CovidSeniorV1, Main, Exploration, bibRecord, 000657

Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients.

Identifieur interne : 000657 ( Main/Exploration ); précédent : 000656; suivant : 000658

Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients.

Auteurs : Rami M. Elshazli [Égypte] ; Eman A. Toraih [États-Unis, Égypte] ; Abdelaziz Elgaml [Égypte] ; Mohammed El-Mowafy [Égypte] ; Mohamed El-Mesery [Égypte] ; Mohamed N. Amin [Égypte] ; Mohammad H. Hussein [États-Unis] ; Mary T. Killackey [États-Unis] ; Manal S. Fawzy [Égypte] ; Emad Kandil [États-Unis]

Source :

PloS one [ 1932-6203 ] ; 2020.

RBID : pubmed:32822430

Descripteurs français

English descriptors

KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (MeSH), Biomarkers (blood), Blood Sedimentation (MeSH), C-Reactive Protein (analysis), Child (MeSH), Coronavirus Infections (blood), Coronavirus Infections (diagnosis), Coronavirus Infections (immunology), Coronavirus Infections (virology), Female (MeSH), Fibrin Fibrinogen Degradation Products (analysis), Humans (MeSH), Interleukin-10 (blood), Interleukin-6 (blood), Leukocyte Count (MeSH), Male (MeSH), Middle Aged (MeSH), Neutrophils (MeSH), Pandemics (MeSH), Pneumonia, Viral (blood), Pneumonia, Viral (diagnosis), Pneumonia, Viral (immunology), Pneumonia, Viral (virology), Procalcitonin (blood), Prognosis (MeSH), Prothrombin Time (MeSH), Young Adult (MeSH).
MESH :
- chemical , analysis : C-Reactive Protein, Fibrin Fibrinogen Degradation Products.
- chemical , blood : Biomarkers, Interleukin-10, Interleukin-6, Procalcitonin.
- blood : Coronavirus Infections, Pneumonia, Viral.
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- immunology : Coronavirus Infections, Pneumonia, Viral.
- virology : Coronavirus Infections, Pneumonia, Viral.
- Adolescent, Adult, Aged, Aged, 80 and over, Betacoronavirus, Blood Sedimentation, Child, Female, Humans, Leukocyte Count, Male, Middle Aged, Neutrophils, Pandemics, Prognosis, Prothrombin Time, Young Adult.

Abstract

OBJECTIVE

Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers.

METHODS

Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to the Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease.

RESULTS

Cohorts with elevated levels of white blood cells (WBCs) (OR = 1.75), neutrophil count (OR = 2.62), D-dimer (OR = 3.97), prolonged prothrombin time (PT) (OR = 1.82), fibrinogen (OR = 3.14), erythrocyte sedimentation rate (OR = 1.60), procalcitonin (OR = 4.76), IL-6 (OR = 2.10), and IL-10 (OR = 4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity = 100%, specificity = 81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74x109/L for identifying patients at high risk of severe COVID-19. Likewise, ICU admission was associated with higher levels of WBCs (OR = 5.21), neutrophils (OR = 6.25), D-dimer (OR = 4.19), and prolonged PT (OR = 2.18). Patients with high IL-6 (OR = 13.87), CRP (OR = 7.09), D-dimer (OR = 6.36), and neutrophils (OR = 6.25) had the highest likelihood of mortality.

CONCLUSIONS

Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.

DOI: 10.1371/journal.pone.0238160
PubMed: 32822430
PubMed Central: PMC7446892

Affiliations:

