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Impairments in sleep and affect regulation are evident across a wide range of mental disorders. Understanding the sleep factors that relate to affect regulatory difficulties will inform mechanistic understanding and aid in treatment. Despite rising interest, some research challenges in this area include integrating across different clinical and non-clinical literatures investigating the role of sleep architecture (measured with polysomnography) and experimentally manipulated sleep, as well as integrating more explicit versus implicit affect regulation processes. In this comprehensive review, we use a unifying framework to examine sleep's relationship with implicit-automatic regulation and explicit-controlled regulation, both of which are relevant to mental health (e.g., PTSD and depression). Many studies of implicit-automatic regulation (e.g., fear extinction and safety learning) demonstrate the importance of sleep, and REM sleep specifically. Studies of explicit-controlled regulation (e.g., cognitive reappraisal and expressive suppression) are less consistent in their findings, with results differing depending on the type of affect regulation and/or way that sleep was measured or manipulated. There is a clear relationship between objective sleep and affect regulation processes. However, there is a need for 1) more studies focusing on sleep and explicit-controlled affect regulation; 2) replication with the same types of regulation strategies; 3) more studies experimentally manipulating sleep to examine its impact on affect regulation and vice versa in order to infer cause and effect; and 4) more studies looking at sleep's impact on next-day affect regulation (not just overnight change in affect reactivity)., CC BY-NC-ND 4.0Corresponding author: 4150 Clement St. (116P), San Francisco, CA, 94121, USA. E-mail address: laura.straus@ucsf.edu (L.D. Straus).LDS is supported by the Department of Veterans Affairs Clinical Science Research and Development Award: IK2CX002032. P.S. was supported by research grants from Emil Aaltonen Foundation (Finland), Alfred Kordelin Foundation (Finland), and the Finnish Cultural Foundation. MtB was supported by research fellowships from the National Science Foundation, P.E.O. International, and the American Association of University Women. PJC is supported by Veterans Affairs RR&D Merit Award 1 I01 RX003623-01.

Rationale: Oral appliances are second-line treatments after continuous positive airway pressure for obstructive sleep apnea (OSA) management. However, the need for oral appliance titration limits their use as a result of monitoring challenges to assess the treatment effect on OSA. Objectives: To assess the validity of mandibular jaw movement (MJM) automated analysis compared with polysomnography (PSG) and polygraphy (PG) in evaluating the effect of oral appliance treatment and the effectiveness of MJM monitoring for oral appliance titration at home in patients with OSA. Methods: This observational, prospective study included 135 patients with OSA eligible for oral appliance therapy. The primary outcome was the apnea-hypopnea index (AHI), measured through in-laboratory PSG/PG and MJM-based technology. Additionally, MJM monitoring at home was conducted at regular intervals during the titration process. The agreement between PSG/PG and MJM automated analysis was revaluated using Bland-Altman analysis. Changes in AHI during the home-based oral appliance titration process were evaluated using a generalized linear mixed model and a generalized estimating equation model. Results: The automated MJM analysis demonstrated strong agreement with PG in assessing AHI at the end of titration, with a median bias of 0.24/h (limits of agreement, -11.2 to 12.8/h). The improvement of AHI from baseline in response to oral appliance treatment was consistent across three evaluation conditions: in-laboratory PG (-59.6%; 95% confidence interval, -59.8% to -59.5%), in-laboratory automated MJM analysis (-59.2%; -65.2% to -52.2%), and at-home automated MJM analysis (-59.7%; -67.4% to -50.2%). Conclusions: Incorporating MJM automated analysis into the oral appliance titration process has the potential to optimize oral appliance therapy outcomes for OSA.

STUDY OBJECTIVES: Recently, criteria have been drawn up for large muscle group movements during sleep (LMM), defined as movements lasting for 3-45 seconds in adults, which are often accompanied by changes in sleep stage, arousals, and increases in heart rate. The aim of this study was to characterize LMM in restless legs syndrome (RLS) in order to better evaluate their impact on the neurophysiology of the disorder and, therefore, the possible clinical implications. METHODS: Consecutive, drug-free patients diagnosed with RLS and controls, aged 18 years or more, were retrospectively enrolled. Leg movement activity-short-interval (SILMS), periodic (PLMS), and isolated (ISOLMS) leg movements during sleep-and LMM were detected and scored. RESULTS: In total, 100 patients and 67 controls were recruited. All movement measures were significantly higher in RLS. A significant positive correlation was found between LMM and ISOLMS index but not PLMS index in both groups. LMM index showed a significant negative correlation with total sleep time, sleep efficiency, and percentage of sleep stages N3 and R, as well as a significant positive correlation with the number of awakenings, and percentage of sleep stages N1 and N2 only in patients with RLS. No significant correlation was found between either LMM or PLMS index and RLS severity. CONCLUSIONS: Different types of movements, including SILMS, ISOLMS, and LMM, play somewhat distinct roles in sleep neurophysiology in RLS. Notably, LMM, a newly recognized category of movements, demonstrates associations with sleep architecture instability and fragmentation, arousals, and awakenings, suggesting potential clinical implications.

Narcolepsy is mainly associated with excessive daytime sleepiness, but the characteristic feature is abnormal rapid eye movement (REM) sleep phenomena. REM sleep disturbances can manifest as cataplexy (in narcolepsy type 1), sleep paralysis, sleep-related hallucinations, REM sleep behavior disorder, abnormal dreams, polysomnographic evidence of REM sleep disruption with sleep-onset REM periods, and fragmented REM sleep. Characterization of REM sleep and related symptoms facilitates the differentiation of narcolepsy from other central hypersomnolence disorders and aids in distinguishing between narcolepsy types 1 and 2. A circuit comprising regions within the brainstem, forebrain, and hypothalamus is involved in generating and regulating REM sleep, which is influenced by changes in monoamines, acetylcholine, and neuropeptides. REM sleep is associated with brainstem functions, including autonomic control, and REM sleep disturbances may be associated with increased cardiovascular risk. Medications used to treat narcolepsy (and REM-related symptoms of narcolepsy) include stimulants/wake-promoting agents, pitolisant, oxybates, and antidepressants; hypocretin agonists are a potential new class of therapeutics. The role of REM sleep disturbances in narcolepsy remains an area of active research in pathophysiology, symptom management, and treatment. This review summarizes the current understanding of the role of REM sleep and its dysfunction in narcolepsy.

Home mechanical ventilation is an assistive technology that assists individuals with respiratory failure to breath, while living in the community. Over the past two decades, there has been a rapid advancement of the technical capabilities of these home mechanical ventilation devices (HMVD), and they now have the capability to provide both the clinician and user with daily data which is available for review remotely. After implementation of HMVD therapy, there is a process of adjustment and titration of the ventilator’s settings to ensure that the treatment is safe and effective. HMVD setting titration has traditionally occurred over a multi-night hospital stay or in a sleep laboratory using polysomnography (PSG), to enable acclimatisation, training and detailed physiological monitoring that informs adjustment of the HMVD. Due to the advancement of HMVD technology, some ventilation healthcare services have incorporated HMVD data to inform the clinical decision-making process to titrate HMVD therapies. What is presently unclear; however, is the impact that using HMVD derived data for both the titration and subsequent prescription of ventilator settings has on the adjustment of therapy. In this thesis, the implementation of HMVD therapy is described and the available evidence that underlies different approaches is considered. The process by which NIV is optimised, including the titration of NIV settings in response to respiratory events is described. Using a novel methodological framework, three experiments in this thesis detail a comprehensive assessment of NIV setting prescription, the identification of these respiratory events and subsequent titration of therapy using different methods of physiological monitoring: NIV PSG, polygraphy, breath-by-breath analysis of ventilator signals alone and finally summarised HMVD data. The results from the experimental chapters of this thesis demonstrate key differences in both the identification of events of respiratory significa

The most basic definition of the sleep is related with organism’s response to environmental stimuli. Sleep can be defined as a reversible, lessthan-awake response to the environment, which recurs on a daily cycle. All problems that affect sleep quality, duration and subject’s daily life are named as sleep disorder. Polysomnography is the gold standard for the evaluation of sleep signals. A polysomnography device records electroencephalography, electrooculography, and electromyography activities at the same time. A polysomnographic measurement can be extended with recording additiona lphysiological signals, like electrocardiography and body position, oxygen level in the blood, and snoring. These additional signals are important for the diagnosis of sleep disorders. The diagnosis of sleep disorder is done with analyzing laborious overnight polysomnography recording. Nowadays, to reduce duration and increase accuracy of diagnosis, artificial intelligence applications are used. These applications developed by using feature extraction-based machine learning or deep learning algorithms that generally apply to one or two polysomnography signals. By using artificial intelligence in sleep studies, duration of diagnosis reduces from hours to minutes and increases accuracy of diagnosis to over 90%. This study gives examples about artificial intelligence applications used in sleep studies.

