CovidSeniorV1, Main, Exploration, bibRecord, 000127

Thrombo-inflammatory features predicting mortality in patients with COVID-19: The FAD-85 score.

Identifieur interne : 000127 ( Main/Exploration ); précédent : 000126; suivant : 000128

Thrombo-inflammatory features predicting mortality in patients with COVID-19: The FAD-85 score.

Auteurs : Junhong Wang [République populaire de Chine] ; Hua Zhang [République populaire de Chine] ; Rui Qiao [République populaire de Chine] ; Qinggang Ge [République populaire de Chine] ; Shuisheng Zhang [République populaire de Chine] ; Zongxuan Zhao [République populaire de Chine] ; Ci Tian [République populaire de Chine] ; Qingbian Ma [République populaire de Chine] ; Ning Shen [République populaire de Chine]

Source :

The Journal of international medical research [ 1473-2300 ] ; 2020.

RBID : pubmed:32960106

Descripteurs français

English descriptors

KwdEn :
- Adult (MeSH), Aged (MeSH), Betacoronavirus (pathogenicity), Biomarkers (blood), Coronavirus Infections (complications), Coronavirus Infections (diagnosis), Coronavirus Infections (mortality), Coronavirus Infections (virology), Disseminated Intravascular Coagulation (complications), Disseminated Intravascular Coagulation (diagnosis), Disseminated Intravascular Coagulation (mortality), Disseminated Intravascular Coagulation (virology), Female (MeSH), Ferritins (blood), Fibrin Fibrinogen Degradation Products (metabolism), Humans (MeSH), Interleukin-6 (blood), Logistic Models (MeSH), Male (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Pneumonia, Viral (complications), Pneumonia, Viral (diagnosis), Pneumonia, Viral (mortality), Pneumonia, Viral (virology), Prognosis (MeSH), Research Design (MeSH), Retrospective Studies (MeSH), Serum Albumin (metabolism), Severity of Illness Index (MeSH), Survival Analysis (MeSH), Thrombosis (complications), Thrombosis (diagnosis), Thrombosis (mortality), Thrombosis (virology), Tumor Necrosis Factor-alpha (blood).
MESH :
- chemical , blood : Biomarkers, Ferritins, Interleukin-6, Tumor Necrosis Factor-alpha.
- complications : Coronavirus Infections, Disseminated Intravascular Coagulation, Pneumonia, Viral, Thrombosis.
- diagnosis : Coronavirus Infections, Disseminated Intravascular Coagulation, Pneumonia, Viral, Thrombosis.
- chemical , metabolism : Fibrin Fibrinogen Degradation Products, Serum Albumin.
- mortality : Coronavirus Infections, Disseminated Intravascular Coagulation, Pneumonia, Viral, Thrombosis.
- pathogenicity : Betacoronavirus.
- virology : Coronavirus Infections, Disseminated Intravascular Coagulation, Pneumonia, Viral, Thrombosis.
- Adult, Aged, Female, Humans, Logistic Models, Male, Middle Aged, Pandemics, Prognosis, Research Design, Retrospective Studies, Severity of Illness Index, Survival Analysis.

Abstract

BACKGROUND

The roles of inflammation and hypercoagulation in predicting outcomes of coronavirus disease 2019 (COVID-19) are unclear.

METHODS

Adult patients diagnosed with COVID-19 from 28 January 2020 to 4 March 2020 in Tongji Hospital, Wuhan were recruited. Data on related parameters were collected. Univariate analysis and multivariable binary logistic regression were used to explore predictors of critical illness and mortality.

RESULTS

In total, 199 and 44 patients were enrolled in the training and testing sets, respectively. Elevated ferritin, tumor necrosis factor-α and D-dimer and decreased albumin concentration were associated with disease severity. Older age, elevated ferritin and elevated interleukin-6 were associated with 28-day mortality. The FAD-85 score, defined as age + 0.01 * ferritin +D-dimer, was used to predict risk of mortality. The sensitivity, specificity and accuracy of FAD-85 were 86.4%, 81.8% and 86.4%, respectively. A nomogram was established using age, ferritin and D-dimer to predict the risk of 28-day mortality.

CONCLUSIONS

Thrombo-inflammatory parameters provide key information on the severity and prognosis of COVID-19 and can be used as references for clinical treatment to correct inflammatory and coagulation abnormalities.

DOI: 10.1177/0300060520955037
PubMed: 32960106
PubMed Central: PMC7511832

Affiliations:

