Abstract 14117: Clinical Characteristics and Cardiovascular Outcomes in Childhood-Onset Hypertrophic Cardiomyopathy

Abstract

Introduction: The prevalence of childhood-onset hypertrophic cardiomyopathy (HCM) is lower than adult-onset disease, thus natural history is not well characterized. We aim to describe the characteristics and outcomes of childhood-onset HCM. Methods: We performed an observational cohort study of 6345 HCM patients from the Sarcomeric Human Cardiomyopathy Registry (SHaRe) and Toronto's SickKids hospital. HCM patients were stratified by age at diagnosis (<1 year (infancy), 1-18 years (childhood), >18 years (adulthood)) and assessed for composite endpoints reflecting heart failure (HF), life-threatening ventricular arrhythmias, atrial fibrillation (AF), and an overall composite that also included stroke and death. Results: Based on defined age of diagnosis stratification, 173 (3%) patients were diagnosed in infancy, 909 (14%) in childhood, and 5263 (83%) in adulthood. Childhood-onset HCM patients had a 2%/year event rate for the overall composite endpoint, with ventricular arrhythmias representing the most common event in the 1st decade following diagnosis, and HF and AF more common by the end of the 2nd decade ( Fig, a ). Sarcomeric HCM was more common in childhood-onset HCM (62%) and carried a worse prognosis than non-sarcomeric disease, including a >2-fold increased risk of HF (HR adj 2.39 [1.36-4.20], p=0.003) and 67% increased risk of overall composite events (HR adj 1.67 [1.16-2.41], p=0.006). When compared to adult-onset HCM, childhood-onset was 36% more likely to develop life-threatening ventricular arrhythmias (HR adj 1.36 [1.03-1.80]) and twice as likely to require transplant or ventricular assist device (HR adj 1.99 [1.23-3.23]) ( Fig, b ). Conclusion: Patients with childhood-onset HCM are more likely to have sarcomeric disease, carry higher risk of life-threatening ventricular arrythmias, and have greater need for advanced HF therapies. These findings provide insight into disease biology and can help improve the precision of risk prediction.