Evidence map›Paper›PMID 39546241›Full record

ArticleJournal of thrombosis and thrombolysis2025

Impact of antiplatelets, anticoagulants and cyclic nucleotide stimulators on neutrophil extracellular traps (NETs) and inflammatory markers during COVID-19.

José D Oliveira, Gislaine Vieira-Damiani, Letícia Q da Silva, Guilherme R Leonardi, Camila O Vaz, Bruna C Jacintho-Robison, Bruna M Mazetto, Erich V de Paula, Fabíola Z Monica, Fernanda A Orsi

Abstract read
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In one paragraph

Article in Journal of thrombosis and thrombolysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Unraveling NETs in Sepsis: From Cellular Mechanisms to Clinical Relevance.International journal of molecular sciences · 2025
    Review
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

10 authors.

José D OliveiraSchool of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Gislaine Vieira-DamianiDepartment of Biology, Federal Institute of Education Science and Technology of São Paulo, Capivari, Brazil.
Letícia Q da SilvaSchool of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Guilherme R LeonardiDepartment of Translational Medicine (Pharmacology), Faculty of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Camila O VazSchool of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Bruna C Jacintho-RobisonSchool of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Bruna M MazettoSchool of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Erich V de PaulaSchool of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Fabíola Z MonicaDepartment of Translational Medicine (Pharmacology), Faculty of Medical Sciences, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
Fernanda A OrsiHematology and Hemotherapy Center, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil. ferorsi@unicamp.br.ORCID http://orcid.org/0000-0002-7908-9073

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 141262/2021-4Fundação de Amparo à Pesquisa do Estado de São Paulo 2020/13956-9
6 · The paper itself

Abstract

While the association between coronavirus disease-19 (COVID-19) and neutrophils extracellular traps (NETs) is recognized, uncertainties remain regarding its precise onset, timing of resolution and target therapy. To assess changes in inflammatory and NET markers during the first week of COVID-19 hospitalization, and the association with disease severity. "In vitro" experiments investigated the effect of antiplatelets, anticoagulants, and cyclic nucleotide stimulators on NETs release. Prospective cohort study, changes in interleukin (IL)-6, IL-8, IL-17, TNF-α, RANTES, PF4, and citrullinated-H3 (citH3) levels within each outcome group was evaluated using ANOVA. Differences between moderately ill, critically ill, and non-survivors were determined using Kruskal-Wallis and logistic regression. Healthy neutrophils were stimulated with phorbol-12-myristate-13-acetate (PMA) or COVID-19 sera and treated with unfractionated heparin (UFH), low molecular weight heparin (LMWH), aspirin (ASA), ticagrelor, cinaciguat, sildenafil, and milrinone. The proportion of NETosis was assessed using IncuCyte Cell Imager. Of the 125 patients, 40.8% had moderate COVID-19, 40.8% had critical COVID-19 but recovered, and 18.4% died. From admission to hospitalization day 8, IL-6 levels decreased in moderately and critically ill, but not in non-survivors, while citH3 levels increased in critically ill and non-survivors. IL-6, IL-8, and TNF-α levels were associated with critical and fatal COVID-19. The release of NETs by neutrophils stimulated with PMA or COVID-19 sera was decreased in the presence of ASA, UFH, LMWH and cyclic nucleotide stimulators in a dose-dependent manner. In the first week of hospitalization, NET markers rose later than inflammatory markers in severe COVID-19 cases. Cyclic nucleotide stimulators, ASA and heparin may emerge as treatment approaches as they may modulate NETosis.

Indexed as

AnticoagulantsCOVID-19COVID-19 Drug TreatmentExtracellular TrapsInflammation MediatorsNeutrophilsPlatelet Aggregation InhibitorsAgedBiomarkersFemaleHumansMaleMiddle AgedProspective StudiesSARS-CoV-2Severity of Illness IndexAnticoagulantsBiomarkersInflammation MediatorsPlatelet Aggregation InhibitorsAnticoagulantsAntiplatelet agentsCOVID-19Cyclic nucleotidesNeutrophil extracellular traps

Identifiers

What OpenQuestion holds

Textmetadata
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.