Obstructive sleep apnea during rapid eye movement sleep

Alzoubaidi, Mohammed; Mokhlesi, Babak

doi:10.1097/mcp.0000000000000319

Cited by 66 publications

(34 citation statements)

References 47 publications

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“…The longest percentage of REM was below 15.68%. It corresponds to a clinical study that estimated the prevalence percentage of REM in the SDB patients (such as OSA patients) was around 13.5% [59], and we obtained below 15.68%.…”

Section: Resultssupporting

confidence: 81%

Automatic Sleep Disorders Classification Using Ensemble of Bagged Tree Based on Sleep Quality Features

2020

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Sleep disorder is a medical disease of the sleep patterns, which commonly suffered by the elderly. Sleep disorders diagnosis and treatment are considered to be challenging due to a time-consuming and inconvenient process for the patient. Moreover, the use of Polysomnography (PSG) in sleep disorder diagnosis is a high-cost process. Therefore, we propose an efficient classification method of sleep disorder by merely using electrocardiography (ECG) signals to simplify the sleep disorders diagnosis process. Different from many current related studies that applied a five-minute epoch to observe the main frequency band of the ECG signal, we perform a pre-processing technique that suitable for the 30-seconds epoch of the ECG signal. By this simplification, the proposed method has a low computational cost so that suitable to be implemented in an embedded hardware device. Structurally, the proposed method consists of five stages: (1) pre-processing, (2) spectral features extraction, (3) sleep stage detection using the Decision-Tree-Based Support Vector Machine (DTB-SVM), (4) assess the sleep quality features, and (5) sleep disorders classification using ensemble of bagged tree classifiers. We evaluate the effectiveness of the proposed method in the task of classifying the sleep disorders into four classes (insomnia, Sleep-Disordered Breathing (SDB), REM Behavior Disorder (RBD), and healthy subjects) from the 51 patients of the Cyclic Alternating Pattern (CAP) sleep data. Based on experimental results, the proposed method presents 84.01% of sensitivity, 94.17% of specificity, 86.27% of overall accuracy, and 0.70 of Cohen’s kappa. This result indicates that the proposed method able to reliably classify the sleep disorders merely using the 30-seconds epoch ECG in order to address the issue of a multichannel signal such as the PSG.

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Section: Resultssupporting

confidence: 81%

Automatic Sleep Disorders Classification Using Ensemble of Bagged Tree Based on Sleep Quality Features

2020

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“…As other authors have suggested, 10,[18][19][20] we propose that individuals with several apneas and hypopneas during REM sleep, even with milder OSA forms, could benefit from treatment to reduce harmful effects to brain health. Consistently, continuous positive airway pressure (CPAP) was previously shown to be effective in reversing at least partially daytime rCBF changes in OSA individuals.…”

Section: Clinical Significance Of Rem Sleep Osamentioning

confidence: 68%

“…Although groups are clinically important, there is many different criteria that exist in the current literature with arguably arbitrary cut-offs to define the presence of REM sleep OSA. 10 Moreover, some studies showed a dose-response relationship between various physiological functions and respiratory events during REM sleep. [18][19][20][21] Regression models are not limited by arbitrary cut-offs and may represent more closely the physiopathology compared to a group analysis.…”

Section: Use Of a Regression Approach In Rem Sleep Osamentioning

confidence: 99%

“…During REM sleep, upper airway muscle activity is reduced and their collapsibility increases, 10,18,34 which may lead to more apneas and hypopneas during REM sleep, even in milder OSA cases. The literature is scarce on the consequences of REM sleep OSA with a mild overall severity.…”

Section: Characteristics Of Osa During Rem Sleep and Daytime Cerebralmentioning

confidence: 99%

“…About 14 to 37 % of individuals with OSA have most of their apneas and hypopneas during rapid-eye movement (REM) sleep, and this proportion is higher for milder OSA cases. [9][10][11][12][13] Because REM sleep represents only a small proportion of total sleep duration, many respiratory events predominantly during REM sleep may still result in a low overall apnea-hypopnea index (AHI), leading to a milder OSA diagnosis. This poses a clinical dilemma as to whether we should treat milder OSA cases that features respiratory events predominantly during REM sleep.…”

Section: Introductionmentioning

confidence: 99%

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Obstructive sleep apnea during REM sleep and daytime cerebral functioning: A regional cerebral blood flow study using high-resolution SPECT

Baril

Gagnon

Brayet

et al. 2018

J Cereb Blood Flow Metab

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Obstructive sleep apnea (OSA) predominantly during rapid eye movement (REM) sleep may have impacts on brain health, even in milder OSA cases. Here, we evaluated whether REM sleep OSA is associated with abnormal daytime cerebral functioning using high-resolution single-photon emission computed tomography (SPECT). We tested 96 subjects (25 F, age: 65.2 ± 6.4) with a wide range of OSA severity from no OSA to severe OSA (apnea–hypopnea index: 0–97 events/h). More respiratory events during REM sleep were associated with reduced daytime regional cerebral blood flow (rCBF) in the bilateral ventromedial prefrontal cortex and in the right insula extending to the frontal cortex. More respiratory events during non-REM (NREM) sleep were associated with reduced daytime rCBF in the left sensorimotor and temporal cortex. In subjects with a lower overall OSA severity (apnea–hypopnea index<15), more respiratory events during REM sleep were also associated with reduced daytime rCBF in the insula and extending to the frontal cortex. Respiratory events that characterized OSA during NREM versus REM sleep are associated with distinct patterns of daytime cerebral perfusion. REM sleep OSA could be more detrimental to brain health, as evidenced by reduced daytime rCBF in milder forms of OSA.

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