Sleep Stages Research Articles

Rapid eye movement (REM)-related obstructive sleep apnea and hypertension: insights from the clinical spectrum of apnea-hypopnea index ratios across REM and non-REM sleep stages in a Chinese cohort.

Previous studies have linked sleep-disordered breathing during rapid eye movement (REM) sleep to hypertension. However, no standardised definition of REM-related obstructive sleep apnea (REM-OSA) exists. This study aimed to evaluate whether the ratio of the apnea-hypopnea index (AHI) in REM to that in non-REM (NREM) (REM-AHI/NREM-AHI) accurately identifies patients with OSA comorbid with hypertension. We screened 1439 participants and included 790 patients with OSA. REM-OSA was defined as AHI ≥5 events/h, REM-AHI/NREM-AHI ≥2, and REM stage ≥30 min. Differences between REM-OSA and NREM-OSA groups, and among quartiles of REM-AHI/NREM-AHI, were assessed. The impact of REM-AHI/NREM-AHI on hypertension was assessed by logistic regression and restricted cubic spline analysis. Overall, patients with REM-OSA, as traditionally defined, had a lower hypertension prevalence, lower blood pressure, and milder OSA. Patients with REM-AHI/NREM-AHI <2 but a higher total AHI had a higher prevalence of hypertension. The highest REM-AHI/NREM-AHI quartile had the mildest OSA and the lowest hypertension prevalence. In subgroups restricted by total AHI or NREM-AHI, a similar trend existed, suggesting that total AHI appeared more influential on hypertension than the predominance of REM-AHI. Restricted cubic spline analysis certified a non-linear relationship between REM-AHI/NREM-AHI and total AHI, blood pressure and hypertension prevalence. Our research showed that patients with REM-OSA defined by REM-AHI/NREM-AHI ≥2 are not the subgroup with the highest hypertension prevalence within the entire OSA population. It is important to avoid focusing solely on the REM-AHI/NREM-AHI ratio and overlooking the overall severity of OSA, which could lead to missing groups that also have a high prevalence of hypertension.

Illnesses and sleep deprivation

Introduction: Sleep is defined on the basis of behavioural and physiological criteria dividing it into two states : non rapid eye movement (NREM) sleep which is subdivided into three stages (N1,N2,N3) abs rapid eye movement (REM) sleep characterized by rapid eye movements, muscle atonia and desynchronized EEG [1]. The most important step in assessing a patient with a sleep complaint is obtaining a detailed history including family and previous histories. Material and Methods: There were analyzed articles from PubMed database from the last 5 years 2019-2024, mentioned such words as “illnesses”, “sleep deprivation” [2]. As well as scientific works that have not lost their relevance today [3-6]. Results: For example, critically ill patients frequently experience poor sleep, characterized by frequent disruptions, loss of circadian rhythms and pancity of time spent in restorative sleep stages. Factors that are associated with sleep stages. One of them is critical condition in the intensive care unit ICU include patient-ventilator dyssynchrony, medications, patient care and interactions environmental noise and light [ 7-24]. Along with ICU patients, also medical human resources ICU suffer from sleep disorders due to psycho-emotional burnout (PEB) [25] and chronic fatigue syndrome [7], sometimes not different from wartime PEB [ 26]. Conclusion: Sleep disturbance during intensive care unit admission is common. Sleep disturbance has been observed in survivors of critical illness even after transfer out of the ICU. Sleep disturbance is common in critically ill patients up to 12 months after hospital discharge. Like, and medical human resources ICU, may suffer from sleep problems throughout their lives.

Detecting sleep and physical activity changes across the perinatal period using wearable technology

