EEG Arousal Research Articles

Lateral parabrachial FoxP2 neurons regulate respiratory responses to hypercapnia

About half of the neurons in the parabrachial nucleus (PB) that are activated by CO2 are located in the external lateral (el) subnucleus, express calcitonin gene-related peptide (CGRP), and cause forebrain arousal. We report here, in male mice, that most of the remaining CO2-responsive neurons in the adjacent central lateral (PBcl) and Kölliker-Fuse (KF) PB subnuclei express the transcription factor FoxP2 and many of these neurons project to respiratory sites in the medulla. PBclFoxP2 neurons show increased intracellular calcium during wakefulness and REM sleep and in response to elevated CO2 during NREM sleep. Photo-activation of the PBclFoxP2 neurons increases respiration, whereas either photo-inhibition of PBclFoxP2 or genetic deletion of PB/KFFoxP2 neurons reduces the respiratory response to CO2 stimulation without preventing awakening. Thus, augmenting the PBcl/KFFoxP2 response to CO2 in patients with sleep apnea in combination with inhibition of the PBelCGRP neurons may avoid hypoventilation and minimize EEG arousals.

Tongue Biting Event in Patients with Sleep-Related Facial Mandibular Myoclonus: A Case Series Study.

Sleep-related facial mandibular myoclonus (SRFMM) remains rare in clinical practice. The aim of this study was to provide a comprehensive understanding of the electroclinical manner, therapeutic regimen, and prognosis of SRFMM. Twenty-three patients who were diagnosed with SRFMM by clinical manifestation, video-electroencephalography (EEG) and electromyography over bilateral masseter and temporalis muscles were enrolled. Clinical and electrophysiological evaluation as well as follow-up information were recorded and analyzed. The cohort involved 4 infants and 19 adults with a mean onset age of 43.5 years for SRFMM, among whom 19 were male. Twenty-one patients complained of tongue injuries and disturbed night-time sleep. SRFMM in 4 patients were ascribed to oral aripiprazole, brainstem ischemia and brain trauma. In 62 SRFMM episodes, 93.5% occurred in NREM sleep and 6.5% in REM sleep, and all events were associated with EEG arousals. In 13 patients with or without clonazepam, the motor events gradually disappeared, and the rest turned to be sporadic. SRFMM is a characteristic parasomnia manifested by tongue biting and accompanying facial mandibular myoclonus, leading to disrupted sleep. Besides adults, infants can also experience SRFMM with spontaneous remission. Most patients respond well to clonazepam, eventually with favorable prognosis.

0195 The association of electronic device use before bedtime on objective sleep quality measured with Odds Ratio Product

Abstract Introduction Previous research has shown mixed results when it comes to electronic device use and the impact on sleep quality. The use of electronic devices before bedtime can impact sleep quality through engaging content and the impact of blue light on melatonin secretion. In the present study, we assessed the relationship between electronic device use and sleep under real-world conditions. Methods Nineteen participants (age 41.1±10.9; 9 females) recorded their sleep with in-home PSG using the Cerebra Sleep System for 18 to 31 nights (21.5±3.4). Sleep quality was measured using odds ratio product (ORP) derived from spectral analysis of the frontal EEG channels during wake, NREM and REM sleep. Participants completed a nighttime questionnaire within one hour of bedtime where they were asked “Did you do any of these activities today” and indicated “social media or surfed the internet in the last hour before bedtime”. The Karolinska Sleepiness Scale (KSS) was also completed during the before bedtime test battery. Results Across the 19 participants, 17 participants reported using social media or surfing the internet within an hour before bedtime for at least one night. Participants reported usage for 9.6 ± 8.2 nights on average (n=165) but no usage for 11.7 ± 7.9 nights on average (n=210). On nights that internet or social media usage before bedtime was reported, participants had lower levels of evening sleepiness on the Karolinska Sleepiness Scale than on nights where no usage was reported (p <.001). On these nights, participants also had higher ORPNREM (p <.001), higher ORPREM (p<.001), higher ORPTRT (p<.001), higher ORP-9 (p<.001) which is an indication of poorer sleep depth after an EEG arousal. Conclusion On the nights when electronic devices were used before bedtime, participants experienced less sleepiness and had worse objective sleep quality during the night. These results indicate the utility of ORP to be sensitive enough to detect changes in sleep quality after electronic device use. Support (if any)

