Multiscale Entropy Analysis of Unattended Oximetric Recordings to Assist in the Screening of Paediatric Sleep Apnoea at Home

Andrea Crespo,Gonzalo C Gutiérrez-Tobal,María L Alonso-Álvarez,Verónica Barroso-García,Félix Del Campo,Joaquín Terán-Santos,Roberto Hornero,Fernando Vaquerizo-Villar,Daniel Álvarez

doi:10.3390/e19060284

Abstract

Untreated paediatric obstructive sleep apnoea syndrome (OSAS) can severely affect the development and quality of life of children. In-hospital polysomnography (PSG) is the gold standard for a definitive diagnosis though it is relatively unavailable and particularly intrusive. Nocturnal portable oximetry has emerged as a reliable technique for OSAS screening. Nevertheless, additional evidences are demanded. Our study is aimed at assessing the usefulness of multiscale entropy (MSE) to characterise oximetric recordings. We hypothesise that MSE could provide relevant information of blood oxygen saturation (SpO2) dynamics in the detection of childhood OSAS. In order to achieve this goal, a dataset composed of unattended SpO2 recordings from 50 children showing clinical suspicion of OSAS was analysed. SpO2 was parameterised by means of MSE and conventional oximetric indices. An optimum feature subset composed of five MSE-derived features and four conventional clinical indices were obtained using automated bidirectional stepwise feature selection. Logistic regression (LR) was used for classification. Our optimum LR model reached 83.5% accuracy (84.5% sensitivity and 83.0% specificity). Our results suggest that MSE provides relevant information from oximetry that is complementary to conventional approaches. Therefore, MSE may be useful to improve the diagnostic ability of unattended oximetry as a simplified screening test for childhood OSAS.

Highlights

Paediatric obstructive sleep apnoea syndrome (OSAS) is a sleep-related breathing disorder characterised by intermittent and repetitive episodes of partial or complete collapse of the child’s upper airway while sleeping [1]
The aim of this study was two-fold: (i) firstly, to accomplish a comprehensive analysis of oximetry dynamics by means of multiscale entropy (MSE) in order to characterise differences between non-OSAS children and paediatric patients suffering from the disease; (ii) and second, to assess the usefulness of MSE-derived features in order to compose an optimum model from unattended oximetry able to accurately screen for paediatric OSAS at home
Se: sensitivity; Sp: specificity; PPV: positive predictive value; NPV: negative predictive value; logistic regression (LR)+: positive likelihood ratio; LR- negative likelihood ratio; Acc: accuracy; AUC: area under the receiver operating characteristic curve; oxygen desaturation index ≥ 3% (ODI3): oxygen desaturation index of 3%; SatMIN: minimum SpO2 during the whole recording; SatAVG: average SpO2 during the whole recording; CT95: percentage of time with a SpO2 below 95%

Summary

Introduction

Paediatric obstructive sleep apnoea syndrome (OSAS) is a sleep-related breathing disorder characterised by intermittent and repetitive episodes of partial or complete collapse of the child’s upper airway while sleeping [1]. Recurrent apnoeic events lead to gas exchange abnormalities and sleep disruption [2], which may cause major long-term adverse consequences in several body systems, such as neuropsychological and cognitive deficits, cardiovascular and metabolic dysfunction, and growth impairment [1,2,3]. This condition severely affects health, development and quality of life of infants and young children [4].

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