Incorporating Risk Stratification Into the Practice of Pediatric Preventive Cardiology

The Detection, Evaluation, and Management of Dyslipidemia in Children and Adolescents: A Canadian Cardiovascular Society/Canadian Pediatric Cardiology Association Clinical Practice Update

Atherosclerosis begins in youth and is directly linked with the presence and severity of cardiovascular risk factors, including dyslipidemia. Thus, the timely identification and management of dyslipidemia in childhood might slow atherosclerotic progression and decrease the risk of cardiovascular disease in adulthood. This is particularly true for children with genetic disorders resulting in marked dyslipidemia, including familial hypercholesterolemia, which remains frequently undiagnosed. Universal and cascade screening strategies can effectively identify cases of pediatric dyslipidemia. In the clinical evaluation of children with dyslipidemia, evaluating for secondary causes of dyslipidemia, including medications and systemic disorders is essential. The first line therapy generally centres around lifestyle modifications, with dietary changes specific to the dyslipidemia phenotype. Indications for medication depend on the severity of dyslipidemia and an individualized assessment of cardiovascular risk. Despite an expanding evidence base supporting the detection and timely management of pediatric dyslipidemia, numerous knowledge gaps remain, including a sufficient evidence base to support more widespread screening, thresholds for initiation of pharmacotherapy, and treatment targets. Further studies on the most appropriate age for statin initiation and long-term safety studies of statin use in youth are also required. The most pressing matter, however, is the development of knowledge translation strategies to improve the screening and detection of lipid disorders in Canadian youth.

Machine learning analysis: general features, requirements and cardiovascular applications

Artificial intelligence represents the science which will probably change the future of medicine by solving actually challenging issues. In this special article, the general features of machine learning are discussed. First, a background explanation regarding the division of artificial intelligence, machine learning and deep learning is given and a focus on the structure of machine learning subgroups is shown. The traditional process of a machine learning analysis is described, starting from the collection of data, across features engineering, modelling and till the validation and deployment phase. Due to the several applications of machine learning performed in literature in the last decades and the lack of some guidelines, the need of a standardization for reporting machine learning analysis results emerged. Some possible standards for reporting machine learning results are identified and discussed deeply; these are related to study population (number of subjects), repeatability of the analysis, validation, results, comparison with current practice. The way to the use of machine learning in clinical practice is open and the hope is that, with emerging technology and advanced digital and computational tools, available from hospitalization and subsequently after discharge, it will also be possible, with the help of increasingly powerful hardware, to build assistance strategies useful in clinical practice.

Healthy Lifestyle Intervention and Weight Loss Improve Cardiovascular Dysfunction in Children with Obesity

Background: The aim of this study was to determine the effects of a 12-month healthy lifestyle intervention based on diet plus physical activity on cardiovascular structure and function in children and adolescents with obesity; Methods: In this longitudinal study we assessed changes in anthropometric, biochemical and cardiovascular variables in 55 subjects with obesity (6–16 years) before and after a 12-month behavioral program based on Mediterranean diet plus exercise regimen. Subjects were divided in two groups based on negative change in BMI z-score ≥10% from baseline: weight losers (WL) and non-weight losers (NWL); Results: After 12 months, WL showed a significant improvement of metabolic parameters. Treatment was effective in increasing the mitral peak early diastolic velocity E and the E/A ratio. In subjects with a reduction of the number of NCEP-ATPIII metabolic syndrome criteria, lifestyle intervention reduced left ventricular area and volume. Intervention reduced carotid intima-media thickness in subjects showing a decrease of the systemic blood pressure; Conclusions: In children with obesity, cardiovascular impairment could be partially reversed by a healthy lifestyle intervention. To adopt prompt behavioral programs in childhood obesity is crucial both for prevention and treatment of precocious complications and could have an exponential impact on long-term morbidity and mortality.

Life-Course Implications of Pediatric Risk Factors for Cardiovascular Disease

The concept that origins of cardiovascular disease (CVD) begin in childhood is supported by substantial evidence. Prospective studies beginning in childhood report associations of childhood obesity, abnormal blood pressure (BP), dyslipidemia, diabetes, and tobacco use with intermediate CVD markers, including left ventricular hypertrophy and vascular stiffness in young adulthood. Trajectory analyses from longitudinal studies describe discrete BP pathways from childhood to young adult status of hypertension and prehypertension. Among individuals with familial hypercholesterolemia, abnormal low-density lipoprotein cholesterol levels are present in childhood. Some children are at risk for future CVD owing to hereditary factors, psychosocial stress, race, low birth weight, or other nonmodifiable exposures. Behavioural factors, including suboptimal diet, sedentary activity, and tobacco use, in childhood augment risk and can be modified to reduce risk. Pharmacologic treatments are reserved for those at high levels of the BP and cholesterol distributions and for those with diabetes and additional risk factors.