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Predictors of disease progression in pediatric dilated cardiomyopathy
Kimberly M Molina1, Peter Shrader, Steven D Colan
1University of Utah School of Medicine, Salt Lake City.
Insights
In children with dilated cardiomyopathy (DCM), older age at diagnosis, larger left ventricular size, and poorer systolic function predict disease progression. These findings aid in identifying pediatric DCM patients at higher risk for adverse outcomes.
Area of Science:
- Pediatric Cardiology
- Cardiovascular Imaging
- Clinical Research
Background:
- Children with dilated cardiomyopathy (DCM) face significant risks of mortality and cardiac transplantation.
- Predicting disease progression in pediatric DCM is crucial for timely intervention.
Purpose of the Study:
- To identify independent predictors of disease progression in pediatric patients with chronic dilated cardiomyopathy.
- To stratify risk for disease progression using clinical and echocardiographic parameters.
Main Methods:
- Prospective echocardiographic and clinical data collection over 18 months in 127 pediatric DCM patients.
- Exclusion of patients requiring advanced support or urgent transplant listing.
- Cox proportional hazards modeling and classification and regression tree analysis to identify predictors.
Main Results:
- Disease progression occurred in 22% of patients during follow-up.
- Independent predictors included older age at diagnosis, larger left ventricular (LV) end-diastolic dimension z-score, and lower septal peak systolic tissue Doppler velocity z-score.
- Risk stratification model achieved 89% sensitivity and 94% specificity.
Conclusions:
- Diagnosis after infancy and specific echocardiographic findings predict disease progression in stable pediatric DCM.
- These predictors can help identify children at risk for adverse events, guiding clinical management.
Background:
Despite medical advances, children with dilated cardiomyopathy (DCM) remain at high risk of death or need for cardiac transplantation. We sought to identify predictors of disease progression in pediatric DCM.
Methods And Results:
The Pediatric Heart Network evaluated chronic DCM patients with prospective echocardiographic and clinical data collection during an 18-month follow-up. Inclusion criteria were age <22 years and DCM disease duration >2 months. Patients requiring intravenous inotropic/mechanical support or listed status 1A/1B for transplant were excluded. Disease progression was defined as an increase in transplant listing status, hospitalization for heart failure, intravenous inotropes, mechanical support, or death. Predictors of disease progression were identified using Cox proportional hazards modeling and classification and regression tree analysis. Of the 127 patients, 28 (22%) had disease progression during the 18-month follow-up. Multivariable analysis identified older age at diagnosis (hazard ratio=1.14 per year; P<0.001), larger left ventricular (LV) end-diastolic M-mode dimension z-score (hazard ratio=1.49; P<0.001), and lower septal peak systolic tissue Doppler velocity z-score (hazard ratio=0.81; P=0.01) as independent predictors of disease progression. Classification and regression tree analysis stratified patients at risk of disease progression with 89% sensitivity and 94% specificity based on LV end-diastolic M-mode dimension z-score ≥7.7, LV ejection fraction <39%, LV inflow propagation velocity (color M-mode) z-score <-0.28, and age at diagnosis ≥8.5 months.
Conclusions:
In children with chronic stable DCM, a combination of diagnosis after late infancy and echocardiographic parameters of larger LV size and systolic and diastolic function predicted disease progression.
Clinical Trial Registration:
URL: http://www.clinicaltrials.gov. Unique identifier: NCT00123071.
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