BackgroundPregnant women may not experience disruptions in sleep duration throughout the course of pregnancy, however, their sleep quality is dramatically impaired. Sleep quality deteriorates throughout pregnancy, reaching its lowest in the third trimester. The purpose of this study was to understand the change in sleep patterns across the perinatal period, as well as the impact of physical activity on sleep.MethodsA total of 18 physically active women trying to conceive wore a WHOOP strap (a fitness monitor) across the perinatal period. Daily behavior changes were tracked including time awake, hours in deep sleep, physical activity, and time in moderate to vigorous physical activity.ResultsWomen maintained overall physical activity levels during and after pregnancy and averaged 20.70 min of physical activity and 6.97 h of sleep per day. Total time in awake hours increased postpartum. Moderate-vigorous physical activity minutes improved deep sleep hours overall (Est. = 0.003 h, p < 0.0001) and during pregnancy (Est. = 0.00001 h, p = 0.0004). Similar effects were found for all activity minutes, although in post pregnancy the moderating impact of activity minutes no longer maintained significance (p = 0.09).\\.ConclusionsWearable technology, including fitness monitors such as WHOOP straps offer a convenient and less invasive way to track sleep and physical activity during the perinatal period. The findings of this study indicate a positive connection between sleep and engaging in moderate to vigorous activity and any activity throughout the perinatal period. These results may help inform clinical and practical recommendations for physical activity to improve sleep outcomes for pregnant women.

O013 Sleep and overnight emotional memory in older adults with depression: A high-density EEG investigation

Abstract Older adults with depression have a high incidence of sleep disturbance which is posited to be mechanistically involved in maladaptive overnight emotional memory consolidation. In older adults (≥ 50 years) with and without depression, we aimed to compare group differences in overnight emotional memory and rapid eye movement (REM) and non-rapid eye movement (NREM) (N2 and N3) sleep disturbance. Secondly, we investigated the relationship between emotional memory consolidation, self-report emotional valence and arousal perception, and sleep disturbance. Participants underwent overnight PSG with high-density EEG. An emotional memory image task with concurrent subjective emotional arousal and valence rating was completed before and after sleep. REM sleep disturbance was measured by REM sleep duration, global REM gamma and alpha activity and REM EEG arousal index. NREM sleep disturbance was measured by NREM sleep duration, global NREM delta, alpha and sigma power, and NREM EEG arousal index. T-tests and non-parametric tests were used for group comparisons. Linear regressions were used to assess relationships between sleep disturbance and emotional memory. Twenty-two older adults (Depression: n = 12, Control: n = 10) with a mean age of 63.7 ± 6.5 years completed the study. Older adults with depression demonstrated differences in overnight perception of emotional valence and arousal for negative information, suggesting sleep may be involved in emotion perception. Global delta power in NREM was reduced in older adults with depression, suggestive of homeostatic alterations. However, no robust associations between overnight memory consolidation, emotional valence or arousal and REM or NREM sleep disturbance were observed.

Infraslow noradrenergic locus coeruleus activity fluctuations are gatekeepers of the NREM-REM sleep cycle.

The noradrenergic locus coeruleus (LC) regulates arousal levels during wakefulness, but its role in sleep remains unclear. Here, we show in mice that fluctuating LC neuronal activity partitions non-rapid-eye-movement sleep (NREMS) into two brain-autonomic states that govern the NREMS-REMS cycle over ~50-s periods; high LC activity induces a subcortical-autonomic arousal state that facilitates cortical microarousals, whereas low LC activity is required for NREMS-to-REMS transitions. This functional alternation regulates the duration of the NREMS-REMS cycle by setting permissive windows for REMS entries during undisturbed sleep while limiting these entries to maximally one per ~50-s period during REMS restriction. A stimulus-enriched, stress-promoting wakefulness was associated with longer and shorter levels of high and low LC activity, respectively, during subsequent NREMS, resulting in more microarousal-induced NREMS fragmentation and delayed REMS onset. We conclude that LC activity fluctuations are gatekeepers of the NREMS-REMS cycle and that this role is influenced by adverse wake experiences.

Does keto make the difference? A comprehensive review of its impact on physical activity, cognitive function and hormonal balance.

