Domiciliary sleep assessment technology for obstructive sleep apnoea diagnosis and upper airway surgical management - A scoping review

Obstructive sleep apnoea (OSA) is characterised by episodic complete or partial upper airway collapse during sleep. Diagnostic methods such as polysomnography (PSG) are resource-intensive and of limited utility for characterising upper-airway collapse to guide surgery. The expanding use of domiciliary sleep assessments presents an opportunity to improve access to OSA diagnosis. This review aims to evaluate the accuracy, clinical utility and limitations of domiciliary sleep assessment to diagnose OSA and localise airway collapse.

A scoping review was performed using PubMed, Scopus, Web of Science and the Cochrane Library. Articles published between January 1, 2015, and September 1, 2025, were included. The analysis focused on diagnostic performance compared with PSG, with exploratory airway phenotyping.

Thirty-three studies met inclusion criteria. Domiciliary sleep assessment showed a sensitivity and specificity for moderate-to-severe OSA exceeding 90% in several studies of selected high pre-test probability cohorts. However, performance to detect mild OSA remains suboptimal. In contrast, entropy-based audio analysis and mandibular positioners show promise in obstructive site localisation and treatment selection. Domiciliary sleep assessments are limited by night-to-night variability and inadequate airway flow phenotyping.

Domiciliary sleep assessment has clinically useful accuracy to diagnose moderate-to-severe OSA. Enhanced integration of upper airway flow characteristics represents a key area of development, with the potential to improve patient selection for targeted surgical interventions.