Longer and Deeper Desaturations Are Associated With the Worsening of Mild Sleep Apnea: The Sleep Heart Health Study

Cerebrovascular pathology mediates associations between hypoxemia during rapid eye movement sleep and medial temporal lobe structure and function in older adults

Obstructive sleep apnea (OSA) is common in older adults and is associated with medial temporal lobe (MTL) degeneration and memory decline in aging and Alzheimer's disease (AD). However, the underlying mechanisms linking OSA to MTL degeneration and impaired memory remains unclear. By combining magnetic resonance imaging (MRI) assessments of cerebrovascular pathology and MTL structure with clinical polysomnography and assessment of overnight emotional memory retention in older adults at risk for AD, cerebrovascular pathology in fronto-parietal brain regions was shown to statistically mediate the relationship between OSA-related hypoxemia, particularly during rapid eye movement (REM) sleep, and entorhinal cortical thickness. Reduced entorhinal cortical thickness was, in turn, associated with impaired overnight retention in mnemonic discrimination ability across emotional valences for high similarity lures. These findings identify cerebrovascular pathology as a contributing mechanism linking hypoxemia to MTL degeneration and impaired sleep-dependent memory in older adults.

Sleep-Disordered Breathing, Hypoxia, and Pulmonary Physiologic Influences in Atrial Fibrillation

BACKGROUND

We leverage a large clinical cohort to elucidate sleep-disordered breathing and sleep-related hypoxia in incident atrial fibrillation (AF) development given the yet unclear contributions of sleep-related hypoxia and pulmonary physiology in sleep-disordered breathing and AF.

METHODS AND RESULTS

Patients who underwent sleep studies at Cleveland Clinic January 2, 2000, to December 30, 2015, comprised this retrospective cohort. Cox proportional hazards models were used to examine apnea hypopnea index, percentage time oxygen saturation <90%, minimum and mean oxygen saturation, and maximum end-tidal carbon dioxide on incident AF adjusted for age, sex, race, body mass index, cardiopulmonary disease and risk factors, antiarrhythmic medications, and positive airway pressure. Those with spirometry were additionally adjusted for forced expiratory volume in 1 second, forced vital capacity, and forced expiratory volume in 1 second/forced vital capacity. This cohort (n=42 057) was 50.7±14.1 years, 51.3% men, 74.1% White individuals, had median body mass index 33.2 kg/m2, and 1947 (4.6%) developed AF over 5 years. A 10-unit apnea hypopnea index increase was associated with 2% higher AF risk (hazard ratio [HR], 1.02 [95% CI, 1.00-1.03]). A 10-unit increase in percentage time oxygen saturation <90% and 10-unit decreases in mean and minimum oxygen saturation were associated with 6% (HR, 1.06 [95% CI, 1.04-1.08]), 30% (HR, 1.30 [95% CI, 1.18-1.42]), and 9% (HR, 1.09 [95% CI, 1.03-1.15]) higher AF risk, respectively. After adjustment for spirometry (n=9683 with available data), only hypoxia remained significantly associated with incident AF, although all coefficients were stable.

CONCLUSIONS

Sleep-related hypoxia was associated with incident AF in this clinical cohort, consistent across 3 measures of hypoxia, persistent after adjustment for pulmonary physiologic impairment. Findings identify a strong role for sleep-related hypoxia in AF development without pulmonary physiologic interdependence.

A Review of Novel Oximetry Parameters for the Prediction of Cardiovascular Disease in Obstructive Sleep Apnoea

Obstructive sleep apnoea (OSA) is a sleep disorder with repetitive collapse of the upper airway during sleep, which leads to intermittent hypoxic events overnight, adverse neurocognitive, metabolic complications, and ultimately an increased risk of cardiovascular disease (CVD). The standard diagnostic parameter for OSA, apnoea-hypopnoea index (AHI), is inadequate to predict CVD morbidity and mortality, because it focuses only on the frequency of apnoea and hypopnoea events, and fails to reveal other physiological information for the prediction of CVD events. Novel parameters have been introduced to compensate for the deficiencies of AHI. However, the calculation methods and criteria for these parameters are unclear, hindering their use in cross-study analysis and studies. This review aims to discuss novel parameters for predicting CVD events from oximetry signals and to summarise the corresponding computational methods.

Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals

The high prevalence of sleep apnea and the limitations of polysomnography have prompted the investigation of strategies aimed at automated diagnosis using a restricted number of physiological measures. This study aimed to demonstrate that thoracic (THO) and abdominal (ABD) movement signals are useful for accurately estimating the severity of sleep apnea, even if central respiratory events are present. Thus, we developed 2D-convolutional neural networks (CNNs) jointly using THO and ABD to automatically estimate sleep apnea severity and evaluate the central event contribution. Our proposal achieved an intraclass correlation coefficient (ICC) = 0.75 and a root mean square error (RMSE) = 10.33 events/h when estimating the apnea-hypopnea index, and ICC = 0.83 and RMSE = 0.95 events/h when estimating the central apnea index. The CNN obtained accuracies of 94.98%, 79.82%, and 81.60% for 5, 15, and 30 events/h when evaluating the complete apnea hypopnea index. The model improved when the nature of the events was central: 98.72% and 99.74% accuracy for 5 and 15 events/h. Hence, the information extracted from these signals using CNNs could be a powerful tool to diagnose sleep apnea, especially in subjects with a high density of central apnea events.

Utilizing Envelope Analysis of a Nasal Pressure Signal for Sleep Apnea Severity Estimation

Obstructive sleep apnea (OSA) severity assessment is based on manually scored respiratory events and their arbitrary definitions. Thus, we present an alternative method to objectively evaluate OSA severity independently of the manual scorings and scoring rules. A retrospective envelope analysis was conducted on 847 suspected OSA patients. Four parameters were calculated from the difference between the nasal pressure signal's upper and lower envelopes: average (AV), median (MD), standard deviation (SD), and coefficient of variation (CoV). We computed the parameters from the entirety of the recorded signals to perform binary classifications of patients using three different apnea-hypopnea index (AHI) thresholds (5-15-30). Additionally, the calculations were undertaken in 30-second epochs to estimate the ability of the parameters to detect manually scored respiratory events. Classification performances were assessed with areas under the curves (AUCs). As a result, the SD (AUCs ≥ 0.86) and CoV (AUCs ≥ 0.82) were the best classifiers for all AHI thresholds. Furthermore, non-OSA and severe OSA patients were separated well with SD (AUC = 0.97) and CoV (AUC = 0.95). Respiratory events within the epochs were identified moderately with MD (AUC = 0.76) and CoV (AUC = 0.82). In conclusion, envelope analysis is a promising alternative method by which to assess OSA severity without relying on manual scoring or the scoring rules of respiratory events.

Mitochondria Need Their Sleep: Redox, Bioenergetics, and Temperature Regulation of Circadian Rhythms and the Role of Cysteine-Mediated Redox Signaling, Uncoupling Proteins, and Substrate Cycles

Although circadian biorhythms of mitochondria and cells are highly conserved and crucial for the well-being of complex animals, there is a paucity of studies on the reciprocal interactions between oxidative stress, redox modifications, metabolism, thermoregulation, and other major oscillatory physiological processes. To address this limitation, we hypothesize that circadian/ultradian interaction of the redoxome, bioenergetics, and temperature signaling strongly determine the differential activities of the sleep–wake cycling of mammalians and birds. Posttranslational modifications of proteins by reversible cysteine oxoforms, S-glutathionylation and S-nitrosylation are shown to play a major role in regulating mitochondrial reactive oxygen species production, protein activity, respiration, and metabolomics. Nuclear DNA repair and cellular protein synthesis are maximized during the wake phase, whereas the redoxome is restored and mitochondrial remodeling is maximized during sleep. Hence, our analysis reveals that wakefulness is more protective and restorative to the nucleus (nucleorestorative), whereas sleep is more protective and restorative to mitochondria (mitorestorative). The “redox–bioenergetics–temperature and differential mitochondrial–nuclear regulatory hypothesis” adds to the understanding of mitochondrial respiratory uncoupling, substrate cycling control and hibernation. Similarly, this hypothesis explains how the oscillatory redox–bioenergetics–temperature–regulated sleep–wake states, when perturbed by mitochondrial interactome disturbances, influence the pathogenesis of aging, cancer, spaceflight health effects, sudden infant death syndrome, and diseases of the metabolism and nervous system.

