Evidence map›Paper›PMID 37964734›Full record

ArticleJournal of cellular and molecular medicine2023

Extracellular vesicle features are associated with COVID-19 severity.

Federica Caponnetto, Maria De Martino, Daniele Stefanizzi, Riccardo Del Sal, Ivana Manini, Feras Kharrat, Federica D'Aurizio, Martina Fabris, Daniela Visentini, Donatella Poz and 6 more

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. CD66bJournal of extracellular vesicles · 2024
    Article
  5. Review
  6. Extracellular vesicle features are associated with COVID-19 severity.Journal of cellular and molecular medicine · 2023
    Article
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

16 authors at 2 institutions in 1 country.

Federica CaponnettoDepartment of Medicine, University of Udine, Udine, Italy.
Maria De MartinoDepartment of Medicine, University of Udine, Udine, Italy.
Daniele StefanizziDepartment of Medicine, University of Udine, Udine, Italy.
Riccardo Del SalDepartment of Medicine, University of Udine, Udine, Italy.
Ivana ManiniDepartment of Medicine, University of Udine, Udine, Italy.
Feras KharratDepartment of Medicine, University of Udine, Udine, Italy.
Federica D'AurizioAzienda Sanitaria Universitaria Friuli Centrale, Udine, Italy.
Martina FabrisDepartment of Medicine, University of Udine, Udine, Italy.
Daniela VisentiniAzienda Sanitaria Universitaria Friuli Centrale, Udine, Italy.
Donatella PozAzienda Sanitaria Universitaria Friuli Centrale, Udine, Italy.
Emanuela SozioAzienda Sanitaria Universitaria Friuli Centrale, Udine, Italy.
Carlo TasciniDepartment of Medicine, University of Udine, Udine, Italy.
Daniela CesselliDepartment of Medicine, University of Udine, Udine, Italy.
Miriam IsolaDepartment of Medicine, University of Udine, Udine, Italy.
Antonio Paolo BeltramiDepartment of Medicine, University of Udine, Udine, Italy.ORCID 0000-0002-0679-2710
Francesco CurcioDepartment of Medicine, University of Udine, Udine, Italy.
University of Udine · ITAzienda Unità Sanitaria Locale di Ferrara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is heterogeneous; therefore, it is crucial to identify early biomarkers for adverse outcomes. Extracellular vesicles (EV) are involved in the pathophysiology of COVID-19 and have both negative and positive effects. The objective of this study was to identify the potential role of EV in the prognostic stratification of COVID-19 patients. A total of 146 patients with severe or critical COVID-19 were enrolled. Demographic and comorbidity characteristics were collected, together with routine haematology, blood chemistry and lymphocyte subpopulation data. Flow cytometric characterization of the dimensional and antigenic properties of COVID-19 patients' plasma EVs was conducted. Elastic net logistic regression with cross-validation was employed to identify the best model for classifying critically ill patients. Features of smaller EVs (i.e. the fraction of EVs smaller than 200 nm expressing either cluster of differentiation [CD] 31, CD 140b or CD 42b), albuminemia and the percentage of monocytes expressing human leukocyte antigen DR (HLA-DR) were associated with a better outcome. Conversely, the proportion of larger EVs expressing N-cadherin, CD 34, CD 56, CD31 or CD 45, interleukin 6, red cell width distribution (RDW), N-terminal pro-brain natriuretic peptide (NT-proBNP), age, procalcitonin, Charlson Comorbidity Index and pro-adrenomedullin were associated with disease severity. Therefore, the simultaneous assessment of EV dimensions and their antigenic properties complements laboratory workup and helps in patient stratification.

Indexed as

COVID-19Extracellular VesiclesBiomarkersHumansInterleukin-6MonocytesBiomarkersInterleukin-6apoptotic bodiesbiomarkerCOVID-19exosomesextracellular vesiclesflow cytometrymachine learningmicrovesiclesoutcomesSARS-CoV2

Identifiers

PMID37964734
PMCPMC10746943
OpenAlexW4388688968

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.