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Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Betacoronavirus (pathogenicity)</term>
<term>Biomarkers (blood)</term>
<term>Coronavirus Infections (complications)</term>
<term>Coronavirus Infections (diagnosis)</term>
<term>Coronavirus Infections (mortality)</term>
<term>Coronavirus Infections (virology)</term>
<term>Disseminated Intravascular Coagulation (complications)</term>
<term>Disseminated Intravascular Coagulation (diagnosis)</term>
<term>Disseminated Intravascular Coagulation (mortality)</term>
<term>Disseminated Intravascular Coagulation (virology)</term>
<term>Female (MeSH)</term>
<term>Ferritins (blood)</term>
<term>Fibrin Fibrinogen Degradation Products (metabolism)</term>
<term>Humans (MeSH)</term>
<term>Interleukin-6 (blood)</term>
<term>Logistic Models (MeSH)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Pandemics (MeSH)</term>
<term>Pneumonia, Viral (complications)</term>
<term>Pneumonia, Viral (diagnosis)</term>
<term>Pneumonia, Viral (mortality)</term>
<term>Pneumonia, Viral (virology)</term>
<term>Prognosis (MeSH)</term>
<term>Research Design (MeSH)</term>
<term>Retrospective Studies (MeSH)</term>
<term>Serum Albumin (metabolism)</term>
<term>Severity of Illness Index (MeSH)</term>
<term>Survival Analysis (MeSH)</term>
<term>Thrombosis (complications)</term>
<term>Thrombosis (diagnosis)</term>
<term>Thrombosis (mortality)</term>
<term>Thrombosis (virology)</term>
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<term>Adulte d'âge moyen (MeSH)</term>
<term>Analyse de survie (MeSH)</term>
<term>Betacoronavirus (pathogénicité)</term>
<term>Coagulation intravasculaire disséminée (complications)</term>
<term>Coagulation intravasculaire disséminée (diagnostic)</term>
<term>Coagulation intravasculaire disséminée (mortalité)</term>
<term>Coagulation intravasculaire disséminée (virologie)</term>
<term>Facteur de nécrose tumorale alpha (sang)</term>
<term>Femelle (MeSH)</term>
<term>Ferritines (sang)</term>
<term>Humains (MeSH)</term>
<term>Indice de gravité de la maladie (MeSH)</term>
<term>Infections à coronavirus (complications)</term>
<term>Infections à coronavirus (diagnostic)</term>
<term>Infections à coronavirus (mortalité)</term>
<term>Infections à coronavirus (virologie)</term>
<term>Interleukine-6 (sang)</term>
<term>Marqueurs biologiques (sang)</term>
<term>Modèles logistiques (MeSH)</term>
<term>Mâle (MeSH)</term>
<term>Pandémies (MeSH)</term>
<term>Plan de recherche (MeSH)</term>
<term>Pneumopathie virale (complications)</term>
<term>Pneumopathie virale (diagnostic)</term>
<term>Pneumopathie virale (mortalité)</term>
<term>Pneumopathie virale (virologie)</term>
<term>Produits de dégradation de la fibrine et du fibrinogène (métabolisme)</term>
<term>Pronostic (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
<term>Sérumalbumine (métabolisme)</term>
<term>Thrombose (complications)</term>
<term>Thrombose (diagnostic)</term>
<term>Thrombose (mortalité)</term>
<term>Thrombose (virologie)</term>
<term>Études rétrospectives (MeSH)</term>
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<term>Ferritins</term>
<term>Interleukin-6</term>
<term>Tumor Necrosis Factor-alpha</term>
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<term>Disseminated Intravascular Coagulation</term>
<term>Pneumonia, Viral</term>
<term>Thrombosis</term>
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<term>Pneumonia, Viral</term>
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<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Thrombose</term>
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<keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Fibrin Fibrinogen Degradation Products</term>
<term>Serum Albumin</term>
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<keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term>
<term>Disseminated Intravascular Coagulation</term>
<term>Pneumonia, Viral</term>
<term>Thrombosis</term>
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<keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Coagulation intravasculaire disséminée</term>
<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Thrombose</term>
</keywords>
<keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Produits de dégradation de la fibrine et du fibrinogène</term>
<term>Sérumalbumine</term>
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<keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>Betacoronavirus</term>
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<keywords scheme="MESH" qualifier="pathogénicité" xml:lang="fr"><term>Betacoronavirus</term>
</keywords>
<keywords scheme="MESH" qualifier="sang" xml:lang="fr"><term>Coagulation intravasculaire disséminée</term>
<term>Facteur de nécrose tumorale alpha</term>
<term>Ferritines</term>
<term>Infections à coronavirus</term>
<term>Interleukine-6</term>
<term>Marqueurs biologiques</term>
<term>Pneumopathie virale</term>
<term>Thrombose</term>
</keywords>
<keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Coagulation intravasculaire disséminée</term>
<term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Thrombose</term>
</keywords>
<keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term>
<term>Disseminated Intravascular Coagulation</term>
<term>Pneumonia, Viral</term>
<term>Thrombosis</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Aged</term>
<term>Female</term>
<term>Humans</term>
<term>Logistic Models</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pandemics</term>
<term>Prognosis</term>
<term>Research Design</term>
<term>Retrospective Studies</term>
<term>Severity of Illness Index</term>
<term>Survival Analysis</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Analyse de survie</term>
<term>Femelle</term>
<term>Humains</term>
<term>Indice de gravité de la maladie</term>
<term>Modèles logistiques</term>
<term>Mâle</term>
<term>Pandémies</term>
<term>Plan de recherche</term>
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<term>Sujet âgé</term>
<term>Études rétrospectives</term>
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<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
</p>