0537 Incident Hypertension Prediction in Obstructive Sleep Apnea using Machine Learning

Abstract Introduction Obstructive sleep apnea (OSA) is associated with hypertension due to intermittent hypoxia and sleep fragmentation. Due to the complex pathogenesis of hypertension, it is difficult to predict incident hypertension associated with OSA. A Machine Learning (ML) model to predict incident hypertension identified up to five years after the diagnosis of OSA by polysomnography developed. Methods Polysomnography provides time-series data on multiple physiological signals. We used the sleep heart health study (SHHS) cohort, where 4,797 participants had OSA. After excluding participants with pre-existing hypertension at baseline, the sample size was 2,652. 1,814 participants with follow-up data at 5 years were included (911/1,814, 50% with incident hypertension). In addition to clinical data (i.e. age and race), features extracted from polysomnography (heart rate variability, HRV calculated based on the electrocardiography R-R interval), electroencephalography delta power, statistical information (i.e., mean and standard deviation of signals), and heart rate periodicity functions fed to support vector machine (SVM) ML model to train and validate. The polysomnography features were calculated over the 30-second epochs identified based on respiratory events and EEG arousal and respiratory events annotation, and their corresponding parts in other signals based on sampling frequency. Technical artifacts in oxygen saturation and ECG were reconstructed with the interpolation method and removed from the signal respectively. The SVM is a robust ML method trained in an iterative fashion to find the global optimum. In comparison to the Deep Neural Network (DNN) approaches, SVMs results are interpretable. Each polysomnography signal and its corresponding features were trained on a separate SVM, followed by a fusion of the SVM results. The final results were fused by voting of individual SVM results. Results The SVM ML model thus far has achieved a test accuracy (area under the curve, AUC) of 66.06%, sensitivity 63.21%, and specificity 68.9%. Conclusion This proof-of-concept study suggests that supervised ML models, such as the SVM, may be useful in predicting incident hypertension associated with OSA. Further research is required regarding optimal input features to boost the accuracy, followed by external validation of the model in additional OSA cohorts. Support (if any) Research support 1R56HL157182, NIH/NHLBI

0435 Machine-learned combination of ventilatory, hypoxic, and arousal burdens classifies daytime sleepiness better than AHI

Abstract Introduction The apnea-hypopnea index (AHI), the current severity metric used clinically for diagnosing obstructive sleep apnea (OSA), does not correlate well to daytime sleepiness measured via the Epworth Sleepiness Scale (ESS). Here, we assessed whether a machine-learned combination of possibly independent metrics across ventilatory/hypoxic/arousal domains would be better associated with ESS than the AHI using data from 3 large cohorts. Methods Polysomnography data were analyzed from The Sleep Heart Health Study (SHHS), The Multi-Ethnic Study of Atherosclerosis (MESA), and The Osteoporotic Fractures in Men (MrOS) Study. A total of N=6618 (39.9% female; age 68.7±6.6) subjects had valid data (ESS and good quality airflow/EEG/SpO2). Ventilatory burden was evaluated using a derived flow signal that utilized the sum of thoracic and abdominal effort signals for SHHS and was evaluated using the Nasal Cannula/Pressure Transducer signal for the MrOS and MESA data. Hypoxic burden was calculated as the area between the baseline and the SpO2 trace for any episode with >= 3% desaturation. Arousal burden was defined as the manually scored arousal index (number/hr.). Based on a cut-off of ESS(ESS>= 10), sleepiness was coded present or absent and was the primary outcome. Data were analyzed in two ways: using all 3 cohorts as train (70%) and test (30%), and by permutations and combinations of the 3 cohorts (70/30 split; e.g., SHHS for training, MESA and MrOS for test). Model performance metrics were the area under the receiver operating characteristic curve (AUROC) and %accuracy. For comparison, a logistic regression model using AHI3a (3% desaturation and/or EEG arousal) was fit. Results The logistic regression model (AHI3a) classified sleepiness with an AUROC of 0.51±0.07. The random forest model trained on 70% of all 3 cohorts achieved the highest AUROC of 0.88±0.07 (mean accuracy of 85.1± 2.13%), whereas the permutations and combinations of the 3 datasets resulted in an average AUROC of 0.63 ±0.12 (mean accuracy of 76.4±6.57%). Conclusion The machine-learned combination of ventilatory/hypoxic/arousal burdens classifies daytime sleepiness in OSA better than AHI3a across data from 3 large cohorts. These results suggest that OSA severity measured using machine-learned combination of ventilatory/hypoxic/arousal burdens better explains the variability in daytime sleepiness. Support (if any)

Sleep Micro-Macro-structures in Psychophysiological Insomnia. PSG Study.

