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.
Insights
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.
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).
Objectives:
This study was designed to investigate clinical differences between pediatric patients who presented with chest pain, tachycardia, and/or tachypnea who subsequently were or were not diagnosed with myocarditis. The results were used to develop a decision tree to aid in rapid diagnosis of pediatric myocarditis.
Methods:
A retrospective case-control study was performed using the electronic medical records of children aged 0 to 18 years between the years 2003 and 2020 with a complaint of chest pain, tachycardia, and/or tachypnea. Patients included in the study were those diagnosed with myocarditis and those with suspected myocarditis, which was ultimately ruled out. Demographic and clinical differences between the research groups were analyzed. A decision tree was rendered using the rpart (Recursive Partitioning and Regression Trees) package.
Results:
Four thousand one hundred twenty-five patients were screened for eligibility. Seventy-three myocarditis patients and 292 nonmyocarditis patients were included. Compared with the control group, the study group was found to have a higher mean respiratory rate (37 ± 23 vs 23 ± 7 breaths per minute) and mean heart rate (121 ± 44 vs 97 ± 25 beats per minute) and lower mean systolic and diastolic blood pressure (102 ± 27/56 ± 17 mm Hg vs 114 ± 14/67 ± 10 mm Hg). The mean white blood cell count was greater in the case group (13 ± 6 vs 10 ± 5 × 10 3 /μL). A decision tree was rendered using simple demographic and clinical variables. The accuracy of the algorithm was 85.2%, with 100% accuracy in patients aged 0 to 2.5 years and 69% in patients aged 2.5 to 18 years.
Conclusion:
The clinical and laboratory characteristics described in this study were similar to what is described in the literature. The decision tree may aid in the diagnosis of myocarditis in patients 2.5 years and younger. In the population aged 2.5 to 18 years, the decision tree did not constitute an adequate tool for detecting myocarditis.