A novel OSA-related model of intermittent hypoxia in endothelial cells under flow reveals pronounced inflammatory pathway activation

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder characterized by recurrent episodes of upper airway obstruction and subsequent hypoxia. In patients with OSA, severity and number of these hypoxic events positively correlate with the extent of associated cardiovascular pathology. The molecular mechanisms underlying intermittent hypoxia (IH)-driven cardiovascular disease in OSA, however, remain poorly understood-partly due to the lack of adequate experimental models. Here, we present a novel experimental approach that utilizes primary human endothelial cells cultivated under shear stress. Oxygen partial pressure dynamics were adopted in our in vitro model according to the desaturation-reoxygenation patterns identified in polysomnographic data of severe OSA patients (n = 10, with 892 severe desaturations, SpO₂<80%). Using western blot analysis, we detected a robust activation of the two major inflammatory pathways ERK and NF-κB in endothelial cells, whereas no HIF1α and HIF2α protein stabilization was observed. In line with these findings, mRNA and protein expression of the pro-inflammatory adhesion and signaling molecule ICAM-1 and the chemokine CCL2 were significantly increased. Hence, we established a novel in vitro model for deciphering OSA-elicited effects on the vascular endothelium. First data obtained in this model point to the endothelial activation of pro-inflammatory rather than hypoxia-associated pathways in OSA. Future studies in this model might contribute to the development of targeted strategies against OSA-induced, secondary cardiovascular disease.

Hypoxic Burden in Obstructive Sleep Apnea: Present and Future

Conventional measures of obstructive sleep apnea (OSA) severity, such as the apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) are commonly used to quantify OSA severity and guide therapeutical decision-making processes. However, it is widely recognized that both AHI and ODI have important limitations and novel physiologically-informed metrics are needed to better capture the severity of OSA and characterize its physiological consequences, particularly the severity of recurrent nocturnal hypoxemia, ensuing the respiratory events. According to recent studies, the sleep apnea-specific "hypoxic burden (HB)", defined as the sum of individual areas under the oxygen desaturation curve, has shown some promise in identifying high risk individuals with OSA. In addition to the frequency of respiratory events, HB capture the depth and duration of OSA-related hypoxemia that may prove to be important disease characterizing features, not captured by the conventional "frequency-based" metrics, such as AHI and ODI. In this "perspective" paper the methods to quantify the HB, its characteristics, associations with health outcomes, and its limitations will be discussed.

Desaturation event scoring criteria affect the perceived severity of nocturnal hypoxic load

OBJECTIVES/BACKGROUND

Interest in using blood oxygen desaturations in the diagnostics of sleep apnea has risen in recent years. However, no standardized criteria for desaturation scoring exist which complicates the drawing of solid conclusions from literature.

PATIENTS/METHODS

We investigated how different desaturation scoring criteria affect the severity of nocturnal hypoxic load and the prediction of impaired daytime vigilance in 845 patients. Desaturations were scored based on three features: 1) minimum oxygen saturation drop during the event (2-20%, 1% interval), 2) minimum duration of the event (2-20s, 1s interval), and 3) maximum plateau duration within the event (5-60s, 5s interval), resulting in 4332 different scoring criteria. The hypoxic load was described with oxygen desaturation index (ODI), desaturation severity (DesSev), and desaturation duration (DesDur) parameters. Association between hypoxic load and impaired vigilance was investigated with covariate-adjusted area under curve (AUC) analyses by dividing patients into normal (≤5 lapses) and impaired (≥36 lapses) vigilance groups based on psychomotor vigilance task performance.

RESULTS

The severity of hypoxic load varied greatly between different scoring criteria. For example, median ODI ranged between 0.4 and 12.9 events/h, DesSev 0.01-0.23 %-point, and DesDur 0.3-9.6 %-point when the minimum transient drop criterion of 3% was used and other two features were altered. Overall, the minimum transient drop criterion had the largest effect on parameter values. All models with differently determined parameters predicted impaired vigilance moderately (AUC = 0.722-0.734).

CONCLUSIONS

Desaturation scoring criteria greatly affected the severity of hypoxic load. However, the difference in the prediction of impaired vigilance between different criteria was rather small.

