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Published on: May 24, 2016
Development of Cardiac Events and Functional Recovery Prediction Models for Pediatric Dilated Cardiomyopathy
Dong-Hee Kim1, Eun Seok Choi1, Bo Sang Kwon1
1Division of Pediatric Cardiac Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Insights
Pediatric dilated cardiomyopathy (DCMP) outcomes can be predicted using risk stratification models. These models help identify patients likely to achieve functional recovery (FR) or experience cardiac events (CEs), improving management strategies.
Area of Science:
- Pediatric Cardiology
- Cardiomyopathy Research
- Clinical Outcome Prediction
Background:
- Pediatric dilated cardiomyopathy (DCMP) presents a dual risk of mortality and potential for spontaneous functional recovery (FR).
- Effective management necessitates individualized outcome predictions to balance these competing possibilities.
Purpose of the Study:
- To develop and validate predictive models for functional recovery (FR) and cardiac events (CEs) in pediatric patients with DCMP.
- To identify key variables associated with FR and CEs within two years of presentation.
- To enhance prognostication and guide management strategies through risk stratification.
Main Methods:
- A retrospective review of 105 pediatric patients (age ≤ 18 years) with DCMP managed between 1994 and 2017.
- Logistic regression analysis to identify predictors of FR and CEs (death or heart transplantation [HTPL]) within two years.
- Formulation of two outcome prediction models based on identified variables.
Main Results:
- Within two years, 24.8% of patients achieved FR and 48.6% experienced CEs.
- Predictors of mortality included earlier presentation era and significant tricuspid regurgitation (TR).
- Predictors of FR included recent era, younger age, post-myocarditis etiology, and arrhythmia-mediated DCMP; idiopathic DCMP predicted CEs.
- A low-risk group identified by the prediction model demonstrated significantly higher HTPL-free survival (67.5% vs. 24.9% at 10 years).
Conclusions:
- Outcome prediction modeling and risk stratification can significantly enhance prognostication for pediatric DCMP.
- These models aid in tailoring management strategies for individual patients, potentially improving survival and reducing cardiac events.
- The study highlights the importance of identifying specific risk factors and protective factors for better patient outcomes.
Abstract:
Background: Since both the risk of death and the probability of spontaneous functional recovery (FR) coexist in association with pediatric dilated cardiomyopathy (DCMP), management should be based on individualized outcome predictions. Methods: A single-center retrospective review of 105 pediatric patients (age at presentation ≤ 18 years) with DCMP, managed between 1994 and 2017, was performed. Logistic regression was conducted to identify variables associated with FR and cardiac events (CEs), i.e., death or heart transplantation (HTPL), within 2 years after initial presentation. Two outcome prediction models were formulated using these variables. Results: Twenty-six (24.8%) and 51 patients (48.6%) experienced FR and CE, respectively, within 2 years after initial presentation. Predictors of mortality without HTPL were earlier era at presentation (HR: 4.13; 95% CI: 1.88-9.06; p < 0.001) and significant TR (≥moderate; HR: 4.31; 95% CI: 1.26-14.77; p = 0.020) in multivariable Cox regression model. Predictors of FR were recent era (HR: 4.49; 95% CI: 1.40-14.44; p = 0.0012), younger age at initial presentation (HR: 0.98 per 1 month increase; 95% CI: 0.97-0.99, p < 0.001), post-myocarditis DCMP (HR: 4.29; 95% CI: 1.32-13.93; p = 0.015), and arrhythmia-mediated DCMP (HR: 26.88; 95% CI: 2.61-276.70; p = 0.006). Risk factors for CEs was idiopathic DCMP (HR: 2.95; 95% CI: 1.32-6.56, p = 0.008). The low-risk group who had higher probability of FR than CE in prediction model had a slightly higher overall survival rate (71.4 vs. 52.2% at 10 years after presentation; log-rank p = 0.09) and a significantly higher HTPL-free survival rate (67.5 vs. 24.9% at 10 years after presentation; log-rank p < 0.001) than the high-risk group. Conclusions: Prognostication and management strategies for pediatric DCMP may be enhanced by risk stratification using outcome prediction modeling.
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