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Le document en format XML

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<term>Adult (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Aged, 80 and over (MeSH)</term>
<term>Betacoronavirus (MeSH)</term>
<term>Biomarkers (blood)</term>
<term>Blood Sedimentation (MeSH)</term>
<term>C-Reactive Protein (analysis)</term>
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<term>Coronavirus Infections (blood)</term>
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<term>Coronavirus Infections (immunology)</term>
<term>Coronavirus Infections (virology)</term>
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<term>Interleukin-6 (blood)</term>
<term>Leukocyte Count (MeSH)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Neutrophils (MeSH)</term>
<term>Pandemics (MeSH)</term>
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<term>Pneumonia, Viral (diagnosis)</term>
<term>Pneumonia, Viral (immunology)</term>
<term>Pneumonia, Viral (virology)</term>
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<term>Prothrombin Time (MeSH)</term>
<term>Young Adult (MeSH)</term>
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<term>Adulte (MeSH)</term>
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<term>Femelle (MeSH)</term>
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<term>Humains (MeSH)</term>
<term>Infections à coronavirus (diagnostic)</term>
<term>Infections à coronavirus (immunologie)</term>
<term>Infections à coronavirus (sang)</term>
<term>Infections à coronavirus (virologie)</term>
<term>Interleukine-10 (sang)</term>
<term>Interleukine-6 (sang)</term>
<term>Jeune adulte (MeSH)</term>
<term>Marqueurs biologiques (sang)</term>
<term>Mâle (MeSH)</term>
<term>Numération des leucocytes (MeSH)</term>
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<term>Pneumopathie virale (immunologie)</term>
<term>Pneumopathie virale (sang)</term>
<term>Pneumopathie virale (virologie)</term>
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<term>Sujet âgé (MeSH)</term>
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<term>Sédimentation du sang (MeSH)</term>
<term>Temps de prothrombine (MeSH)</term>
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<keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>C-Reactive Protein</term>
<term>Fibrin Fibrinogen Degradation Products</term>
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<term>Interleukin-10</term>
<term>Interleukin-6</term>
<term>Procalcitonin</term>
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<term>Protéine C-réactive</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>
</keywords>
<keywords scheme="MESH" qualifier="sang" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Interleukine-10</term>
<term>Interleukine-6</term>
<term>Marqueurs biologiques</term>
<term>Pneumopathie virale</term>
<term>Procalcitonine</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>
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<term>Adult</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
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<keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term>
<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Betacoronavirus</term>
<term>Enfant</term>
<term>Femelle</term>
<term>Granulocytes neutrophiles</term>
<term>Humains</term>
<term>Jeune adulte</term>
<term>Mâle</term>
<term>Numération des leucocytes</term>
<term>Pandémies</term>
<term>Pronostic</term>
<term>Sujet âgé</term>
<term>Sujet âgé de 80 ans ou plus</term>
<term>Sédimentation du sang</term>
<term>Temps de prothrombine</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b>
</p>
<p>Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to the Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>Cohorts with elevated levels of white blood cells (WBCs) (OR = 1.75), neutrophil count (OR = 2.62), D-dimer (OR = 3.97), prolonged prothrombin time (PT) (OR = 1.82), fibrinogen (OR = 3.14), erythrocyte sedimentation rate (OR = 1.60), procalcitonin (OR = 4.76), IL-6 (OR = 2.10), and IL-10 (OR = 4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity = 100%, specificity = 81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74x109/L for identifying patients at high risk of severe COVID-19. Likewise, ICU admission was associated with higher levels of WBCs (OR = 5.21), neutrophils (OR = 6.25), D-dimer (OR = 4.19), and prolonged PT (OR = 2.18). Patients with high IL-6 (OR = 13.87), CRP (OR = 7.09), D-dimer (OR = 6.36), and neutrophils (OR = 6.25) had the highest likelihood of mortality.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.</p>
</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32822430</PMID>
<DateCompleted><Year>2020</Year>
<Month>09</Month>
<Day>01</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>09</Month>
<Day>01</Day>
</DateRevised>
<Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>15</Volume>
<Issue>8</Issue>
<PubDate><Year>2020</Year>
</PubDate>
</JournalIssue>
<Title>PloS one</Title>
<ISOAbbreviation>PLoS One</ISOAbbreviation>
</Journal>
<ArticleTitle>Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients.</ArticleTitle>
<Pagination><MedlinePgn>e0238160</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0238160</ELocationID>
<Abstract><AbstractText Label="OBJECTIVE">Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers.</AbstractText>
<AbstractText Label="METHODS">Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to the Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease.</AbstractText>
<AbstractText Label="RESULTS">Cohorts with elevated levels of white blood cells (WBCs) (OR = 1.75), neutrophil count (OR = 2.62), D-dimer (OR = 3.97), prolonged prothrombin time (PT) (OR = 1.82), fibrinogen (OR = 3.14), erythrocyte sedimentation rate (OR = 1.60), procalcitonin (OR = 4.76), IL-6 (OR = 2.10), and IL-10 (OR = 4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity = 100%, specificity = 81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74x109/L for identifying patients at high risk of severe COVID-19. Likewise, ICU admission was associated with higher levels of WBCs (OR = 5.21), neutrophils (OR = 6.25), D-dimer (OR = 4.19), and prolonged PT (OR = 2.18). Patients with high IL-6 (OR = 13.87), CRP (OR = 7.09), D-dimer (OR = 6.36), and neutrophils (OR = 6.25) had the highest likelihood of mortality.</AbstractText>