Introduction: The ketogenic diet, characterized by high fat and low carbohydrate intake, has become increasingly popular among athletes and fitness enthusiasts due to its potential for supporting weight loss and enhancing metabolic health. This study aims to analyze the impact of the keto diet on physical and cognitive performance, as well as to understand the mechanisms and challenges associated with its use. Materials and methods: A systematic review of available studies was conducted through extensive searches in databases such as PubMed, NCBI, and Google Scholar. State of knowledge: The ketogenic diet can be beneficial in endurance sports by improving fat utilization as an energy source and increasing energy stability, but its impact on aerobic capacity and time to exhaustion varies. In strength sports that require intense effort, carbohydrate restriction can negatively affect strength and muscle mass development, as glycogen is a key energy source in such activities. The ketogenic diet does not provide full benefits in high-intensity sports, such as sprints or team sports, due to limited glycogen availability. The ketogenic diet can improve body composition and metabolic efficiency in athletes, but its impact on performance depends on individual responses, and the adaptation process may involve challenges such as "keto flu." Ketogenic diet may positively impact mental health by reducing symptoms of anxiety and depression. Additionally, it may enhance sleep quality, particularly by supporting deep sleep, and potentially increase testosterone production. Conclusions: The ketogenic diet can benefit endurance sports by improving fat oxidation and sustaining energy levels, though its effectiveness in high-intensity, glycogen-dependent activities is less certain. Strategies like TKD or CKD, along with performance monitoring, can help athletes optimize results.

NREM sleep improves behavioral performance by desynchronizing cortical circuits.

Sleep improves cognitive performance, yet little is known about the neural mechanisms of this improvement. We performed multielectrode recording in macaque visual and dorsolateral prefrontal cortex while animals performed a visual discrimination task before and after non-rapid eye movement (NREM) sleep. Although sleep induces synchronized fluctuations in population activity across cortical areas, the post-sleep population activity became more desynchronized relative to the pre-sleep state. The changes after sleep were correlated with an increase in information encoded in population activity in each area and improved behavioral performance. Electrically stimulating visual cortex at 4 hertz emulated the beneficial effects of sleep on network and perceptual performance. A large-scale neural network model indicated that asymmetric depression of local intracortical synapses is consistent with the observed changes in neural activity after sleep.

Gong’s acupuncture treatment for mid pregnancy insomnia and anxiety: A case report

Rationale: Gong’s brain acupuncture (GBA) is a acupuncture technique that restores the balance of the central nervous system by stimulating specific acupoints on the skull to transmit stimulation to the nerves. Insomnia during pregnancy is an increasingly concerning issue, and GBA provides new solutions. Patient’s concerns: The patient, a 26-year old woman at 26 + 1 weeks of pregnancy, presented with unexplained insomnia for 3 weeks. Her symptoms included difficulty initiating sleep, light sleep, and intermittent wakefulness throughout the night. Diagnoses: The patient was diagnosed with primary insomnia, scoring 16 on the Pittsburgh sleep quality index, which indicates poor sleep quality. Her self-rating anxiety scale (SAS) score was 49 points, suggesting that she had not yet reached a state of mild anxiety. Interventions: The patient received 15 sessions of GBA treatment. Outcomes: One month after treatment completion, the patient’s Pittsburgh sleep quality index score improved to 3 points, indicating good sleep quality. Her self-rating anxiety scale score decreased to 39 points. Lessons: This case report demonstrated the successful treatment of mid pregnancy insomnia with GBA, providing preliminary evidence for further research on the therapeutic potential of GBA. However, further research is still needed to enhance persuasiveness.

Associations between Sleep, Energy Balance and Obesity Markers over 6 Months in Black Emerging Adults - Pilot Study Findings from the Sleep, Health Outcomes and Body Weight (SHOW) Study.

Insufficient sleep (short sleep duration and poor sleep quality) is associated with obesity risk. Emerging adults (ages 18-28 years) have a greater risk of excess weight gain and insufficient sleep, and these risks are higher in Black individuals. Using a measurement burst design, we assessed associations between sleep with energy balance components and obesity marker changes over 6 months in 15 Black emerging adults (12 females; age 21±2.5 years; body mass index 25.7±4.5 kg/m2; body fat 25.8±11.9%). Since our sample was predominantly female (80%), we repeated our analyses for females only. Participants completed the following measurements at baseline (BLN) and 6 months later (6MO): 7 days of actigraphy-based sleep and physical activity energy expenditure (EE) and 2 nights of in-home polysomnography-based sleep; resting EE and thermic effect of food with indirect calorimetry; ad libitum energy intake (EI) via self-reported methods over 4 days and directly measured over 3 days with provided meals. Body weight (2.6 kg, p=0.01) and waist circumference (2.4 cm, p=0.03) increased from BLN to 6MO. Changes in actigraphy-based sleep duration were associated with changes in body weight (β=0.03, Standard error (SE)=0.02, p=0.04) and fat mass (β=0.07, SE=0.03 p=0.03) in females only. Greater rapid eye movement sleep duration was associated with increases in resting EE (β=2.24, SE=0.84, p=0.02). Greater slow-wave sleep was associated with increases in self-reported EI (β=18.34, SE=4.7, p<0.01). Sleep may impact components of energy balance and risk of weight gain in Black emerging adults. Additional research is needed to confirm our pilot findings.

