Evidence map›Paper›PMID 42675682›Full record

ArticleMedicine2026

Microscopic giant platelets versus automated mean platelet volume for severity assessment in COVID-19.

Muhammed Ali Coşkuner, Seyit Uyar, Fatma Aykaş, Mehmet Kök, Gökhan Köker, Tuba Güllü Koca, Nizameddin Koca

Abstract readComparative Study
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Muhammed Ali CoşkunerDepartment of Internal Medicine, Antalya City Hospital, Antalya, Turkey.ORCID 0000-0001-9203-2285
Seyit UyarDepartment of Internal Medicine, Antalya Training and Research Hospital, Antalya, Turkey.
Fatma AykaşDepartment of Hematology, Antalya Training and Research Hospital, Antalya, Turkey.ORCID 0000-0002-2463-3676
Mehmet KökDepartment of Internal Medicine, Antalya Training and Research Hospital, Antalya, Turkey.
Gökhan KökerDepartment of Internal Medicine, Antalya Training and Research Hospital, Antalya, Turkey.
Tuba Güllü KocaDepartment of Hematology, Bursa Uludağ University, Faculty of Medicine, Bursa, Turkey.
Nizameddin KocaDepartment of Internal Medicine, Bursa City Training and Research Hospital, Bursa, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19-associated coagulopathy (immunothrombosis) contributes to mortality. Automated hematology analyzers are widely used for risk stratification but may not capture morphological platelet abnormalities. We examined whether peripheral blood smear (PBS) findings, particularly giant platelets, are associated with severe COVID-19 beyond automated mean platelet volume (MPV) in hospitalized patients. In this retrospective cohort study, 96 patients with confirmed COVID-19 were classified at hospital admission as mild/moderate (n = 60) or severe (n = 36). Admission PBS samples were independently reviewed by 2 blinded observers. Multivariable logistic regression was used to assess factors associated with severe disease, and ROC analysis compared the discriminatory performance of microscopic giant platelet detection with automated MPV. Giant platelet presence was associated with severe disease after adjustment for age, sex, and diabetes mellitus (OR: 2.86, 95% CI: 1.02-8.07, P = .047); older age and diabetes mellitus were also associated with severity, whereas female sex was inversely associated. The corresponding unadjusted association did not reach conventional statistical significance, and the adjusted estimate had a wide confidence interval. In an exploratory model additionally including MPV, giant platelet presence remained associated with severe disease (OR: 3.88, 95% CI: 1.25-12.01, P = .019), whereas MPV was not associated with severity in the same model (P = .114). Giant platelet detection showed weak stand-alone discrimination (AUC: 0.597, 95% CI: 0.497-0.694), and its discriminatory performance did not differ significantly from that of MPV (AUC: 0.465, 95% CI: 0.349-0.584; DeLong P = .058). In this cohort, giant platelet presence was associated with severe COVID-19 at admission after adjustment for selected baseline covariates; however, the imprecision of the estimate, nonsignificant unadjusted comparison, and weak discriminatory performance indicate that this finding should be considered exploratory. These results do not establish that PBS review improves clinical severity assessment, and external validation in larger prospective cohorts is required.

Indexed as

Blood PlateletsCOVID-19Mean Platelet VolumeAgedFemaleHumansMaleMiddle AgedPandemicsRetrospective StudiesSARS-CoV-2Severity of Illness IndexCOVID-19disease severitygiant plateletsmean platelet volumeperipheral blood smearthrombopoiesis

Identifiers

PMID42675682
PMCPMC13529116

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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.