To address sleep micro-macro-structures in psychophysiological insomnia (PPI) as denoted by cyclic alternating pattern (CAP), Sleep spindles, and hyperarousal as microstructures and sleep characteristics such as sleep stages' variables, and heart rate as macrostructures. Two statistical populations, with 20 participants in each, are addressed: good sleepers (GS) and patients with psychophysiological insomnia (PPI). The sleep polysomnography (PSG) for one night was performed and sleep macro-micro-structures extraction was implemented for each participant. Cyclic alternating patterns were scored manually and other structures were monitored by the original PSG's device software. Analytical methods are used to dissect the results. The findings imply: (a) psychophysiological insomnia is characterized by CAP differences from good sleepers which are associated with hyperarousal; (b) Regarding microstructure, more microarousals in sleep stages caused more number of wake index. (c) The ratio of sleep stages, sleep latency and heart rate as sleep macrostructure are significantly changed. (d) There is no significant difference between PPI and GS groups on spindles length in our research. Regarding all sleep disorders and especially PPI, CAP variables, EEG arousals, and sleep spindles as microstructures and Total Sleep Time, Sleep Latency, number of waking, REM duration, and Heart Rate as macrostructures were found to be critical for the diagnosis of psychophysiological insomnia The analysis contributes to understanding better approaches in the quantitative specification of psychophysiological insomnia compare to good sleepers.

Functional connectivity between medial pulvinar and cortical networks as a predictor of arousal to noxious stimuli during sleep.

The interruption of sleep by a nociceptive stimulus is favoured by an increase in the pre-stimulus functional connectivity between sensory and higher level cortical areas. In addition, stimuli inducing arousal also trigger a widespread electroencephalographic (EEG) response reflecting the coordinated activation of a large cortical network. Because functional connectivity between distant cortical areas is thought to be underpinned by trans-thalamic connections involving associative thalamic nuclei, we investigated the possible involvement of one principal associative thalamic nucleus, the medial pulvinar (PuM), in the sleeper's responsiveness to nociceptive stimuli. Intra-cortical and intra-thalamic signals were analysed in 440 intracranial electroencephalographic (iEEG) segments during nocturnal sleep in eight epileptic patients receiving laser nociceptive stimuli. The spectral coherence between the PuM and 10 cortical regions grouped in networks was computed during 5s before and 1 s after the nociceptive stimulus and contrasted according to the presence or absence of an arousal EEG response. Pre- and post-stimulus phase coherence between the PuM and all cortical networks was significantly increased in instances of arousal, both during N2 and paradoxical (rapid eye movement [REM]) sleep. Thalamo-cortical enhancement in coherence involved both sensory and higher level cortical networks and predominated in the pre-stimulus period. The association between pre-stimulus widespread increase in thalamo-cortical coherence and subsequent arousal suggests that the probability of sleep interruption by a noxious stimulus increases when it occurs during phases of enhanced trans-thalamic transfer of information between cortical areas.

GABAergic neurons in the dorsomedial hypothalamus regulate states of consciousness in sevoflurane anesthesia

The neural inhibitory gamma-aminobutyric acid (GABA) system in the regulation of anesthetic consciousness is heterogeneous, and the medial hypothalamus (MH), consisting of ventromedial hypothalamus (VMH) and dorsomedial hypothalamus (DMH), plays an important role in sleep and circadian rhythm. However, the role of MH GABAergic neurons (MHGABA) in anesthesia remains unclear. In this study, we used righting reflex, electroencephalogram (EEG), and arousal behavioral score to evaluate the sevoflurane anesthesia. Activation of MHGABA or DMHGABA neurons prolonged the anesthesia induction time, shortened the anesthesia emergence time, and induced EEG arousal and body movement during anesthesia; meanwhile, VMHGABA neurons activated only induced EEG changes during 1.5% sevoflurane anesthesia. Furthermore, inhibition of DMHGABA neurons significantly deepened sevoflurane anesthesia. Therefore, DMHGABA neurons exert a strong emergence-promoting effect on induction, maintenance, and arousal during sevoflurane general anesthesia, which helps to reveal the mechanism of anesthesia.