Obstructive sleep apnea in 12 to 24 months old toddlers referred for sleep study in a tertiary care center.

To assess OSA prevalence, comorbidities, and the influence of sleep stages and body positions on respiratory events distribution in toddlers aged 12-24 months. A single center retrospective study that included toddlers aged 12-24 months old who underwent overnight PSG. OSA severity was categorized by obstructive apnea-hypopnea index (OAHI) as mild (1-4.9 events/h), moderate (5-9.9 events/h), and severe (≥ 10 events/h). 283 PSG data were included with a median age of 18 months (IQR 16-20.25) for the OSA group (168/283) and 19 months (IQR 16-22) for the non-OSA group (115/283) (p = 0.047). OSA prevalence was 68.5% (42.3% mild, 18.5% moderate, and 39% severe). 38.1% of children had no comorbidities, 24.4% had a history of prematurity and 11.3% had Down syndrome. Multivariate binominal regression analysis showed that children with history of prematurity (p = 0.017) and Down syndrome (p = 0.043) had higher odds of having OSA. The mean SaO2 in REM sleep was lower, and the mean time spent with oxygen saturation below 90% was higher in children with neuromuscular disease compared to those with other comorbidities. In toddlers without comorbidities, the median REM OAHI was 29.8 events/h (IQR: 58.48), whereas the median non-REM OAHI was 4.1 events/h (IQR: 10.4 p < 0.001). Supine OAHI was 7.9 (IQR: 24.9), and off supine OAHI was 10.5 (IQR: 18.1, p = 0.407). In toddlers aged 12-24 months, history of prematurity and Down syndrome were significantly associated with OSA. Obstructive respiratory events occurred predominantly in REM sleep, and no significant positional relations were noted.

Quantitative Impact of Traditional Open Surgery and Minimally Invasive Surgery on Patients' First-Night Sleep Status in the Intensive Care Unit: Prospective Cohort Study.

The sleep status of patients in the surgical intensive care unit (ICU) significantly impacts their recoveries. However, the effects of surgical procedures on sleep are rarely studied. This study aimed to investigate quantitatively the impact of traditional open surgery (TOS) versus minimally invasive surgery (MIS) on patients' first-night sleep status in a surgical ICU. Patients transferred to the ICU after surgery were prospectively screened. The sleep status on the night of surgery was assessed by the patient- and nurse-completed Richards-Campbell Sleep Questionnaire (RCSQ) and Huawei wearable sleep monitoring wristband. Surgical types and sleep parameters were analyzed. A total of 61 patients were enrolled. Compared to patients in the TOS group, patients in the MIS group had a higher nurse-RCSQ score (mean 60.9, SD 16.9 vs mean 51.2, SD 17.3; P=.03), self-RCSQ score (mean 58.6, SD 16.2 vs mean 49.5, SD 14.8; P=.03), and Huawei sleep score (mean 77.9, SD 4.5 vs mean 68.6, SD 11.1; P<.001). Quantitative sleep analysis of Huawei wearable data showed a longer total sleep period (mean 503.0, SD 91.4 vs mean 437.9, SD 144.0 min; P=.04), longer rapid eye movement sleep period (mean 81.0, 52.1 vs mean 55.8, SD 44.5 min; P=.047), and higher deep sleep continuity score (mean 56.4, SD 7.0 vs mean 47.5, SD 12.1; P=.001) in the MIS group. MIS, compared to TOS, contributed to higher sleep quality for patients in the ICU after surgery.

Low-Frequency Deep Brain Stimulation in Non-Rapid Eye Movement Sleep Modifies Memory Retention in Parkinson's Disease.

