Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"?

Paediatric sleep diagnostics is performed using complex multichannel tests in specialised centres, limiting access and availability and resulting in delayed diagnosis and management. Such investigations are often challenging due to patient size (prematurity), tolerability, and compliance with "gold standard" equipment. Children with sensory/behavioural issues, at increased risk of sleep disordered breathing (SDB), often find standard diagnostic equipment difficult.SDB can have implications for a child both in terms of physical health and neurocognitive development. Potential sequelae of untreated SDB includes failure to thrive, cardiopulmonary disease, impaired learning and behavioural issues. Prompt and accurate diagnosis of SDB is important to facilitate early intervention and improve outcomes.The current gold-standard diagnostic test for SDB is polysomnography (PSG), which is expensive, requiring the interpretation of a highly specialised physiologist. PSG is not feasible in low-income countries or outwith specialist sleep centres. During the coronavirus disease 2019 pandemic, efforts were made to improve remote monitoring and diagnostics in paediatric sleep medicine, resulting in a paradigm shift in SDB technology with a focus on automated diagnosis harnessing artificial intelligence (AI). AI enables interrogation of large datasets, setting the scene for an era of "sleep-omics", characterising the endotypic and phenotypic bedrock of SDB by drawing on genetic, lifestyle and demographic information. The National Institute for Health and Care Excellence recently announced a programme for the development of automated home-testing devices for SDB. Scorer-independent scalable diagnostic approaches for paediatric SDB have potential to improve diagnostic accuracy, accessibility and patient tolerability; reduce health inequalities; and yield downstream economic and environmental benefits.

Role of overnight oximetry in assessing the severity of obstructive sleep apnoea in typically developing children: a multicentre study.

BACKGROUND AND OBJECTIVE: Cardiorespiratory polygraphy (CRP) is the predominant technology used to diagnose obstructive sleep apnoea (OSA) in tertiary centres in the UK. Nocturnal pulse oximetry (NPO) is, however, cheaper and more accessible. This study evaluated the ability of NPO indices to predict OSA in typically developing (TD) children. METHODS: Indices from simultaneous NPO and CRP recordings were compared in TD children (aged 1-16 years) referred to evaluate OSA in three tertiary centres. OSA was defined as an obstructive apnoea-hypopnoea index (OAHI) ≥1 event/hour. Receiver operating characteristic curves assessed the diagnostic accuracy of NPO indices including ODI3 (3% Oxygen Desaturation Index, ODI4 (4% Oxygen Desaturation Index), delta 12 s index and minimum oxygen saturation. Two-by-two tables were generated to determine the sensitivities and specificities of whole number cut-off values for predicting OAHIs ≥1, 5 and 10 events/hour. RESULTS: Recordings from 322 TD children, 197 male (61.2%), median age 4.9 years (range 1.1-15.6), were reviewed. OAHI was ≥1/hour in 144 (44.7%), ≥5/hour in 61 (18.9%) and ≥10/hour in 28 (8.7%) cases. ODI3 and ODI4 had the best diagnostic accuracy. ODI3 ≥7/hour and ODI4 ≥4/hour predicted OSA in TD children with sensitivities/specificities of 57.6%/85.4% and 46.2%/91.6%, respectively. ODI3 ≥8/hour was the best predictor of OAHI ≥5/hour (sensitivity 82.0%, specificity 84.3%). CONCLUSION: Raised ODI3 and ODI4 predict OSA in TD children with high specificity but variable sensitivity. NPO may be an alternative to diagnose moderate-severe OSA if access to CRP is limited. Low sensitivities to detect mild OSA mean that confirmatory CRP is needed if NPO is normal.