Study Objectives: Excessive daytime sleepiness (EDS) is a major symptom of obstructive sleep apnea (OSA). Traditional polysomnographic (PSG) measures only partially explain EDS in OSA. This study analyzed traditional and novel PSG characteristics of two different measures of EDS among patients with OSA. Methods: Sleepiness was assessed using the Epworth Sleepiness Scale (>10 points defined as "risk of dozing") and a measure of general sleepiness (feeling sleepy >= 3 times/week defined as "feeling sleepy"). Four sleepiness phenotypes were identified: "non-sleepy," "risk of dozing only," "feeling sleepy only," and "both at risk of dozing and feeling sleepy." Results: Altogether, 2083 patients with OSA (69% male) with an apnea-hypopnea index (AHI) >= 5 events/hour were studied; 46% were "non-sleepy," 26% at "risk of dozing only," 7% were "feeling sleepy only," and 21% reported both. The two phenotypes at "risk of dozing" had higher AHI, more severe hypoxemia (as measured by oxygen desaturation index, minimum and average oxygen saturation [SpO(2)], time spent < 90% SpO(2), and hypoxic impacts) and they spent less time awake, had shorter sleep latency, and higher heart rate response to arousals than "non-sleepy" and "feeling sleepy only" phenotypes. While statistically significant, effect sizes were small. Sleep stages, frequency of arousals, wake after sleep onset and limb movement did not differ between sleepiness phenotypes after adjusting for confounders. Conclusions: In a large international group of patients with OSA, PSG characteristics were weakly associated with EDS. The physiological measures differed among individuals characterized as "risk of dozing" or "non-sleepy," while "feeling sleepy only" did not differ from "non-sleepy" individuals.

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages. The sensor is already used for diagnosis of sleep-disordered breathing (SDB) conditions, but besides respiratory effort it can detect cardiac vibrations transmitted through the trachea. We collected the SSP sensor signal in 100 adults (57 male) undergoing clinical polysomnography for suspected sleep disorders, including sleep apnea syndrome, insomnia, and movement disorders. Here, we separate respiratory effort and cardiac activity related signals, then input these into a neural network trained to estimate sleep stages. Using the original mixed signal the results show a moderate agreement with manual scoring, with a Cohen's kappa of 0.53 in Wake/N1-N2/N3/rapid eye movement sleep discrimination and 0.62 in Wake/Sleep. We demonstrate that decoupling the two signals and using the cardiac signal to estimate the instantaneous heart rate improves the process considerably, reaching an agreement of 0.63 and 0.71. Our proposed method achieves high accuracy, specificity, and sensitivity across different sleep staging tasks. We also compare the total sleep time calculated with our method against manual scoring, with an average error of -1.83 min but a relatively large confidence interval of ±55 min. Compact systems that employ the SSP sensor information-rich signal may enable new ways of clinical assessments, such as night-to-night variability in obstructive sleep apnea and other sleep disorders.

ObjectiveDrug induced sleep endoscopy (DISE) is often performed for pediatric obstructive sleep apnea (OSA) when initial diagnostic studies do not provide adequate information for therapy. However, DISE scoring is subjective and with limitations. This proof-of-concept study demonstrates the use of a novel long-range optical coherence tomography (LR-OCT) system during DISE of two pediatric patients.MethodsLR-OCT was used to visualize the airway of pediatric patients during DISE. At the conclusion of DISE, the OCT probe was guided in the airway under endoscopic visual guidance, and cross-sectional images were acquired at the four VOTE locations. Data processing involved image resizing and alignment, followed by rendering of three-dimensional (3D) volumetric models of the airways.ResultsTwo patients were included in this study. Patient one had 18.4%, 20.9%, 72.3%, and 97.3% maximal obstruction at velum, oropharynx, tongue base, and epiglottis, while patient two had 40.2%, 41.4%, 8.0%, and 17.5% maximal obstruction at these regions, respectively. Three-dimensional reconstructions of patients' airways were also constructed from the OCT images.ConclusionThis proof-of-concept study demonstrates the successful evaluation of pediatric airway during DISE using LR-OCT, which accurately identified sites and degrees of obstruction with respective 3D airway reconstruction.

Zielsetzung. Im aktuellen Forschungsstand finden sich nur wenige Befunde über Veränderungen in der Schlafarchitektur, die vor dem Ausbruch einer psychischen Erkrankung auftreten. Ziel dieser Untersuchung ist es, zu überprüfen, ob Veränderungen in der Wachzeit während des Schlafs mit einem erhöhten Risiko für künftige psychische Erkrankungen stehen. Methode. Die retrospektive Kohortenstudie beinhaltet Patientinnen und Patienten, die im Zeitraum von 2004 bis 2010 eine Nacht im Schlaflabor Innsbruck verbracht haben. Personen über 18 Jahre sowie Personen ohne psychische Erkrankung bei Baseline oder innerhalb von einem Jahr nach Baseline wurden in die Analyse einbezogen. Personen mit Einnahme von Psychopharmaka bei Baseline oder innerhalb von einem Jahr nach Baseline wurden von der Untersuchung ausgeschlossen. Outcome-Variablen. Diagnose einer psychischen Erkrankung sowie die Einnahme von Psychopharmaka als Indikator für eine psychische Erkrankung. Ergebnisse. Von insgesamt 2.624 PatientInnen wurden 1.329 in die Studie aufgenommen (956 männlich [72%]; Alter im Mittelwert [IQR] 53 [42 - 64] Jahre). Insgesamt wurden 126 (10%) Diagnosen und 312 (24%) medikamentöse Interventionen beobachtet. Nach Adjustierung für demografische, schlafbezogene und klinische Kovariaten hatten Patientinnen und Patienten mit einer 30-minütigen Erhöhung der „Wake after Sleep Onset“ zu jedem Zeitpunkt des Studienzeitraums ein um 22% und 32% erhöhtes Risiko an einer Anpassungsstörung oder einem Abhängigkeitssyndrom zu erkranken. Das Risiko an einer affektiven Störung zu erkranken war um 27% reduziert. Bei einer um 30 Minuten erhöhten „Wake after Sleep Onset“ zeigte sich zu jedem Zeitpunkt des untersuchten Zeitraums ein um 13% erhöhtes Risiko für eine Intervention mit Psychopharmaka. Fazit. Die Ergebnisse zeigen einen Zusammenhang zwischen der „Wake after Sleep Onset“ und dem Risiko für das Auftreten einer psychischen Störung sowie der Notwendigkeit einer medikamentösen Intervention. Dies zeigt das, Objective. Longitudinal findings on changes in sleep architecture prior to a mental illness are sparse in the current state of research. The aim of this study is to examine whether changes in wake after sleep onset are associated with the risk of developing a mental disorder. Method. A retrospective cohort study of patients referred to the sleep laboratory between 2004 and 2010 was conducted. Patients over the age of 18 and without mental illness at baseline or within one year after baseline were included in the analysis. Patients taking psychotropic medication at baseline or within one year of baseline were excluded from the study. Outcomes. Diagnosis of mental illness as well as the use of psychotropic drugs as an indicator of mental illness. Results. Of 2624 patients available, 1329 were included in the study (956 man [72 %]; mean age 53 [IQR 42 - 64] years). A total of 126 (10%) diagnoses and 312 (24%) drug interventions were observed. After controlling for demographic, sleep, and clinical covariates, patients with a 30-minute increase in wake after sleep onset had a 22% and 32% increased risk of developing an adjustment disorder or substance use disorder at any given time during the study period. The risk of developing an affective disorder was reduced by 27%. With a 30-minute increase in wake after sleep onset, the risk of an intervention with psychotropic drugs was 13% higher at any given time during the study period. Conclusion. The results show an association between waking time and the risk of developing a mental disorder as well as the need for drug intervention. This demonstrates the potential of using wake time as a marker for the early detection of mental illness., Nicolas Nenning, B.Sc., in englischer Sprache, Masterarbeit Universität Innsbruck 2024

The prevalence of obstructive sleep apnea (OSA) among the bariatric surgery population is estimated to be 45–70%. However, weight loss obtained by bariatric surgery is not always associated with full remission of OSA, suggesting that other confounding factors are present. This article aims to review the current literature, focusing on factors that could predict the persistence of OSA after bariatric surgery. For this purpose, relevant studies of more than 50 patients that assessed pre-and post-operative presence and severity of OSA detected by poly(somno)graphy (PG/PSG) in bariatric populations were collected. Six retrospective and prospective studies were evaluated that included 1302 OSA patients, with a BMI range of 42.6 to 56 kg/m2, age range of 44.8 to 50.7 years, and percentage of women ranging from 45% to 91%. The studies were very heterogeneous regarding type of bariatric surgery, diagnostic criteria for OSA and OSA remission, and delay of OSA reassessment. OSA remission was observed in 26% to 76% of patients at 11–12 months post-surgery. Loss to follow-up was high in all studies, leading to a potential underestimation of OSA remission. Based on this limited sample of bariatric patients, age, pre-operative OSA severity, proportion of weight loss, and type 2 diabetes (T2D) were identified as factors associated with OSA persistence but the results were inconsistent between studies regarding the impact of age and the magnitude of weight loss. Several other factors may potentially lead to OSA persistence in the bariatric surgery population, such as fat distribution, ethnicity, anatomical predisposition, pathophysiological traits, supine position, and REM-predominant hypopnea and apnea. Further well-conducted multicentric prospective studies are needed to document the importance of these factors to achieve a better understanding of OSA persistence after bariatric surgery in obese patients., SCOPUS: re.j, info:eu-repo/semantics/published

