Non-rapid Eye Movement Sleep Stages Research Articles

NREM sleep brain networks modulate cognitive recovery from sleep deprivation.

Decrease in cognitive performance after sleep deprivation followed by recovery after sleep suggests its key role, and especially non-rapid eye movement (NREM) sleep, in the maintenance of cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during NREM sleep stages N2 and N3 while participants took a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we advance a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. Our results show that network segregation increased in the default mode, dorsal attention and somatomotor networks during NREM sleep compared to wakefulness. Segregation within the visual, limbic, and executive control networks exhibited N2 versus N3 sleep-specific voxel-level patterns. More segregation during N3 was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. The level of spatial resolution of network segregation varied among brain regions and was associated with the recovery of performance in distinct cognitive tasks. We demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

New-Onset Postoperative Atrial Fibrillation and Preoperative Sleep in Cardiac Surgical Patients

BackgroundNew-onset postoperative atrial fibrillation is associated with adverse clinical outcomes in older adults. Poor preoperative sleep quality is a putative modifiable risk factor. The relationships between new-onset postoperative atrial fibrillation and preoperative sleep structure in older adults undergoing elective cardiac surgery were investigated at a single center. MethodsThis was a prespecified substudy within a prospective observational trial of perioperative electroencephalographic markers (ClinicalTrials.gov; NCT03291626). We analyzed preoperative sleep recordings from 71 cardiac surgical patients aged ≥60 years without a prior history of atrial fibrillation. Overnight recordings were acquired using a consumer-grade headband and underwent manual sleep staging. Electroencephalographic slow wave activity (power in the 0.5-4 Hz frequency band) was computed in 1-minute intervals for non-rapid eye movement sleep stages. Associations between new-onset postoperative atrial fibrillation incidence and sleep measures were evaluated using univariate logistic regression models and multivariate logistic regression models including age and sex. ResultsNew-onset postoperative atrial fibrillation was present in 22 of 71 (31%) patients. A higher preoperative percentage of total sleep time in non-rapid eye movement stage 1 was associated with new-onset postoperative atrial fibrillation (median difference of 5.4%, P = .0002, Mann-Whitney U-test), independent of age and sex. No associations were observed between new-onset postoperative atrial fibrillation and other sleep metrics, including slow wave activity (all P > .05, Mann-Whitney U-test). ConclusionsExcess preoperative non-rapid eye movement stage 1 sleep, consistent with greater sleep fragmentation, is a potential modifiable target for mitigating new-onset postoperative atrial fibrillation risk in older adults undergoing elective cardiac surgery requiring cardiopulmonary bypass.

Effects of the low Fowler's sleep position and methazolamide treatment on sleep bruxism: A randomized controlled trial.

Intracranial pressure is one of the determinants of sympathetic activities, and sleep bruxism is associated with increased sympathetic activities. This study aimed to investigate effects of the low Fowler's sleep position and methazolamide treatment on the occurrence of rhythmic masticatory muscle activities/sleep bruxism episodes in patients with sleep bruxism in a randomized controlled trial. Polysomnographic recordings were performed on the patients with sleep bruxism sleeping in the low Fowler's (15°-30°) or supine position (n = 11), and with methazolamide or placebo treatment (100 mg, 3-4 hr before bedtime, P.O., n = 9), and changes in sleep variables and heart rate variance during sleep in the low Fowler's position or with methazolamide treatment were determined. Sleep bruxism index, number of masseter muscle electromyographic bursts per hour of sleep, ratio of rhythmic masticatory muscle activities/sleep bruxism duration to the total sleep duration, index of total limb movements, index of limb movements with rhythmic masticatory muscle activities, and number of sleep bruxism clusters per hour of sleep in the low Fowler's position and after methazolamide intake were significantly smaller (p < 0.05-0.001) than those in the supine position and after placebo intake, respectively. The low-frequency heart rate variance powers during non-rapid eye movement sleep stage 2 (N2) in the low Fowler's position and with methazolamide treatment were significantly lower (p < 0.05) than those during sleep in the supine position and with placebo treatment, respectively. In conclusion, sleep in the low Fowler's position and methazolamide treatment were associated with significant decreases in the occurrence of rhythmic masticatory muscle activities/sleep bruxism episodes, which might be due to a reduction in intracranial pressure and sympathetic activities mainly during non-rapid eye movement sleep stage 2.