<AbstractText Label="CONCLUSIONS">Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Elshazli</LastName>
<ForeName>Rami M</ForeName>
<Initials>RM</Initials>
<Identifier Source="ORCID">0000-0002-3381-2641</Identifier>
<AffiliationInfo><Affiliation>Department of Biochemistry and Molecular Genetics, Faculty of Physical Therapy, Horus University - Egypt, New Damietta, Egypt.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Toraih</LastName>
<ForeName>Eman A</ForeName>
<Initials>EA</Initials>
<Identifier Source="ORCID">0000-0001-9267-3787</Identifier>
<AffiliationInfo><Affiliation>Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, United States of America.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Genetics Unit, Department of Histology and Cell Biology, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Elgaml</LastName>
<ForeName>Abdelaziz</ForeName>
<Initials>A</Initials>
<Identifier Source="ORCID">0000-0001-6790-5849</Identifier>
<AffiliationInfo><Affiliation>Department of Microbiology and Immunology, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Microbiology and Immunology, Faculty of Pharmacy, Horus University - Egypt, New Damietta, Egypt.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>El-Mowafy</LastName>
<ForeName>Mohammed</ForeName>
<Initials>M</Initials>
<Identifier Source="ORCID">0000-0002-4375-5724</Identifier>
<AffiliationInfo><Affiliation>Department of Microbiology and Immunology, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>El-Mesery</LastName>
<ForeName>Mohamed</ForeName>
<Initials>M</Initials>
<Identifier Source="ORCID">0000-0003-2649-3002</Identifier>
<AffiliationInfo><Affiliation>Department of Biochemistry, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Amin</LastName>
<ForeName>Mohamed N</ForeName>
<Initials>MN</Initials>
<AffiliationInfo><Affiliation>Department of Biochemistry, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hussein</LastName>
<ForeName>Mohammad H</ForeName>
<Initials>MH</Initials>
<AffiliationInfo><Affiliation>Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, United States of America.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Killackey</LastName>
<ForeName>Mary T</ForeName>
<Initials>MT</Initials>
<AffiliationInfo><Affiliation>Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, United States of America.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Fawzy</LastName>
<ForeName>Manal S</ForeName>
<Initials>MS</Initials>
<Identifier Source="ORCID">0000-0003-1252-8403</Identifier>
<AffiliationInfo><Affiliation>Department of Medical Biochemistry and Molecular Biology, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Biochemistry, Faculty of Medicine, Northern Border University, Arar, KSA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Kandil</LastName>
<ForeName>Emad</ForeName>
<Initials>E</Initials>
<AffiliationInfo><Affiliation>Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Los Angeles, United States of America.</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>21</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>PLoS One</MedlineTA>
<NlmUniqueID>101285081</NlmUniqueID>
<ISSNLinking>1932-6203</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D015415">Biomarkers</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D005338">Fibrin Fibrinogen Degradation Products</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="C508609">IL10 protein, human</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="C508600">IL6 protein, human</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>130068-27-8</RegistryNumber>
<NameOfSubstance UI="D016753">Interleukin-10</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>9007-41-4</RegistryNumber>
<NameOfSubstance UI="D002097">C-Reactive Protein</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="D000293" MajorTopicYN="N">Adolescent</DescriptorName>
</MeshHeading>
<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="Y">Betacoronavirus</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015415" MajorTopicYN="N">Biomarkers</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D001799" MajorTopicYN="N">Blood Sedimentation</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002097" MajorTopicYN="N">C-Reactive Protein</DescriptorName>
<QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="Y">blood</QualifierName>
<QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005338" MajorTopicYN="N">Fibrin Fibrinogen Degradation Products</DescriptorName>
<QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016753" MajorTopicYN="N">Interleukin-10</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015850" MajorTopicYN="N">Interleukin-6</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007958" MajorTopicYN="N">Leukocyte Count</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009504" MajorTopicYN="N">Neutrophils</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="Y">blood</QualifierName>
<QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000077740" MajorTopicYN="N">Procalcitonin</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="N">blood</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011379" MajorTopicYN="N">Prognosis</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011517" MajorTopicYN="N">Prothrombin Time</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<CoiStatement>The authors have declared that no competing interests exist.</CoiStatement>
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<Month>05</Month>
<Day>12</Day>
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<Month>08</Month>
<Day>11</Day>
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Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients.

Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients.

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