Evidence map›Paper›PMID 33116752›Full record

ReviewJournal of inflammation research2020

Cytokine Response in SARS-CoV-2 Infection in the Elderly.

Subuhi Sherwani, Mohd Wajid Ali Khan

Open access · goldAbstract readReview
In one paragraph

Review in Journal of inflammation research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

29 citing papers in PubMed, 48 citations in OpenAlex.

  1. Trial
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  10. Challenges in the Vaccination of the Elderly and Strategies for Improvement.Pathophysiology : the official journal of the International Society for Pathophysiology · 2023
    Review
  11. Review
  12. Article
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  19. Cytokine producing ability of peripheral blood cells from COVID-19 patients after unspecific in vitro stimulation.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2022
    Article
  20. 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

2 authors at 1 institution in 1 country.

Subuhi SherwaniDepartment of Biology, College of Sciences, University of Ha'il, Ha'il 2440, Saudi Arabia.ORCID 0000-0002-0631-708X
Mohd Wajid Ali KhanDepartment of Chemistry, College of Sciences, University of Ha'il, Ha'il 2440, Saudi Arabia.
University of Ha'il · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The last few months of 2019 witnessed the emergence, rise and rapid spread of a novel coronavirus known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), causing an acute respiratory disease called coronavirus disease 2019 or Covid-19. Severe pathological manifestations of the disease in the infected population with comorbidities are linked to acute respiratory distress syndrome (ARDS), associated with an exaggerated synthesis and expression of cytokines, leading to a systemic inflammatory response also known as a cytokine storm (CS). Elderly patients (>60 years of age) showed more deaths in Covid-19 infection. Age-related immune imbalance increases patient susceptibility to CS. In acute Covid-19 infection, it is difficult to minimize or control the overproduction of cytokines; hence, limited medical treatments are effective. This review aims to provide an overview of the current knowledge of involvement of cytokines in SARS-CoV-2 infection, susceptibility factors for the accompanying cytokine storm in severe Covid-19 cases and possible treatment strategies.

Indexed as

coronavirusCovid-19cytokine stormelderlyinflammationSARS-CoV-2

Identifiers

PMID33116752
PMCPMC7585778
OpenAlexW3093276866

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.