Serum levels of neurotensin, pannexin-1, and sestrin-2 and the correlations with sleep quality or/and cognitive function in the patients with chronic insomnia disorder.

To examine serum concentrations of neurotensin, pannexin-1 and sestrin-2, and their correlations with subjective and objective sleep quality and cognitive function in the patients with chronic insomnia disorder (CID). Sixty-five CID patients were enrolled continuously and fifty-six good sleepers in the same period were served as healthy controls (HCs). Serum levels of neurotensin, pannexin-1 and sestrin-2 were measured by enzyme-linked immunosorbent assays. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI) and polysomnography, and mood was evaluated by 17-item Hamilton Depression Rating Scale. General cognitive function was assessed with the Chinese-Beijing Version of Montreal Cognitive Assessment and spatial memory was evaluated by Blue Velvet Arena Test (BVAT). Relative to the HCs, the CID sufferers had higher levels of neurotensin (t=5.210, p<0.001) and pannexin-1 (Z=-4.169, p<0.001), and lower level of sestrin-2 (Z=-2.438, p=0.015). In terms of objective sleep measures, pannexin-1 was positively associated with total sleep time (r=0.562, p=0.002) and sleep efficiency (r=0.588, p=0.001), and negatively with wake time after sleep onset (r=-0.590, p=0.001) and wake time (r=-0.590, p=0.001); sestrin-2 was positively associated with percentage of rapid eye movement sleep (r=0.442, p=0.016) and negatively with non-rapid eye movement sleep stage 2 in the percentage (r=-0.394, p=0.034). Adjusted for sex, age and HAMD, pannexin-1 was still associated with the above objective sleep measures, but sestrin-2 was only negatively with wake time (r=-0.446, p=0.022). However, these biomarkers showed no significant correlations with subjective sleep quality (PSQI score). Serum concentrations of neurotensin and pannexin-1 were positively associated with the mean erroneous distance in the BVAT. Adjusted for sex, age and depression, neurotensin was negatively associated with MoCA score (r=-0.257, p=0.044), pannexin-1 was positively associated with the mean erroneous distance in the BVAT (r=0.270, p=0.033). The CID patients had increased neurotensin and pannexin-1 and decreased sestrin-2 in the serum levels, indicating neuron dysfunction, which could be related to poor sleep quality and cognitive dysfunction measured objectively.

Different heart rate variability profile during sleep in mid-later life adults with remitted early-onset versus late-onset depression

BackgroundIn mid-later life adults, early-onset and late-onset (i.e., onset ≥50 years) depression appear to be underpinned by different pathophysiology yet have not been examined in relation to autonomic function. Sleep provides an opportunity to examine the autonomic nervous system as the physiology changes across the night. Hence, we aimed to explore if autonomic profile is altered in mid-later life adults with remitted early-onset, late-onset and no history of lifetime depression. MethodsParticipants aged 50–90 years (n = 188) from a specialised clinic underwent a comprehensive clinical assessment and completed an overnight polysomnography study. General Linear Models were used to examine the heart rate variability differences among the three groups for four distinct sleep stages and the wake after sleep onset. All analyses controlled for potential confounders – age, sex, current depressive symptoms and antidepressant usage. ResultsFor the wake after sleep onset, mid-later life adults with remitted early-onset depression had reduced standard deviation of Normal to Normal intervals (SDNN; p = .014, d = −0.64) and Shannon Entropy (p = .004, d = −0.46,) than those with no history of lifetime depression. Further, the late-onset group showed a reduction in high-frequency heart rate variability (HFn.u.) during non-rapid eye movement sleep stage 2 (N2; p = .005, d = −0.53) and non-rapid eye movement sleep stage 3 (N3; p = .009, d = −0.55) when compared to those with no lifetime history. LimitationsCausality between heart rate variability and depression cannot be derived in this cross-sectional study. Longitudinal studies are needed to examine the effects remitted depressive episodes on autonomic function. ConclusionThe findings suggest differential autonomic profile for remitted early-onset and late-onset mid-later life adults during sleep stages and wake periods. The differences could potentially serve as peripheral biomarkers in conjunction with more disease-specific markers of depression to improve diagnosis and prognosis.

