CovidSeniorV1, Main, Exploration, bibRecord, 000336

Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.

Identifieur interne : 000336 ( Main/Exploration ); précédent : 000335; suivant : 000337

Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.

Auteurs : Stefano Figliozzi [Royaume-Uni, Italie] ; Pier Giorgio Masci [Royaume-Uni] ; Navid Ahmadi [Pologne] ; Lara Tondi [Italie] ; Evangelia Koutli [Royaume-Uni] ; Alberto Aimo [Italie] ; Kimon Stamatelopoulos [Grèce] ; Meletios-Athanasios Dimopoulos [Grèce] ; Alida L P. Caforio [Italie] ; Georgios Georgiopoulos [Royaume-Uni, Grèce]

Source :

European journal of clinical investigation [ 1365-2362 ] ; 2020.

RBID : pubmed:32726868

Descripteurs français

English descriptors

KwdEn :
- Acute Disease (MeSH), Acute Kidney Injury (epidemiology), Adrenal Cortex Hormones (therapeutic use), Adult (MeSH), Age Factors (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (MeSH), C-Reactive Protein (metabolism), Cardiovascular Diseases (epidemiology), Cerebrovascular Disorders (epidemiology), Coronavirus Infections (epidemiology), Coronavirus Infections (metabolism), Coronavirus Infections (mortality), Coronavirus Infections (therapy), Diabetes Mellitus (epidemiology), Female (MeSH), Ferritins (metabolism), Fibrin Fibrinogen Degradation Products (metabolism), Heart Diseases (MeSH), Hospital Mortality (MeSH), Hospitalization (MeSH), Humans (MeSH), Hypertension (epidemiology), Intensive Care Units (MeSH), Interleukin-6 (metabolism), Liver Diseases (epidemiology), Lymphopenia (epidemiology), Male (MeSH), Middle Aged (MeSH), Neoplasms (epidemiology), Obesity (epidemiology), Pandemics (MeSH), Pneumonia, Viral (epidemiology), Pneumonia, Viral (metabolism), Pneumonia, Viral (mortality), Pneumonia, Viral (therapy), Procalcitonin (metabolism), Prognosis (MeSH), Pulmonary Disease, Chronic Obstructive (epidemiology), Respiration, Artificial (MeSH), Severity of Illness Index (MeSH), Sex Factors (MeSH), Smoking (epidemiology), Thrombocytopenia (epidemiology), Young Adult (MeSH).
MESH :
- chemical , metabolism : C-Reactive Protein, Ferritins, Fibrin Fibrinogen Degradation Products, Interleukin-6, Procalcitonin.
- chemical , therapeutic use : Adrenal Cortex Hormones.
- epidemiology : Acute Kidney Injury, Cardiovascular Diseases, Cerebrovascular Disorders, Coronavirus Infections, Diabetes Mellitus, Hypertension, Liver Diseases, Lymphopenia, Neoplasms, Obesity, Pneumonia, Viral, Pulmonary Disease, Chronic Obstructive, Smoking, Thrombocytopenia.
- metabolism : Coronavirus Infections, Pneumonia, Viral.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- therapy : Coronavirus Infections, Pneumonia, Viral.
- Acute Disease, Adult, Age Factors, Aged, Aged, 80 and over, Betacoronavirus, Female, Heart Diseases, Hospital Mortality, Hospitalization, Humans, Intensive Care Units, Male, Middle Aged, Pandemics, Prognosis, Respiration, Artificial, Severity of Illness Index, Sex Factors, Young Adult.

Abstract

BACKGROUND

Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management.

METHODS

A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates.

RESULTS

We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality.

CONCLUSIONS

Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.

