Short-Term Impact of Sleep Apnea/Hypopnea on the Interaction Between Various Cortical Areas

Introduction Sleep apnea/hypopnea syndrome (SAHS) can change brain structure and function. These alterations are related to respiratory event-induced abnormal sleep, however, how brain activity changes during these events is less well understood. Methods To study information content and interaction among various cortical regions, we analyzed the variations of permutation entropy (PeEn) and symbolic transfer entropy (STE) of electroencephalography (EEG) activity during respiratory events. In this study, 57 patients with moderate SAHS were enrolled, including 2804 respiratory events. The events terminated with cortical arousal were independently researched. Results PeEn and STE were lower during apnea/hypopnea, and most of the brain interaction was higher after apnea/hypopnea termination than that before apnea in N2 stage. As indicated by STE, the respiratory events also affected the stability of information transmission mode. In N1, N2, and rapid eye movement (REM) stages, the information flow direction was posterior-to-anterior, but the anterior-to-posterior increased relatively during apnea/hypopnea. The above EEG activity trends maintained in events with cortical arousal. Conclusions These results may be related to the intermittent hypoxia during apnea and the cortical response. Furthermore, increased frontal information outflow, which was related to the compensatory activation of frontal neurons, may associate with cognitive function.

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Predictors of changes in cerebral perfusion and oxygenation during obstructive sleep apnea

Scientific Reports ◽

10.1038/s41598-021-02829-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhongxing Zhang ◽

Ming Qi ◽

Gordana Hügli ◽

Ramin Khatami

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Near Infrared ◽

Sleep Apnea Syndrome ◽

Apnea Hypopnea Index ◽

Mixed Effect ◽

Respiratory Events ◽

Obstructive Sleep ◽

Respiratory Event ◽

Titration Protocol

AbstractObstructive sleep apnea syndrome (OSAS) is a common sleep disorder. Severe OSAS defined as apnea–hypopnea index (AHI) ≥ 30/h is a risk factor for developing cerebro-cardiovascular diseases. The mechanisms of how repetitive sleep apneas/hypopneas damage cerebral hemodynamics are still not well understood. In this study, changes in blood volume (BV) and oxygen saturation (StO2) in the left forehead of 29 newly diagnosed severe OSAS patients were measured by frequency-domain near-infrared spectroscopy during an incremental continuous positive airway pressure (CPAP) titration protocol together with polysomnography. The coefficients of variation of BV (CV-BV) and the decreases of StO2 (de-StO2) of more than 2000 respiratory events were predicted using linear mixed-effect models, respectively. We found that longer events and apneas rather than hypopneas induce larger changes in CV-BV and stronger cerebral desaturation. Respiratory events occurring during higher baseline StO2 before their onsets, during rapid-eye-movement sleep and those associated with higher heart rate induce smaller changes in CV-BV and de-StO2. The stepwise increased CPAP pressures can attenuate these changes. These results suggest that in severe OSAS the length and the type of respiratory event rather than widely used AHI may be better parameters to indicate the severity of cerebral hemodynamic changes.

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Automatic detection of respiratory events during sleep from Polysomnography data using Layered Hidden Markov Model

Physiological Measurement ◽

10.1088/1361-6579/ac45e1 ◽

2021 ◽

Author(s):

Azadeh Sadoughi ◽

Mohammad Bagher Shamsollahi ◽

Emad Fatemizadeh

Keyword(s):