Prevalence and Predictors of Sleep-Disordered Breathing in Men Participating in the Multicenter AIDS Cohort Study

Data on the prevalence of sleep-disordered breathing (SDB) in people with HIV are limited. Moreover, whether the associations between SDB and age or BMI differ by HIV status is unknown. Is SDB more prevalent in men with HIV than those without HIV, and do the predictors of SDB differ between the two groups? Home polysomnography was used in the Multicenter AIDS Cohort Study to assess SDB prevalence in men with (n= 466; 92%virologically suppressed) and without (n= 370) HIV. SDB was defined using the oxygen desaturation index (ODI) and the apnea-hypopnea index (AHI), using four definitions:≥ 5 events/h based on an ODI with a 3%(ODI3) or 4%(ODI4) oxygen desaturation, or an AHI with a 3%oxygen desaturation or EEG arousal (AHI3a) or with a 4%oxygen desaturation (AHI4). SDB prevalence was similar in men with and without HIV using the ODI3 and AHI3a definitions. However, SDB prevalence was higher in men with than without HIV using the ODI4 (55.9%vs47.8%; P= .04) and the AHI4 definitions (57.9%vs50.4%; P= .06). Mild and moderate SDB were more common in men with than without HIV. Associations between SDB prevalence and age, race, and BMI were similar in men with and without HIV. Among men with HIV, viral load, CD4 cell count, and use of antiretroviral medications were not associated with SDB prevalence. SDB prevalence was high overall but greater in men with than without HIV using the ODI4 threshold definition. Efforts to diagnose SDB are warranted in people with HIV, given that SDB is associated with daytime sleepiness and impaired quality of life.

Computer-assisted analysis of polysomnographic recordings improves inter-scorer associated agreement and scoring times.

To investigate inter-scorer agreement and scoring time differences associated with visual and computer-assisted analysis of polysomnographic (PSG) recordings. A group of 12 expert scorers reviewed 5 PSGs that were independently selected in the context of each of the following tasks: (i) sleep staging, (ii) scoring of leg movements, (iii) detection of respiratory (apneic-related) events, and (iv) of electroencephalographic (EEG) arousals. All scorers independently reviewed the same recordings, hence resulting in 20 scoring exercises per scorer from an equal amount of different subjects. The procedure was repeated, separately, using the classical visual manual approach and a computer-assisted (semi-automatic) procedure. Resulting inter-scorer agreement and scoring times were examined and compared among the two methods. Computer-assisted sleep scoring showed a consistent and statistically relevant effect toward less time required for the completion of each of the PSG scoring tasks. Gain factors ranged from 1.26 (EEG arousals) to 2.41 (leg movements). Inter-scorer kappa agreement was also consistently increased with the use of supervised semi-automatic scoring. Specifically, agreement increased from Κ = 0.76 to K = 0.80 (sleep stages), Κ = 0.72 to K = 0.91 (leg movements), Κ = 0.55 to K = 0.66 (respiratory events), and Κ = 0.58 to Κ = 0.65 (EEG arousals). Inter-scorer agreement on the examined set of diagnostic indices did also show a trend toward higher Interclass Correlation Coefficient scores when using the semi-automatic scoring approach. Computer-assisted analysis can improve inter-scorer agreement and scoring times associated with the review of PSG studies resulting in higher efficiency and overall quality in the diagnosis sleep disorders.

Absolute gamma power of EEG arousal is modulated by respiratory event type and severity in OSA

Absolute gamma power of EEG arousal is modulated by respiratory event type and severity in OSA

Brain reactivity to emotion persists in NREM sleep and is associated with individual dream recall.

The waking brain efficiently detects emotional signals to promote survival. However, emotion detection during sleep is poorly understood and may be influenced by individual sleep characteristics or neural reactivity. Notably, dream recall frequency has been associated with stimulus reactivity during sleep, with enhanced stimulus-driven responses in high vs. low recallers. Using electroencephalography (EEG), we characterized the neural responses of healthy individuals to emotional, neutral voices, and control stimuli, both during wakefulness and NREM sleep. Then, we tested how these responses varied with individual dream recall frequency. Event-related potentials (ERPs) differed for emotional vs. neutral voices, both in wakefulness and NREM. Likewise, EEG arousals (sleep perturbations) increased selectively after the emotional voices, indicating emotion reactivity. Interestingly, sleep ERP amplitude and arousals after emotional voices increased linearly with participants’ dream recall frequency. Similar correlations with dream recall were observed for beta and sigma responses, but not for theta. In contrast, dream recall correlations were absent for neutral or control stimuli. Our results reveal that brain reactivity to affective salience is preserved during NREM and is selectively associated to individual memory for dreams. Our findings also suggest that emotion-specific reactivity during sleep, and not generalized alertness, may contribute to the encoding/retrieval of dreams.

