Evidence map›Paper›PMID 35126355›Full record

ReviewFrontiers in immunology2021

Potential Immune Indicators for Predicting the Prognosis of COVID-19 and Trauma: Similarities and Disparities.

Hamed Fouladseresht, Atefe Ghamar Talepoor, Nahid Eskandari, Marzieh Norouzian, Behrooz Ghezelbash, Mohammad Reza Beyranvand, Seyed Aria Nejadghaderi, Kristin Carson-Chahhoud, Ali-Asghar Kolahi, Saeid Safiri

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

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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 at 6 institutions in 2 countries.

Hamed FouladsereshtDepartment of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Atefe Ghamar TalepoorDepartment of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Nahid EskandariDepartment of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Marzieh NorouzianDepartment of Laboratory Sciences, School of Allied Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
Behrooz GhezelbashDepartment of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Mohammad Reza BeyranvandSocial Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Seyed Aria NejadghaderiResearch Center for Integrative Medicine in Aging, Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran.
Kristin Carson-ChahhoudAustralian Centre for Precision Health, Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.
Ali-Asghar KolahiSocial Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Saeid SafiriSocial Determinants of Health Research Center, Department of Community Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Isfahan University of Medical Sciences · IRShahid Beheshti University of Medical Sciences · IRTabriz University of Medical Sciences · IRHormozgan University of Medical Sciences · IRShiraz University of Medical Sciences · IRUniversity of South Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although cellular and molecular mediators of the immune system have the potential to be prognostic indicators of disease outcomes, temporal interference between diseases might affect the immune mediators, and make them difficult to predict disease complications. Today one of the most important challenges is predicting the prognosis of COVID-19 in the context of other inflammatory diseases such as traumatic injuries. Many diseases with inflammatory properties are usually polyphasic and the kinetics of inflammatory mediators in various inflammatory diseases might be different. To find the most appropriate evaluation time of immune mediators to accurately predict COVID-19 prognosis in the trauma environment, researchers must investigate and compare cellular and molecular alterations based on their kinetics after the start of COVID-19 symptoms and traumatic injuries. The current review aimed to investigate the similarities and differences of common inflammatory mediators (C-reactive protein, procalcitonin, ferritin, and serum amyloid A), cytokine/chemokine levels (IFNs, IL-1, IL-6, TNF-α, IL-10, and IL-4), and immune cell subtypes (neutrophil, monocyte, Th1, Th2, Th17, Treg and CTL) based on the kinetics between patients with COVID-19 and trauma. The mediators may help us to accurately predict the severity of COVID-19 complications and follow up subsequent clinical interventions. These findings could potentially help in a better understanding of COVID-19 and trauma pathogenesis.

Indexed as

COVID-19CytokinesHumansInflammation MediatorsPrognosisSARS-CoV-2Th1 CellsT-Lymphocyte SubsetsWounds and InjuriesCytokinesInflammation MediatorsCOVID-19cytokineprognosisT celltrauma

Identifiers

PMID35126355
PMCPMC8815083
OpenAlexW4206090467

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.