Back to Search Start Over

Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program

Authors :
Suchitra Rao
Naimin Jing
Xiaokang Liu
Vitaly Lorman
Mitchell Maltenfort
Julia Schuchard
Qiong Wu
Jiayi Tong
Hanieh Razzaghi
Asuncion Mejias
Grace M. Lee
Nathan M. Pajor
Grant S. Schulert
Deepika Thacker
Ravi Jhaveri
Dimitri A. Christakis
L. Charles Bailey
Christopher B. Forrest
Yong Chen
Source :
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract Multi-system inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection in children, and there is a critical need to unfold its highly heterogeneous disease patterns. Our objective was to characterize the illness spectrum of MIS-C for improved recognition and management. We conducted a retrospective cohort study using data from March 1, 2020–September 30, 2022, in 8 pediatric medical centers from PEDSnet. We included 1139 children hospitalized with MIS-C and used their demographics, symptoms, conditions, laboratory values, and medications for analyses. We applied heterogeneity-adaptive latent class analyses and identified three latent classes. We further characterized the sociodemographic and clinical characteristics of the latent classes and evaluated their temporal patterns. Class 1 (47.9%) represented children with the most severe presentation, with more admission to the ICU, higher inflammatory markers, hypotension/shock/dehydration, cardiac involvement, acute kidney injury and respiratory involvement. Class 2 (23.3%) represented a moderate presentation, with 4–6 organ systems involved, and some overlapping features with acute COVID-19. Class 3 (28.8%) represented a mild presentation. Our results indicated that MIS-C has a spectrum of clinical severity ranging from mild to severe and the proportion of severe or critical MIS-C decreased over time.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.4586999d374bf5bf1fdb2ccf056d7b
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-023-47655-y