Immediate Physiological Responses to Inspiratory Flow Limited Events in Mild Obstructive Sleep Apnea.

Rationale: Inspiratory flow limitation (IFL), characterized by flattening of individual breaths on the airflow/time tracing, is a noninvasive indicator of elevated upper airway resistance. An IFL "event" in isolation has not been defined, nor has the ability to reproducibly identify event occurrence been tested. IFL events and their association with immediate physiological responses-as well as the impact of characteristics such as age, sex, sleep stage, sleepiness, and event duration on their association with such outcomes-have not been studied. Symptomatic patients with a normal to mildly abnormal apnea-hypopnea index who have predominant IFL on their polysomnography may benefit from treatment. Objectives: To test the reproducibility of identifying IFL events and their termination and to determine the frequency of the immediate physiological response to their occurrence, including desaturation, electroencephalography (EEG) arousal, and increased heart rate (HR). Methods: Fifty-eight patients with obstructive sleep apnea (OSA) underwent full diagnostic polysomnography. IFL events and their termination were identified manually using predefined rules from the unscored nasal cannula flow channel alone and were evaluated for responses such as EEG arousal, oxygen desaturation of ⩾3%, and HR increase. Results: Interscorer reliability was acceptable, with an average percent agreement for occurrence of 82% ± 3%. Of all IFL events, 24% (regardless of the definition) were not associated with an EEG arousal, an increase in HR, or O2 desaturation. Of all IFL events scored, 25% caused O2 desaturation, 40% were associated with an EEG arousal, and 55% were associated with an increase in HR; 67% caused either an EEG arousal and/or an increase in HR. Responses were observed to occur either in isolation or in combination. IFL events that terminated with at least two non-IFL breaths, one of which had a 200% increase in amplitude, were significantly associated with O2 desaturation, EEG arousal, and increase in HR compared with events that ended in one non-IFL breath. IFL events that had a >50% reduction in flow amplitude compared with baseline were significantly associated with O2 desaturation compared with events that had a 30% reduction or less. Conclusions: Most IFL events resulted in immediate physiological responses, and no single consequence reliably occurred after every event. We propose a framework that can incorporate the scoring of IFL events into assessing the diagnosis and severity of OSA and suggest that no single consequence be used to define IFL as a respiratory event. The relationship of IFL events to OSA outcomes remains to be tested.

Obstructive Sleep Apnea Syndrome and Features of the Neurophysiological Sleep Pattern

The high prevalence of obstructive sleep apnea syndrome (OSA) causes a steady interest in this pathology. In recent years, one of the urgent problems in modern somnology is the assessment of the main mechanisms of neuronal dysfunction during the day and at night in OSA, the ideas about which, to a large extent, remain contradictory and not fully understood. One of the modern methods for assessing neuronal dysfunction during sleep is the study of the sleep microstructure, and for its assessment, the method of analysis of cyclic alternating pattern (CAP), an EEG marker of unstable sleep, is used. The cyclic alternating pattern is found both in the sleep of adults and children with various sleep disorders and, in particular, with OSAS, therefore, it is a sensitive tool for studying sleep disorders throughout life. With the elimination of night hypoxia against the background of CPAP therapy, the sleep microstructure is restored, the spectral characteristics of the EEG change, and a decrease in the number of EEG arousals after treatment leads to the restoration of daytime functioning. Understanding the role of short-term EEG activations of the brain during sleep can provide significant data on sleep functions in health and disease. Despite the improving diagnosis of sleep disorders using machine algorithms, assessing the relationship of structures and functions of the brain during sleep, neurophysiological data are not entirely clear, which requires further research. In this review, we tried to analyze the results of the main studies of the neurophysiological sleep pattern in OSA against the background of respiratory support during sleep.

