Evidence map›Paper›PMID 36380068›Full record

ArticlePediatric research2023

Multisystemic Inflammatory Syndrome in Children: a step towards a better understanding of this entity.

Cecília Rotava Buratti, Philippe Jouvet

Open access · bronzeAbstract read
In one paragraph

Article in Pediatric research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 73% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Cecília Rotava BurattiPediatric Intensive Care, Department of Pediatrics, Hospital de Clínicas de Porto Alegre and Graduate Program in Child and Adolescent Health, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Philippe JouvetPediatric Intensive Care, Department of Pediatrics, Sainte-Justine Hospital, University of Montreal, Montreal, QC, Canada. philippe.jouvet.med@ssss.gouv.qc.ca.ORCID 0000-0001-5684-3398
Centre Hospitalier Universitaire Sainte-Justine · CAUniversidade Federal do Rio Grande do Sul · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As pediatricians, we all have to deal with new childhood inflammatory disorder due to COVID 19: the Multisystem Inflammatory Syndrome in Children (MIS-C). The recent article by Savorgnan et al. on the physiologic profiles associated with MIS-C proposed a classification through the "MIS-C severity score" (MSS). The authors also identified a combination of seven variables collected during the first 3 h of admission in the PICU that contributes to stratify MIS-C severity with an area under the receiver operating characteristic curve (AUC) >0.90. This work represents an important first step in the development of a MIS-C severity score and is a call for collaborative groups to validate the prediction model through multicenter studies and thereby refine the management of MIS-C. IMPACT: The recent article by Savorgnan et al. on physiologic profile associated with MIS-C represents an important first step in the development of an MIS-C severity score and is a call for collaborative groups to validate the prediction model through multicenter studies and thereby refine the management of MIS-C. Our manuscript helps in the methodology interpretation of the manuscript by Savorgnan et al. And our manuscript promotes collaborative work on MIS-C.

Indexed as

COVID-19ChildHospitalizationHumansSyndromeSystemic Inflammatory Response Syndrome

Identifiers

PMID36380068
PMCPMC9665019
OpenAlexW4309048170

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.