Sleep Apnea ◽

Probabilistic Models ◽

Markov Models ◽

Hidden Markov ◽

Automatic Detection ◽

Detection Algorithm ◽

Respiratory Disorder ◽

Respiratory Events ◽

Increased Risk ◽

Respiratory Event

Abstract Objective. Sleep apnea is a serious respiratory disorder, which is associated with increased risk factors for cardiovascular disease. Many studies in recent years have been focused on automatic detection of sleep apnea from polysomnography (PSG) recordings, however, detection of subtle respiratory events named Respiratory Event Related Arousals (RERAs) that do not meet the criteria for apnea or hypopnea is still challenging. The objective of this study was to develop automatic detection of sleep apnea based on Hidden Markov Models (HMMs) which are probabilistic models with the ability to learn different dynamics of the real time-series such as clinical recordings. Approach. In this study, a hierarchy of HMMs named Layered HMM was presented to detect respiratory events from PSG recordings. The recordings of 210 PSGs from Massachusetts General Hospital’s database were used for this study. To develop detection algorithms, extracted feature signals from airflow, movements over the chest and abdomen, and oxygen saturation in blood (SaO2) were chosen as observations. The respiratory disturbance index (RDI) was estimated as the number of apneas, hypopneas, and RERAs per hour of sleep. Main results. The best F1 score of the event by event detection algorithm was between 0.22±0.16 and 0.70±0.08 for different groups of sleep apnea severity. There was a strong correlation between the estimated and the PSG-derived RDI (R2=0.91, p<0.0001). The best recall of RERA detection was achieved 0.45±0.27. Significance. The results showed that the layered structure can improve the performance of the detection of respiratory events during sleep.

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Arousal from sleep: implications for obstructive sleep apnea pathogenesis and treatment

Journal of Applied Physiology ◽

10.1152/japplphysiol.00649.2013 ◽

2014 ◽

Vol 116 (3) ◽

pp. 302-313 ◽

Cited By ~ 116

Author(s):

Danny J. Eckert ◽

Magdy K. Younes

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Upper Airway ◽

Protective Role ◽

Blood Gas ◽

Cortical Arousal ◽

Physiological Factors ◽

Respiratory Events ◽

Obstructive Sleep ◽

Hypoventilation Syndrome

Historically, brief awakenings from sleep (cortical arousals) have been assumed to be vitally important in restoring airflow and blood-gas disturbances at the end of obstructive sleep apnea (OSA) breathing events. Indeed, in patients with blunted chemical drive (e.g., obesity hypoventilation syndrome) and in instances when other defensive mechanisms fail, cortical arousal likely serves an important protective role. However, recent insight into the pathogenesis of OSA indicates that a substantial proportion of respiratory events do not terminate with a cortical arousal from sleep. In many cases, cortical arousals may actually perpetuate blood-gas disturbances, breathing instability, and subsequent upper airway closure during sleep. This brief review summarizes the current understanding of the mechanisms mediating respiratory-induced cortical arousal, the physiological factors that influence the propensity for cortical arousal, and the potential dual roles that cortical arousal may play in OSA pathogenesis. Finally, the extent to which existing sedative agents decrease the propensity for cortical arousal and their potential to be therapeutically beneficial for certain OSA patients are highlighted.

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Longer apneas and hypopneas are associated with greater ultra-short-term HRV in obstructive sleep apnea

Scientific Reports ◽

10.1038/s41598-020-77780-x ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Salla Hietakoste ◽

Henri Korkalainen ◽

Samu Kainulainen ◽

Saara Sillanmäki ◽

Sami Nikkonen ◽

...

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Short Term ◽

Event Duration ◽

Rr Intervals ◽

Rr Interval ◽

Respiratory Events ◽

Obstructive Sleep ◽

Respiratory Event ◽

S Period

AbstractLow long-term heart rate variability (HRV), often observed in obstructive sleep apnea (OSA) patients, is a known risk factor for cardiovascular diseases. However, it is unclear how the type or duration of individual respiratory events modulate ultra-short-term HRV and beat-to-beat intervals (RR intervals). We aimed to examine the sex-specific changes in RR interval and ultra-short-term HRV during and after apneas and hypopneas of various durations. Electrocardiography signals, recorded as a part of clinical polysomnography, of 758 patients (396 men) with suspected OSA were analysed retrospectively. Average RR intervals and time-domain HRV parameters were determined during the respiratory event and the 15-s period immediately after the event. Parameters were analysed in three pooled sex-specific subgroups based on the respiratory event duration (10–20 s, 20–30 s, and > 30 s) separately for apneas and hypopneas. We observed that RR intervals shortened after the respiratory events and the magnitude of these changes increased in both sexes as the respiratory event duration increased. Furthermore, ultra-short-term HRV generally increased as the respiratory event duration increased. Apneas caused higher ultra-short-term HRV and a stronger decrease in RR interval compared to hypopneas. In conclusion, the respiratory event type and duration modulate ultra-short-term HRV and RR intervals. Considering HRV and the respiratory event characteristics in the diagnosis of OSA could be useful when assessing the cardiac consequences of OSA in a more detailed manner.

