Predictors of disease progression in pediatric dilated cardiomyopathy.
Ontology highlight
ABSTRACT: 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.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.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.URL: http://www.clinicaltrials.gov. Unique identifier: NCT00123071.
SUBMITTER: Molina KM
PROVIDER: S-EPMC4111626 | biostudies-literature | 2013 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA