The future of paediatric obstructive sleep apnoea assessment: Integrating artificial intelligence, biomarkers, and more

Assessing obstructive sleep apnoea (OSA) in children involves various methodologies, including sleep studies, nocturnal oximetry, and clinical evaluations. Previous literature has extensively discussed these traditional methods. Despite this, there is no consensus on the optimal screening method for childhood OSA, further complicated by the complexity and limited availability of diagnostic polysomnography (PSG). Recent advancements, such as the integration of artificial intelligence, biomarkers, 3D facial photography, and wearable technology, offer promising alternatives for early detection and more accurate diagnosis of OSA in children. This article provides a comprehensive review of these innovative techniques, highlighting their potential to enhance diagnostic accuracy and overcome the limitations of current methods. With an emphasis on cutting-edge technologies and emerging biomarkers, we discuss the future directions for paediatric OSA assessments and their potential to revolutionise clinical practice.