FoxP2 cells in the lateral parabrachial area may drive respiratory responses to hypercapnia

We have previously reported that CGRP neurons in the external lateral parabrachial nucleus (PBCGRP) play a critical role in transmitting the arousal signal to cause EEG desynchronization in response to hypercapnia. A second population of neurons adjacent to the PBCGRP group, which projects to respiratory control areas in the medulla, are marked by expression of the transcription factor FoxP2. We hypothesize that while the PBCGRP neurons wake up the forebrain during apneas, the adjacent PBFoxP2 neurons may trigger sudden activation of the airway dilators and other components of the respiratory system during apnea. We first exposed mice (n=4) to 2h of 10% CO2, and tested if PBFoxP2 cells can be activated by such exposure, by double- immunostaining the brain tissue for both FoxP2 and cFos. We found that PBFoxP2 neurons showed cFos activation during CO2 exposure, but that none of them also stained for CGRP. Second, we investigated the response of either optogenetic inhibition or activation of PBFoxP2 neurons on respiration. We injected FoxP2Cre mice, that express Cre-recombinase enzyme in all the FoxP2 cells, bilaterally in the PB with adeno-associated virus containing the gene for either channel rhodopsin2 (AAV-FLEX-ChR2-mCherry; n=3, for neuronal activation) or archaerhodopsin T TP009 (AAV-FLEX-ArchT-GFP ArchT; n=2, for neuronal inhibition) in a Cre-inducible FLEX cassette that expressed either ChR2 or ArchT only in the PBFoxP2 cells. These mice were prepared for sleep recordings and were implanted with bilateral optic fiber targeting the PB. Blue laser (473nm) light targeted to the PB, activated ChR2 expressing neurons with 10ms pulses of 473nm given at 5, 10 and 20Hz, for 5s every 5 minutes, without any hypercapnia stimulus and then respiration was measured. Photo-stimulation of ChR2 expressing PBFoxP2 at 10Hz for 5s significantly increased the respiratory rate (RR) (F2, 12= 6.35, P=0.013) and the tidal volume (TV) compared to the pre-stimulation period (F2, 12= 3.20, P=0.04), with no effect at 5 Hz. At 20 Hz for 5s, RR increased by 63% and VT by 62%. Animals woke-up in most trials towards the end of the 5s stimulation period. We also investigated the respiratory response to10% CO2 given for 30s every 300s, with and without photo-inhibition of the PBFoxP2 neurons with 593 nm laser light. Laser light was on for 60s beginning 20s prior and extending 10s after the CO2 stimulus. Inhibition of the PBFoxP2 cells caused 27% reduction in the ventilatory effort as calculated by the minute ventilation (MV) during the time the animals were exposed to CO2 both before (F1,11=3.68; P= 0.026) and after EEG arousal (F1,11=3.68; P<0.001), without affecting the latency of arousal from CO2. Finally, the GCaMP fiber photometry recordings suggested that the firing of the PBFoxP2 neurons as seen by the increase in GCaMP fluorescence correlates positively with respiratory rate and tidal volume (R2= 0.36; P<0.001), thus corroborating the role of PBFoxP2 neurons in regulating respiratory response to hypercapnia.

K-complexes are a sensitive marker of noise-related sensory processing during sleep: a pilot study.

The primary aim of this study was to examine dose-response relationships between sound pressure levels (SPLs) and K-complex occurrence probability for wind farm and road traffic noise. A secondary aim was to compare K-complex dose-responses to manually scored electroencephalography arousals and awakenings. Twenty-five participants underwent polysomnography recordings and noise exposure during sleep in a laboratory. Wind farm and road traffic noise recordings of 20-sec duration were played in random order at 6 SPLs between 33 and 48 dBA during established N2 or deeper sleep. Noise periods were separated with periods of 23 dBA background noise. K-complexes were scored using a validated algorithm. K-complex occurrence probability was compared between noise types controlling for noise SPL, subjective noise sensitivity, and measured hearing acuity. Noise-induced K-complexes were observed in N2 sleep at SPLs as low as 33 dBA (Odds ratio, 33 dBA vs 23 dBA, mean (95% confidence interval); 1.75 (1.16, 2.66)) and increased with SPL. EEG arousals and awakenings were only associated with noise above 39 dBA in N2 sleep. K-complexes were 2 times more likely to occur in response to noise than EEG arousals or awakenings. Subjective noise sensitivity and hearing acuity were associated with the K-complex occurrence, but not arousal or awakening. Noise type did not detectably influence K-complexes, EEG arousals, or awakening responses. These findings support that K-complexes are a sensitive marker of sensory processing of environmental noise during sleep and that increased hearing acuity and decreased self-reported noise sensitivity increase K-complex probability.

