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Noninvasive Assessment of Cardiac Abnormalities in Experimental Autoimmune Myocarditis by Magnetic Resonance Microscopy Imaging in the Mouse

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Published on: June 20, 2014

Myocarditis-A Helpful Algorithm to Overcome Diagnostic Challenges in the Pediatric Population.

Nitzan Knoler¹, Hanna Krymko², Leonel Slanovic²

¹From the Faculty of Health Sciences, Ben Gurion University of the Negev.

Pediatric Emergency Care

|March 12, 2024

Summary

This study developed a decision tree to help diagnose pediatric myocarditis, finding it most accurate for children under 2.5 years old. The tool aids in identifying myocarditis in young children but is less effective in older pediatric patients.

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Last Updated: Jul 1, 2025

Noninvasive Assessment of Cardiac Abnormalities in Experimental Autoimmune Myocarditis by Magnetic Resonance Microscopy Imaging in the Mouse

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Published on: June 20, 2014

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A Modified Sonographic Algorithm for Image Acquisition in Life-Threatening Emergencies in the Critically Ill Newborn

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Published on: April 7, 2023

Area of Science:

Pediatric Cardiology
Infectious Diseases
Clinical Decision Support

Background:

Myocarditis is a serious condition in children presenting with symptoms like chest pain, tachycardia, and tachypnea.
Accurate and timely diagnosis is crucial for effective management and improved patient outcomes.
Existing diagnostic methods may benefit from decision support tools, especially in emergency settings.

Purpose of the Study:

To identify clinical differences between pediatric myocarditis cases and controls presenting with chest pain, tachycardia, and/or tachypnea.
To develop and evaluate a decision tree algorithm for the rapid diagnosis of pediatric myocarditis.

Main Methods:

Retrospective case-control study of electronic medical records from 2003-2020.
Inclusion criteria: children (0-18 years) with chest pain, tachycardia, and/or tachypnea, diagnosed with or suspected myocarditis.
Analysis of demographic and clinical data; decision tree developed using Recursive Partitioning and Regression Trees (rpart).

Main Results:

73 myocarditis patients and 292 non-myocarditis controls were analyzed.
Myocarditis group showed higher respiratory rate, heart rate, white blood cell count, and lower blood pressure compared to controls.
Decision tree achieved 85.2% overall accuracy, with 100% accuracy in children aged 0-2.5 years and 69% in those aged 2.5-18 years.

Conclusions:

Clinical and laboratory findings align with existing literature on pediatric myocarditis.
The developed decision tree shows promise as a diagnostic aid for myocarditis in children aged 2.5 years and younger.
The decision tree's diagnostic utility is limited in older pediatric patients (2.5-18 years).