Evidence map›Paper›PMID 32921711›Full record

ReviewActa bio-medica : Atenei Parmensis2020

An Outbreak of Kawasaki-like Disease in children during SARS-CoV- 2 Epidemic: No Surprise?

Federica Cavallo, Francesco Chiarelli

Open access · greenAbstract readReview
In one paragraph

Review in Acta bio-medica : Atenei Parmensis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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 2 institutions in 2 countries.

Federica CavalloArray. federica-cavallo@libero.it.
Francesco ChiarelliUniversity of Chieti. chiarelli@unich.it.
Array Information Technology (United States) · USUniversity of Chieti-Pescara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimKawasaki disease is an acute systemic febrile illness of unknown aetiology, which usually affects children under 5 years of age. It is well known that Kawasaki disease is one of the most common causes of acquired heart diseases in children in the developed countries. Many studies, have suggested that heterogeneous infectious agents, such as common viruses, may trigger Kawasaki disease in young children with genetic background.  Nowadays we are facing a pandemic caused by a Novel Coronavirus named SARS-CoV-2. Consequently, it could be possible that once exposed to this new coronavirus, some children, genetically predisposed, may mount an exaggerated inflammatory response which clinically manifests as Kawasaki Disease.

methodsfrom January to May 2020 a systematic search was performed on Pubmed for the following search terms: "COVID-19", "children", "SARS-CoV-2", "complications", "Kawasaki disease", "cytokine storm".

resultsUsually, infants and children present milder symptoms of SARS-CoV-2 disease with a better outcome than adults. At variance, some children may be genetically disposed to a more robust inflammatory response to SARS-CoV-2, similar to Kawasaki disease. In fact, Kawasaki disease is the result of an abnormal immune response, in susceptible children, to an external trigger such as an infection. Thus, according to the pathogenesis of Kawasaki disease, paediatricians may expect an increase in cases of Kawasaki disease during the COVID-19 pandemic.

Indexed as

BetacoronavirusDisease OutbreaksChildCoronavirus InfectionsCOVID-19Global HealthHumansMucocutaneous Lymph Node SyndromePandemicsPneumonia, ViralSARS-CoV-2

Identifiers

PMID32921711
PMCPMC7716964
OpenAlexW3085760127

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.