Unique Aspects of Hypertrophic Cardiomyopathy in Children.

Hypertrophic cardiomyopathy (HCM) is a primary heart muscle disease characterized by left ventricular hypertrophy that can be asymptomatic or with presentations that vary from left ventricular outflow tract obstruction, heart failure from diastolic dysfunction, arrhythmias, and/or sudden cardiac death. Children younger than 1 year of age tend to have worse outcomes and often have HCM secondary to inborn errors of metabolism or syndromes such as RASopathies. For children who survive or are diagnosed after 1 year of age, HCM outcomes are often favourable and similar to those seen in adults. This is because of sudden cardiac death risk stratification and medical and surgical innovations. Genetic testing and timely cardiac screening are paving the way for disease-modifying treatment as gene-specific therapies are being developed.

Exploring Health-Related Quality of Life in Children With Hypertrophic Cardiomyopathy and Relationship to Physical Activity.

BACKGROUND: Hypertrophic cardiomyopathy is a burdensome condition that inflicts both physical and psychological impairment on those with the disease, negatively impacting health-related quality of life (HRQoL). Given the abundance of evidence suggesting a role of physical activity (PA) in modulating HRQoL in healthy populations of children, we sought to determine the relationship between HRQoL and PA in children diagnosed with hypertrophic cardiomyopathy. METHODS AND RESULTS: A multicenter prospective observational cohort study was conducted, with patients with hypertrophic cardiomyopathy aged 10 to 19 years being provided a wrist-worn activity tracker (Fitbit Charge HR) to wear for 14 days. Patients self-reported on Pediatric Quality of Life 4.0 quality of life inventory items, which were associated with PA metrics following covariate adjustment using linear regression. A total of 56 participants were recruited to the study. The median age at enrollment was 15.5 years (interquartile range, 13.8-16.8), and 16 out of 56 (29%) of the cohort were girls. The cohort reported decreased metrics of physical, psychosocial, and total summary scores compared with health reference populations, with scores comparable with that of published populations with chronic disease. Increased physical HRQoL scores were significantly associated with increased daily steps taken, distance traveled, and flights of stairs climbed. CONCLUSIONS: These results show that impaired PA correlates with reduced HRQoL in children with hypertrophic cardiomyopathy, suggesting PA may partially mediate HRQoL in this population.

Administrative Databases: Friend or Foe in Paediatric Cardiomyopathy.

Background: Cardiomyopathy (CM) is a rare childhood disease associated with morbidity and mortality. Limited data exist on paediatric CM in Canada. Given the rare nature, single-centre studies are not sufficiently powered to address important questions. Therefore, administrative health data may serve as a resource for the study of childhood CM. The goal of this study was to validate the accuracy of International Classification of Diseases (ICD)-based algorithms to identify paediatric CM in health databases using a clinical registry as the gold standard. Methods: The clinical registry was compiled from outpatient and inpatient records at the Stollery Children's Hospital (January 1, 2013, to December 31, 2021). Patients were categorized as having CM or screened without CM. Data were linked to administrative health databases using the patient's Unique Lifetime Identifier. Algorithms based on the presence of ICD, 10th Revision, codes for CM were then evaluated, and cross-tabulations against the clinical registry were generated. Accuracy, positive predictive value, negative predictive value, sensitivity, and specificity were calculated. Results: The clinical registry had 90 patients with CM and 249 screened without CM. The algorithms ruled out CM (high negative predictive value) but had variability in the ability to diagnose CM positive predictive value. The algorithm that performed the best was based on a diagnosis of CM in a hospitalization or 2 ambulatory visits. Conclusions: A combination of inpatient and outpatient databases can be used, with acceptable accuracy, to identify paediatric patients with CM. This finding allows for the use of the identified algorithm for the comprehensive study of paediatric CM in Canada.

Contexte: La cardiomyopathie (CM) est une maladie rare de l'enfance associée à des taux élevés de morbidité et de mortalité et sur laquelle les données sont limitées en contexte canadien. En raison de la rareté de cette maladie, les études monocentriques ne peuvent atteindre la puissance statistique nécessaire pour répondre à certaines questions importantes. Les données administratives sur la santé peuvent donc constituer une ressource intéressante pour examiner la CM chez les enfants. La présente étude visait à valider l'exactitude d'algorithmes fondés sur la Classification internationale des maladies (CIM) pour repérer les cas de CM pédiatrique dans des bases de données sur la santé, en utilisant un registre clinique comme référence. Méthodologie: Un registre clinique a été élaboré à partir des dossiers de clinique interne et externe du Stollery Children's Hospital (du 1er janvier 2013 au 31 décembre 2021). Les patients ont été classés en deux catégories : atteints de CM ou dépistés sans CM. Les données ont été liées aux bases de données administratives sur la santé en utilisant le numéro d'identification unique des patients (Unique Lifetime Identifier). Des algorithmes fondés sur les codes de la CIM-10 ont été évalués et des analyses croisées avec le registre clinique ont été réalisées. L'exactitude, la valeur prédictive positive (VPP), la valeur prédictive négative (VPN), la sensibilité et la spécificité des algorithmes ont été calculées. Résultats: Le registre clinique comprenait 90 patients atteints de CM et 249 patients dépistés sans CM. Les algorithmes permettaient d'exclure correctement la CM (VPN élevée), mais leur capacité à établir le diagnostic de CM variait (VPP). L'algorithme le plus performant était fondé sur l'attribution d'un code diagnostique de CM lors d'une hospitalisation ou de deux visites ambulatoires. Conclusions: La combinaison de bases de données sur les hospitalisations et sur les soins externes peut être utilisée pour identifier les enfants atteints de CM avec une exactitude acceptable. Cette observation corrobore l'utilisation de l'algorithme ciblé pour réaliser une étude exhaustive de la CM chez l'enfant au Canada.