Electroencephalography-based investigation of the effects of oral desmopressin on improving slow-wave sleep time in nocturnal polyuria patients (the DISTINCT study): A single-arm, open-label, single-assignment trial.

To investigate changes in subjective and objective sleep quality after desmopressin administration in patients with nocturia due to nocturnal polyuria (NP) using electroencephalography (EEG) and the Pittsburgh sleep quality index (PSQI). Twenty male patients (≥65 years old) with NP participated in this study. The inclusion criteria were nocturnal frequency ≥ 2, NP index (NPi) ≥ 0.33, first uninterrupted sleep period (FUSP) ≤ 2.5 h, serum sodium concentration ≥ 135 mEq/L, and estimated glomerular filtration rate ≥ 50 mL/min/1.73 m2. Participants were given 50 μg of desmopressin to be taken orally once daily before bed. The primary endpoint was the change in the duration of slow-wave sleep (nonrapid eye movement sleep stages 3 and 4), as evaluated by EEG 28 days from the baseline. The visual analog scale (VAS) was used as an additional indicator of sleep quality. Analysis of data from 15 participants (median age: 74.0 [70.5, 76.0] years) revealed that from before to after desmopressin administration, significant decreases occurred in the median nocturnal frequency (3.0 [2.0, 4.0] to 1.5 [1.0, 2.0]) and NPi (0.445 [0.380, 0.475] to 0.360 [0.250, 0.430]). Furthermore, FUSP was significantly prolonged from 120.0 (94.0, 150.0) min to 210.0 (203.8, 311.3) min. Although the VAS scores improved, slow-wave sleep duration and the PSQI global score showed no significant differences (68.50 [47.50, 75.50] and 48.00 [38.00, 66.50]; 5.0 [5.0, 10.0] and 7.0 [5.0, 9.0] min, respectively). Oral administration of 50 μg desmopressin improved nocturnal frequency and FUSP in older individuals with NP but did not significantly enhance sleep quality. In older adults, decreased nighttime urinary frequency may enhance quality of life; however, its influence on objective sleep quality may be limited.

Modulation index predicts the effect of ethosuximide on developmental and epileptic encephalopathy with spike-and-wave activation in sleep

PurposeIn developmental and epileptic encephalopathy with spike-and-wave activation in sleep (DEE-SWAS), the thalamocortical network is suggested to play an important role in the pathophysiology of the progression from focal epilepsy to DEE-SWAS. Ethosuximide (ESM) exerts effects by blocking T-type calcium channels in thalamic neurons. With the thalamocortical network in mind, we studied the prediction of ESM effectiveness in DEE-SWAS treatment using phase-amplitude coupling (PAC) analysis. MethodsWe retrospectively enrolled children with DEE-SWAS who had an electroencephalogram (EEG) recorded between January 2009 and September 2022 and were prescribed ESM at Okayama University Hospital. Only patients whose EEG showed continuous spike-and-wave during sleep were included. We extracted 5-min non-rapid eye movement sleep stage N2 segments from EEG recorded before starting ESM. We calculated the modulation index (MI) as the measure of PAC in pair combination comprising one of two fast oscillation types (gamma, 40–80 Hz; ripples, 80–150 Hz) and one of five slow-wave bands (delta, 0.5–1, 1–2, 2–3, and 3–4 Hz; theta, 4–8 Hz), and compared it between ESM responders and non-responders. ResultsWe identified 20 children with a diagnosis of DEE-SWAS who took ESM. Fifteen were ESM responders. Regarding gamma oscillations, significant differences were seen only in MI with 0.5–1 Hz slow waves in the frontal pole and occipital regions. Regarding ripples, ESM responders had significantly higher MI in coupling with all slow waves in the frontal pole region, 0.5–1, 3–4, and 4–8 Hz slow waves in the frontal region, 3–4 Hz slow waves in the parietal region, 0.5–1, 2–3, 3–4, and 4–8 Hz slow waves in the occipital region, and 3–4 Hz slow waves in the anterior-temporal region. SignificanceHigh MI in a wider area of the brain may represent the epileptic network mediated by the thalamus in DEE-SWAS and may be a predictor of ESM effectiveness.

