemic.

OBJECTIVE

To describe the clinical characteristics and risk factors associated with mortality in a large patient population in the USA.

DESIGN

Retrospective cohort study.

PARTICIPANTS

6493 patients who had laboratory-confirmed COVID-19 with clinical outcomes between March 13 and April 17, 2020, who were seen in one of the 8 hospitals and/or over 400 ambulatory practices in the New York City metropolitan area MAIN MEASURES: Clinical characteristics and risk factors associated with in-hospital mortality.

KEY RESULTS

A total of 858 of 6493 (13.2%) patients in our total cohort died: 52/2785 (1.9%) ambulatory patients and 806/3708 (21.7%) hospitalized patients. Cox proportional hazard regression modeling showed an increased risk of in-hospital mortality associated with age older than 50 years (hazard ratio [HR] 2.34, CI 1.47-3.71), systolic blood pressure less than 90 mmHg (HR 1.38, CI 1.06-1.80), a respiratory rate greater than 24 per min (HR 1.43, CI 1.13-1.83), peripheral oxygen saturation less than 92% (HR 2.12, CI 1.56-2.88), estimated glomerular filtration rate less than 60 mL/min/1.73m

CONCLUSIONS

Among patients with COVID-19, older age, male sex, hypotension, tachypnea, hypoxia, impaired renal function, elevated D-dimer, and elevated troponin were associated with increased in-hospital mortality and hydroxychloroquine use was associated with decreased in-hospital mortality.

DOI: 10.1007/s11606-020-05983-z
PubMed: 32607928
PubMed Central: PMC7325642

Affiliations:

