Evidence map›Paper›PMID 38476443›Full record

ArticleFrontiers in medicine2024

Potential marker subset of blood-circulating cytokines on hematopoietic progenitor-to-Th1 pathway in COVID-19.

Yasuo Takashima, Tohru Inaba, Tasuku Matsuyama, Kengo Yoshii, Masami Tanaka, Kazumichi Matsumoto, Kazuki Sudo, Yuichi Tokuda, Natsue Omi, Masakazu Nakano and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
8.9field-weighted citation impact, top 1% 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

4 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. 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 3 institutions in 1 country.

Yasuo Takashima *Department of Genomic Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Tohru Inaba *Department of Infection Control and Laboratory Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Tasuku Matsuyama *Department of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kengo YoshiiDepartment of Mathematics and Statistics in Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Masami TanakaDepartment of Genomic Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kazumichi MatsumotoFaculty of Clinical Laboratory, University Hospital Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kazuki SudoDepartment of Anesthesiology, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Yuichi TokudaDepartment of Genomic Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Natsue OmiDepartment of Genomic Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Masakazu NakanoDepartment of Genomic Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Takaaki NakayaDepartment of Infectious Diseases, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Naohisa FujitaDepartment of Infection Control and Laboratory Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Chie SotozonoDepartment of Ophthalmology, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Teiji SawaDepartment of Anesthesiology, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kei TashiroDepartment of Genomic Medical Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Bon OhtaDepartment of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kyoto Prefectural University of Medicine · JPUniversity Hospital Kyoto Prefectural University of Medicine · JPKyoto Prefectural Institute of Public Health and Environment · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we analyzed a relatively large subset of proteins, including 109 kinds of blood-circulating cytokines, and precisely described a cytokine storm in the expression level and the range of fluctuations during hospitalization for COVID-19. Of the proteins analyzed in COVID-19, approximately 70% were detected with Bonferroni-corrected significant differences in comparison with disease severity, clinical outcome, long-term hospitalization, and disease progression and recovery. Specifically, IP-10, sTNF-R1, sTNF-R2, sCD30, sCD163, HGF, SCYB16, IL-16, MIG, SDF-1, and fractalkine were found to be major components of the COVID-19 cytokine storm. Moreover, the 11 cytokines (i.e., SDF-1, SCYB16, sCD30, IL-11, IL-18, IL-8, IFN-γ, TNF-α, sTNF-R2, M-CSF, and I-309) were associated with the infection, mortality, disease progression and recovery, and long-term hospitalization. Increased expression of these cytokines could be explained in sequential pathways from hematopoietic progenitor cell differentiation to Th1-derived hyperinflammation in COVID-19, which might also develop a novel strategy for COVID-19 therapy with recombinant interleukins and anti-chemokine drugs.

Indexed as

blood-circulating cytokinecoefficient of variationCOVID-19cytokine stormtimelapse monitoring

Identifiers

PMID38476443
PMCPMC10927758
OpenAlexW4392195651

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.