High stability of EEG spectral power across polysomnography and multiple sleep latency tests in good sleepers and chronic insomniacs

To assess the stability of electroencephalographic (EEG) spectral features across overnight polysomnography (PSG) and daytime multiple sleep latency tests (MSLTs) in chronic insomniacs (CIs) and normal controls (NCs). A total of 20 NCs and 22 CIs underwent standard PSG and MSLTs. Spectral analyses were performed on EEG data from PSG and MSLTs and absolute and relative power in central, frontal and occipital channels were obtained for wake (W) and non-rapid eye movement sleep stage 1 and 2 (N1, N2). Intraclass correlation coefficients (ICCs) were used to assess the stability of EEG spectral power across PSG and MSLTs for W, N1 and N2. The absolute power of all frequency bands except delta exhibited high stability across PSG and MSLTs in both NCs and CIs (ICCs ranged from 0.430 to 0.978). Although delta absolute power was stable in NCs during N1 and N2 stages (ICCs ranged from 0.571 to 0.835), it tended to be less stable in CIs during W and sleep stages (ICCs ranged from 0.042 to 0.807). We also observed lower stability of relative power compared to absolute power though the majority of relative power outcomes maintained high stability in both groups (ICCs in relative power ranged from 0.044 to 0.962). Most EEG spectral bandwidths across PSG and MSLT in W, N1 and N2 show high stability in good sleepers and chronic insomniacs. EEG signals from either an overnight PSG or a daytime MSLT may be useful for reliably exploring EEG spectral features during wakefulness or sleep.

Network alterations in temporal lobe epilepsy during non-rapid eye movement sleep and wakefulness

ObjectiveInvestigate sleep and temporal lobe epilepsy (TLE) effects on brain networks derived from electroencephalography (EEG). MethodsHigh-density EEG was recorded during non-rapid eye movement (NREM) sleep stage 2 (N2) and wakefulness in 23 patients and healthy controls (HC). Epochs without epileptic discharges were source-reconstructed in 72 brain regions and connectivity was estimated. We calculated network integration and segregation at global (global efficiency, GE; average clustering coefficient, avgCC) and hemispheric level. These were compared between groups across frequency bands and correlated with the individual proportion of wakefulness- or sleep-related seizures. ResultsAt the global level, patients had higher delta GE, delta avgCC and theta avgCC than controls, irrespective of the vigilance state. During wakefulness, theta GE of patients was higher than controls and, for patients, theta GE during wakefulness was higher than during N2. Wake-to-sleep differences in TLE were notable only in the ipsilateral hemisphere. Only measures from wakefulness recordings correlated with the proportion of wakefulness- or sleep-related seizures. ConclusionsTLE network alterations are more prominent during wakefulness and at lower frequencies. Increased integration and segregation suggest a pathological ‘small world’ configuration with a possible inhibitory role. SignificanceNetwork alterations in TLE occur and are easier to detect during wakefulness.

The Reciprocal Relationship between Sleep and Epilepsy.

The relationship between sleep and epilepsy is bidirectional. Certain epilepsy syndromes predominantly or exclusively manifest during sleep, with seizures frequently originating from non-rapid eye movement (NREM) sleep. Interictal epileptiform discharges observed on electroencephalograms are most likely to be activated during the deep NREM sleep stage known as N3. Conversely, epileptiform discharges, anti-seizure medications (ASMs), as well as other anti-seizure therapies can exert detrimental effects on sleep architecture. Moreover, the co-occurrence of sleep disorders has the potential to exacerbate seizure control. Understating the relationship between sleep and epilepsy is crucial for healthcare providers. Addressing and managing sleep-related problems in individuals with epilepsy can potentially contribute to improved seizure control and overall well-being. At the same time, improving seizure control can improve sleep quality and quantity, thus further improving the health of individuals with epilepsy.