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

to stream Main, to step Corpus: 001263
to stream Main, to step Curation: 001263

Le document en format XML

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<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
</p>
<p>New York City emerged as an epicenter of the coronavirus disease 2019 (COVID-19) pandemic.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b>
</p>
<p>To describe the clinical characteristics and risk factors associated with mortality in a large patient population in the USA.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>DESIGN</b>
</p>
<p>Retrospective cohort study.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>PARTICIPANTS</b>
</p>
<p>6493 patients who had laboratory-confirmed COVID-19 with clinical outcomes between March 13 and April 17, 2020, who were seen in one of the 8 hospitals and/or over 400 ambulatory practices in the New York City metropolitan area MAIN MEASURES: Clinical characteristics and risk factors associated with in-hospital mortality.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>KEY RESULTS</b>
</p>
<p>A total of 858 of 6493 (13.2%) patients in our total cohort died: 52/2785 (1.9%) ambulatory patients and 806/3708 (21.7%) hospitalized patients. Cox proportional hazard regression modeling showed an increased risk of in-hospital mortality associated with age older than 50 years (hazard ratio [HR] 2.34, CI 1.47-3.71), systolic blood pressure less than 90 mmHg (HR 1.38, CI 1.06-1.80), a respiratory rate greater than 24 per min (HR 1.43, CI 1.13-1.83), peripheral oxygen saturation less than 92% (HR 2.12, CI 1.56-2.88), estimated glomerular filtration rate less than 60 mL/min/1.73m</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>Among patients with COVID-19, older age, male sex, hypotension, tachypnea, hypoxia, impaired renal function, elevated D-dimer, and elevated troponin were associated with increased in-hospital mortality and hydroxychloroquine use was associated with decreased in-hospital mortality.</p>
</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32607928</PMID>
<DateCompleted><Year>2021</Year>
<Month>02</Month>
<Day>12</Day>
</DateCompleted>
<DateRevised><Year>2021</Year>
<Month>03</Month>
<Day>12</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1525-1497</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>36</Volume>
<Issue>1</Issue>
<PubDate><Year>2021</Year>
<Month>01</Month>
</PubDate>
</JournalIssue>
<Title>Journal of general internal medicine</Title>
<ISOAbbreviation>J Gen Intern Med</ISOAbbreviation>
</Journal>
<ArticleTitle>Risk Factors for Mortality in Patients with COVID-19 in New York City.</ArticleTitle>
<Pagination><MedlinePgn>17-26</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1007/s11606-020-05983-z</ELocationID>
<Abstract><AbstractText Label="BACKGROUND">New York City emerged as an epicenter of the coronavirus disease 2019 (COVID-19) pandemic.</AbstractText>
<AbstractText Label="OBJECTIVE">To describe the clinical characteristics and risk factors associated with mortality in a large patient population in the USA.</AbstractText>
<AbstractText Label="DESIGN">Retrospective cohort study.</AbstractText>
<AbstractText Label="PARTICIPANTS">6493 patients who had laboratory-confirmed COVID-19 with clinical outcomes between March 13 and April 17, 2020, who were seen in one of the 8 hospitals and/or over 400 ambulatory practices in the New York City metropolitan area MAIN MEASURES: Clinical characteristics and risk factors associated with in-hospital mortality.</AbstractText>
<AbstractText Label="KEY RESULTS">A total of 858 of 6493 (13.2%) patients in our total cohort died: 52/2785 (1.9%) ambulatory patients and 806/3708 (21.7%) hospitalized patients. Cox proportional hazard regression modeling showed an increased risk of in-hospital mortality associated with age older than 50 years (hazard ratio [HR] 2.34, CI 1.47-3.71), systolic blood pressure less than 90 mmHg (HR 1.38, CI 1.06-1.80), a respiratory rate greater than 24 per min (HR 1.43, CI 1.13-1.83), peripheral oxygen saturation less than 92% (HR 2.12, CI 1.56-2.88), estimated glomerular filtration rate less than 60 mL/min/1.73m<sup>2</sup>
 (HR 1.80, CI 1.60-2.02), IL-6 greater than 100 pg/mL (HR 1.50, CI 1.12-2.03), D-dimer greater than 2 mcg/mL (HR 1.19, CI 1.02-1.39), and troponin greater than 0.03 ng/mL (HR 1.40, CI 1.23-1.62). Decreased risk of in-hospital mortality was associated with female sex (HR 0.84, CI 0.77-0.90), African American race (HR 0.78 CI 0.65-0.95), and hydroxychloroquine use (HR 0.53, CI 0.41-0.67).</AbstractText>
<AbstractText Label="CONCLUSIONS">Among patients with COVID-19, older age, male sex, hypotension, tachypnea, hypoxia, impaired renal function, elevated D-dimer, and elevated troponin were associated with increased in-hospital mortality and hydroxychloroquine use was associated with decreased in-hospital mortality.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Mikami</LastName>
<ForeName>Takahisa</ForeName>
<Initials>T</Initials>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Beth Israel, 281 First Ave, Box #218, New York, 10003, NY, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Miyashita</LastName>
<ForeName>Hirotaka</ForeName>
<Initials>H</Initials>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Beth Israel, 281 First Ave, Box #218, New York, 10003, NY, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Yamada</LastName>