WITHDRAWN: Mitochondria need their sleep: Sleep-wake cycling and the role of redox, bioenergetics, and temperature regulation, involving cysteine-mediated redox signaling, uncoupling proteins, and substrate cycles

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ABOSA - Freely available automatic blood oxygen saturation signal analysis software: Structure and validation

BACKGROUND AND OBJECTIVE

Many sleep recording software used in clinical settings have some tools to automatically analyze the blood oxygen saturation (SpO₂) signal by detecting desaturations. However, these tools are often inadequate for scientific research as they do not provide SpO₂ signal-based parameters which are superior in the estimation of sleep apnea severity and related medical consequences. In addition, these software require expensive licenses and they lack batch analysis tools. Thus, we developed the first freely available automatic blood oxygen saturation analysis software (ABOSA) that provides sophisticated SpO₂ signal-based parameters and enables batch analysis of large datasets.

METHODS

ABOSA was programmed with MATLAB. ABOSA automatically detects desaturation and recovery events from the SpO₂ signals (EDF files) and calculates numerous parameters, such as oxygen desaturation index (ODI) and desaturation severity (DesSev). The accuracy of the ABOSA software was evaluated by comparing its desaturation scorings to manual scorings in Kuopio (n = 1981) and Loewenstein (n = 930) sleep apnea patient datasets. Validation was performed in a second-by-second manner by calculating Matthew's correlation coefficients (MCC) and median differences in parameter values. Finally, the performance of the ABOSA software was compared to two commercial software, Noxturnal and Profusion, in 100 patient subpopulations. As Noxturnal or Profusion does not calculate novel desaturation parameters, these were calculated with custom-made functions.

RESULTS

The agreements between ABOSA and manual scorings were great in both Kuopio (MCC = 0.801) and Loewenstein (MCC = 0.898) datasets. However, ABOSA slightly overestimated the desaturation parameter values. The median differences in ODIs were 0.8 (Kuopio) and 0.0 (Loewenstein) events/h. Similarly, the median differences in DesSevs were 0.02 (Kuopio) and 0.01 (Loewenstein) percentage points. In a second-by-second analysis, ABOSA performed very similarly to Noxturnal and Profusion software in both Kuopio (MCC_ABOSA = 0.807, MCC_Noxturnal = 0.807, MCC_Profusion = 0.811) and Loewenstein (MCC_ABOSA = 0.904, MCC_Noxturnal = 0.911, MCC_Profusion = 0.871) datasets. Based on Noxturnal and Profusion scorings, the desaturation parameter values were similarly overestimated compared to ABOSA.

CONCLUSIONS

ABOSA is an accurate and freely available software that calculates both traditional clinical parameters and novel parameters, provides a detailed characterization of desaturation and recovery events, and enables batch analysis of large datasets. These are features that no other software currently provides making ABOSA uniquely suitable for scientific research use.

Hypoxic Burden in Obstructive Sleep Apnea: Present and Future

Conventional measures of obstructive sleep apnea (OSA) severity, such as the apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) are commonly used to quantify OSA severity and guide therapeutical decision-making processes. However, it is widely recognized that both AHI and ODI have important limitations and novel physiologically informed metrics are needed to better capture the severity of OSA and characterize its physiological consequences, particularly the severity of recurrent nocturnal hypoxemia, ensuing the respiratory events. According to recent studies, the sleep apnea-specific "Hypoxic Burden (HB)", defined as the sum of individual areas under the oxygen desaturation curve, has shown some promise in identifying high risk individuals with OSA. In addition to the frequency of respiratory events, HB capture the depth and duration of OSA-related hypoxemia that may prove to be important disease characterizing features, not captured by the conventional "frequency-based" metrics, such as AHI and ODI. In this "Perspective" paper the methods to quantify the HB, its characteristics, associations with health outcomes, and its limitations will be discussed.

Associations of sleep apnea risk and oxygen desaturation indices with cerebral small vessel disease burden in patients with stroke

Background

Obstructive sleep apnea (OSA) is associated with cerebral small vessel disease (CSVD). Nonetheless, whether OSA-risk determined by a simple screening questionnaire or indices quantifying nocturnal hypoxemia other than the conventional apnea–hypopnea index (AHI) by the home sleep apnea test (HSAT) associated with CSVD burden remains uncertain.

