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Sleep Medicine Clinics Sep 2017Excessive daytime sleepiness is defined as the inability to maintain wakefulness during waking hours, resulting in unintended lapses into sleep. It is important to... (Review)
Review
Excessive daytime sleepiness is defined as the inability to maintain wakefulness during waking hours, resulting in unintended lapses into sleep. It is important to distinguish sleepiness from fatigue. The evaluation of a sleep patient begins with a careful clinical assessment that includes a detailed sleep history, medical and psychiatric history, a review of medications, as well as a social and family history. Physical examination should include a general medical examination with careful attention to the upper airway and the neurologic examination. Appropriate objective testing with a polysomnogram and a multiple sleep latency test if needed will help confirm the diagnosis and direct the appropriate treatment plan.
Topics: Disorders of Excessive Somnolence; Humans; Polysomnography
PubMed: 28778229
DOI: 10.1016/j.jsmc.2017.03.006 -
Sleep Medicine Clinics Dec 2016Autonomic arousal at the end of sleep apnea events are not well-explored. We prospectively studied 20 patients with obstructive sleep apnea (OSA) and 24 healthy... (Review)
Review
Autonomic arousal at the end of sleep apnea events are not well-explored. We prospectively studied 20 patients with obstructive sleep apnea (OSA) and 24 healthy volunteers for 2 nights with cardiorespiratory polysomnography and continuous noninvasive blood pressure (Portapres). Recordings were scored visually for cortical and autonomic arousal. In the OSA group, 2151 cortical arousals and in the controls 1089 cortical arousals were scored. Respiratory arousal caused most frequently an increase of highest mean arterial blood pressure in patients and controls. A useful definition for autonomic arousal for OSA and controls based on blood pressure and heart rate analysis was developed.
Topics: Arousal; Autonomic Nervous System; Humans; Polysomnography; Sleep Apnea Syndromes
PubMed: 28118868
DOI: 10.1016/j.jsmc.2016.08.009 -
Physiological Measurement Aug 2022Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring... (Review)
Review
Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone to errors. Current research has confirmed the correlations between sleep and the respiratory/circulatory system. Electrocardiography (ECG) is convenient to perform, and ECG data are rich in breathing information. Therefore, sleep research based on ECG data has become popular. Currently, deep learning (DL) methods have achieved promising results on predictive health care tasks using ECG signals. Therefore, in this review, we systematically identify recent research studies and analyze them from the perspectives of data, model, and task. We discuss the shortcomings, summarize the findings, and highlight the potential opportunities. For sleep-related tasks, many ECG-based DL methods produce more accurate results than traditional approaches by combining multiple signal features and model structures. Methods that are more interpretable, scalable, and transferable will become ubiquitous in the daily practice of medicine and ambient-assisted-living applications. This paper is the first systematic review of ECG-based DL methods for sleep tasks.
Topics: Deep Learning; Electrocardiography; Humans; Polysomnography; Sleep; Sleep Apnea Syndromes
PubMed: 35853448
DOI: 10.1088/1361-6579/ac826e -
Annual International Conference of the... Jul 2023Explainable Artificial Intelligence (xAI) is a rapidly growing field that focuses on making deep learning models interpretable and understandable to human...
Explainable Artificial Intelligence (xAI) is a rapidly growing field that focuses on making deep learning models interpretable and understandable to human decision-makers. In this study, we introduce xAAEnet, a novel xAI model applied to the assessment of Obstructive Sleep Apnea (OSA) severity. OSA is a prevalent sleep disorder that can lead to numerous medical conditions and is currently assessed using the Apnea-Hypopnea Index (AHI). However, AHI has been criticized for its inability to accurately estimate the effect of OSAs on related medical conditions. To address this issue, we propose a human-centric xAI approach that emphasizes similarity between apneic events as a whole and reduces subjectivity in diagnosis by examining how the model makes its decisions. Our model was trained and tested on a dataset of 60 patients' Polysomnographic (PSG) recordings. Our results demonstrate that the proposed model, xAAEnet, outperforms models with traditional architectures such as convolutional regressor, autoencoder (AE), and variational autoencoder (VAE). This study highlights the potential of xAI in providing an objective OSA severity scoring method.Clinical relevance- This study provides an objective OSA severity scoring technique which could improve the management of apneic patients in clinical practice.
Topics: Humans; Artificial Intelligence; Polysomnography; Sleep Apnea, Obstructive
PubMed: 38083271
DOI: 10.1109/EMBC40787.2023.10341035 -
Journal of Sleep Research Apr 2021Our objectives were to assess the prevalence of REM sleep behaviour disorder in patients with Essential Tremor, using video-polysomnography and to compare REM sleep...