BACKGROUND: Sleep-disordered breathing (SDB) affects a significant portion of the population. As such, there is a need for accessible and affordable assessment methods for diagnosis but also case-finding and long-term follow-up. Research has focused on exploiting cardiac and respiratory signals to extract proxy measures for sleep combined with SDB event detection. We introduce a novel multi-task model combining cardiac activity and respiratory effort to perform sleep-wake classification and SDB event detection in order to automatically estimate the apnea-hypopnea index (AHI) as severity indicator.METHODS: The proposed multi-task model utilized both convolutional and recurrent neural networks and was formed by a shared part for common feature extraction, a task-specific part for sleep-wake classification, and a task-specific part for SDB event detection. The model was trained with RR intervals derived from electrocardiogram and respiratory effort signals. To assess performance, overnight polysomnography (PSG) recordings from 198 patients with varying degree of SDB were included, with manually annotated sleep stages and SDB events.RESULTS: We achieved a Cohen's kappa of 0.70 in the sleep-wake classification task, corresponding to a Spearman's correlation coefficient (R) of 0.830 between the estimated total sleep time (TST) and the TST obtained from PSG-based sleep scoring. Combining the sleep-wake classification and SDB detection results of the multi-task model, we obtained an R of 0.891 between the estimated and the reference AHI. For severity classification of SBD groups based on AHI, a Cohen's kappa of 0.58 was achieved. The multi-task model performed better than a single-task model proposed in a previous study for AHI estimation, in particular for patients with a lower sleep efficiency (R of 0.861 with the multi-task model and R of 0.746 with single-task model with subjects having sleep efficiency < 60%).CONCLUSION: Assisted with automat

Objective. Sleep staging based on full polysomnography is the gold standard in the diagnosis of many sleep disorders. It is however costly, complex, and obtrusive due to the use of multiple electrodes. Automatic sleep staging based on single-channel electro-oculography (EOG) is a promising alternative, requiring fewer electrodes which could be self-applied below the hairline. EOG sleep staging algorithms are however yet to be validated in clinical populations with sleep disorders. Approach. We utilized the SOMNIA dataset, comprising 774 recordings from subjects with various sleep disorders, including insomnia, sleep-disordered breathing, hypersomnolence, circadian rhythm disorders, parasomnias, and movement disorders. The recordings were divided into train (574), validation (100), and test (100) groups. We trained a neural network that integrated transformers within a U-Net backbone. This design facilitated learning of arbitrary-distance temporal relationships within and between the EOG and hypnogram. Main results. For 5-class sleep staging, we achieved median accuracies of 85.0% and 85.2% and Cohen’s kappas of 0.781 and 0.796 for left and right EOG, respectively. The performance using the right EOG was significantly better than using the left EOG, possibly because in the recommended AASM setup, this electrode is located closer to the scalp. The proposed model is robust to the presence of a variety of sleep disorders, displaying no significant difference in performance for subjects with a certain sleep disorder compared to those without. Significance. The results show that accurate sleep staging using single-channel EOG can be done reliably for subjects with a variety of sleep disorders.

Non-rapid eye movement parasomnia disorders, also called disorders of arousal, are characterized by abnormal nocturnal behaviours, such as confusional arousals or sleep walking. Their pathophysiology is not yet fully understood, and objective diagnostic criteria are lacking. It is known, however, that behavioural episodes occur mostly in the beginning of the night, after an increase in slow-wave activity during slow-wave sleep. A better understanding of the prospect of such episodes may lead to new insights in the underlying mechanisms and eventually facilitate objective diagnosis. We investigated temporal dynamics of transitions from slow-wave sleep of 52 patients and 79 controls. Within the patient group, behavioural and non-behavioural N3 awakenings were distinguished. Patients showed a higher probability to wake up after an N3 bout ended than controls, and this probability increased with N3 bout duration. Bouts longer than 15 min resulted in an awakening in 73% and 34% of the time in patients and controls, respectively. Behavioural episodes reduced over sleep cycles due to a reduction in N3 sleep and a reducing ratio between behavioural and non-behavioural awakenings. In the first two cycles, N3 bouts prior to non-behavioural awakenings were significantly shorter than N3 bouts advancing behavioural awakenings in patients, and N3 awakenings in controls. Our findings provide insights in the timing and prospect of both behavioural and non-behavioural awakenings from N3, which may result in prediction and potentially prevention of behavioural episodes. This work, moreover, leads to a more complete characterization of a prototypical hypnogram of parasomnias, which could facilitate diagnosis.

Polysomnography (PSG) is the gold standard for recording sleep. However, the standard PSG systems are bulky, expensive, and often confined to lab environments. These systems are also time-consuming in electrode placement and sleep scoring. Such limitations render standard PSG systems less suitable for large-scale or longitudinal studies of sleep. Recent advances in electronics and artificial intelligence enabled ‘wearable’ PSG systems. Here, we present a study aimed at validating the performance of ZMax, a widely-used wearable PSG that includes frontal electroencephalography (EEG) and actigraphy but no submental electromyography (EMG). We analyzed 135 nights with simultaneous ZMax and standard PSG recordings amounting to over 900 hours from four different datasets, and evaluated the performance of the headband’s proprietary automatic sleep scoring (ZLab) alongside our open-source algorithm (DreamentoScorer) in comparison with human sleep scoring. ZLab and DreamentoScorer compared to human scorers with moderate and substantial agreement and Cohen’s kappa scores of 59.61% and 72.18%, respectively. We further analyzed the competence of these algorithms in determining sleep assessment metrics, as well as shedding more lights on the bandpower computation, and morphological analysis of sleep microstructural features between ZMax and standard PSG. Relative bandpower computed by ZMax implied an error of 5.5% (delta), 4.5% (theta), 1.6% (alpha), 0.5% (sigma), 0.8% (beta), and 0.2% (gamma), compared to standard PSG. In addition, the microstructural features detected in ZMax did not represent exactly the same characteristics as in standard PSG. Besides similarities and discrepancies between ZMax and standard PSG, we measured and discussed the technology acceptance rate, feasibility of data collection with ZMax, and highlighted essential factors for utilizing ZMax as a reliable tool for both monitoring and modulating sleep., Preprint.

Obstructive Sleep Apnea Syndrome (OSAS) is a prevalent clinical condition marked by recurrent upper airway obstruction during sleep, impacting normal ventilation. Linked to non-modifiable factors like age and modifiable ones such as obesity, OSAS often presents challenging symptoms, particularly when individuals sleep alone. A comprehensive evaluation, including polysomnography, is crucial for diagnosis. While continuous positive airway pressure therapy (CPAP) remains standard, alternative are available for those intolerant or unresponsive to CPAP. OSAS poses a significant public health concern due to the heightened cardiovascular risk associated with mechanical, biological, and neurological factors. Comprehensive care is imperative for effective management., El Síndrome de Apnea Obstructiva del Sueño (SAOS) es una condición clínica prevalente, caracterizada por la obstrucción recurrente de la vía aérea superior durante el sueño, afectando la ventilación normal. Asociado a factores no modificables como la edad y modificables como la obesidad, el SAOS presenta síntomas desafiantes, especialmente en individuos que duermen solos. Una evaluación exhaustiva, que incluye la polisomnografía, es crucial para el diagnóstico. Aunque la terapia con presión positiva continua en las vías respiratorias (CPAP) es estándar, existen alternativas para aquellos intolerantes o con respuesta insuficiente al CPAP. El SAOS representa una preocupación significativa para la salud pública debido al aumento del riesgo cardiovascular vinculado a factores mecánicos, biológicos y neurológicos. La atención integral es esencial para un manejo efectivo.

Over recent years, positive airway pressure (PAP) remote monitoring has transformed the management of OSA and produced a large amount of data. Accumulated PAP data provide valuable and objective information regarding patient treatment adherence and efficiency. However, the majority of studies that have analyzed longitudinal PAP remote monitoring have summarized data trajectories in static and simplistic metrics for PAP adherence and the residual apnea-hypopnea index by the use of mean or median values. The aims of this article are to suggest directions for improving data cleaning and processing and to address major concerns for the following data science applications: (1) conditions for residual apnea-hypopnea index reliability, (2) lack of standardization of indicators provided by different PAP models, (3) missing values, and (4) consideration of treatment interruptions. To allow fair comparison among studies and to avoid biases in computation, PAP data processing and management should be conducted rigorously with these points in mind. PAP remote monitoring data contain a wealth of information that currently is underused in the field of sleep research. Improving the quality and standardizing data handling could facilitate data sharing among specialists worldwide and enable artificial intelligence strategies to be applied in the field of sleep apnea.