Dynamic Sleep Architecture Revealed: Sleep Auditory Evoked Potentials from N100 to P900

Background: The research landscape in sleep is currently shifting toward minute changes in brain functioning during different stages. This fine approach necessitates a dynamic assessment as in the case of electrophysiology. The present study aimed to investigate brain responsiveness during different stages and times of nocturnal sleep using auditory evoked potentials (AEPs). Materials and Methods: Sleep recordings of 18 volunteer subjects were analyzed. During sleep recordings, auditory stimuli were presented in the ear channels. Sleep stages were scored according to the American Academy of Sleep Medicine system. AEPs were analyzed in nonrapid eye movement sleep stages. Alterations of N100, P200, N300, P450, N550, and P900 waveforms were investigated in the first and second halves of sleep duration. Results: N100 amplitude was higher in light sleep, both in the first and the second halves of the night (sleep duration). The amplitude of P900 was higher in the deep sleep stage in both halves. Significant amplitude reductions were found in N100, P200, P450, and P900 in the second half of the sleep. Conclusions: The changes found suggest that they are related to the dynamics of sensory processing to maintain functional sleep. The findings of the present study emphasize that in the course of sleep, both the proportions of sleep stages and the microarchitecture within the stages alter between the first and second halves of sleep.

Seizures and electrophysiological features in familial cortical myoclonic tremor with epilepsy 1.

To investigate and characterize epileptic seizures and electrophysiological features of familial cortical myoclonic tremor with epilepsy (FCMTE) type 1 patients in a large Chinese cohort. We systematically evaluated 125 FCMTEtype 1 patients carrying the pentanucleotide (TTTCA) repeat expansion in the SAMD12 gene in China. Among the 28 probands, epileptic seizures (96.4%, 27/28) were the most common reason for an initial clinic visit. Ninety-seven (77.6%, 97/125) patients had experienced seizures. The seizures onset age was 36.5 ± 9.0 years, which was 6.9 years later than cortical tremors. The seizures were largely rare (<1/year, 58.8%) and occasional (1-6/year, 37.1%). Prolonged prodromes were reported in 57.7% (56/97). Thirty-one patients (24.8%, 31/125) reported photosensitivity history, and 79.5% (31/39) had a photoparoxysmal response. Interictal epileptiform discharges (IEDs) were recorded in 69.1% (56/81) of patients. Thirty-three patients showed generalized IEDs and 72.7% (24/33) were occipitally dominant, while 23 patients presented with focal IEDs with 65.2% (15/23) taking place over the occipital lobe. Overnight EEG of FCMTE patients displayed paradoxical sleep-wake fluctuation, with a higher average IED index of 0.82 ± 0.88/min during wakefulness and a lower IED index of 0.04 ± 0.06/min during non-rapid eye movement sleep stages I-II. FCMTE type 1 has a benign course of epilepsy and distinct clinical and electrophysiological features. In addition to a positive family history and cortical myoclonus tremor, the seizure prodromes, specific seizure triggers, photosensitivity, distribution of IEDs, and unique fluctuations during sleep-wake cycle are cues for proper genetic testing and an early diagnosis of FCMTE.

Effect of sleep deprivation and NREM sleep stage on physiological brain pulsations.

