Evidence map›Paper›PMID 41333341›Full record

ArticleJugan geon-gang gwa jilbyeong2023

[Results of the Coronavirus Disease 2019-associated Multisystem Inflammatory Syndrome in Children (MIS-C) National Surveillance System in Republic of Korea].

Hye Rim Park, Yeon Haw Jung, Mi Yu, Hye Young Lee, Hye-Jin Kim, Hee Kyoung Kim, Sang-Eun Lee, Hyeokjin Lee, Eun-Jin Kim, Hyungmin Lee and 1 more

Erratum issuedAbstract readCase ReportsEnglish Abstract
In one paragraph

Article in Jugan geon-gang gwa jilbyeong, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Hye Rim Park질병관리청 중앙방역대책본부 환자관리팀.
Yeon Haw Jung질병관리청 중앙방역대책본부 환자관리팀.
Mi Yu질병관리청 중앙방역대책본부 역학조사팀.
Hye Young Lee질병관리청 중앙방역대책본부 역학조사팀.
Hye-Jin Kim질병관리청 중앙방역대책본부 역학조사팀.
Hee Kyoung Kim질병관리청 중앙방역대책본부 역학조사팀.
Sang-Eun Lee질병관리청 중앙방역대책본부 역학조사팀.
Hyeokjin Lee질병관리청 중앙방역대책본부 검사분석팀.
Eun-Jin Kim질병관리청 중앙방역대책본부 검사분석팀.
Hyungmin Lee질병관리청 중앙방역대책본부 환자관리팀.
Jungyeon Kim질병관리청 중앙방역대책본부 환자관리팀.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multisystem inflammatory syndrome in children (MIS-C), a severe complication of the coronavirus disease 2019 (COVID-19), similar to Kawasaki disease, has been reported in the United States and Europe, with the World Health Organization calling on clinicians worldwide to be vigilant for MIS-C. In response, the Korea Disease Control and Prevention Agency operated a prospective surveillance system from June 2020 to April 2023 to assess the incidence and level of MIS-C associated with COVID-19 in the Republic of Korea. With the nationwide cooperation of pediatricians, a total of 180 suspected cases were reported. After review by the Case Assessment Committee, 146 cases were confirmed to be consistent with MIS-C, with no fatalities reported. The establishment of a prospective surveillance system for MIS-C and securing basic data, such as clinical information and epidemiological characteristics of domestic cases through national-level operations, is important as part of the preemptive prevention policies in response to COVID-19. Establishing a diagnostic system in preparation for the anticipated transition of COVID-19 patients into the general healthcare system, with the expectation of continued spread and endemicity, ongoing attention and further research are necessary to ensure timely diagnosis and treatment in clinical practice.

Indexed as

ChildCovid-19Mucocutaneous lymph node syndromeRepublic of KoreaSystemic inflammatory response syndrome/complications

Identifiers

PMID41333341
PMCPMC12480234

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.