STUDY OBJECTIVES: Hypotonia, commonly seen in infants with Down syndrome (I-DS), can contribute to masticatory and oropharyngeal muscle weakness, increasing the risk for dysphagia and sleep-disordered breathing. Data describing the occurrence of dysphagia and sleep-disordered breathing in I-DS are limited. This study aims to determine the frequency and severity of dysphagia and its relationship to polysomnogram parameters in I-DS. METHODS: We included I-DS who underwent polysomnography at a single academic center over a 6-year period. Data collected included sex, age, presence of dysphagia (low suspicion of dysphagia vs dysphagia vs feeding tube), and polysomnographic data. Dysphagia was determined by a video fluoroscopic swallow study in the presence of clinical suspicion. RESULTS: A total of 40 I-DS were identified (mean age 6.6 months ± 3; male 65%). There were 11, 13, and 16 I-DS with low suspicion of dysphagia, dysphagia, and feeding tube, respectively. Obstructive sleep apnea was more severe in I-DS in the feeding tube group when compared with the group with a low suspicion of dysphagia and (apnea-hypopnea index mean [standard error] = 49.3 [7.6] vs 19.2 [9.2] events/h; P = .016). Dysphagia severity was positively correlated with a higher obstructive apnea-hypopnea index (r = .43, P = .006). CONCLUSIONS: There is a high incidence of dysphagia and sleep-disordered breathing in I-DS. Dysphagia severity correlated with obstructive apnea-hypopnea index severity. Our results suggest that I-DS need early evaluation of both sleep-disordered breathing and dysphagia. CITATION: Cho Y, Kwon Y, DelRosso L, Sobremonte-King M. Dysphagia severity is associated with worse sleep-disordered breathing in infants with Down syndrome. J Clin Sleep Med. 2023;19(5):883-887.

BackgroundMany cellular processes are controlled by sleep. Therefore, alterations in sleep might be expected to stress biological systems that could influence malignancy risk.Research questionWhat is the association between polysomnographic measures of sleep disturbances and incident cancer, and what is the validity of cluster analysis in identifying polysomnography phenotypes?Study design and methodsWe conducted a retrospective multicenter cohort study using linked clinical and provincial health administrative data on consecutive adults free of cancer at baseline with polysomnography data collected between 1994 and 2017 in four academic hospitals in Ontario, Canada. Cancer status was derived from registry records. Polysomnography phenotypes were identified by k-means cluster analysis. A combination of validation statistics and distinguishing polysomnographic features was used to select clusters. Cox cause-specific regressions were used to assess the relationship between identified clusters and incident cancer.ResultsAmong 29,907 individuals, 2,514 (8.4%) received a diagnosis of cancer over a median of 8.0 years (interquartile range, 4.2-13.5 years). Five clusters were identified: mild (mildly abnormal polysomnography findings), poor sleep, severe OSA or sleep fragmentation, severe desaturations, and periodic limb movements of sleep (PLMS). The associations between cancer and all clusters compared with the mild cluster were significant while controlling for clinic and year of polysomnography. When additionally controlling for age and sex, the effect remained significant only for PLMS (adjusted hazard ratio [aHR], 1.26; 95% CI, 1.06-1.50) and severe desaturations (aHR, 1.32; 95% CI, 1.04-1.66). Further controlling for confounders, the effect remained significant for PLMS, but was attenuated for severe desaturations.InterpretationIn a large cohort, we confirmed the importance of polysomnographic phenotypes and highlighted the role that PLMS and oxygenation d

Rationale: Central sleep apnea (CSA) is pervasive during sleep at high altitude, disproportionately impacting men and associated with increased peripheral chemosensitivity. Objectives: We aimed to assess whether biological sex affects loop gain (LGn) and CSA severity during sleep over 9-10 days of acclimatization to 3,800 m. We hypothesized that CSA severity would worsen with acclimatization in men but not in women because of greater increases in LGn in men. Methods: Sleep studies were collected from 20 (12 male) healthy participants at low altitude (1,130 m, baseline) and after ascent to (nights 2/3, acute) and residence at high altitude (nights 9/10, prolonged). CSA severity was quantified as the respiratory event index (REI) as a surrogate of the apnea-hypopnea index. LGn, a measure of ventilatory control instability, was quantified using a ventilatory control model fit to nasal flow. Linear mixed models evaluated effects of time at altitude and sex on respiratory event index and LGn. Data are presented as contrast means with 95% confidence intervals. Results: REI was comparable between men and women at acute altitude (4.1 [-9.3, 17.5] events/h; P = 0.54) but significantly greater in men at prolonged altitude (23.7 [10.3, 37.1] events/h; P = 0.0008). Men had greater LGn than did women for acute (0.08 [0.001, 0.15]; P = 0.047) and prolonged (0.17 [0.10, 0.25]; P < 0.0001) altitude. The change in REI per change in LGn was significantly greater in men than in women (107 ± 46 events/h/LGn; P = 0.02). Conclusions: The LGn response to high altitude differed between sexes and contributed to worsening of CSA over time in men but not in women. This sex difference in acclimatization appears to protect females from high altitude-related CSA. These data provide fundamental sex-specific physiological insight into high-altitude acclimatization in healthy individuals and may help to inform sex differences in sleep-disordered breathing pathogenesis in patients with

Background: The gold standard for diagnosing sleep bruxism (SB) and obstructive sleep apnea (OSA) is polysomnography (PSG). However, a final hypermotor muscle activity often occurs after apnea episodes, which can confuse the diagnosis of SB when using portable electromyography (EMG) devices. This study aimed to compare the number of SB episodes obtained from PSG with manual analysis by a sleep expert, and from a manual and automatic analysis of an EMG and electrocardiography (EKG) device, in a population with suspected OSA. Methods: Twenty-two subjects underwent a polysomnographic study with simultaneous recording with the EMG-EKG device. SB episodes and SB index measured with both tools and analyzed manually and automatically were compared. Masticatory muscle activity was scored according to published criteria. Patients were segmented by severity of OSA (mild, moderate, severe) following the American Academy of Sleep Medicine (AASM) criteria. ANOVA and the Bland–Altman plot were used to quantify the agreement between both methods. The concordance was calculated through the intraclass correlation coefficient (ICC). Results: On average, the total events of SB per night in the PSG study were (8.41 ± 0.85), lower than the one obtained with EMG-EKG manual (14.64 ± 0.76) and automatic (22.68 ± 16.02) analysis. The mean number of SB episodes decreases from the non-OSA group to the OSA group with both PSG (5.93 ± 8.64) and EMG-EKG analyses (automatic = 22.47 ± 18.07, manual = 13.93 ± 11.08). However, this decrease was minor in proportion compared to the automatic EMG-EKG analysis mode (from 23.14 to 22.47). The ICC based on the number of SB episodes in the segmented sample by severity degree of OSA along the three tools shows a moderate correlation in the non-OSA (0.61) and mild OSA (0.53) groups. However, it is poorly correlated in the moderate (0.24) and severe (0.23) OSA groups: the EMG-EKG automatic analysis measures 14.27 units more than PSG. The results of the manual, Depto. de Odontología Conservadora y Prótesis, Fac. de Odontología, TRUE, pub, Descuento UCM

Introduktion: Sömn är en erkänt viktig del för idrottslig prestation. Intresset och möjligheterna att övervaka den har ökat betänkligt till följd av antalet tillgängliga sömnmonitorerande bärbara verktyg (SBV) idag. Denna utrustning bidrar med en möjlighet att kontinuerligt samla in data, men till följd av den snabba utvecklingen av dessa verktyg finns det ett ständigt behov av mer valideringsarbete. Syfte: Syftet med litteraturöversikten var att undersöka och redogöra hur väl olika sömnmonitorerande bärbara verktyg kan monitorera sömn i relation till polysomnografi (PSG), nivå I bland friska individer. Metod: En strukturerad litteratursökning utfördes i databaserna SPORTdiscus och PubMed under tidsperioden 2023-03-15 till och med 2023-04-06 med syftet att identifiera artiklar som jämförde kommersiellt tillgängliga SBV mot PSG, nivå I bland friska individer. Vi utvärderade kvaliteten och risken för bias för de inkluderade studierna genom en modifierad checklista av Downs & Black (1998). Resultat: Efter en granskning av 213 artiklar inkluderades 11 av dem, innehållandes totalt 368 deltagare. Resultatet visade att SBV har svårigheter att korrekt estimera tid spenderad i respektive sömnfas i jämförelse mot PSG. Förmågan att uppskatta Total Sleep Time (TST) och Wake After Sleep Onset (WASO) varierade stort mellan de olika modellerna. Gällande Sleep Onset Latency (SOL), hjärtfrekvensen (HR) och hjärtfrekvensvariabiliteten (HRV) var det få statistiskt signifikanta resultat samt antal studier som undersökte dessa tre variabler. Konklusion: I dagsläget har SBV problem att uppmäta tiden spenderad i respektive sömnfas, och uppvisar varierande resultat i fråga om estimeringen av TST och WASO. Gällande SOL, HR och HRV fanns det inte tillräckligt med underlag i de inkluderande studierna för att dra slutsatser om förmågan hos SBV att uppskatta dessa variabler. Individer bör vara försiktiga vid appliceringen av data från verktygen, samt medvetna om de eventuella risker s, Introduction: Sleep is widely recognized as an important factor for athletic performance. The interest and possibility of measuring it has increased dramatically following the number of available wearable devices today. These wearables provide an opportunity to continuously collect data in a home environment, but because of the rapid increase of commercial availability, there remains a constant need for more validation of the most recent models. Purpose: The purpose of this review was to examine the capability of different wearables to monitor sleep in comparison to polysomnography (PSG), level I in healthy individuals. Method: A structured literature review was performed in the databases SPORTDiscus and PubMed under the period 2023-03-15 until 2023-04-06 with the aim of identifying relevant articles that compared commercially available wearables to PSG level I in healthy individuals. We assessed the quality and risk of bias of the included studies with a modified questionnaire from Downs & Black (1998). Results: After screening 213 articles, 11 of them were included, which in total amounted to 368 participants. The result showed that wearables struggle to correctly estimate the time spent in each sleep-stage in comparison with PSG. The capability to assess Total Sleep Time (TST) and Wake After Sleep Onset (WASO) varied between the different models. There were few statistically significant results of the ability to measure Sleep Onset Latency (SOL), Heart Rate (HR) and Heart Rate Variability (HRV). Conclusion: Wearables have, at present time, a difficult time correctly estimating time spent in each sleep-stage and show varied results in monitoring TST and WASO. Too few studies analyzed SOL, HR and HRV to draw conclusions regarding these variables. Individuals should be cautious when implementing the data from these devices, and aware of the potential risks when it is used with athletes.

