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Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program
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 ma...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684592/ https://www.ncbi.nlm.nih.gov/pubmed/38017007 http://dx.doi.org/10.1038/s41598-023-47655-y |
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author | Rao, Suchitra Jing, Naimin Liu, Xiaokang Lorman, Vitaly Maltenfort, Mitchell Schuchard, Julia Wu, Qiong Tong, Jiayi Razzaghi, Hanieh Mejias, Asuncion Lee, Grace M. Pajor, Nathan M. Schulert, Grant S. Thacker, Deepika Jhaveri, Ravi Christakis, Dimitri A. Bailey, L. Charles Forrest, Christopher B. Chen, Yong |
author_facet | Rao, Suchitra Jing, Naimin Liu, Xiaokang Lorman, Vitaly Maltenfort, Mitchell Schuchard, Julia Wu, Qiong Tong, Jiayi Razzaghi, Hanieh Mejias, Asuncion Lee, Grace M. Pajor, Nathan M. Schulert, Grant S. Thacker, Deepika Jhaveri, Ravi Christakis, Dimitri A. Bailey, L. Charles Forrest, Christopher B. Chen, Yong |
author_sort | Rao, Suchitra |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10684592 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106845922023-11-30 Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program Rao, Suchitra Jing, Naimin Liu, Xiaokang Lorman, Vitaly Maltenfort, Mitchell Schuchard, Julia Wu, Qiong Tong, Jiayi Razzaghi, Hanieh Mejias, Asuncion Lee, Grace M. Pajor, Nathan M. Schulert, Grant S. Thacker, Deepika Jhaveri, Ravi Christakis, Dimitri A. Bailey, L. Charles Forrest, Christopher B. Chen, Yong Sci Rep Article 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. Nature Publishing Group UK 2023-11-28 /pmc/articles/PMC10684592/ /pubmed/38017007 http://dx.doi.org/10.1038/s41598-023-47655-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Rao, Suchitra Jing, Naimin Liu, Xiaokang Lorman, Vitaly Maltenfort, Mitchell Schuchard, Julia Wu, Qiong Tong, Jiayi Razzaghi, Hanieh Mejias, Asuncion Lee, Grace M. Pajor, Nathan M. Schulert, Grant S. Thacker, Deepika Jhaveri, Ravi Christakis, Dimitri A. Bailey, L. Charles Forrest, Christopher B. Chen, Yong Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program |
title | Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program |
title_full | Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program |
title_fullStr | Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program |
title_full_unstemmed | Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program |
title_short | Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program |
title_sort | spectrum of severity of multisystem inflammatory syndrome in children: an ehr-based cohort study from the recover program |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684592/ https://www.ncbi.nlm.nih.gov/pubmed/38017007 http://dx.doi.org/10.1038/s41598-023-47655-y |
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