Our objectives were to assess the prevalence of REM sleep behaviour disorder in patients with Essential Tremor, using video-polysomnography and to compare REM sleep behaviour disorder features in essential tremor with those of patients with alpha-synucleinopathies. Forty-nine patients with essential tremor were screened with the REM Sleep Behaviour Disorder Screening Questionnaire. Patients scoring positive and those with spontaneous complaints of REM sleep behaviour disorder (n = 6) underwent video-polysomnography. The clinical features of essential tremor were compared between patients with and without REM sleep behaviour disorder. Video-polysomnography data were compared between patients who had essential tremor and Parkinson's disease with REM sleep behaviour disorder and those with idiopathic REM sleep behaviour disorder. Fourteen patients (23.5%) screened positive for REM sleep behaviour disorder, confirmed by video-polysomnography in five (11.6%). All patients with essential tremor and REM sleep behaviour disorder had rest tremor, compared with 13 (34.2%) in the group with essential tremor but without REM sleep behaviour disorder (p = .009). In video-polysomnography, patients with essential tremor and REM sleep behaviour disorder were similar to patients with Parkinson's disease with REM sleep behaviour disorder and presented worse sleep dysfunction and lower severity of REM sleep behaviour disorder compared to those with idiopathic REM sleep behaviour disorder. We found a high prevalence of REM sleep behaviour disorder in patients with essential tremor, associated with a predominance of rest tremor. Polysomnography data from patients with essential tremor and REM sleep behaviour disorder were similar to those in patients with Parkinson's disease. This suggests a relation between this subgroup of patients with essential tremor and the alpha-synucleinopathies.
Topics: Aged; Essential Tremor; Humans; Male; Middle Aged; Polysomnography; REM Sleep Behavior Disorder; Surveys and Questionnaires
PubMed: 32323893
DOI: 10.1111/jsr.13050 -
Sleep Medicine Reviews Oct 2018One of the most common sleep-related disorders is obstructive sleep apnea, characterized by a reduction of airflow while breathing during sleep and cause significant... (Review)
Review
One of the most common sleep-related disorders is obstructive sleep apnea, characterized by a reduction of airflow while breathing during sleep and cause significant health problems. This disorder is mainly diagnosed in sleep labs with polysomnography, involving high costs and stress for the patient. To address this situation multiple systems have been proposed to conduct the examination and analysis in the patient's home, using sensors to detect physiological signals that are examined by algorithms. The objective of this research is to review publications that show the performance of different devices for ambulatory diagnosis of sleep apnea. Commercial systems that were examined by an independent research group and validated research projects were selected. In total 117 articles were analysed, including a total of 50 commercial devices. Each article was evaluated according to diagnostic elements, level of automatisation implemented and the deducted level of evidence and quality rating. Each device was categorized using the SCOPER categorization system, including an additional proposed category, and a final comparison was performed to determine the sensors that provided the best results.
Topics: Home Care Services; Humans; Monitoring, Physiologic; Oximetry; Polysomnography; Sleep Apnea, Obstructive
PubMed: 30149930
DOI: 10.1016/j.smrv.2018.02.004 -
Journal of Sleep Research Jun 2021An intermediate phenotype of a disease is a trait in the path of pathogenesis from genetic predisposition to disease manifestation. Identifying intermediate phenotypes...
An intermediate phenotype of a disease is a trait in the path of pathogenesis from genetic predisposition to disease manifestation. Identifying intermediate phenotypes with high heritability is helpful in delineating the genetics of a disorder. In this study, we aimed to examine various traits with regards to obesity, cardiovascular risk and upper airway structure to identify potential intermediate phenotypes of childhood obstructive sleep apnea (OSA). Children aged between 6 and 18 years and their parents and siblings were recruited. All subjects underwent anthropometric measurements, cardiovascular risk assessment, sonographic measurement of lateral parapharyngeal wall (LPW) thickness, X-ray cephalometry and overnight polysomnography. A total of 34 phenotypes were examined. One hundred and one families consisting of 127 children (46 overweight) and 198 adults (84 overweight) were recruited. Heritability of obstructive apnea-hypopnea index (OAHI) was significant in overweight (h = 0.54) but not normal-weight individuals (h = 0.12). LPW thickness (h = 0.68) and resting blood pressure (h = 0.36 and 0.43 for systolic blood pressure [SBP] and diastolic blood pressure [DBP], respectively) were significantly heritable and associated with OAHI. Moreover, these traits were found to have shared genetic variance with OAHI in the overweight subgroup. Hyoid bone position also had significant heritability (h = 0.55) and association with OAHI but genetic correlation with OSA severity was not demonstrated. These findings suggest that LPW thickness and resting blood pressure are possible intermediate phenotypes of OSA independent of body mass index, especially in overweight patients. Identifying genes relevant to these phenotypes may help to elucidate the genetic susceptibility of OSA.