Post-traumatic stress disorder (PTSD) is a debilitating and enduring disorder that a small but significant number of people develop following exposure to a traumatic event. A common feature of PTSD is disrupted sleep including insomnia and nightmares. Ongoing difficulties in sleeping prevent the sleep-dependent adaptive processing of traumatic memories. Further, sleep disruptions prevent recovery, and perpetuate the disorder when established. This thesis aimed to investigate the bi-directional association between changes in sleep and PTSD symptoms as well as between sleep and underlying fear memory processes. In part I, I examined the immediate effect of changes in sleep on fluctuations of PTSD symptoms and vice versa. Here I used both subjective and, for the first time, objective measures of sleep (study 1). This study found differences in the association between sleep and daytime PTSD symptoms depending on the sleep measurement method. Additionally, preliminary evidence suggests sex-specificity in the association between night-time sleep and daytime PTSD symptoms. Part II focused on the role of sleep in fear conditioning and extinction learning – the experimental model of PTSD development and treatment. Extinction learning and extinction recall (i.e., the ability to learn and remember that previously dangerous stimuli are not threatening anymore) are thought to be impaired in PTSD and impacted by sleep. Particularly rapid eye movement (REM) sleep has been suggested as the sleep stage most important for processing emotional memories. First, a systematic review summarized the available literature assessing the effect of REM and other sleep stages using a meta-analytic approach (study 2). The overwhelming majority of research highlighted the importance of REM sleep, but the meta-analysis did not find the expected REM sleep effect on extinction recall. Following this and the finding from part I, the third and last study investigated the effect of subjectively reported

BackgroundMechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort is one of the main features of OSA and is associated with sympathetic overactivity, leading to increased vascular wall stiffness and remodelling. This study investigated associations between a new measure of respiratory effort (percentage of total sleep time spent with increased respiratory effort based on measurement of mandibular jaw movements (MJM): REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA.MethodsA machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices and MJM-derived parameters (including REMOV). The model was evaluated in a training subset and a test subset.ResultsThe analysis included 1127 patients: 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on 18 input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75 and specificity 0.83). Using the Shapley additive explanation method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index and neck circumference) and time with oxygen saturation <90%, ahead of standard PSG metrics (including the apnoea-hypopnoea index and oxygen desaturation index).ConclusionThe proportion of sleep time spent with increased respiratory effort automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA.

Case summaryA 3-month-old Airedale dog with clinically diagnosed generalized tetanus was investigated for the occurrence of excessive paddling and chewing movements when sleeping. Electroencephalogram (EEG) with time-locked video over 31 hours determined occurrence of the abnormal movements to be within 20 to 180 seconds of the onset of rapid eye movement (REM) sleep, but not at any other stage of wakefulness or sleep. No epileptiform activity was noted. Clinical signs of generalized tetanus resolved over 8 weeks with antimicrobial and symptomatic treatment, and sleep-associated movements resolved 6 weeks after presentation.Clinical relevanceRapid eye movement sleep behavior disorder (RBD) has been suspected in dogs with generalized tetanus but not confirmed by correlation of repeated episodes of vocalization or motor behaviors or both with REM sleep defined by an EEG. The case further defines RBD in dogs with tetanus, and highlights the value of EEG to differentiate among different parasomnias and epileptiform activity.

PurposeSleep disordered breathing in decompensated heart failure has physiological consequences (e.g., intermittent hypoxemia) that may predispose to subclinical myocardial injury, yet a temporal relationship between sleep apnea and troponin elevation has not been established.MethodsWe assessed the feasibility of performing respiratory polygraphy and measuring overnight high-sensitivity cardiac troponin T change in adults admitted to the hospital with acutely decompensated heart failure. Repeat sleep apnea tests (SATs) were performed to determine response to optimal medical heart failure therapy. Multivariable logistic regression was used to identify associations between absolute overnight troponin change and sleep apnea characteristics.ResultsAmong the 19 subjects with acutely decompensated heart failure, 92% of SATs demonstrated sleep disordered breathing (apnea-hypopnea index [AHI] > 5 events/h). For those with repeat SATs, AHI increased in 67% despite medical management of heart failure. Overnight troponin increase was associated with moderate to severe sleep apnea (vs. no to mild sleep apnea, odds ratio (OR = 18.4 [1.51-224.18]), central apnea index (OR = 1.11 [1.01-1.22]), and predominantly central sleep apnea (vs. obstructive, OR = 22.9 [1.29-406.32]).ConclusionsSleep apnea severity and a central apnea pattern may be associated with myocardial injury. Respiratory polygraphy with serial biomarker assessment is feasible in this population, and combining this approach with interventions (e.g., positive airway pressure) may help establish if a link exists between sleep apnea and subclinical myocardial injury.

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

Obstructive Sleep Apnea (OSA) it’s a pathology whose prevalence it’s on the rise. It’s characterized by frequent upper airway obstruction during sleep that led to episodes of apnea – hypopnea. Even though its risk factor and comorbidities are well-described, an important number of patients show less symptoms or have a less common phenotype, which tends to distract from the correct diagnosis a lot of the occasions. The basis for OSA diagnosis lies in a good clinical history, physical exam, screening questionaries and the help of Polysomnography or, more recently, Home Sleep Apnea Tests (HSAT). Therapies range from Continuous Positive Airway Pressure and Oral appliances to surgical treatments., El síndrome de apnea obstructiva del sueño (SAOS) es una patología cuya prevalencia se encuentra en aumento. Se caracteriza por episodios frecuentes de obstrucción de la vía aérea superior durante el sueño, lo cual da como resultado apnea – hipopnea. A pesar de que sus factores riesgo y comorbilidades se encuentran bien documentados, una cantidad no despreciable de pacientes muestra poca sintomatología o fenotipos diversos a los esperados, lo cual distrae del diagnóstico correcto en muchas ocasiones. El diagnóstico de SAOS se fundamenta en una historia clínica adecuada, examen físico, cuestionarios de tamizaje y la ayuda de la polisomnografía o, recientemente, de los equipos para el diagnóstico en el hogar (HSAT). El tratamiento de los pacientes involucra una gran gama de terapias que van desde la presión aérea positiva continua (PAP-C) y dispositivos orales, hasta procedimientos quirúrgicos.

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

We investigated the effects of transcranial alternating stimulation (tACS) in patients with insomnia. Nine patients with chronic insomnia underwent two in-laboratory polysomnography, 2 weeks apart, and were randomized to receive tACS either during the first or second study. The stimulation was applied simultaneously and bilaterally at F3/M1 and F4/M2 electrodes (0.75 mA, 0.75 Hz, 5-minute). Sleep onset latency and wake after sleep onset dropped on the stimulation night but they did not reach statistical significance; however, there were significant improvements in spontaneous and total arousals, sleep quality, quality of life, recall memory, sleep duration, sleep efficiency, and daytime sleepiness.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) and insomnia frequently co-occur, making diagnosis and treatment challenging. We investigated differences in sleep structure between patients with OSA, insomnia, and comorbid insomnia and sleep apnea (COMISA) to identify characteristics that can be used to improve the diagnosis of COMISA.METHODS: We obtained polysomnography data of 326 patients from the Sleep and OSA Monitoring with Non-Invasive Applications database. The group included patients with OSA (n = 199), insomnia (n = 47), and COMISA (n = 80). We compared statistics related to sleep structure between the 3 patient groups.RESULTS: Wake after sleep onset was significantly shorter for the OSA group (median: 60.0 minutes) compared to the COMISA (median: 83.3 minutes, P < .01) and the insomnia (median: 83.5 minutes, P = .01) groups. No significant differences were found in the total number of awakenings and the number of short (up to and including 2 minutes) and medium-length awakenings (2.5 up to and including 4.5 minutes). However, the number of long awakenings (5 minutes or longer) and wake after sleep onset containing only long awakenings was significantly lower for patients with OSA (median: 2 awakenings and 25.5 minutes) compared to patients with COMISA (median: 3 awakenings, P < .01 and 43.3 minutes, P < .001) or with insomnia (median: 3 awakenings, P < .01 and 56.0 minutes, P < .001). Total sleep time was significantly longer and sleep efficiency was significantly higher for the OSA group (median: 418.5 minutes and 84.4%) compared to both the COMISA (median: 391.5 minutes, P < .001 and 77.3%, P < .001) and the insomnia (median: 381.5 minutes, P < .001 and 78.2%, P < .001) groups. The number of sleep-stage transitions during the night for patients with COMISA (median: 194.0) was lower compared to that for patients with OSA (median: 218.0, P < .01) and higher compared to that for patients with insomnia (median

