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. 2023 Jan;93(1):102-109.
doi: 10.1038/s41390-022-02108-6. Epub 2022 May 14.

Physiologic profile associated with severe multisystem inflammatory syndrome in children: a retrospective study

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Physiologic profile associated with severe multisystem inflammatory syndrome in children: a retrospective study

Fabio Savorgnan et al. Pediatr Res. 2023 Jan.

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Trajectory of the MSS.
Daily stacked bar plot of the MSS (left) and frequency histogram of the peak-MSS (right).
Fig. 2
Fig. 2. Univariate and multivariate analyses.
Odds ratios for the univariate (left) and multivariate (right) logistic regression analyses for the classification of mild vs severe MIS-C. Odds ratios are associated with an interquartile range increase in the respective variables. The interquartile ranges are listed in Tables 3 and 4.
Fig. 3
Fig. 3. Classification performance.
Receiver operating characteristic curve (left), and sensitivity and specificity curves (right) for the multivariate logistic model to classify mild vs severe MIS-C.

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References

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