DOI: 10.1111/eci.13362
PubMed: 32726868

Affiliations:

Grèce, Italie, Pologne, Royaume-Uni
Angleterre, Grand Londres, Lombardie, Toscane
Londres, Milan, Pise
University College de Londres

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Le document en format XML

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<affiliation wicri:level="3"><nlm:affiliation>Department of Cardiovascular Medicine, Humanitas Clinical and Research Center - IRCCS, Milan, Italy.</nlm:affiliation>
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<affiliation wicri:level="3"><nlm:affiliation>Department of Radiology, Humanitas Clinical and Research Center - IRCCS, Milan, Italy.</nlm:affiliation>
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<author><name sortKey="Tondi, Lara" sort="Tondi, Lara" uniqKey="Tondi L" first="Lara" last="Tondi">Lara Tondi</name>
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<author><name sortKey="Koutli, Evangelia" sort="Koutli, Evangelia" uniqKey="Koutli E" first="Evangelia" last="Koutli">Evangelia Koutli</name>
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<country xml:lang="fr">Royaume-Uni</country>
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<author><name sortKey="Aimo, Alberto" sort="Aimo, Alberto" uniqKey="Aimo A" first="Alberto" last="Aimo">Alberto Aimo</name>
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<country xml:lang="fr">Italie</country>
<wicri:regionArea>Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa</wicri:regionArea>
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<affiliation wicri:level="3"><nlm:affiliation>Cardiology Division, University Hospital of Pisa, Pisa, Italy.</nlm:affiliation>
<country xml:lang="fr">Italie</country>
<wicri:regionArea>Cardiology Division, University Hospital of Pisa, Pisa</wicri:regionArea>
<placeName><settlement type="city">Pise</settlement>
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<author><name sortKey="Stamatelopoulos, Kimon" sort="Stamatelopoulos, Kimon" uniqKey="Stamatelopoulos K" first="Kimon" last="Stamatelopoulos">Kimon Stamatelopoulos</name>
<affiliation wicri:level="1"><nlm:affiliation>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.</nlm:affiliation>
<country xml:lang="fr">Grèce</country>
<wicri:regionArea>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen</wicri:regionArea>
<wicri:noRegion>Athen</wicri:noRegion>
</affiliation>
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<author><name sortKey="Dimopoulos, Meletios Athanasios" sort="Dimopoulos, Meletios Athanasios" uniqKey="Dimopoulos M" first="Meletios-Athanasios" last="Dimopoulos">Meletios-Athanasios Dimopoulos</name>
<affiliation wicri:level="1"><nlm:affiliation>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.</nlm:affiliation>
<country xml:lang="fr">Grèce</country>
<wicri:regionArea>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen</wicri:regionArea>
<wicri:noRegion>Athen</wicri:noRegion>
</affiliation>
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<author><name sortKey="Caforio, Alida L P" sort="Caforio, Alida L P" uniqKey="Caforio A" first="Alida L P" last="Caforio">Alida L P. Caforio</name>
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<country xml:lang="fr">Italie</country>
<wicri:regionArea>Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padua Medical School, Padova</wicri:regionArea>
<wicri:noRegion>Padova</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Georgiopoulos, Georgios" sort="Georgiopoulos, Georgios" uniqKey="Georgiopoulos G" first="Georgios" last="Georgiopoulos">Georgios Georgiopoulos</name>
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<series><title level="j">European journal of clinical investigation</title>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Acute Disease (MeSH)</term>
<term>Acute Kidney Injury (epidemiology)</term>
<term>Adrenal Cortex Hormones (therapeutic use)</term>
<term>Adult (MeSH)</term>
<term>Age Factors (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Aged, 80 and over (MeSH)</term>
<term>Betacoronavirus (MeSH)</term>
<term>C-Reactive Protein (metabolism)</term>
<term>Cardiovascular Diseases (epidemiology)</term>
<term>Cerebrovascular Disorders (epidemiology)</term>
<term>Coronavirus Infections (epidemiology)</term>
<term>Coronavirus Infections (metabolism)</term>
<term>Coronavirus Infections (mortality)</term>
<term>Coronavirus Infections (therapy)</term>
<term>Diabetes Mellitus (epidemiology)</term>
<term>Female (MeSH)</term>
<term>Ferritins (metabolism)</term>
<term>Fibrin Fibrinogen Degradation Products (metabolism)</term>
<term>Heart Diseases (MeSH)</term>
<term>Hospital Mortality (MeSH)</term>
<term>Hospitalization (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Hypertension (epidemiology)</term>
