Publication Date

1-1-2023

Journal

Pediatric Research

DOI

10.1038/s41390-022-02108-6

PMID

35568731

PMCID

PMC9106980

PubMedCentral® Posted Date

5-14-2022

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Child, Humans, Retrospective Studies, Systemic Inflammatory Response Syndrome, COVID-19, Critical Care

Abstract

OBJECTIVE: The purpose of this study was to describe the clinical presentation and physiologic profile of individuals with varying degrees of severity of multisystem inflammatory syndrome in children (MIS-C).

METHODS: We performed a retrospective study of children diagnosed with MIS-C admitted to a single quaternary children's hospital from May 2020 to April 2021. We created an MIS-C severity score using the following parameters: hospital admission status (e.g., floor vs intensive care unit), need for inotropic or vasoactive medications, and need for mechanical ventilation. Univariate and multivariate analyses were performed to associate risk factors corresponding to the MIS-C severity score.

RESULTS: The study included 152 children who were followed for 14 days post hospital admission. A stepwise forward selection process identified seven physiologic variables associated with "severe" MIS-C according to a logistic regression. Specifically, a combination of elevated creatinine (p = 0.013), international normalized ratio (p = 0.002), brain natriuretic peptide (p = 0.001), white blood cell count (p = 0.009), ferritin (p = 0.041), respiratory rate (p = 0.047), and decreased albumin (p = 0.047) led to an excellent discrimination between mild versus severe MIS-C (AUC = 0.915).

CONCLUSION: This study derived a physiologic profile associated with the stratification of MIS-C severity.

IMPACT: Based on a cohort of 152 individuals diagnosed with MIS-C, this study derived a nomenclature that stratifies the severity of MIS-C. Investigated demographic, presentational vital signs, and blood analytes associated with severity of illness. Identification of a multivariate physiologic profile that strongly associates with MIS-C severity. This model allows the care team to recognize patients likely to require a higher level of intensive care.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.