Memory impairment is a frequent and debilitating symptom in neurodegenerative disorders. The objective of this study was to provide proof-of-principle that deep brain stimulation during sleep can modify memory consolidation in people with Parkinson's disease depending on the stimulation frequency that is applied. Twenty-four patients with Parkinson's disease who were treated with deep brain stimulation of the subthalamic nucleus were included in this single-blind pilot study. Six patients had to be excluded because of insomnia on the night of testing. Patients were randomized (1:1 ratio) to receiving either low frequency deep brain stimulation (4 Hz) or clinically used high frequency deep brain stimulation (130 Hz) during early non-rapid eye movement (NREM) sleep. The main outcome measure was overnight memory retention as measured by a validated declarative memory task. Patients receiving low frequency deep brain stimulation during early NREM sleep (n = 9, 4 females, mean age 61.1 ± 4.3 years) showed improved overnight memory retention (z = 2.549, P = 0.011). Patients receiving clinically used high frequency deep brain stimulation (n = 9, 2 females, mean age 62.2 ± 7.1) did not show any improvement (z = 1.023, P = 0.306) leading to a significant difference between groups (z = 2.214, P = 0.027). Stronger improvement in memory function was correlated with increased cortical low frequency activity after low frequency deep brain stimulation as measured by electroencephalography (ρ = 0.711, P = 0.037). These results provide proof-of-principle that memory can be modulated by frequency-specific deep brain stimulation during sleep. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Slow oscillation-spindle coupling predicts sequence-based language learning.

Sentence comprehension involves the rapid decoding of both semantic and grammatical information, a process fundamental to communication. As with other complex cognitive processes, language comprehension relies, in part, on long-term memory. However, the electrophysiological mechanisms underpinning the initial encoding and generalisation of higher-order linguistic knowledge remain elusive, particularly from a sleep-based consolidation perspective. One candidate mechanism that may support the consolidation of higher-order language is the temporal coordination of slow oscillations (SO) and sleep spindles during non-rapid eye movement sleep (NREM). To examine this hypothesis, we analysed electroencephalographic (EEG) data recorded from 35 participants (Mage = 25.4, SD = 7.10; 16 males) during an artificial language learning task, contrasting performance between individuals who were given an 8hr nocturnal sleep period or an equivalent period of wake. We found that sleep relative to wake was associated with superior performance for rules that followed a sequence-based word order. Post-sleep sequence-based word order processing was further associated with less task-related theta desynchronisation, an electrophysiological signature of successful memory consolidation, as well as cognitive control and working memory. Frontal NREM SO-spindle coupling was also positively associated with behavioural sensitivity to sequence-based word order rules, as well as with task-related theta power. As such, theta activity during retrieval of previously learned information correlates with SO-spindle coupling, thus linking neural activity in the sleeping and waking brain. Taken together, this study presents converging behavioral and neurophysiological evidence for a role of NREM SO-spindle coupling and task-related theta activity as signatures of successful memory consolidation and retrieval in the context of higher-order language learning.Significance statement The endogenous temporal coordination of neural oscillations supports information processing during both wake and sleep states. Here we demonstrate that slow oscillation-spindle coupling during non-rapid eye movement sleep predicts the consolidation of complex grammatical rules and modulates task-related oscillatory dynamics previously implicated in sentence processing. We show that increases in theta power predict enhanced sensitivity to grammatical violations after a period of sleep and strong slow oscillation-spindle coupling modulates subsequent task-related theta activity to influence behaviour. Our findings reveal a complex interaction between both wake- and sleep-related oscillatory dynamics during the early stages of language learning beyond the single word level.

SleepNetZero: Zero-Burden Zero-Shot Reliable Sleep Staging with Neural Networks Based on Ballistocardiograms

SleepNetZero: Zero-Burden Zero-Shot Reliable Sleep Staging with Neural Networks Based on Ballistocardiograms

Stimulation-Evoked Resonant Neural Activity in the Subthalamic Nucleus Is Modulated by Sleep.

Deep brain stimulation is a treatment for advanced Parkinson's disease and currently tuned to target motor symptoms during daytime. Parkinson's disease is associated with multiple nocturnal symptoms such as akinesia, insomnia, and sleep fragmentation, which may require adjustments of stimulation during sleep for best treatment outcome. There is a need for a robust biomarker to guide stimulation titration across sleep stages. This study aimed to investigate whether evoked resonant neural activity (ERNA) is modulated by sleep. We recorded local field potentials from the subthalamic nucleus of four Parkinson's patients with externalized electrodes while applying single stimulation pulses to investigate the effect of sleep on ERNA. We found that ERNA features change with wakefulness and sleep stages and are correlated with canonical frequency bands and heart rate. Given that ERNA modulates with sleep, it could be used as a robust marker for automatic stimulation titration during sleep. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Thalamic spindles and Up states coordinate cortical and hippocampal co-ripples in humans.