<term>Intensive Care Units (MeSH)</term>
<term>Interleukin-6 (metabolism)</term>
<term>Liver Diseases (epidemiology)</term>
<term>Lymphopenia (epidemiology)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Neoplasms (epidemiology)</term>
<term>Obesity (epidemiology)</term>
<term>Pandemics (MeSH)</term>
<term>Pneumonia, Viral (epidemiology)</term>
<term>Pneumonia, Viral (metabolism)</term>
<term>Pneumonia, Viral (mortality)</term>
<term>Pneumonia, Viral (therapy)</term>
<term>Procalcitonin (metabolism)</term>
<term>Prognosis (MeSH)</term>
<term>Pulmonary Disease, Chronic Obstructive (epidemiology)</term>
<term>Respiration, Artificial (MeSH)</term>
<term>Severity of Illness Index (MeSH)</term>
<term>Sex Factors (MeSH)</term>
<term>Smoking (epidemiology)</term>
<term>Thrombocytopenia (epidemiology)</term>
<term>Young Adult (MeSH)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Angiopathies intracrâniennes (épidémiologie)</term>
<term>Atteinte rénale aigüe (épidémiologie)</term>
<term>Betacoronavirus (MeSH)</term>
<term>Broncho-pneumopathie chronique obstructive (épidémiologie)</term>
<term>Cardiopathies (MeSH)</term>
<term>Diabète (épidémiologie)</term>
<term>Facteurs sexuels (MeSH)</term>
<term>Facteurs âges (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>Ferritines (métabolisme)</term>
<term>Fumer (épidémiologie)</term>
<term>Hormones corticosurrénaliennes (usage thérapeutique)</term>
<term>Hospitalisation (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Hypertension artérielle (épidémiologie)</term>
<term>Indice de gravité de la maladie (MeSH)</term>
<term>Infections à coronavirus (mortalité)</term>
<term>Infections à coronavirus (métabolisme)</term>
<term>Infections à coronavirus (thérapie)</term>
<term>Infections à coronavirus (épidémiologie)</term>
<term>Interleukine-6 (métabolisme)</term>
<term>Jeune adulte (MeSH)</term>
<term>Lymphopénie (épidémiologie)</term>
<term>Maladie aigüe (MeSH)</term>
<term>Maladies cardiovasculaires (épidémiologie)</term>
<term>Maladies du foie (épidémiologie)</term>
<term>Mortalité hospitalière (MeSH)</term>
<term>Mâle (MeSH)</term>
<term>Obésité (épidémiologie)</term>
<term>Pandémies (MeSH)</term>
<term>Pneumopathie virale (mortalité)</term>
<term>Pneumopathie virale (métabolisme)</term>
<term>Pneumopathie virale (thérapie)</term>
<term>Pneumopathie virale (épidémiologie)</term>
<term>Procalcitonine (métabolisme)</term>
<term>Produits de dégradation de la fibrine et du fibrinogène (métabolisme)</term>
<term>Pronostic (MeSH)</term>
<term>Protéine C-réactive (métabolisme)</term>
<term>Sujet âgé (MeSH)</term>
<term>Sujet âgé de 80 ans ou plus (MeSH)</term>
<term>Thrombopénie (épidémiologie)</term>
<term>Tumeurs (épidémiologie)</term>
<term>Unités de soins intensifs (MeSH)</term>
<term>Ventilation artificielle (MeSH)</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>C-Reactive Protein</term>
<term>Ferritins</term>
<term>Fibrin Fibrinogen Degradation Products</term>
<term>Interleukin-6</term>
<term>Procalcitonin</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="therapeutic use" xml:lang="en"><term>Adrenal Cortex Hormones</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Acute Kidney Injury</term>
<term>Cardiovascular Diseases</term>
<term>Cerebrovascular Disorders</term>
<term>Coronavirus Infections</term>
<term>Diabetes Mellitus</term>
<term>Hypertension</term>
<term>Liver Diseases</term>
<term>Lymphopenia</term>
<term>Neoplasms</term>
<term>Obesity</term>
<term>Pneumonia, Viral</term>
<term>Pulmonary Disease, Chronic Obstructive</term>
<term>Smoking</term>
<term>Thrombocytopenia</term>
</keywords>
<keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
</keywords>
<keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Ferritines</term>
<term>Infections à coronavirus</term>
<term>Interleukine-6</term>
<term>Pneumopathie virale</term>
<term>Procalcitonine</term>
<term>Produits de dégradation de la fibrine et du fibrinogène</term>
<term>Protéine C-réactive</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="usage thérapeutique" xml:lang="fr"><term>Hormones corticosurrénaliennes</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Angiopathies intracrâniennes</term>
<term>Atteinte rénale aigüe</term>
<term>Broncho-pneumopathie chronique obstructive</term>
<term>Diabète</term>
<term>Fumer</term>
<term>Hypertension artérielle</term>
<term>Infections à coronavirus</term>
<term>Lymphopénie</term>
<term>Maladies cardiovasculaires</term>
<term>Maladies du foie</term>
<term>Obésité</term>
<term>Pneumopathie virale</term>
<term>Thrombopénie</term>
<term>Tumeurs</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Acute Disease</term>
<term>Adult</term>
<term>Age Factors</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