<p>The roles of inflammation and hypercoagulation in predicting outcomes of coronavirus disease 2019 (COVID-19) are unclear.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>Adult patients diagnosed with COVID-19 from 28 January 2020 to 4 March 2020 in Tongji Hospital, Wuhan were recruited. Data on related parameters were collected. Univariate analysis and multivariable binary logistic regression were used to explore predictors of critical illness and mortality.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>In total, 199 and 44 patients were enrolled in the training and testing sets, respectively. Elevated ferritin, tumor necrosis factor-α and D-dimer and decreased albumin concentration were associated with disease severity. Older age, elevated ferritin and elevated interleukin-6 were associated with 28-day mortality. The FAD-85 score, defined as age + 0.01 * ferritin +D-dimer, was used to predict risk of mortality. The sensitivity, specificity and accuracy of FAD-85 were 86.4%, 81.8% and 86.4%, respectively. A nomogram was established using age, ferritin and D-dimer to predict the risk of 28-day mortality.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>Thrombo-inflammatory parameters provide key information on the severity and prognosis of COVID-19 and can be used as references for clinical treatment to correct inflammatory and coagulation abnormalities.</p>
</div>
</front>
</TEI>
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<Month>10</Month>
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<JournalIssue CitedMedium="Internet"><Volume>48</Volume>
<Issue>9</Issue>
<PubDate><Year>2020</Year>
<Month>Sep</Month>
</PubDate>
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<Title>The Journal of international medical research</Title>
<ISOAbbreviation>J Int Med Res</ISOAbbreviation>
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<ArticleTitle>Thrombo-inflammatory features predicting mortality in patients with COVID-19: The FAD-85 score.</ArticleTitle>
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<ELocationID EIdType="doi" ValidYN="Y">10.1177/0300060520955037</ELocationID>
<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">The roles of inflammation and hypercoagulation in predicting outcomes of coronavirus disease 2019 (COVID-19) are unclear.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">Adult patients diagnosed with COVID-19 from 28 January 2020 to 4 March 2020 in Tongji Hospital, Wuhan were recruited. Data on related parameters were collected. Univariate analysis and multivariable binary logistic regression were used to explore predictors of critical illness and mortality.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">In total, 199 and 44 patients were enrolled in the training and testing sets, respectively. Elevated ferritin, tumor necrosis factor-α and D-dimer and decreased albumin concentration were associated with disease severity. Older age, elevated ferritin and elevated interleukin-6 were associated with 28-day mortality. The FAD-85 score, defined as age + 0.01 * ferritin +D-dimer, was used to predict risk of mortality. The sensitivity, specificity and accuracy of FAD-85 were 86.4%, 81.8% and 86.4%, respectively. A nomogram was established using age, ferritin and D-dimer to predict the risk of 28-day mortality.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Thrombo-inflammatory parameters provide key information on the severity and prognosis of COVID-19 and can be used as references for clinical treatment to correct inflammatory and coagulation abnormalities.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Junhong</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Emergency Department, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Hua</ForeName>
<Initials>H</Initials>
<AffiliationInfo><Affiliation>Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Qiao</LastName>
<ForeName>Rui</ForeName>
<Initials>R</Initials>
<AffiliationInfo><Affiliation>Department of Clinical Laboratory Medicine, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ge</LastName>
<ForeName>Qinggang</ForeName>
<Initials>Q</Initials>
<AffiliationInfo><Affiliation>Department of Critical Care Medicine, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Shuisheng</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Department of General Surgery, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhao</LastName>
<ForeName>Zongxuan</ForeName>
<Initials>Z</Initials>
<AffiliationInfo><Affiliation>The Third School of Clinical Medicine, Peking University, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
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<ForeName>Ci</ForeName>
<Initials>C</Initials>
<Identifier Source="ORCID">https://orcid.org/0000-0002-6569-9364</Identifier>
<AffiliationInfo><Affiliation>Emergency Department, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Ma</LastName>
<ForeName>Qingbian</ForeName>
<Initials>Q</Initials>
<AffiliationInfo><Affiliation>Emergency Department, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Shen</LastName>
<ForeName>Ning</ForeName>
<Initials>N</Initials>
<Identifier Source="ORCID">https://orcid.org/0000-0003-2352-0677</Identifier>
<AffiliationInfo><Affiliation>Department of Respiratory and Critical Medicine, Peking University Third Hospital, Beijing, China.</Affiliation>
</AffiliationInfo>
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<Language>eng</Language>
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<MedlineJournalInfo><Country>England</Country>
<MedlineTA>J Int Med Res</MedlineTA>
<NlmUniqueID>0346411</NlmUniqueID>
<ISSNLinking>0300-0605</ISSNLinking>
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<NameOfSubstance UI="D015415">Biomarkers</NameOfSubstance>
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</MeshHeading>
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<QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName>
</MeshHeading>
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<QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName>
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<QualifierName UI="Q000150" MajorTopicYN="N">complications</QualifierName>
<QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName>
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<affiliations><list><country><li>République populaire de Chine</li>
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Thrombo-inflammatory features predicting mortality in patients with COVID-19: The FAD-85 score.

Thrombo-inflammatory features predicting mortality in patients with COVID-19: The FAD-85 score.

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