Sleep increases brain fluid transport and the power of pulsations driving the fluids. We investigated how sleep deprivation or electrophysiologically different stages of non-rapid-eye-movement (NREM) sleep affect the human brain pulsations. Fast functional magnetic resonance imaging (fMRI) was performed in healthy subjects (n = 23) with synchronous electroencephalography (EEG), that was used to verify arousal states (awake, N1 and N2 sleep). Cardiorespiratory rates were verified with physiological monitoring. Spectral power analysis assessed the strength, and spectral entropy assessed the stability of the pulsations. In N1 sleep, the power of vasomotor (VLF < 0.1 Hz), but not cardiorespiratory pulsations, intensified after sleep deprived vs. non-sleep deprived subjects. The power of all three pulsations increased as a function of arousal state (N2 > N1 > awake) encompassing brain tissue in both sleep stages, but extra-axial CSF spaces only in N2 sleep. Spectral entropy of full band and respiratory pulsations decreased most in N2 sleep stage, while cardiac spectral entropy increased in ventricles. In summary, the sleep deprivation and sleep depth, both increase the power and harmonize the spectral content of human brain pulsations.

The effects of hypercortisolism on the frequency and magnitude of sleep EEG waves in patients with Cushing syndrome: A spectral analysis study

ObjectivesOur aim was to investigate the effects of endogenous chronic hypercortisolism on sleep electroencephalogram (EEG) and differences between the adrenocorticotropic hormone (ACTH)-dependent and independent Cushing Syndrome (CS) patients through a sleep spectral analysis program. MethodsA total of 32 patients diagnosed as having endogenous CS (12 ACTH-dependent and 20 ACTH-independent) and a control group comprising 16 healthy individuals were included in the study. Polysomnographic analysis was performed. Blood samples were collected at 08:00 AM for analysis of ACTH and basal cortisol, and at 00:00 AM for midnight cortisol levels. The frequency and power of the slow wave activity (SWA), theta, alpha, and beta waves of the first and last non-rapid eye movement (NREM) cycles were measured with a spectral analysis program. ResultsThe CS patient group had higher SWA power, especially in the first NREM cycle. In the ACTH-dependent group, SWA maximum and mean power values were higher in the frontal channels in the first NREM, compared to the last NREM sleep stage (p<0.05). ConclusionCortisol has been found to be associated with SWA waves, making these waves higher in power, especially in the first NREM phase. This difference was much less pronounced in the final NREM sleep stage. The difference between the first and last NREM sleep stages with respect to the power of SWA in the frontal channel in the ACTH-dependent group suggests that not only cortisol but also high levels of ACTH affect the power of slow waves during sleep.

Deep-learning detection of mild cognitive impairment from sleep electroencephalography for patients with Parkinson's disease.

Parkinson's disease which is the second most prevalent neurodegenerative disorder in the United States is a serious and complex disease that may progress to mild cognitive impairment and dementia. The early detection of the mild cognitive impairment and the identification of its biomarkers is crucial to support neurologists in monitoring the progression of the disease and allow an early initiation of effective therapeutic treatments that will improve the quality of life for the patients. In this paper, we propose the first deep-learning based approaches to detect mild cognitive impairment in the sleep Electroencephalography for patients with Parkinson's disease and further identify the discriminative features of the disease. The proposed frameworks start by segmenting the sleep Electroencephalography time series into three sleep stages (i.e., two non-rapid eye movement sleep-stages and one rapid eye movement sleep stage), further transforming the segmented signals in the time-frequency domain using the continuous wavelet transform and the variational mode decomposition and finally applying novel convolutional neural networks on the time-frequency representations. The gradient-weighted class activation mapping was also used to visualize the features based on which the proposed deep-learning approaches reached an accurate prediction of mild cognitive impairment in Parkinson's disease. The proposed variational mode decomposition-based model offered a superior accuracy, sensitivity, specificity, area under curve, and quadratic weighted Kappa score, all above 99% as compared with the continuous wavelet transform-based model (that achieved a performance that is almost above 92%) in differentiating mild cognitive impairment from normal cognition in sleep Electroencephalography for patients with Parkinson's disease. In addition, the features attributed to the mild cognitive impairment in Parkinson's disease were demonstrated by changes in the middle and high frequency variational mode decomposition components across the three sleep-stages. The use of the proposed model on the time-frequency representation of the sleep Electroencephalography signals will provide a promising and precise computer-aided diagnostic tool for detecting mild cognitive impairment and hence, monitoring the progression of Parkinson's disease.