In the neocortex, ~90 Hz ripples couple to ~12 Hz sleep spindles on the ~1 Hz Down-to-Up state transition during non-rapid eye movement sleep. This conjunction of sleep waves is critical for the consolidation of memories into long-term storage. The widespread co-occurrences of ripples ("co-ripples") may integrate information across the neocortex and hippocampus to facilitate consolidation. While the thalamus synchronizes spindles and Up states in the cortex for memory, it is not known whether it may also organize co-ripples. Using human intracranial recordings during NREM sleep, we investigated whether cortico-cortical co-ripples and hippocampo-cortical co-ripples are either: (1) driven by directly projected thalamic ripples; or (2) coordinated by propagating thalamic spindles or Up states. We found ripples in the anterior and posterior thalamus, with similar characteristics as hippocampal and cortical ripples, including having a center frequency of ~90 Hz and coupling to local spindles on the Down-to-Up state transition. However, thalamic ripples rarely co-occur or phase-lock with cortical or hippocampal ripples. By contrast, spindles and Up states that propagate from the thalamus strongly coordinate co-ripples in the cortex and hippocampus. Thus, thalamo-cortical spindles and Up states, rather than thalamic ripples, may provide input facilitating spatially distributed co-rippling that integrates information for memory consolidation during sleep in humans.

VAEEG: Variational Auto-encoder for Extracting EEG Representation

The electroencephalogram (EEG) exhibits characteristics of complexity and strong randomness. Existing deep learning models for EEG typically target specific objectives and datasets, with their scalability constrained by the size of the dataset, resulting in limited perceptual and generalization abilities. In order to obtain more intuitive, concise, and useful representations of brain activity, we constructed a reconstruction-based self-supervised learning model for EEG based on Variational Autoencoder (VAE) with separate frequency bands, termed variational auto-encoder for EEG (VAEEG). VAEEG achieved outstanding reconstruction performance. Furthermore, we validated the efficacy of the latent representations in three clinical tasks concerning pediatric brain development, epileptic seizure, and sleep stage classification. We discovered that certain latent features: 1) correlate with adolescent brain developmental changes; 2) exhibit significant distinctions in the distribution between epileptic seizures and background activity; 3) show significant variations across different sleep cycles. In corresponding downstream fitting or classification tasks, models constructed based on the representations extracted by VAEEG demonstrated superior performance. Our model can extract effective features from complex EEG signals, serving as an early feature extractor for downstream classification tasks. This reduces the amount of data required for downstream tasks, simplifies the complexity of downstream models, and streamlines the training process.

Differential effects of sleep position and sleep stage on the severity of obstructive sleep apnea.

This study compared the effects of sleeping in the supine position and rapid eye movement sleep on the severity of obstructive sleep apnea, and investigated the effect of sleep stage on position-dependent obstructive sleep apnea, and of sleep position on rapid eye movement-dependent obstructive sleep apnea. We analysed epoch-labelled polysomnographic readouts of 3843 patients, and calculated the apnea-hypopnea index for each sleep position and sleep stage. Subgroup analyses were performed to evaluate whether the proportion of position-dependent obstructive sleep apnea patients changed during rapid eye movement and non-rapid eye movement sleep, and whether that of rapid eye movement-dependent obstructive sleep apnea patients changed during supine/lateral sleep. The apnea-hypopnea index was highest in the rapid eye movement-supine position (50.7 ± 22.6 events per hr), followed by non-rapid eye movement-supine, rapid eye movement-lateral and non-rapid eye movement-lateral (39.2 ± 25.3, 22.9 ± 24.4, 15.9 ± 21.9 events per hr, respectively; p < 0.001). Patients with position-dependent obstructive sleep apnea had a higher ratio of rapid eye movement sleep, and those with rapid eye movement-dependent obstructive sleep apnea had a higher ratio of sleep time in the supine position (p < 0.001). During rapid eye movement sleep, position-dependent obstructive sleep apnea was not observed in 21.1% of patients who otherwise had position-dependent obstructive sleep apnea. In the lateral position, 36.9% of patients with rapid eye movement-dependent obstructive sleep apnea did not retain rapid eye movement dependency. Although sleeping in the supine position and rapid eye movement sleep were both associated with more frequent respiratory events, this was the first study to demonstrate that the former had a stronger correlation with obstructive sleep apnea severity. Position dependency in patients with obstructive sleep apnea decreased during rapid eye movement sleep, and worsening of rapid eye movement dependency was alleviated in the lateral position, suggesting potential for personalized obstructive sleep apnea management.