Methods

From 2018 to 2021, we recruited patients with transient ischemic attack (TIA)/minor stroke from the Queen Mary Hospital Acute Stroke Unit and TIA/Stroke Outpatient Clinics. Logistic regression models were applied to determine the association of baseline OSA-risk (on STOP-BANG questionnaire) or HSAT-derived indices quantifying nocturnal hypoxemia with global burden/individual markers of CSVD on MRI. Indices included oxygen desaturation (≥3%) index (ODI), minimum oxygen saturation (SpO₂), percentage of total sleep time with an oxygen saturation <90% (CT90%), and desaturation duration (≥3%, DesDur).

Results

In 283 patients with TIA/minor stroke (mean age 65 years, 64% men), OSA-risk was significantly associated with total CSVD score (multivariate-adjusted odds ratio: 1.23, 95% confidence interval 1.01–1.51), presence of lacunes [1.39 (1.09–1.79)] and burden of basal ganglia PVSs [1.32 (1.06–1.67)]. In 85/283 patients who completed HSAT, neither AHI, minimum SpO₂ nor CT90% was associated with CSVD burden. Nonetheless, ODI and DesDur remained significantly associated with total CSVD score after covariate adjustment: ODI [1.04 (1.01–1.07)] and DesDur [1.04 (1.01–1.08)].

Conclusion

In patients with TIA/minor stroke, high OSA-risk was associated with a greater CSVD burden. Oxygen desaturation indices (ODI and DesDur) rather than AHI were independently associated with global CSVD burden, indicating that longer and more severe desaturations may contribute to the pathogenesis of CSVD.

Factors Associated With Undiagnosed Obstructive Sleep Apnea in Overweight and Obese High-Tech Employees: A Multisite Cross-Sectional Study

Background: Being overweight or obese is regarded as crucial risk factors for obstructive sleep apnea (OSA). Objectives: This study aimed to determine the influencing factors of overweight and obese employees with OSA in high-tech workplaces. Methods: A cross-sectional study design was employed. A total of 491 overweight and obese participants were recruited from a large-scale electronics industry. The Chinese version of Pittsburgh Sleep Quality Index, the Epworth Sleep Scale, and a portable sleep monitoring device were used for data collection. Logistic regression analysis was conducted to identify the factors affecting overweight and obese employees with OSA. This study was conducted from August 2019 to July 2020. Results: 60.5% of the overweight and obese participants were found to have OSA, of which 58.9% had mild and 18.5% had severe OSA, respectively. The results showed that age, neck circumference, snoring, and habitual drinking were the crucial factors affecting OSA. Remarkably, age and snoring times showed a significant correlation in predicting OSA of different severities. Neck circumference was an independent risk factor for moderate and severe OSA. Conclusion: More than 60% of the overweight and obese high-tech workplace employees were found to have OSA. We found that the older the age, the larger the neck circumference, a higher number of snoring instances, and drinking were important risk factors for predicting OSA in overweight high-tech employees. The healthcare providers should actively educate OSA-related information for employees in the workplace, and promote high-risk OSA groups to adopt screening based on at-home sleep apparatus.

Diabetes and cardiovascular diseases are associated with the worsening of intermittent hypoxaemia

