Evidence map›Paper›PMID 37360365›Full record

ArticleFrontiers in pediatrics2023

Platelet role in the prediction of MIS-C severity.

Ausra Snipaitiene, Aurelija Sirataviciene, Leila Varoneckaite, Rima Sileikiene, Lina Jankauskaite

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Ausra SnipaitienePediatric Department, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Aurelija SiratavicienePediatric Department, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Leila VaroneckaitePediatric Department, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Rima SileikienePediatric Department, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Lina JankauskaitePediatric Department, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Hospital of Lithuanian University of Health Sciences Kaunas Clinics · LTLithuanian University of Health Sciences · LT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Multisystem inflammatory syndrome in children (MIS-C) has been reported as one of the cytokine storm syndromes associated with COVID-19. Despite the several proposed diagnostic criteria, MIS-C remains a diagnostic and clinical challenge. Recent studies have demonstrated that platelets (PLTs) play a crucial role in COVID-19 infection and its prognosis. This study aimed to investigate the clinical importance of PLT count and PLT indices in predicting MIS-C severity in children. Patients and methods: We conducted a retrospective single-center study at our university hospital. A total of 43 patients diagnosed with MIS-C during a 2-year period (from October 2020 to October 2022) were included in the study. MIS-C severity was evaluated according to the composite severity score. Results: Half of the patients were treated in the pediatric intensive care unit. No single clinical sign was associated with a severe condition, except for shock ( Conclusions: Our study emphasizes the importance of PLT in MIS-C pathogenesis and severity. It revealed that together with routine biomarkers (e.g., CBC and CRP), it could highly improve the prediction of MIS-C severity.

Indexed as

biomarkerchildrenCOVID-19multisystem inflammatory syndrome in childrenplatelets

Identifiers

PMID37360365
PMCPMC10285299
OpenAlexW4380047543

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.