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Termination of Respiratory Events with and without Cortical Arousal in Obstructive Sleep Apnea

American Journal of Respiratory and Critical Care Medicine ◽

10.1164/rccm.201106-0975oc ◽

2011 ◽

Vol 184 (10) ◽

pp. 1183-1191 ◽

Cited By ~ 55

Author(s):

Amy S. Jordan ◽

Danny J. Eckert ◽

Andrew Wellman ◽

John A. Trinder ◽

Atul Malhotra ◽

...

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Cortical Arousal ◽

Respiratory Events ◽

Obstructive Sleep

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Postevent ventilation as a function of CO2 load during respiratory events in obstructive sleep apnea

Journal of Applied Physiology ◽

10.1152/japplphysiol.01082.2001 ◽

2002 ◽

Vol 93 (3) ◽

pp. 917-924 ◽

Cited By ~ 48

Author(s):

Kenneth I. Berger ◽

Indu Ayappa ◽

I. Barry Sorkin ◽

Robert G. Norman ◽

David M. Rapoport ◽

...

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Inverse Relationship ◽

Direct Relationship ◽

Ventilatory Response ◽

Respiratory Events ◽

Response Slope ◽

Obstructive Sleep ◽

Respiratory Event ◽

Preceding Event

Maintenance of eucapnia during sleep in obstructive sleep apnea (OSA) requires a balance between CO2 loading during apnea and CO2 elimination. This study examines individual respiratory events and relates magnitude of postevent ventilation to CO2 load during the preceding respiratory event in 14 patients with OSA (arterial Pco 2 42–56 Torr). Ventilation and expiratory CO2 and O2 fractions were measured on a breath-by-breath basis during daytime sleep. Calculations included CO2 load during each event (metabolic CO2 production − exhaled CO2) and postevent ventilation in the 10 s after an event. In 12 of 14 patients, a direct relationship existed between postevent ventilation and CO2 load during the preceding event ( P < 0.05); the slope of this relationship varied across subjects. Thus the postevent ventilation is tightly linked to CO2 loading during each respiratory event and may be an important mechanism that defends against development of acute hypercapnia in OSA. An inverse relationship was noted between this postevent ventilatory response slope and the chronic awake arterial Pco 2 ( r = 0.90, P < 0.001), suggesting that this mechanism is impaired in patients with chronic hypercapnia. The link between development of acute hypercapnia during respiratory events asleep and maintenance of chronic awake hypercapnia in OSA remains to be further investigated.

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Detecting Apnea/Hypopnea Events Time Location from Sound Recordings for Patients with Severe or Moderate Sleep Apnea Syndrome

Applied Sciences ◽

10.3390/app11156888 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6888

Author(s):

Georgia Korompili ◽

Lampros Kokkalas ◽

Stelios A. Mitilineos ◽

Nicolas-Alexander Tatlas ◽

Stelios M. Potirakis

Keyword(s):

Sleep Apnea ◽

Sleep Apnea Syndrome ◽

Apnea Hypopnea Index ◽

Event Time ◽

Severity Estimation ◽

Apnea Duration ◽

Respiratory Events ◽

Moderate Sensitivity ◽

Apnea Syndrome

The most common index for diagnosing Sleep Apnea Syndrome (SAS) is the Apnea-Hypopnea Index (AHI), defined as the average count of apnea/hypopnea events per sleeping hour. Despite its broad use in automated systems for SAS severity estimation, researchers now focus on individual event time detection rather than the insufficient classification of the patient in SAS severity groups. Towards this direction, in this work, we aim at the detection of the exact time location of apnea/hypopnea events. We particularly examine the hypothesis of employing a standard Voice Activity Detection (VAD) algorithm to extract breathing segments during sleep and identify the respiratory events from severely altered breathing amplitude within the event. The algorithm, which is tested only in severe and moderate patients, is applied to recordings from a tracheal and an ambient microphone. It proves good sensitivity for apneas, reaching 81% and 70.4% for the two microphones, respectively, and moderate sensitivity to hypopneas—approx. 50% were identified. The algorithm also presents an adequate estimator of the Mean Apnea Duration index—defined as the average duration of the detected events—for patients with severe or moderate apnea, with mean error 1.7 s and 3.2 s for the two microphones, respectively.

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