Intermittent hypoxaemia is a risk factor for numerous diseases. However, the reverse pathway remains unclear. Therefore, we investigated whether pre-existing hypertension, diabetes or cardiovascular diseases are associated with the worsening of intermittent hypoxaemia. Among the included 2,535 Sleep Heart Health Study participants, hypertension (n = 1,164), diabetes (n = 170) and cardiovascular diseases (n = 265) were frequently present at baseline. All participants had undergone two polysomnographic recordings approximately 5.2 years apart. Covariate-adjusted linear regression analyses were utilized to investigate the difference in the severity of intermittent hypoxaemia at baseline between each comorbidity group and the group of participants free from all comorbidities (n = 1,264). Similarly, we investigated whether the pre-existing comorbidities are associated with the progression of intermittent hypoxaemia. Significantly higher oxygen desaturation index (β = 1.77 [95% confidence interval: 0.41-3.13], p = 0.011), desaturation severity (β = 0.07 [95% confidence interval: 0.00-0.14], p = 0.048) and desaturation duration (β = 1.50 [95% confidence interval: 0.31-2.69], p = 0.013) were observed in participants with pre-existing cardiovascular diseases at baseline. Furthermore, the increase in oxygen desaturation index (β = 3.59 [95% confidence interval: 1.78-5.39], p < 0.001), desaturation severity (β = 0.08 [95% confidence interval: 0.02-0.14], p = 0.015) and desaturation duration (β = 2.60 [95% confidence interval: 1.22-3.98], p < 0.001) during the follow-up were higher among participants with diabetes. Similarly, the increase in oxygen desaturation index (β = 2.73 [95% confidence interval: 1.15-4.32], p = 0.001) and desaturation duration (β = 1.85 [95% confidence interval: 0.62-3.08], p = 0.003) were higher among participants with cardiovascular diseases. These results suggest that patients with pre-existing diabetes or cardiovascular diseases are at increased risk for an expedited worsening of intermittent hypoxaemia. As intermittent hypoxaemia is an essential feature of sleep apnea, these patients could benefit from the screening and follow-up monitoring of sleep apnea.

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea

The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) that have led to the search for artificial intelligence-based alternatives. Many classic machine learning methods have been already evaluated for this purpose. In this chapter, we show the main approaches found in the scientific literature along with the most used data to develop the models, useful and large easily available databases, and suitable methods to assess performances. In addition, a range of results from selected studies are presented as examples of these methods. Very high diagnostic performances are reported in these results regardless of the approaches taken. This leads us to conclude that conventional machine learning methods are useful techniques to develop new OSA diagnosis simplification proposals and to act as benchmark for other more recent methods such as deep learning.

Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

Pediatric obstructive sleep apnea (OSA) is a prevalent disorder that disrupts sleep and is associated with neurocognitive and behavioral negative consequences, potentially hampering the development of children for years. However, its relationships with sleep electroencephalogram (EEG) have been scarcely investigated. Here, our main objective was to characterize the overnight EEG of OSA-affected children and its putative relationships with polysomnographic measures and cognitive functions. A two-step analysis involving 294 children (176 controls, 57% males, age range: 5-9 years) was conducted for this purpose. First, the activity and irregularity of overnight EEG spectrum were characterized in the typical frequency bands by means of relative spectral power and spectral entropy, respectively: δ1 (0.1-2 Hz), δ2 (2-4 Hz), θ (4-8 Hz), α (8-13 Hz), σ (10-16 Hz), β1 (13-19 Hz), β2 (19-30 Hz), and γ (30-70 Hz). Then, a correlation network analysis was conducted to evaluate relationships between them, six polysomnography variables (apnea-hypopnea index, respiratory arousal index, spontaneous arousal index, overnight minimum blood oxygen saturation, wake time after sleep onset, and sleep efficiency), and six cognitive scores (differential ability scales, Peabody picture vocabulary test, expressive vocabulary test, design copying, phonological processing, and tower test). We found that as the severity of the disease increases, OSA broadly affects sleep EEG to the point that the information from the different frequency bands becomes more similar, regardless of activity or irregularity. EEG activity and irregularity information from the most severely affected children were significantly associated with polysomnographic variables, which were coherent with both micro and macro sleep disruptions. We hypothesize that the EEG changes caused by OSA could be related to the occurrence of respiratory-related arousals, as well as thalamic inhibition in the slow oscillation generation due to increases in arousal levels aimed at recovery from respiratory events. Furthermore, relationships between sleep EEG and cognitive scores emerged regarding language, visual-spatial processing, and executive function with pronounced associations found with EEG irregularity in δ1 (Peabody picture vocabulary test and expressive vocabulary test maximum absolute correlations 0.61 and 0.54) and β2 (phonological processing, 0.74; design copying, 0.65; and Tow 0.52). Our results show that overnight EEG informs both sleep alterations and cognitive effects of pediatric OSA. Moreover, EEG irregularity provides new information that complements and expands the classic EEG activity analysis. These findings lay the foundation for the use of sleep EEG to assess cognitive changes in pediatric OSA.