<term>Betacoronavirus</term>
<term>Female</term>
<term>Heart Diseases</term>
<term>Hospital Mortality</term>
<term>Hospitalization</term>
<term>Humans</term>
<term>Intensive Care Units</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pandemics</term>
<term>Prognosis</term>
<term>Respiration, Artificial</term>
<term>Severity of Illness Index</term>
<term>Sex Factors</term>
<term>Young Adult</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Betacoronavirus</term>
<term>Cardiopathies</term>
<term>Facteurs sexuels</term>
<term>Facteurs âges</term>
<term>Femelle</term>
<term>Hospitalisation</term>
<term>Humains</term>
<term>Indice de gravité de la maladie</term>
<term>Jeune adulte</term>
<term>Maladie aigüe</term>
<term>Mortalité hospitalière</term>
<term>Mâle</term>
<term>Pandémies</term>
<term>Pronostic</term>
<term>Sujet âgé</term>
<term>Sujet âgé de 80 ans ou plus</term>
<term>Unités de soins intensifs</term>
<term>Ventilation artificielle</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
</p>
<p>Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.</p>
</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32726868</PMID>
<DateCompleted><Year>2020</Year>
<Month>10</Month>
<Day>02</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>10</Month>
<Day>02</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1365-2362</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>50</Volume>
<Issue>10</Issue>
<PubDate><Year>2020</Year>
<Month>Oct</Month>
</PubDate>
</JournalIssue>
<Title>European journal of clinical investigation</Title>
<ISOAbbreviation>Eur J Clin Invest</ISOAbbreviation>
</Journal>
<ArticleTitle>Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.</ArticleTitle>
<Pagination><MedlinePgn>e13362</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1111/eci.13362</ELocationID>
<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.</AbstractText>
<CopyrightInformation>© 2020 Stichting European Society for Clinical Investigation Journal Foundation.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Figliozzi</LastName>
<ForeName>Stefano</ForeName>
<Initials>S</Initials>
<Identifier Source="ORCID">https://orcid.org/0000-0003-2991-1548</Identifier>
<AffiliationInfo><Affiliation>School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Cardiovascular Medicine, Humanitas Clinical and Research Center - IRCCS, Milan, Italy.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Radiology, Humanitas Clinical and Research Center - IRCCS, Milan, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Masci</LastName>
<ForeName>Pier Giorgio</ForeName>
<Initials>PG</Initials>
<AffiliationInfo><Affiliation>School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ahmadi</LastName>
<ForeName>Navid</ForeName>
<Initials>N</Initials>
<AffiliationInfo><Affiliation>Department of Cardiology-Intensive Therapy, Poznan University of Medical Sciences, Poznan, Poland.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Tondi</LastName>
<ForeName>Lara</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Department of Multimodality Cardiovascular Imaging, IRCCS Policlinico San Donato, San Donato Milanese, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Koutli</LastName>
<ForeName>Evangelia</ForeName>
<Initials>E</Initials>
<AffiliationInfo><Affiliation>Institute for Liver and Digestive Health, Royal Free Hospital & UCL, University College London, London, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Aimo</LastName>
<ForeName>Alberto</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Cardiology Division, University Hospital of Pisa, Pisa, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Stamatelopoulos</LastName>
<ForeName>Kimon</ForeName>
<Initials>K</Initials>
<AffiliationInfo><Affiliation>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Dimopoulos</LastName>
<ForeName>Meletios-Athanasios</ForeName>
<Initials>MA</Initials>
<AffiliationInfo><Affiliation>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Caforio</LastName>
<ForeName>Alida L P</ForeName>
<Initials>ALP</Initials>
<AffiliationInfo><Affiliation>Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padua Medical School, Padova, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Georgiopoulos</LastName>
<ForeName>Georgios</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D017418">Meta-Analysis</PublicationType>
<PublicationType UI="D000078182">Systematic Review</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>08</Month>
<Day>27</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>Eur J Clin Invest</MedlineTA>
<NlmUniqueID>0245331</NlmUniqueID>