The challenges in scoring hypopneas in children: is pulse wave amplitude drop the answer?

BackgroundIdentifying electroencephalogram (EEG) cortical arousals are crucial in scoring hypopneas and respiratory efforts related arousals (RERAs) during a polysomnogram. As children have high arousal threshold, many of the flow limited breaths or hypopneas may not be associated with visual EEG arousals, hence this may lead to potential underestimation of the degree of sleep disordered breathing. Pulse wave amplitude (PWA) is a signal obtained from finger photoplethysmography which correlates directly to finger blood flow. The drop in PWA has been shown to be a sensitive marker for subcortical/autonomic and cortical arousals. Our aim was to use the drop in PWA as a surrogate for arousals to guide scoring of respiratory events in pediatric patients. MethodsTen polysomnograms for patients between the ages of 5–15 years who had obstructive apnea-hypopnea indices between 1 and 5 events/hour were identified. Patients with syndromes were excluded. A drop in PWA signal of at least 30% that lasted for 3 s was needed to identify subcortical/autonomic arousals. Arousals were rescored based on this criteria and subsequently respiratory events were rescored. Paired t-tests were employed to compare PSG indices scored with or without PWA incorporation. ResultsThe sample of 10 children included 2 females, and the average age was 9.8 ± 3.1 years. Overall, polysomnography revealed an average total sleep time of 464.1 ± 25 min, sleep efficiency of 92% +/−4.2, sleep latency of 19.6 ± 17.0 min, rapid eye movement (REM) latency 143 ± 66 min, N1 3.9% +/−2.0, N2 50.3% +/−12.0, N3 28.2% +/−9.1, REM 16.7% +/−4.0, and wakefulness after sleep onset (WASO) 18.1 ± 7.5 min. Including arousals from PWA changes, respiratory indices significantly increased including total AHI (2.3 ± 0.7 vs 5.7 ± 2.1, p < 0.001), obstructive AHI (1.45 ± 0.7 vs 4.8 ± 1.8, p < 0.001), and RDI (2.36 ± 0.7 vs 7.6 ± 2.0, p < 0.001). Likewise, total arousal index was significantly higher (8.7 ± 2.3 vs 29.4 ± 6.5, p < 0.001). ConclusionsThe drop in pulse wave amplitude signal is a useful marker to guide scoring arousals that are not otherwise easily identified in pediatric polysomnography and subsequently helped in scoring respiratory events that otherwise would not be scored. Further studies are needed to delineate if such methodology would affect clinical outcome.

The Evaluation of Autonomic Arousals in Scoring Sleep Respiratory Disturbances with Polysomnography and Portable Monitor Devices: A Proof of Concept Study.

BackgroundAutonomic arousals can be considered as surrogates of electroencephalography (EEG) arousals when calculating respiratory disturbance index (RDI). The main objective of this proof of concept study was to evaluate the use of heart rate acceleration (HRa) arousals associated with sleep respiratory events in a population undergoing full polysomnography (type 1) and in another undergoing portable monitor study (type 3). Our hypothesis is that when compared to other commonly used indexes, RDI based on HRa will capture more events in both types of recording.Materials and MethodsA retrospective analysis was performed in two different populations of patients with suspected OSA: a) 72 patients undergoing one night of type 1 recording and b) 79 patients undergoing one night of type 3 recording. Variables for type 1 were 4% oxygen desaturation index (ODI), apnea/hypopnea index (AHI), RDI based on EEG arousals (RDIe), and RDI based on HRa with threshold of 5bpm (RDIa5). For type 3, variables were 4% ODI, AHI, and RDIa5 (it is not possible to calculate RDIe due to the absence of EEG). Calculated data were 1) Mean values for each sleep disturbance index in type 1 and 3 recordings; 2) Frequency of migration from lower to higher OSA severity categories using RDIa5 in comparison to AHI (thresholds: ≥5/h mild, ≥15/h moderate, ≥30/h severe); and 3) Bland–Altman plots to assess agreement between AHI vs RDIe and RDIa5 in type 1 population, and AHI vs RDIa5 in type 3 populations.ResultsMore respiratory disturbance events were captured with RDIa5 index in both type 1 and type 3 recordings when compared to the other indexes. In type 1 recording, when using RDIa5 37% of patients classified as not having OSA with AHI were now identified as having OSA, and a total of 59% migrated to higher severity categories. In type 3 recording, similar results were obtained, as 37% of patients classified as not having OSA with AHI were now identified as having OSA using RDIa5, and a total of 55% patients migrated to higher severity categories. Mean differences for RDIa5 and AHI in type 1 and 3 populations were similar.ConclusionThe use of autonomic arousals such as HRa can help to detect more respiratory disturbance events when compared to other indexes, being a variable that may help to capture borderline mild cases. This becomes especially relevant in type 3 recordings. Future research is needed to determine its validity, optimization, and its clinical significance.

