Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea.

Adrián Martín-Montero,Gonzalo C Gutiérrez-Tobal,Félix Del Campo,Roberto Hornero,Leila Kheirandish-Gozal,Verónica Barroso-García,David Gozal,Daniel Álvarez

doi:10.3390/e23081016

Abstract

Pediatric obstructive sleep apnea (OSA) is a breathing disorder that alters heart rate variability (HRV) dynamics during sleep. HRV in children is commonly assessed through conventional spectral analysis. However, bispectral analysis provides both linearity and stationarity information and has not been applied to the assessment of HRV in pediatric OSA. Here, this work aimed to assess HRV using bispectral analysis in children with OSA for signal characterization and diagnostic purposes in two large pediatric databases (0–13 years). The first database (training set) was composed of 981 overnight ECG recordings obtained during polysomnography. The second database (test set) was a subset of the Childhood Adenotonsillectomy Trial database (757 children). We characterized three bispectral regions based on the classic HRV frequency ranges (very low frequency: 0–0.04 Hz; low frequency: 0.04–0.15 Hz; and high frequency: 0.15–0.40 Hz), as well as three OSA-specific frequency ranges obtained in recent studies (BW1: 0.001–0.005 Hz; BW2: 0.028–0.074 Hz; BWRes: a subject-adaptive respiratory region). In each region, up to 14 bispectral features were computed. The fast correlation-based filter was applied to the features obtained from the classic and OSA-specific regions, showing complementary information regarding OSA alterations in HRV. This information was then used to train multi-layer perceptron (MLP) neural networks aimed at automatically detecting pediatric OSA using three clinically defined severity classifiers. Both classic and OSA-specific MLP models showed high and similar accuracy (Acc) and areas under the receiver operating characteristic curve (AUCs) for moderate (classic regions: Acc = 81.0%, AUC = 0.774; OSA-specific regions: Acc = 81.0%, AUC = 0.791) and severe (classic regions: Acc = 91.7%, AUC = 0.847; OSA-specific regions: Acc = 89.3%, AUC = 0.841) OSA levels. Thus, the current findings highlight the usefulness of bispectral analysis on HRV to characterize and diagnose pediatric OSA.

Highlights

Licensee MDPI, Basel, Switzerland.Obstructive sleep apnea (OSA) is a common respiratory disorder affecting up to 5% of the general pediatric population [1]
In a study using regular spectral analysis [27], we recently showed that there exist obstructive sleep apnea (OSA)-specific frequency ranges that allow for better characterization of the alterations occurring in heart rate variability (HRV) in the context of pediatric OSA
Our methodology allowed us to obtain two feature subsets, one containing information regarding bispectral regions based on classic HRV frequency ranges, and the other one with OSA-specific bispectral regions

Summary

Introduction

Licensee MDPI, Basel, Switzerland.Obstructive sleep apnea (OSA) is a common respiratory disorder affecting up to 5% of the general pediatric population [1]. OSA is characterized by the occurrence of either total upper airway obstruction (apnea events) and/or events of significant airflow reduction (hypopnea events) during sleep, leading to decreased blood oxygen saturation and/or sleep fragmentation [2,3]. The increased cognitive and cardiovascular risks obviously threaten the long-term cardiovascular health [1,3,6] and academic potential of children [7], such that early detection and treatment of pediatric OSA are essential. Nocturnal laboratory-based polysomnography (PSG) is considered the standard diagnosis technique for pediatric OSA. This test allows for the detection of the presence or absence of pediatric OSA and enables estimates of OSA severity [8,9]

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