Topics: Adolescent; Child; Female; Humans; Male; Polysomnography; Sleep Apnea, Obstructive
PubMed: 32926500
DOI: 10.1111/jsr.13191 -
Journal of the American Dental... Apr 2024The concept of sleep bruxism (SB) has evolved exponentially over the past several decades. Many theories and hypotheses have been proposed as to the definition,... (Review)
Review
BACKGROUND
The concept of sleep bruxism (SB) has evolved exponentially over the past several decades. Many theories and hypotheses have been proposed as to the definition, pathophysiology, and management of SB, from the early 1960s through the present. The role of peripheral factors, such as dental occlusion, in the pathogenesis of SB has been discarded.
TYPES OF STUDIES REVIEWED
The authors searched several electronic databases (ie, PubMed, Google Scholar, Web of Science, Embase, and Ovid MEDLINE) for studies on bruxism. The search was conducted from January 1961 through May 2023 and yielded 4,612 articles, of which 312 were selected for comprehensive review after eliminating duplicates and nonfocused articles.
RESULTS
There has been an evident progressive shift from the role of peripheral factors, such as dental occlusion, to more central factors, such as the involvement of a central pattern generator as well as the autonomic nervous system, in the genesis of bruxing movements. There is continued robust interest in the dental community to elucidate the contributing factors involved in SB.
CONCLUSIONS AND PRACTICAL IMPLICATIONS
The neurophysiology of SB appears to be leaning more toward central rather than peripheral factors. There is increasing evidence of the role of the autonomic nervous system, genetics, and comorbidities in the genesis of SB. The scientific literature seems to refute the role of dental occlusion in the causation of bruxing movements. As per the literature, there has been a paradigm shift in the definition and genesis of SB and its possible dental implications and management, which also highlights the need for succinct scientific studies in this regard.
Topics: Humans; Sleep Bruxism; Polysomnography
PubMed: 38363252
DOI: 10.1016/j.adaj.2023.12.004 -
Journal of Medical Internet Research Sep 2022American Academy of Sleep Medicine guidelines suggest that clinical prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) without... (Review)
Review
BACKGROUND
American Academy of Sleep Medicine guidelines suggest that clinical prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) without replacing polysomnography, the gold standard.
OBJECTIVE
We aimed to identify, gather, and analyze existing machine learning approaches that are being used for disease screening in adult patients with suspected OSA.
METHODS
We searched the MEDLINE, Scopus, and ISI Web of Knowledge databases to evaluate the validity of different machine learning techniques, with polysomnography as the gold standard outcome measure and used the Prediction Model Risk of Bias Assessment Tool (Kleijnen Systematic Reviews Ltd) to assess risk of bias and applicability of each included study.
RESULTS
Our search retrieved 5479 articles, of which 63 (1.15%) articles were included. We found 23 studies performing diagnostic model development alone, 26 with added internal validation, and 14 applying the clinical prediction algorithm to an independent sample (although not all reporting the most common discrimination metrics, sensitivity or specificity). Logistic regression was applied in 35 studies, linear regression in 16, support vector machine in 9, neural networks in 8, decision trees in 6, and Bayesian networks in 4. Random forest, discriminant analysis, classification and regression tree, and nomogram were each performed in 2 studies, whereas Pearson correlation, adaptive neuro-fuzzy inference system, artificial immune recognition system, genetic algorithm, supersparse linear integer models, and k-nearest neighbors algorithm were each performed in 1 study. The best area under the receiver operating curve was 0.98 (0.96-0.99) for age, waist circumference, Epworth Somnolence Scale score, and oxygen saturation as predictors in a logistic regression.
CONCLUSIONS
Although high values were obtained, they still lacked external validation results in large cohorts and a standard OSA criteria definition.
TRIAL REGISTRATION
PROSPERO CRD42021221339; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=221339.
Topics: Adult; Bayes Theorem; Humans; Machine Learning; Neural Networks, Computer; Polysomnography; Sleep Apnea, Obstructive
PubMed: 36178720
DOI: 10.2196/39452 -
Deutsche Medizinische Wochenschrift... Jan 2016Obstructive sleep apnea (OSA) is a clinically significant condition associated with an increase in cardiovascular risk, daytime sleepiness and in risk of accidents.... (Review)
Review
Obstructive sleep apnea (OSA) is a clinically significant condition associated with an increase in cardiovascular risk, daytime sleepiness and in risk of accidents. Diagnosis usually relies on a detailed anamnesis and an ambulatory nocturnal polygraphy. Suspecting the presence of OSA or a persisting unclear daytime sleepiness in need of treatment further polysomnographic diagnosis should be performed in a specialized sleep center. Cardiorespiratory polysomnography is the diagnostic gold standard in differentiating sleep-related breathing and movement disorders.
Topics: Diagnosis, Differential; Diagnostic Techniques, Cardiovascular; Diagnostic Techniques, Respiratory System; Humans; Polysomnography; Sleep Apnea, Obstructive; Sleep Medicine Specialty
PubMed: 26710202
DOI: 10.1055/s-0041-106846