Evidence map›Paper›PMID 33073244›Full record

ReviewThe Lancet. Rheumatology2020

Imperfect storm: is interleukin-33 the Achilles heel of COVID-19?

Gaetano Zizzo, Philip L Cohen

Open access · bronzeAbstract readReview
In one paragraph

Review in The Lancet. Rheumatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 pooled it
8.4field-weighted citation impact, top 2% 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

61 citing papers in PubMed, 1 synthesis or guideline pooled it, 103 citations in OpenAlex.

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  7. IL-1 Family Blockade in Cytokine Storm Syndromes.Advances in experimental medicine and biology · 2024
    Review
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1 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Gaetano ZizzoTemple Autoimmunity Center, Lewis Katz School of Medicine at Temple University, Philadelphia, PA 19140, USA.
Philip L CohenTemple Autoimmunity Center, Lewis Katz School of Medicine at Temple University, Philadelphia, PA 19140, USA.
Aziende Socio Sanitarie Territoriale Ovest MilaneseTemple University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The unique cytokine signature of COVID-19 might provide clues to disease mechanisms and possible future therapies. Here, we propose a pathogenic model in which the alarmin cytokine, interleukin (IL)-33, is a key player in driving all stages of COVID-19 disease (ie, asymptomatic, mild-moderate, severe-critical, and chronic-fibrotic). In susceptible individuals, IL-33 release by damaged lower respiratory cells might induce dysregulated GATA-binding factor 3-expressing regulatory T cells, thereby breaking immune tolerance and eliciting severe acute respiratory syndrome coronavirus 2-induced autoinflammatory lung disease. Such disease might be initially sustained by IL-33-differentiated type-2 innate lymphoid cells and locally expanded γδ T cells. In severe COVID-19 cases, the IL-33-ST2 axis might act to expand the number of pathogenic granulocyte-macrophage colony-stimulating factor-expressing T cells, dampen antiviral interferon responses, elicit hyperinflammation, and favour thromboses. In patients who survive severe COVID-19, IL-33 might drive pulmonary fibrosis by inducing myofibroblasts and epithelial-mesenchymal transition. We discuss the therapeutic implications of these hypothetical pathways, including use of therapies that target IL-33 (eg, anti-ST2), T helper 17-like γδ T cells, immune cell homing, and cytokine balance.

Identifiers

PMID33073244
PMCPMC7546716
OpenAlexW3092387456

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.