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Murine Myocardial Infarction Model using Permanent Ligation of Left Anterior Descending Coronary Artery

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Development of a Predictive Model for Cardiac Dysfunction in MIS-C Patients Utilizing Laboratory Biomarkers.

Guliz Erdem¹, Brendan Galdo², Roshini S Abraham³

¹Division of Infectious Diseases, Department of Pediatrics, Nationwide Children's Hospital, Columbus, OH 43205, USA.

Children (Basel, Switzerland)

|February 27, 2026

Summary

This summary is machine-generated.

Early identification of cardiac dysfunction in children with multi-system inflammatory syndrome (MIS-C) is key. Biomarkers like C-reactive protein, fibrinogen, and procalcitonin can predict left ventricular systolic dysfunction (LVSD) in MIS-C patients.

Keywords:

Kawasaki disease MIS-C data analytics left ventricular systolic dysfunction

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Area of Science:

Pediatric Cardiology
Pediatric Critical Care
Immunology

Background:

Multi-system inflammatory syndrome in children (MIS-C) can lead to cardiac dysfunction.
Early identification of left ventricular systolic dysfunction (LVSD) is critical for managing MIS-C.

Purpose of the Study:

To predict LVSD in MIS-C patients using admission laboratory data.
To assess the efficacy of a predictive model for LVSD in MIS-C.

Main Methods:

Retrospective chart review of 1474 MIS-C patients.
LASSO logistic regression model developed using laboratory data within 24 hours of admission.
Analysis included lymphocyte count, albumin, C-reactive protein, fibrinogen, and procalcitonin.

Main Results:

297 out of 1474 MIS-C patients had LVSD.
C-reactive protein, fibrinogen, and procalcitonin were identified as early predictive biomarkers.
The predictive model achieved a cross-validated AUC of 0.845 for LVSD.

Conclusions:

Widely available biomarkers can effectively predict systolic dysfunction in MIS-C.
Elevated C-reactive protein, fibrinogen, and procalcitonin levels indicate high risk for LVSD.
A validated logistic regression model demonstrates excellent discrimination for LVSD in MIS-C.