Managing Dyslipidemia in Children: Current Approaches and the Potential of Artificial Intelligence

Dyslipidemia is abnormal lipid and lipoprotein levels in the blood, influenced mainly by genetics, lifestyle, and environmental factors. The management of lipid levels in children involves early screening, nonpharmacological interventions such as lifestyle modifications and dietary changes, nutraceuticals, and pharmacological treatments, including drug therapy. However, the prevalence of dyslipidemia in the pediatric population is increasing, particularly among obese children, which is a significant risk factor for cardiovascular complications. This narrative review analyzes current literature on the management of dyslipidemia in children and explores the potential of artificial intelligence (AI) to improve screening, diagnosis, and treatment outcomes. A comprehensive literature search was conducted using Google Scholar and PubMed databases, focusing primarily on the application of AI in managing dyslipidemia. AI has been beneficial in managing lipid disorders, including lipid profile analysis, obesity assessments, and familial hypercholesterolemia screening. Deep learning models, machine learning algorithms, and artificial neural networks have improved diagnostic accuracy and treatment efficacy. While most studies are done in the adult population, the promising results suggest further exploring AI management of dyslipidemia in children.