Background: People with intellectual disabilities (ID) have a higher risk of sleep disorders. Polysomnography (PSG) remains the diagnostic gold standard in sleep medicine. However, PSG in people with ID can be challenging, as sensors can be burdensome and have a negative influence on sleep. Alternative methods of assessing sleep have been proposed that could potentially transfer to less obtrusive monitoring devices. The goal of this study was to investigate whether analysis of heart rate variability and respiration variability is suitable for the automatic scoring of sleep stages in sleep-disordered people with ID. Methods: Manually scored sleep stages in PSGs of 73 people with ID (borderline to profound) were compared with the scoring of sleep stages by the CardioRespiratory Sleep Staging (CReSS) algorithm. CReSS uses cardiac and/or respiratory input to score the different sleep stages. Performance of the algorithm was analysed using input from electrocardiogram (ECG), respiratory effort and a combination of both. Agreement was determined by means of epochper-epoch Cohen’s kappa coefficient. The influence of demographics, comorbidities and potential manual scoring difficulties (based on comments in the PSG report) was explored. Results: The use of CReSS with combination of both ECG and respiratory effort provided the best agreement in scoring sleep and wake when compared with manually scored PSG (PSG versus ECG = kappa 0.56, PSG versus respiratory effort = kappa 0.53 and PSG versus both = kappa 0.62). Presence of epilepsy or difficulties in manually scoring sleep stages negatively influenced agreement significantly, but nevertheless, performance remained acceptable. In people with ID without epilepsy, the average kappa approximated that of the general population with sleep disorders. Conclusions: Using analysis of heart rate and respiration variability, sleep stages can be estimated in people with ID. This could in the future lead to less obtrusive measurements of

Objectives Objectively validated pediatric sleep questionnaires covering a broader age range and different sleep disturbances are lacking, therefore we developed the Sleep Screening Questionnaire Children and Adolescents (SSQ-CA) and compared it with objective sleep parameters. Methods This child-reported questionnaire was developed by a multidisciplinary panel and face validated. In a cross-sectional prospective design, participants aged 6–17, answered the questionnaire twice with 21–28 days in between, wore actigraphy (AG) and kept a sleep diary for seven nights and home-polysomnography (PSG) for one of these nights. Exploratory factor analyses (EFA), reliability and validity assessments were performed. Results Of the 139 participants, 128 (F:47.7%, AG: n = 128, PSG: n = 59), were included in the analyses. Mean age: 11.3 years (SD: 2.9). EFA revealed 11 factors and 40 items loading above r = 0.4. Subscale internal consistency: 0.54–0.92. Subscale test-retest reliability: r = 0.71–0.87. Total sleep time (TST) from SSQ-CA on weekdays correlated with PSG (r = 0.48, p = 0.001) and with AG (r = 0.75, p < 0.001). The subscale total score for “Sleep duration and latency” correlated with TST from AG (r = −0.19, p = 0.03) and sleep latency (r = 0.31, p < 0.001), but not for PSG variables. The subscale “Awakenings” showed no correlation with objective measures whereas “Circadian rhythm” correlated to AG-derived mid-sleep time (r = 0.34, p < 0.001). Conclusions The SSQ-CA shows adequate reliability for the 6–17-year-olds and acceptable criterion validity for two subscales. It appears to be a useful tool for screening for sleep disturbances in combination with objective tools as the subjective and objective parameters seem to uncover different aspects of sleep., Objectives: Objectively validated pediatric sleep questionnaires covering a broader age range and different sleep disturbances are lacking, therefore we developed the Sleep Screening Questionnaire Children and Adolescents (SSQ-CA) and compared it with objective sleep parameters. Methods: This child-reported questionnaire was developed by a multidisciplinary panel and face validated. In a cross-sectional prospective design, participants aged 6–17, answered the questionnaire twice with 21–28 days in between, wore actigraphy (AG) and kept a sleep diary for seven nights and home-polysomnography (PSG) for one of these nights. Exploratory factor analyses (EFA), reliability and validity assessments were performed. Results: Of the 139 participants, 128 (F:47.7%, AG: n = 128, PSG: n = 59), were included in the analyses. Mean age: 11.3 years (SD: 2.9). EFA revealed 11 factors and 40 items loading above r = 0.4. Subscale internal consistency: 0.54–0.92. Subscale test-retest reliability: r = 0.71–0.87. Total sleep time (TST) from SSQ-CA on weekdays correlated with PSG (r = 0.48, p = 0.001) and with AG (r = 0.75, p < 0.001). The subscale total score for “Sleep duration and latency” correlated with TST from AG (r = −0.19, p = 0.03) and sleep latency (r = 0.31, p < 0.001), but not for PSG variables. The subscale “Awakenings” showed no correlation with objective measures whereas “Circadian rhythm” correlated to AG-derived mid-sleep time (r = 0.34, p < 0.001). Conclusions: The SSQ-CA shows adequate reliability for the 6–17-year-olds and acceptable criterion validity for two subscales. It appears to be a useful tool for screening for sleep disturbances in combination with objective tools as the subjective and objective parameters seem to uncover different aspects of sleep.

Background: Post-traumatic stress disorder (PTSD) is the clinical manifestation of traumatic events and is associated with sleep disturbances. Sleep disturbances, if left untreated, may perpetuate or even worsen symptoms of PTSD. Previous studies of other PTSD populations show a higher incidence of sleep impairments and sleep disorders compared to healthy controls (HCs); however, this has never been investigated in trauma-affected refugees diagnosed with PTSD. Objectives: To examine subjective sleep quality, measure sleep architecture, and identify latent sleep disorders in refugees diagnosed with PTSD compared to HCs. Method: This comparative study included 20 trauma-affected refugees diagnosed with PTSD and 20 HC matched on age, sex, and body mass index. All participants completed self-report questionnaires assessing sleep quality, insomnia severity, and disturbing nocturnal behaviour, and all took part in a one-night polysomnography (PSG) assessment. Results: Patients reported significantly poorer subjective sleep quality, sleep latency, sleep duration, and sleep efficiency compared to HCs. Subjective reports on hours spent in bed were not significantly different between patients and HCs. Patients reported significantly higher nightmare frequency and severity compared to HCs. PSG measures showed that patients had significantly reduced sleep efficiency, more awakenings, and longer REM sleep latency, and spent more time awake, whereas there was no significant differences regarding total time in bed, total sleep time, or sleep latency. The prevalence of sleep disorders was equal between groups. Conclusions: The study identified significant impairments in several sleep domains, with a preponderance of disturbed regulation of sleep resulting in awakenings. These results indicate a need for more focus on hyperarousal and nightmares as key elements of disturbed sleep in PTSD. Furthermore, the study identified a discrepancy between sub, Background: Post-traumatic stress disorder (PTSD) is the clinical manifestation of traumatic events and is associated with sleep disturbances. Sleep disturbances, if left untreated, may perpetuate or even worsen symptoms of PTSD. Previous studies of other PTSD populations show a higher incidence of sleep impairments and sleep disorders compared to healthy controls (HCs); however, this has never been investigated in trauma-affected refugees diagnosed with PTSD. Objectives: To examine subjective sleep quality, measure sleep architecture, and identify latent sleep disorders in refugees diagnosed with PTSD compared to HCs. Method: This comparative study included 20 trauma-affected refugees diagnosed with PTSD and 20 HC matched on age, sex, and body mass index. All participants completed self-report questionnaires assessing sleep quality, insomnia severity, and disturbing nocturnal behaviour, and all took part in a one-night polysomnography (PSG) assessment. Results: Patients reported significantly poorer subjective sleep quality, sleep latency, sleep duration, and sleep efficiency compared to HCs. Subjective reports on hours spent in bed were not significantly different between patients and HCs. Patients reported significantly higher nightmare frequency and severity compared to HCs. PSG measures showed that patients had significantly reduced sleep efficiency, more awakenings, and longer REM sleep latency, and spent more time awake, whereas there was no significant differences regarding total time in bed, total sleep time, or sleep latency. The prevalence of sleep disorders was equal between groups. Conclusions: The study identified significant impairments in several sleep domains, with a preponderance of disturbed regulation of sleep resulting in awakenings. These results indicate a need for more focus on hyperarousal and nightmares as key elements of disturbed sleep in PTSD. Furthermore, the study identified a discrepancy between subjective and objective measures co

