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Physiological Research Aug 2023In patients with obstructive sleep apnea (OSA) during obstructive events, episodes of hypoxia and hypercapnia may modulate the autonomic nervous system (ANS) by... (Review)
Review
In patients with obstructive sleep apnea (OSA) during obstructive events, episodes of hypoxia and hypercapnia may modulate the autonomic nervous system (ANS) by increasing sympathetic tone and irritability, which contributes to sympathovagal imbalance and ultimately dysautonomia. Because OSA can alter ANS function through biochemical changes, we can assume that heart rate variability (HRV) will be altered in patients with OSA. Most studies show that in both the time and frequency domains, patients with OSA have higher sympathetic components and lower parasympathetic dominance than healthy controls. These results confirm autonomic dysfunction in these patients, but also provide new therapeutic directions. Respiratory methods that modulate ANS, e.g., cardiorespiratory biofeedback, could be beneficial for these patients. Heart rate variability assessment can be used as a tool to evaluate the effectiveness of OSA treatment due to its association with autonomic impairment.
Topics: Humans; Public Health; Polysomnography; Autonomic Nervous System; Sleep Apnea, Obstructive; Heart Rate
PubMed: 37795885
DOI: 10.33549/physiolres.935065 -
Journal of Neural Engineering Oct 2023Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential...
Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential for the diagnosis of sleep disorders, as frequent and excessive occurrences of arousals disrupt sleep stage patterns and lead to poor sleep quality, negatively impacting physical and mental health. Polysomnography is a traditional method for arousal and sleep stage detection that is time-consuming and prone to high variability among experts.. In this paper, we propose a novel multi-task learning approach for arousal and sleep stage detection using fully convolutional neural networks. Our model, FullSleepNet, accepts a full-night single-channel EEG signal as input and produces segmentation masks for arousal and sleep stage labels. FullSleepNet comprises four modules: a convolutional module to extract local features, a recurrent module to capture long-range dependencies, an attention mechanism to focus on relevant parts of the input, and a segmentation module to output final predictions.By unifying the two interrelated tasks as segmentation problems and employing a multi-task learning approach, FullSleepNet achieves state-of-the-art performance for arousal detection with an area under the precision-recall curve of 0.70 on Sleep Heart Health Study and Multi-Ethnic Study of Atherosclerosis datasets. For sleep stage classification, FullSleepNet obtains comparable performance on both datasets, achieving an accuracy of 0.88 and an F1-score of 0.80 on the former and an accuracy of 0.83 and an F1-score of 0.76 on the latter.. Our results demonstrate that FullSleepNet offers improved practicality, efficiency, and accuracy for the detection of arousal and classification of sleep stages using raw EEG signals as input.
Topics: Electroencephalography; Sleep Stages; Sleep; Polysomnography; Arousal
PubMed: 37769664
DOI: 10.1088/1741-2552/acfe3a -
Sleep Jan 2024This study explores polysomnographic and multiple sleep latency test (MSLT) differences between myotonic dystrophy type 1/type 2 (DM1/DM2) patients and controls. (Meta-Analysis)
Meta-Analysis
STUDY OBJECTIVES
This study explores polysomnographic and multiple sleep latency test (MSLT) differences between myotonic dystrophy type 1/type 2 (DM1/DM2) patients and controls.
METHODS
An electronic literature search was conducted in MEDLINE, EMBASE, All EBM databases, and Web of Science from inception to Aug 2023.
RESULTS
Meta-analyses revealed significant reductions in sleep efficiency, N2 percentage, mean SpO2, and MSLT measured mean sleep latency, and increases in N3 sleep, wake time after sleep onset, apnea hypopnea index, and periodic limb movement index in DM1 patients compared with controls. However, any differences of polysomnographic sleep change between DM2 patients and controls could not be established due to limited available studies.
CONCLUSIONS
Multiple significant polysomnographic abnormalities are present in DM1. More case-control studies evaluating polysomnographic changes in DM2 compared with controls are needed.
Topics: Humans; Case-Control Studies; Myotonic Dystrophy; Polysomnography; Sleep; Sleep, Slow-Wave
PubMed: 37967212
DOI: 10.1093/sleep/zsad280 -
Sensors (Basel, Switzerland) Nov 2023Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea-hypopnea index is a measure used to assess the... (Review)
Review
Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea-hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. This comprehensive paper reviews devices, emphasizing distinctions among representative apnea devices and technologies for home detection of OSA. The collected articles are analyzed to present a clear discussion. Each article is evaluated according to diagnostic elements, the implemented automation level, and the derived level of evidence and quality rating. The findings indicate that the critical variables for monitoring sleep behavior include oxygen saturation (oximetry), body position, respiratory effort, and respiratory flow. Also, the prevalent trend is the development of level IV devices, measuring one or two signals and supported by prediction software. Noteworthy methods showcasing optimal results involve neural networks, deep learning, and regression modeling, achieving an accuracy of approximately 99%.
Topics: Humans; Polysomnography; Sleep Apnea, Obstructive; Sleep; Sleep Apnea Syndromes; Oximetry
PubMed: 38067885
DOI: 10.3390/s23239512 -
Annals of the American Thoracic Society Jan 2024The physiological factors modulating the severity of snoring have not been adequately described. Airway collapse or obstruction is generally the leading determinant of...