A Single Night in Hypoxia Either with or without Ketone Ester Ingestion Reduces Sleep Quality Without Impacting Next Day Exercise Performance

ABSTRACT Background Sleeping at altitude is highly common in athletes as an integral part of altitude training camps or sport competitions. However, concerns have been raised due to expected negative effects on sleep quality, thereby potentially hampering exercise recovery and next-day exercise performance. We recently showed that ketone ester (KE) ingestion beneficially impacted sleep following strenuous, late evening exercise in normoxia, and alleviated hypoxemia. Therefore, we hypothesized that KE ingestion may be an effective strategy to attenuate hypox(em)ia-induced sleep dysregulations. Methods Eleven healthy, male participants completed three experimental sessions including normoxic training and subsequent sleep in normoxia or at a simulated altitude of 3,000 m while receiving either KE or placebo post-exercise and pre-sleep. Sleep was evaluated using polysomnography, while next-day exercise performance was assessed through a 30-min all-out time trial (TT30’). Physiological measurements included oxygen status, heart rate variability, ventilatory parameters, blood acid-base balance and capillary blood gases. Results Hypoxia caused a ~3% drop in sleep efficiency, established through a doubled wakefulness after sleep onset and a ~22% reduction in slow wave sleep. KE ingestion alleviated the gradual drop in SpO2 throughout the first part of the night, but did not alter hypoxia-induced sleep dysregulations. Neither KE, nor nocturnal hypoxia affected TT30’ performance, but nocturnal hypoxia hampered heart rate recovery following TT30’. Conclusions We observed that sleeping at 3,000 m altitude impairs sleep efficiency. Although this hypoxia-induced sleep disruption was too subtle to limit exercise performance, we for the first time indicate that sleeping at altitude might impair next-day exercise recovery. KE alleviated nocturnal hypoxemia only when SpO2 values dropped below ~85%, but this did not translate into improved sleep or next-day exercise performance.

The Combination of Topological Data Analysis and Mathematical Modeling Improves Sleep Stage Prediction From Consumer-Grade Wearables.

Wearable devices have become commonplace tools for tracking behavioral and physiological parameters in real-world settings. Nonetheless, the practical utility of these data for clinical and research applications, such as sleep analysis, is hindered by their noisy, large-scale, and multidimensional characteristics. Here, we develop a neural network algorithm that predicts sleep stages by tracking topological features (TFs) of wearable data and model-driven clock proxies (CPs) reflecting the circadian propensity for sleep. To evaluate its accuracy, we apply it to motion and heart rate data from the Apple Watch worn by young subjects undergoing polysomnography (PSG) and compare the predicted sleep stages with the corresponding ground truth PSG records. The neural network that includes TFs and CPs along with raw wearable data as inputs shows improved performance in classifying Wake/REM/NREM sleep. For example, it shows significant improvements in identifying REM and NREM sleep (AUROC/AUPRC improvements >13% and REM/NREM accuracy improvement of 12%) compared with the neural network using only raw data inputs. We find that this improvement is mainly attributed to the heart rate TFs. To further validate our algorithm on a different population, we test it on elderly subjects from the Multi-ethnic Study of Atherosclerosis cohort. This confirms that TFs and CPs contribute to the improvements in Wake/REM/NREM classification. We next compare the performance of our algorithm with previous state-of-the-art wearable-based sleep scoring algorithms and find that our algorithm outperforms them within and across different populations. This study demonstrates the benefits of combining topological data analysis and mathematical modeling to extract hidden inputs of neural networks from puzzling wearable data.