Sleep fragmentation may be associated with several diseases, including dementia. In this sense, sleep fragmentation, indicated by the rates of arousals and/or periodic leg movements (PLM), could be an early marker of Mild Cognitive Impairment (MCI), a syndromic stage prior to dementia. Therefore, the objective of this study was to compare the index of PLM with that of arousals and correlate both indexes in people with MCI and without MCI during all sleep stages. In 9 participants (3 control women and 3 women with MCI; and 3 men with MCI) (ages: 69.1 ± 5; years of education: 8 ± 2), one night of polysomnography was performed. Hourly rates of arousals and PLM were scored from each sleep stage. Analyses were performed within and between PLM and arousals for each group. Significant differences and a positive correlation were found between the arousal and the PLM rates for the group with MCI during the whole night. Knowledge of the prevalence and the association of both phenomena may contribute to a more careful and thorough evaluation of older adults at risk of developing MCI and/or dementia., La fragmentación del sueño puede asociarse con distintas enfermedades, entre ellas, la demencia. En este sentido, la fragmentación de sueño, indicada por el índice de alertamientos y/o movimientos periódicos de las piernas (MPP), podría ser un marcador temprano de deterioro cognitivo leve (DCL), un síndrome precursor de la demencia. El objetivo del presente estudio fue medir el índice de prevalencia de los alertamientos y de los MPP durante el sueño en un grupo control y un grupo con DCL, así como determinar si hay diferencia entre los grupos en ambos índices y establecer si existe una correlación entre los dos fenómenos. En 9 participantes (3 mujeres controles y 3 mujeres con DCL; y 3 hombres con DCL) (edad: 69.1 ± 5; años de educación: 8 ± 2) se registró una noche de polisomnografía. Se obtuvieron los índices por hora de alertamientos y para cada etapa de sueño, así como los MPP globales y por hora; además se realizaron análisis entre y dentro de cada grupo. Se encontró una correlación positiva y un mayor número de MPP que de alertamientos durante toda la noche en los participantes con DCL. Conocer la prevalencia y asociación de ambos fenómenos contribuye en la formulación de una evaluación más cuidadosa y profunda de los adultos mayores en riesgo de desarrollar DCL y/o demencia.

Sleep restriction therapy is a central component of cognitive behavioural therapy for insomnia, but can lead to excessive sleepiness, which may impede treatment adherence. Sleep compression therapy has been suggested as a possibly gentler alternative. The aim of this study was to compare the effects of sleep restriction therapy and sleep compression therapy on objective measures of sleep, with a focus on magnitude and timing of effects. From a larger study of participants with insomnia, a sub-sample of 36 underwent polysomnographic recordings, before being randomised to either sleep restriction (n = 19) or sleep compression (n = 17) and receiving online treatment for 10 weeks. Assessments with polysomnography were also carried out after 2, 5, and 10 weeks of treatment. Data were analysed with multilevel linear mixed effect modelling. As per treatment instructions, participants in sleep restriction initially spent shorter time in bed compared with sleep compression. Participants in sleep restriction also showed an initial decrease of total sleep time, which was not seen in the sleep compression group. Both treatments led to improvements in sleep continuity variables, with a tendency for the improvements to come earlier during treatment in sleep restriction. No substantial differences were found between the two treatments 10 weeks after the treatment start. The results indicate that homeostatic sleep pressure may not be as important as a mechanism in sleep compression therapy as in sleep restriction therapy, and an investigation of other mechanisms is needed. In conclusion, the treatments led to similar changes in objective sleep at a somewhat different pace, and possibly through different mechanisms.

Alcohol Use Disorder (AUD) results in sleep disturbances that may have deleterious impacts on cognition, especially on memory. However, little is known about the sleep architecture in patients with Korsakoff's syndrome (KS). This study aims at characterizing sleep disturbances in KS compared to AUD without KS and at specifying the relationships with cognitive impairments. Twenty-nine AUD patients (22 without KS and 7 with KS) and 15 healthy controls underwent a neuropsychological assessment and a polysomnography. The severity of sleep-disordered breathing and sleep fragmentation was similar in AUD and KS patients compared to controls. Sleep architecture differed between both patient groups: the proportion of slow-wave sleep was reduced in AUD patients only, while a lower proportion of rapid-eye movement (REM) sleep was specifically observed in KS patients. The proportion of REM sleep correlated with the severity of episodic memory deficits when AUD and KS were examined together. These data provide evidence for both similarities and specificities regarding sleep alterations in AUD patients with and without KS. They also indicate that altered sleep architecture may contribute to the pathophysiology of alcohol-related memory disorders., info:eu-repo/semantics/published

Obstructive sleep apnea syndrome (OSAS) is a chronic, progressive, disabling respiratory disorder with serious systemic repercussions; It is characterized by recurrent events of upper airway obstruction (UA) during sleep. In this way, it directly affects the individual's quality of life, since this occurrence causes daytime hypersomnolence, a feeling of suffocation when waking up, memory failure, sexual impotence, psychological changes such as anxiety and depression and, even, in more severe cases, acute heart attack. myocardial injury (AMI), cerebrovascular accident (CVA), as well as car accidents, which, therefore, constitute a public health problem. The objective of this literature review is to highlight the importance of the dentist's knowledge and conduct regarding the early diagnosis and treatment of OSAS, the request for appropriate complementary exams, their classifications and assertive therapeutic measures according to the individual's peculiarities. As a methodology, several searches were carried out in the SciELO, LILACS, PubMed, MEDLINE and Google Scholar databases from 1999 to 2023, with the following indexing terms: Sleep apnea syndrome, polysomnography, diagnosis, treatment, snoring, sleep. In this sense, it appears that Sleep Dentistry is a new field of activity for dental surgeons as a result of the possibility of conservative, effective and cost-effective treatments favorable to patients through clinically manufactured intraoral appliances (AIO). Therefore, it is expected that, in the medium term, the Federal Council of Dentistry (CFO) will recognize it as a dental specialty., El síndrome de apnea obstructiva del sueño (SAOS) es un trastorno respiratorio crónico, progresivo e incapacitante con graves repercusiones sistémicas; Se caracteriza por eventos recurrentes de obstrucción de las vías respiratorias superiores (UA) durante el sueño. De esta manera, afecta directamente la calidad de vida del individuo, ya que esta ocurrencia provoca hipersomnolencia diurna, sensación de asfixia al despertar, falla de memoria, impotencia sexual, cambios psicológicos como ansiedad y depresión e, incluso, en casos más severos, infarto agudo de miocardio (IAM), accidente cerebrovascular (ACV), así como accidentes automovilísticos, que, por tanto, constituyen un problema de salud pública. El objetivo de esta revisión bibliográfica es resaltar la importancia del conocimiento y conducta del odontólogo respecto del diagnóstico temprano y tratamiento del SAOS, la solicitud de exámenes complementarios adecuados, sus clasificaciones y medidas terapéuticas asertivas según las peculiaridades del individuo. Como metodología, se realizaron varias búsquedas en las bases de datos SciELO, LILACS, PubMed, MEDLINE y Google Scholar de 1999 a 2023 con los siguientes términos de indexación: Apnea obstructiva del sueño, polisomnografía, diagnóstico, terapia, ronquido, sueño. En este sentido, parece que la Odontología del Sueño es un nuevo campo de actividad para los cirujanos dentistas debido a la posibilidad de realizar tratamientos conservadores, efectivos y rentables favorables para los pacientes a través de aparatos intraorales (AIO) clínicamente fabricados. Por lo tanto, se espera que, en el mediano plazo, el Consejo Federal de Odontología (CFO) la reconozca como especialidad odontológica., A Síndrome da apneia obstrutiva do sono (SAOS) é um distúrbio respiratório crônico, progressivo, incapacitante e com graves repercussões sistêmicas; caracteriza-se por eventos recorrentes de obstrução das vias aéreas superiores (VAS) durante o sono. Desse modo, afeta diretamente na qualidade de vida do indivíduo, uma vez que tal ocorrência causa hipersonolência diurna, sensação de sufocamento ao acordar, falha de memória, impotência sexual, alterações psicológicas como ansiedade e depressão e, ainda, em casos mais severos infarto agudo do miocárdio (IAM), acidente vascular encefálico (AVE), bem como, acidentes automobilísticos, o que, por conseguinte, constitui um problema de saúde pública. O objetivo da presente revisão de literatura é evidenciar a importância do conhecimento e da conduta do cirurgião-dentista acerca do diagnóstico precoce e tratamento da SAOS, da solicitação de exames complementares adequados, das suas classificações e medidas terapêuticas assertivas de acordo com as peculiaridades do indivíduo. Como metodologia, foram realizadas diversas buscas nas bases de dados SciELO, LILACS, PubMed, MEDLINE e Google Scholar no período de 1999 a 2023 com os seguintes termos de indexação: Apneia obstrutiva do sono, polissonografia, diagnóstico, terapêutica, ronco, sono. Nesse viés, constata-se que a Odontologia do Sono é um novo campo de atuação para cirurgiões-dentistas em consequência da possibilidade de tratamentos conservadores, efetivos e com custo-benefício favorável aos pacientes por meio dos aparelhos intraorais (AIO) confeccionados clinicamente. Destarte, espera-se que, a médio prazo, o Conselho Federal de Odontologia (CFO) a reconheça como especialidade odontológica.