Longer duration electroencephalogram arousals have a better relationship with impaired vigilance and health status in obstructive sleep apnoea.

Obstructive sleep apnoea (OSA) is a prevalent sleep disorder with significant health consequences. Sleep fragmentation is a feature of OSA and is often determined by the arousal index (ArI), a metric based on the electroencephalograph (EEG). The ArI has a weak correlation with neurocognitive outcomes in OSA patients. In this study, we examine whether changing from the current minimum EEG arousal duration of 3s improves the association between sleep fragmentation and neurocognitive outcomes. In a retrospective study, we selected OSA patients without any other comorbidities that are associated with neurocognitive impairment. The OSA patients were clustered into two groups based on their psychomotor vigilance task (PVT) performance to represent impaired and unimpaired neurocognition. While no differences were found in demographics or usual sleep study statistics, the impaired group had a greater number of EEG arousals greater than 5s (P= 0.034), 7s (P= 0.041), and 15s (P= 0.036) in duration. There were no differences in the number of EEG arousals associated with sleep-disordered breathing events. These differences also corresponded with quality of life outcomes between the two groups. An ArI with a duration of 5s or greater had the best combination of sensitivity (70.0%) and specificity (66.7%) compared with the usual 3s duration (sensitivity and specificity of 70.0% and 53.3%, respectively). A re-examination of the EEG arousal scoring rules, and their duration, may help with allocation of health resources to OSA patients most in need.

0164 Evidence Suggesting Early Airway Collapse as Cause of Spontaneous Arousals

Abstract Introduction Spontaneous arousals can occur in response to a number of stimuli like noise, movement, hypoxia, or airway obstruction. Some arousals occur “spontaneously” and in individuals donning a hyper-arousable phenotype, spontaneous arousals can dominate the sleep architecture. While arousal mechanisms for some stimuli have been well described, there is a profound lack of knowledge to explain spontaneous arousals. During clinical testing of a device that was designed by SleepMethods, Inc. to anticipate obstructive sleep apnea events by the ability to sense minute airway caliber changes, it was noted, incidentally that the device would signal impeding airway collapse but a spontaneous arousal followed the signal before an obstructive airway event ever developed. This phenomenon was observed many times within and between subjects, suggesting the possibility that very early airway changes are causing “spontaneous arousals” Methods Ten adults (7M;3F) aged 18-80y/o (avg. 54.7y/o) with a known AHI ≥ 15/hr (avg. AHI = 42.6/hr) underwent 1 overnight PSG recording while wearing the device. Patients were required to forego their usual CPAP therapy on the night of study in efforts to expose the device to an adequate number of total obstructive events (defined as apneas and hypopneas; RERAs and snores were excluded). Standard PSG analysis was performed. Scoring rules were applied to determine whether signals were true/false positives and/or true/false negatives based on pre-clinical data showing anticipation accuracy for up to 45 seconds prior to an obstructive airway event. Signals designed to herald obstructive events were noted, incidentally, appearing prior to spontaneous arousals. Results Preliminary results suggest that early phases of airway collapse, as the airway progresses from patency to clinically significant obstruction, are causing EEG arousals which, by current standards, are considered “spontaneous”. Because these findings were incidental to another primary purpose of the clinical study, data analysis is in early stages but currently suggesting at least an associative relationship. Conclusion If final data analysis shows statistically significant correlation between early airway collapse and “spontaneous arousals”, it may have tremendous implications for patients with hyper-arousability, insomnia, and/or pathologically elevated spontaneous arousal indices by proposing therapies aimed at airway patency maintenance. Support N/A