Infant Heart Development, Attachment, and Long-Term Cardiovascular Risk: From Congenital Disease to IoT-Based Predictions

This review explores the multifaceted relationship among infant heart development, early attachment experiences, and lifelong cardiovascular risks, shaped by genetic, environmental, and technological factors. The primary objective is to synthesise current global research on how congenital heart disease (CHD), parent-infant bonding, and early biological regulation interact to influence long-term cardiac health. Infant cardiac maturation depends on precise genetic programming, but it is susceptible to prenatal conditions, epigenetic modifications, perinatal inflammation, and preterm birth. Beyond structural development, early attachment plays a significant role in modulating stress physiology and autonomic balance, both of which have lasting impacts on cardiovascular function. Secure attachment is increasingly recognised as a protective factor that can buffer the effects of early biological vulnerabilities associated with cardiac disease. At a global level, CHD remains one of the most prevalent congenital anomalies, and advancing neonatal care has transformed survival outcomes. However, this improved survival has highlighted the growing burden of heart failure and other chronic complications later in life. Current clinical trials across continents are examining new biomarkers, early detection techniques, and interventions that target both cardiac repair and developmental adaptation. Parallel to these medical advances, digital health innovations are dramatically reshaping paediatric cardiology. Internet of Things (IoT)-based technologies—such as biosensing wearables, wireless monitors, and cloud-supported data analytics—are creating new possibilities for continuous monitoring and predictive modelling of infant cardiac health. These tools enable early detection of abnormalities, assist in personalised care planning, and may help forecast long-term heart failure risks by integrating physiological, behavioural, and environmental data. This interdisciplinary review calls for closer collaboration among cardiologists, developmental scientists, and data engineers to develop equitable, ethically responsible predictive systems. By linking traditional clinical understanding with emerging digital frameworks, it emphasises a holistic perspective on the prevention and management of cardiovascular disease from infancy through adulthood.