<ForeName>Takayuki</ForeName>
<Initials>T</Initials>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Beth Israel, 281 First Ave, Box #218, New York, 10003, NY, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Harrington</LastName>
<ForeName>Matthew</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Beth Israel, 281 First Ave, Box #218, New York, 10003, NY, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Steinberg</LastName>
<ForeName>Daniel</ForeName>
<Initials>D</Initials>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Beth Israel, 281 First Ave, Box #218, New York, 10003, NY, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Dunn</LastName>
<ForeName>Andrew</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Hospital, New York, NY, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Siau</LastName>
<ForeName>Evan</ForeName>
<Initials>E</Initials>
<Identifier Source="ORCID">0000-0002-9765-4187</Identifier>
<AffiliationInfo><Affiliation>Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Evan.Siau@mountsinai.org.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medicine, Mount Sinai Beth Israel, 281 First Ave, Box #218, New York, 10003, NY, USA. Evan.Siau@mountsinai.org.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>06</Month>
<Day>30</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>J Gen Intern Med</MedlineTA>
<NlmUniqueID>8605834</NlmUniqueID>
<ISSNLinking>0884-8734</ISSNLinking>
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<CitationSubset>IM</CitationSubset>
<CommentsCorrectionsList><CommentsCorrections RefType="CommentIn"><RefSource>Int J Infect Dis. 2020 Oct;99:138-139</RefSource>
<PMID Version="1">32745629</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="CommentIn"><RefSource>J Gen Intern Med. 2021 Mar;36(3):811-812</RefSource>
<PMID Version="1">33432434</PMID>
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</CommentsCorrectionsList>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000367" MajorTopicYN="N">Age Factors</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="D000553" MajorTopicYN="N">Ambulatory Care</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName>
<QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016022" MajorTopicYN="N">Case-Control Studies</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015897" MajorTopicYN="N">Comorbidity</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D017052" MajorTopicYN="Y">Hospital Mortality</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006760" MajorTopicYN="N">Hospitalization</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D053208" MajorTopicYN="N">Kaplan-Meier Estimate</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009519" MajorTopicYN="N" Type="Geographic">New York City</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016016" MajorTopicYN="N">Proportional Hazards Models</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012189" MajorTopicYN="N">Retrospective Studies</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012737" MajorTopicYN="N">Sex Factors</DescriptorName>
</MeshHeading>
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<Month>05</Month>
<Day>06</Day>
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<Day>11</Day>
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<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>État de New York</li>
</region>
</list>
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<name sortKey="Dunn, Andrew" sort="Dunn, Andrew" uniqKey="Dunn A" first="Andrew" last="Dunn">Andrew Dunn</name>
<name sortKey="Dunn, Andrew" sort="Dunn, Andrew" uniqKey="Dunn A" first="Andrew" last="Dunn">Andrew Dunn</name>
<name sortKey="Harrington, Matthew" sort="Harrington, Matthew" uniqKey="Harrington M" first="Matthew" last="Harrington">Matthew Harrington</name>
<name sortKey="Harrington, Matthew" sort="Harrington, Matthew" uniqKey="Harrington M" first="Matthew" last="Harrington">Matthew Harrington</name>
<name sortKey="Mikami, Takahisa" sort="Mikami, Takahisa" uniqKey="Mikami T" first="Takahisa" last="Mikami">Takahisa Mikami</name>
<name sortKey="Miyashita, Hirotaka" sort="Miyashita, Hirotaka" uniqKey="Miyashita H" first="Hirotaka" last="Miyashita">Hirotaka Miyashita</name>
<name sortKey="Miyashita, Hirotaka" sort="Miyashita, Hirotaka" uniqKey="Miyashita H" first="Hirotaka" last="Miyashita">Hirotaka Miyashita</name>
<name sortKey="Siau, Evan" sort="Siau, Evan" uniqKey="Siau E" first="Evan" last="Siau">Evan Siau</name>
<name sortKey="Siau, Evan" sort="Siau, Evan" uniqKey="Siau E" first="Evan" last="Siau">Evan Siau</name>
<name sortKey="Steinberg, Daniel" sort="Steinberg, Daniel" uniqKey="Steinberg D" first="Daniel" last="Steinberg">Daniel Steinberg</name>
<name sortKey="Steinberg, Daniel" sort="Steinberg, Daniel" uniqKey="Steinberg D" first="Daniel" last="Steinberg">Daniel Steinberg</name>
<name sortKey="Yamada, Takayuki" sort="Yamada, Takayuki" uniqKey="Yamada T" first="Takayuki" last="Yamada">Takayuki Yamada</name>
<name sortKey="Yamada, Takayuki" sort="Yamada, Takayuki" uniqKey="Yamada T" first="Takayuki" last="Yamada">Takayuki Yamada</name>
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Risk Factors for Mortality in Patients with COVID-19 in New York City.

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