The accurate detection of respiratory effort during polysomnographyis a critical element in the diagnosis of sleep-disordered breathing conditions such as sleep apnea. Unfortunately, the sensors currently used to estimate respiratory effort are either indirect and ignore upper airway dynamics or are too obtrusive for patients. One promising alternative is the suprasternal notch pressure (SSP) sensor: a small element placed on the skin in the notch above the sternum within an airtight capsule that detects pressure swings in the trachea. Besides providing information on respiratory effort, the sensor is sensitive to small cardiac oscillations caused by pressure perturbations in the carotid arteries or the trachea. While current clinical research considers these as redundant noise, they may contain physiologically relevant information. We propose a method to separate the signal generated by cardiac activity from the one caused by breathing activity. Using only information available from the SSP sensor, we estimate the heart rate and track its variations, then use a set of tuned filters to process the original signal in the frequency domain and reconstruct the cardiac signal. We also include an overview of the technical and physiological factors that may affect the quality of heart rate estimation. The output of our method is then used as a reference to remove the cardiac signal from the original SSP pressure signal, to also optimize the assessment of respiratory activity. We provide a qualitative comparison against methods based on filters with fixed frequency cutoffs. In comparison with ECG-derived heart rate, we achieve an agreement error of 0.06±5.09bpm, with minimal bias drift across the measurement range, and only 6.36% of the estimates larger than 10bpm. Together with qualitative improvements in the characterization of respiratory effort, this opens the development of novel portable clinical devices for the detection and assessment of sleep disordered breathin

OBJECTIVES: The primary objective was to compare the effect of cognitive behavioural therapy for insomnia (CBT-I) to usual care on sleep efficiency, measured by polysomnography (PSG) immediately after the intervention at week 7. Secondary objectives included comparing the longer-term effect on sleep- and RA-related outcomes at week 26. METHODS: In a randomized controlled trial using a parallel group design, the experimental intervention was 6 weeks' nurse-led group-based CBT-I; the comparator was usual care. Analyses were based on the intention-to-treat (ITT) principle; missing data were statistically modelled using repeated-measures linear mixed effects models adjusted for the level at baseline. RESULTS: The ITT population consisted of 62 patients (89% women), with an average age of 58 years and an average sleep efficiency of 83.1%. At primary end point, sleep efficiency was 88.7% in the CBT-I group, compared with 83.7% in the control group (difference: 5.03 [95% CI -0.37, 10.43]; P = 0.068) measured by PSG at week 7. Key secondary outcomes measured with PSG had not improved at week 26. However, for all the patient-reported key secondary sleep- and RA-related outcomes, there were statistically highly significant differences between CBT-I and usual care (P < 0.0001), e.g. insomnia (Insomnia Severity Index: -9.85 [95% CI -11.77, -7.92]) and the RA impact of disease (RAID: -1.36 [95% CI -1.92, -0.80]) at week 26. CONCLUSION: Nurse-led group-based CBT-I did not lead to an effect on sleep efficiency objectively measured with PSG. However, CBT-I showed improvement on all patient-reported key secondary sleep- and RA-related outcomes measured at week 26. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT03766100.

Sleep deprivation is expected in the intensive care unit (ICU) and is associated with delirium and increased mortality. Polysomnography (PSG) is the gold standard for sleep assessment, but practical issues limit the method. Hence, many ICUs worldwide use subjective sleep assessment (SSA) for sleep monitoring, but the agreement between SSA and PSG is unknown. The hypothesis was that the level of agreement between SSA and PSG was low and that total sleep time (TST) assessed with SSA would be overestimated compared to PSG in this existing cohort database. In this sub-analysis, 30 consecutive study participants underwent 15-h PSG recordings during two consecutive nights. The attending nurse performed an hourly subjective observer rating of sleep quantity during both nights, and the agreement between SSA and PSG was determined along with mean TST. Primary outcome: The level of agreement between SSA and PSG determined by Bland–Altman analysis. Secondary outcome: (1) The overall mean TST estimated by SSA compared to PSG in all study participants enrolled in the main study during both study nights, (2) TST for all study participants evaluated hourly during both study nights, (3) TST assessed with SSA compared to PSG in study participants sedated with dexmedetomidine during the second night and for study participants treated with placebo or non-sedation the first and second nights. The level of agreement between SSA and PSG was low. Mean TST estimated by SSA during the time interval 4.00 p.m. to 7.00 a.m. was 481 min (428;534, 95% CI) vs. PSG at 437 min (386;488, 95% CI) (p =.05). When sedated with dexmedetomidine, TST estimated using SSA was 650 min (571;729, 95% CI) versus PSG which was 588 min (531;645, 95% CI) (p = 0.56). For participants treated with placebo or non-sedation TST estimated with SSA was 397 min (343;450, 95% CI) versus PSG at 362 min (302;422, 95% CI) versus (p = 0.17). In mechanically ventilated critically ill ICU patients, the level of agreement betwe

Background: Abnormal sleep is commonly observed in the ICU and is associated with delirium and increased mortality. If sedation is necessary, it is often performed with gamma-aminobutyric acid agonists such as propofol or midazolam leading to an absence of restorative sleep. We aim to evaluate the effect of dexmedetomidine on sleep quality and quantity. Methods: Thirty consecutive patients were included. The study was conducted as a double-blinded, randomized, placebo-controlled trial with two parallel groups: 20 patients were treated with dexmedetomidine, and 10 with placebo. Two 16 h of polysomnography recordings were done for each patient on two consecutive nights. Patients were randomized to dexmedetomidine or placebo after the first recording, thus providing a control recording for all patients. Dexmedetomidine was administered during the second recording (6 p.m.–6 a.m.). Objective: To compare the effect of dexmedetomidine versus. placebo on sleep - quality and quantity. Primary outcome: Sleep quality, total sleep time (TST), Sleep efficiency (SE), and Rapid Eye Movement (REM) sleep determined by Polysomnography (PSG). Secondary outcome: Delirium and daytime function determined by Confusion Assessment Method of the Intensive Care Unit and physical activity. Alertness and wakefulness were determined by RASS (Richmond Agitation and Sedation Scale). Results: SE were increased in the dexmedetomidine group by; 37.6% (29.7;45.6 95% CI) versus 3.7% (−11.4;18.8 95% CI) (p <.001) and TST were prolonged by 271 min. (210;324 95% CI) versus 27 min. (−82;135 95% CI), (p <.001). No significant difference in REM sleep, delirium physical activity, or RASS score was found except for RASS night two. Conclusion: Total sleep time and sleep efficiency were significantly increased, without elimination of REM sleep, in mechanically ventilated ICU patients randomized to dexmedetomidine, when compared to a control PSG recording performed during non-sedation/standard care.

REM sleep behavior disorder (RBD) is a parasomnia with dream enactment and presence of REM sleep without atonia (RSWA). RBD diagnosed manually via polysomnography (PSG) scoring, which is time intensive. Isolated RBD (iRBD) is also associated with a high probability of conversion to Parkinson's disease. Diagnosis of iRBD is largely based on clinical evaluation and subjective PSG ratings of REM sleep without atonia. Here we show the first application of a novel spectral vision transformer (SViT) to PSG signals for detection of RBD and compare the results to the more conventional convolutional neural network architecture. The vision-based deep learning models were applied to scalograms (30 or 300 second windows) of the PSG data (EEG, EMG and EOG) and the predictions interpreted. A total of 153 RBD (96 iRBD and 57 RBD with PD) and 190 controls were included in the study and 5-fold bagged ensemble was used. Model outputs were analyzed per-patient (averaged), with regards to sleep stage, and the SViT was interpreted using integrated gradients. Models had a similar per-epoch test F1 score. However, the vision transformer had the best per-patient performance, with an F1 score 0.87. Training the SViT on channel subsets, it achieved an F1 score of 0.93 on a combination of EEG and EOG. EMG is thought to have the highest diagnostic yield, but interpretation of our model showed that high relevance was placed on EEG and EOG, indicating these channels could be included for diagnosing RBD.

Machine and deep learning has become one of the most useful tools in the last years as a diagnosis-decision-support tool in the health area. However, it is widely known that artificial intelligence models are considered a black box and most experts experience difficulties explaining and interpreting the models and their results. In this context, explainable artificial intelligence is emerging with the aim of providing black-box models with sufficient interpretability so that models can be easily understood and further applied. Obstructive sleep apnea is a common chronic respiratory disease related to sleep. Its diagnosis nowadays is done by processing different data signals, such as electrocardiogram or respiratory rate. The waveform of the respiratory signal is of importance too. Machine learning models could be applied to the signal's analysis. Data from a polysomnography study for automatic sleep apnea detection have been used to evaluate the use of the Local Interpretable Model-Agnostic (LIME) library for explaining the health data models. Results obtained help to understand how several features have been used in the model and their influence in the quality of sleep.