Evidence map›Paper›PMID 35437914›Full record

ArticleInternational journal of laboratory hematology2022

A retrospective study of age-defined hematologic inflammatory markers related to pediatric COVID-19 diagnosis.

Yasemin Üstündağ, Elif G Kazanci, Rahime F Koloğlu, Hatice A Çağlak, Fatih Yildirim, Elif Y Arikan, Kağan Huysal

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Article in International journal of laboratory hematology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yasemin ÜstündağDepartment of Clinical Biochemistry, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0003-2415-0372
Elif G KazanciDepartment of Pediatric Hemato-Oncology, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0003-0910-1142
Rahime F KoloğluDepartment of Clinical Biochemistry, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0002-1990-9623
Hatice A ÇağlakDepartment of Clinical Biochemistry, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0002-4358-4339
Fatih YildirimDepartment of Clinical Biochemistry, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0003-1799-4227
Elif Y ArikanDepartment of Clinical Biochemistry, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0002-8699-1751
Kağan HuysalDepartment of Clinical Biochemistry, University of Health Sciences, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Turkey.ORCID https://orcid.org/0000-0003-3142-5944

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to examine age-related differences in hemogram parameters and hematologic inflammatory markers in pediatric patients with COVID-19.

methodsThis retrospective study included children aged 2 months to 18 years (n = 208) who have a confirmed diagnosis of COVID-19 and a control group comprising 117 healthy children between February 2021 and July 2021. The analysis of subgroup hematological values were performed according to the children's age cutoffs.

resultsThe most significant difference between pediatric patients with COVID-19 and controls were peripheral blood eosinophil counts and eosinophil-to-monocyte ratio (EMR) levels on admission. The levels of monocyte-to-lymphocyte ratio, aggeregate index of systemic inflammation (neutrophil × platelet × monocyte/lymphocyte), neutrophil-to- lymphocyte × platelet ratio, and systemic inflammation response index (neutrophil × monocyte/ lymphocyte) were higher in patients than in controls. EMR had the highest area under the curve (AUC) value of 0.777, with a cutoff value of 0.26. The sensitivity for EMR was 75% under 2 years of age, and between 78.6-87.5% in the other age groups.

conclusionIn children younger than 6 months, the discriminative power of hematological indices is low, while the discriminative power of EMR is high at all ages when age appropriate cutoffs are used. Hematological inflammatory parameters may be particularly practical in pediatric clinics to help identify COVID-19 infection.

Indexed as

COVID-19BiomarkersChildCOVID-19 TestingHumansInflammationLymphocytesNeutrophilsPrognosisRetrospective StudiesBiomarkerschildCOVID-19eosinophilsleukocyteslymphocytes

Identifiers

PMID35437914
PMCPMC9111715

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.