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

Mon Ohn; Kathleen J Maddison; Jennifer H Walsh; Britta S von Ungern-Sternberg

doi:10.1016/j.prrv.2025.01.004

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

Paediatr Respir Rev. 2025 Jan 19:S1526-0542(25)00006-5. doi: 10.1016/j.prrv.2025.01.004. Online ahead of print.

Authors

Mon Ohn¹, Kathleen J Maddison², Jennifer H Walsh³, Britta S von Ungern-Sternberg⁴

Affiliations

¹ Department of Respiratory and Sleep Medicine, Perth Children's Hospital Nedlands WA Australia; Division of Paediatrics, Medical School, The University of Western Australia, Crawley WA Australia; Perioperative Medicine Team, The Kids Research Institute Australia Nedlands WA Australia; Institute for Paediatric Perioperative Excellence, The University of Western Australia, Crawley WA Australia. Electronic address: mon.ohn@health.wa.gov.au.
² Institute for Paediatric Perioperative Excellence, The University of Western Australia, Crawley WA Australia; Centre for Sleep Science, School of Human Sciences, The University of Western Australia, Crawley WA Australia; West Australian Sleep Disorders Research Institute, Department of Pulmonary Physiology & Sleep Medicine, Sir Charles Gairdner Hospital Nedlands WA Australia.
³ Institute for Paediatric Perioperative Excellence, The University of Western Australia, Crawley WA Australia; Centre for Sleep Science, School of Human Sciences, The University of Western Australia, Crawley WA Australia; West Australian Sleep Disorders Research Institute, Department of Pulmonary Physiology & Sleep Medicine, Sir Charles Gairdner Hospital Nedlands WA Australia. Electronic address: https://twitter.com/jenforsleep.
⁴ Perioperative Medicine Team, The Kids Research Institute Australia Nedlands WA Australia; Institute for Paediatric Perioperative Excellence, The University of Western Australia, Crawley WA Australia; Division of Emergency Medicine, Anaesthesia and Pain Medicine, Medical School, The University of Western Australia, Crawley WA Australia; Department of Anaesthesia and Pain Medicine, Perth Children's Hospital Nedlands WA Australia. Electronic address: https://twitter.com/britta_sleepydr.

PMID: 39893075
DOI: 10.1016/j.prrv.2025.01.004

Abstract

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.

Keywords: Artificial Intelligence (AI); Biomarkers; Innovative assessment; Oximetry; Paediatric obstructive sleep apnoea (OSA); Polysomnography; Screening.

Publication types

Review