The physiological factors modulating the severity of snoring have not been adequately described. Airway collapse or obstruction is generally the leading determinant of snore sound generation; however, we suspect that ventilatory drive is of equal importance. To determine the relationship between airway obstruction and ventilatory drive on snore loudness. In 40 patients with suspected or diagnosed obstructive sleep apnea (1-98 events/hr), airflow was recorded via a pneumotachometer attached to an oronasal mask, ventilatory drive was recorded using calibrated intraesophageal diaphragm electromyography, and snore loudness was recorded using a calibrated microphone attached over the trachea. "Obstruction" was taken as the ratio of ventilation to ventilatory drive and termed flow:drive, i.e., actual ventilation as a percentage of intended ventilation. Lower values reflect increased flow resistance. Using 165,063 breaths, mixed model analysis (quadratic regression) quantified snore loudness as a function of obstruction, ventilatory drive, and the presence of extreme obstruction (i.e., apneic occlusion). In the presence of obstruction (flow:drive = 50%, i.e., doubled resistance), snore loudness increased markedly with increased drive (+3.4 [95% confidence interval, 3.3-3.5] dB per standard deviation [SD] change in ventilatory drive). However, the effect of drive was profoundly attenuated without obstruction (at flow:drive = 100%: +0.23 [0.08-0.39] dB per SD change in drive). Similarly, snore loudness increased with increasing obstruction exclusively in the presence of increased drive (at drive = 200% of eupnea: +2.1 [2.0-2.2] dB per SD change in obstruction; at eupneic drive: +0.14 [-0.08 to 0.28] dB per SD change). Further, snore loudness decreased substantially with extreme obstruction, defined as flow:drive <20% (-9.9 [-3.3 to -6.6] dB vs. unobstructed eupneic breathing). This study highlights that ventilatory drive, and not simply pharyngeal obstruction, modulates snore loudness. This new framework for characterizing the severity of snoring helps better understand the physiology of snoring and is important for the development of technologies that use snore sounds to characterize sleep-disordered breathing.
Topics: Humans; Snoring; Polysomnography; Sleep Apnea Syndromes; Sleep Apnea, Obstructive; Sound
PubMed: 37879037
DOI: 10.1513/AnnalsATS.202305-438OC -
Sleep Mar 2024The body-first Parkinson's disease (PD) hypothesis suggests initial gut Lewy body pathology initially propagates to the pons before reaching the substantia nigra, and...
STUDY OBJECTIVES
The body-first Parkinson's disease (PD) hypothesis suggests initial gut Lewy body pathology initially propagates to the pons before reaching the substantia nigra, and subsequently progresses to the diencephalic and cortical levels, a disease course presumed to likely occur in PD with rapid eye movement sleep behavior disorder (RBD). We aimed to explore the potential association between colonic phosphorylated alpha-synuclein histopathology (PASH) and diencephalic or cortical dysfunction evidenced by non-rapid eye movement (NREM) sleep and wakefulness polysomnographic markers.
METHODS
In a study involving 43 patients with PD who underwent clinical examination, rectosigmoidoscopy, and polysomnography, we detected PASH on colonic biopsies using whole-mount immunostaining. We performed a visual semi-quantitative analysis of NREM sleep and wake electroencephalography (EEG), confirmed it with automated quantification of spindle and slow wave features of NREM sleep, and the wake dominant frequency, and then determined probable Arizona PD stage classifications based on sleep and wake EEG features.
RESULTS
The visual analysis aligned with the automated quantified spindle characteristics and the wake dominant frequency. Altered NREM sleep and wake parameters correlated with markers of PD severity, colonic PASH, and RBD diagnosis. Colonic PASH frequency also increased in parallel to probable Arizona PD stage classifications.
CONCLUSIONS
Colonic PASH is strongly associated with widespread brain sleep and wake dysfunction, suggesting an extensive diffusion of the pathologic process in PD. Visual and automated analyses of polysomnography signals provide useful markers to gauge covert brain dysfunction in PD.
CLINICAL TRIAL
Name: SYNAPark, URL: https://clinicaltrials.gov/study/NCT01748409, registration: NCT01748409.
Topics: Humans; Parkinson Disease; Sleep; REM Sleep Behavior Disorder; Brain; Polysomnography
PubMed: 38156524
DOI: 10.1093/sleep/zsad310 -
Chest Aug 2023
Topics: Humans; Polysomnography; Restless Legs Syndrome; Neoplasms; Movement
PubMed: 37558323
DOI: 10.1016/j.chest.2023.04.035 -
Sleep Aug 2023
Topics: Humans; Aged; Polysomnography; Reproducibility of Results; Sleep Apnea, Obstructive
PubMed: 37074871
DOI: 10.1093/sleep/zsad116 -
Journal of Attention Disorders Aug 2023Sleep problems have been commonly observed in children with attention deficit hyperactivity disorder (ADHD). The aim of current study was to investigate the impact of... (Randomized Controlled Trial)
Randomized Controlled Trial
OBJECTIVE
Sleep problems have been commonly observed in children with attention deficit hyperactivity disorder (ADHD). The aim of current study was to investigate the impact of physical activity on sleep quality in young adolescent with attention deficit hyperactivity disorder.
METHOD
A total of 33 children diagnosed with attention deficit hyperactivity disorder (mean age = 10.12 years) were randomized into intervention group and control group respectively. Mention the intervention detail here. Four specific sleep parameters, including sleep efficiency, sleep onset latency, sleep duration, and wake after sleep onset, were assessed before and after the intervention period in both groups.
RESULTS
Results revealed the significant improvements in sleep efficiency, sleep onset latency and wake after sleep onset in the intervention group but not in the control group.
CONCLUSION
Current findings highlight the benefits of PA on enhancing sleep quality among children with ADHD.
Topics: Adolescent; Humans; Child; Attention Deficit Disorder with Hyperactivity; Sleep Quality; Sleep Wake Disorders; Polysomnography; Sleep; Exercise
PubMed: 37248735
DOI: 10.1177/10870547231171723 -
CMAJ : Canadian Medical Association... Feb 2024
Topics: Child; Humans; Sleep Apnea, Obstructive; Polysomnography
PubMed: 38408779
DOI: 10.1503/cmaj.230897