IMPORTANCE Sudden cardiac death (SCD) is the most common mode of death in childhood hypertrophic cardiomyopathy (HCM), but there is no validated algorithm to identify those at highest risk. OBJECTIVE To develop and validate an SCD risk prediction model that provides individualized risk estimates. DESIGN, SETTING, AND PARTICIPANTS A prognostic model was developed from a retrospective, multicenter, longitudinal cohort study of 1024 consecutively evaluated patients aged 16 years or younger with HCM. The study was conducted from January 1, 1970, to December 31, 2017. EXPOSURES The model was developed using preselected predictor variables (unexplained syncope, maximal left-ventricular wall thickness, left atrial diameter, left-ventricular outflow tract gradient, and nonsustained ventricular tachycardia) identified from the literature and internally validated using bootstrapping. MAIN OUTCOMES AND MEASURES A composite outcome of SCD or an equivalent event (aborted cardiac arrest, appropriate implantable cardioverter defibrillator therapy, or sustained ventricular tachycardia associated with hemodynamic compromise). RESULTS Of the 1024 patients included in the study, 699 were boys (68.3%); mean (interquartile range [IQR]) age was 11 (7-14) years. Over a median follow-up of 5.3 years (IQR, 2.6-8.3; total patient years, 5984), 89 patients (8.7%) died suddenly or had an equivalent event (annual event rate, 1.49; 95% CI, 1.15-1.92). The pediatric model was developed using preselected variables to predict the risk of SCD. The model's ability to predict risk at 5 years was validated; the C statistic was 0.69 (95% CI, 0.66-0.72), and the calibration slope was 0.98 (95% CI, 0.59-1.38). For every 10 implantable cardioverter defibrillators implanted in patients with 6% or more of a 5-year SCD risk, 1 patient may potentially be saved from SCD at 5 years. CONCLUSIONS AND RELEVANCE This new, validated risk stratification model for SCD in childhood HCM may provide individualized estimates of risk at 5 years using readily obtained clinical risk factors. External validation studies are required to demonstrate the accuracy of this model's predictions in diverse patient populations.
Aims Calmodulinopathies are rare life-threatening arrhythmia syndromes which affect mostly young individuals and are, caused by mutations in any of the three genes (CALM 1–3) that encode identical calmodulin proteins. We established the International Calmodulinopathy Registry (ICalmR) to understand the natural history, clinical features, and response to therapy of patients with a CALM-mediated arrhythmia syndrome. Methods and results A dedicated Case Report File was created to collect demographic, clinical, and genetic information. ICalmR has enrolled 74 subjects, with a variant in the CALM1 (n = 36), CALM2 (n = 23), or CALM3 (n = 15) genes. Sixty-four (86.5%) were symptomatic and the 10-year cumulative mortality was 27%. The two prevalent phenotypes are long QT syndrome (LQTS; CALM-LQTS, n = 36, 49%) and catecholaminergic polymorphic ventricular tachycardia (CPVT; CALM-CPVT, n = 21, 28%). CALM-LQTS patients have extremely prolonged QTc intervals (594 ± 73 ms), high prevalence (78%) of life-threatening arrhythmias with median age at onset of 1.5 years [interquartile range (IQR) 0.1–5.5 years] and poor response to therapies. Most electrocardiograms (ECGs) show late onset peaked T waves. All CALM-CPVT patients were symptomatic with median age of onset of 6.0 years (IQR 3.0–8.5 years). Basal ECG frequently shows prominent U waves. Other CALM-related phenotypes are idiopathic ventricular fibrillation (IVF, n = 7), sudden unexplained death (SUD, n = 4), overlapping features of CPVT/LQTS (n = 3), and predominant neurological phenotype (n = 1). Cardiac structural abnormalities and neurological features were present in 18 and 13 patients, respectively. Conclusion Calmodulinopathies are largely characterized by adrenergically-induced life-threatening arrhythmias. Available therapies are disquietingly insufficient, especially in CALM-LQTS. Combination therapy with drugs, sympathectomy, and devices should be considered.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.