<ISSNLinking>0014-2972</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D000305">Adrenal Cortex Hormones</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D005338">Fibrin Fibrinogen Degradation Products</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D015850">Interleukin-6</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D000077740">Procalcitonin</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="C036309">fibrin fragment D</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>9007-41-4</RegistryNumber>
<NameOfSubstance UI="D002097">C-Reactive Protein</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>9007-73-2</RegistryNumber>
<NameOfSubstance UI="D005293">Ferritins</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="D000208" MajorTopicYN="N">Acute Disease</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058186" MajorTopicYN="N">Acute Kidney Injury</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000305" MajorTopicYN="N">Adrenal Cortex Hormones</DescriptorName>
<QualifierName UI="Q000627" MajorTopicYN="N">therapeutic use</QualifierName>
</MeshHeading>
<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="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002097" MajorTopicYN="N">C-Reactive Protein</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002318" MajorTopicYN="N">Cardiovascular Diseases</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002561" MajorTopicYN="N">Cerebrovascular Disorders</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
<QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName>
<QualifierName UI="Q000628" MajorTopicYN="Y">therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D003920" MajorTopicYN="N">Diabetes Mellitus</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005293" MajorTopicYN="N">Ferritins</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005338" MajorTopicYN="N">Fibrin Fibrinogen Degradation Products</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006331" MajorTopicYN="N">Heart Diseases</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D017052" MajorTopicYN="N">Hospital Mortality</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006760" MajorTopicYN="N">Hospitalization</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006973" MajorTopicYN="N">Hypertension</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007362" MajorTopicYN="N">Intensive Care Units</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015850" MajorTopicYN="N">Interleukin-6</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008107" MajorTopicYN="N">Liver Diseases</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008231" MajorTopicYN="N">Lymphopenia</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009369" MajorTopicYN="N">Neoplasms</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009765" MajorTopicYN="N">Obesity</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
<QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName>
<QualifierName UI="Q000628" MajorTopicYN="Y">therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000077740" MajorTopicYN="N">Procalcitonin</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011379" MajorTopicYN="N">Prognosis</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D029424" MajorTopicYN="N">Pulmonary Disease, Chronic Obstructive</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012121" MajorTopicYN="N">Respiration, Artificial</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012720" MajorTopicYN="N">Severity of Illness Index</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012737" MajorTopicYN="N">Sex Factors</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012907" MajorTopicYN="N">Smoking</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D013921" MajorTopicYN="N">Thrombocytopenia</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword>
<Keyword MajorTopicYN="N">meta-analysis</Keyword>
<Keyword MajorTopicYN="N">outcomes</Keyword>
<Keyword MajorTopicYN="N">predictors</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year>
<Month>05</Month>
<Day>31</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2020</Year>
<Month>07</Month>
<Day>10</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>07</Month>
<Day>20</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2020</Year>
<Month>7</Month>
<Day>30</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2020</Year>
<Month>10</Month>
<Day>3</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2020</Year>
<Month>7</Month>
<Day>30</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">32726868</ArticleId>
<ArticleId IdType="doi">10.1111/eci.13362</ArticleId>
</ArticleIdList>
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Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.

Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.

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