1036 Traumatic Complications of Unrecognized Somnambulance in a Pediatric Patient

Abstract Introduction Parasomnias are unusual, disruptive, and abnormal verbal or motor events that occur during sleep or between wake and sleep transitions. They can occur in non-rapid eye movement (NREM) or rapid eye movement (REM) sleep stages. NREM parasomnias are typically more prevalent in pediatric populations. One such NREM parasomnia is sleep walking or somnambulance. One study estimates somnambulance has a prevalence of 17% in ages 3-13 years¹. Somnambulance typically occurs during stage 3 sleep which is clustered in the first half of sleep when REM is less prevalent Report of case(s) A 4-year-old previously healthy male presented to clinic for a somnambulance consult. Around 6 months prior, his parents awoke around 3 AM to check on their crying infant, a sibling of our patient, and noticed the patient was missing. They noticed the back door open. Two blocks away they saw police lights and found he had been hit by a vehicle. He was admitted to the hospital for polytrauma, including bilateral pulmonary contusions with acute respiratory failure, grade 4 liver and kidney lacerations, grade 3 adrenal injury, and right parietal lobe parenchymal and subarachnoid hemorrhages. He was later discharged in stable condition with persistent but improved spasticity, impaired mobility, and cognition. His parents had not noticed any prior episodes of somnambulance. However, they did report other frequent parasomnias: somniloquy and confusional arousals. These episodes were worse following late evenings. There was a strong family history of somnambulance in the parent’s siblings. They denied any sleep disordered breathing symptoms. Parents were reassured and educated about parasomnia's self-limited nature but to keep a safe environment and avoid sleep deprivation. Conclusion The majority of parasomnia in children have benign outcomes and eventual self-resolution with age. However, rare circumstances arise where these events can be hazardous including sleep-cooking, risking fire and burns or, as in this case, unknowingly walking into traffic. A sleep study is not always needed as parasomnias are a clinical diagnosis. However, it’s important to note that if a patient has a history of parasomnias parents should be educated on the importance of keeping a safe environment to prevent possible harm. Support (if any)

Associations Between Systemic Inflammatory Markers Based on Blood Cells and Polysomnographic Factors in Obstructive Sleep Apnea.

Systemic inflammation plays a key role in the pathogenesis of obstructive sleep apnea (OSA); however, easy-to-use methods to evaluate the severity of systemic inflammation have yet to be developed. This study investigated the association between systemic inflammation markers that could be derived from the complete blood count (CBC) profile and sleep parameters in a large number of patients with OSA. Patients who visited our hospital's Otorhinolaryngology Sleep Clinic between January 2017 and April 2022 underwent polysomnography and routine laboratory tests, including a CBC. Associations between three systemic inflammatory markers-the systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR)-and polysomnographic and demographic factors including age, sex, body mass index, the apnea-hypopnea index (AHI), the hypopnea index (HI), lowest oxygen saturation (%), the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale, and percentages of non-rapid eye movement (REM) sleep stage 3, REM sleep, and snoring time were analyzed. The inflammation markers were compared among OSA subgroups, and associations were also analyzed in subgroups with different OSA severities. In total, 1,102 patients (968 men and 134 women) were included, and their mean AHI was 33.0±24.3. PSQI was significantly associated with SII (P=0.027). No independent significant factors were identified for the NLR or PLR. Within the simple snoring and mild OSA subgroups, no significant association was found between sleep parameters and the SII. In the severe OSA subgroup, the AHI (P=0.004) and PSQI (P=0.012) were independently associated with the SII. Our study analyzed systemic inflammatory markers based on the CBC, a simple, relatively cost-effective test, and showed that the AHI and SII were significantly correlated only in the severe OSA subgroup.

Effects of demographic and sleep-related factors on snoring sound parameters

ObjectiveTo investigate the effect of frequently reported between-individual (viz., age, gender, body mass index [BMI], and apnea-hypopnea index [AHI]) and within-individual (viz., sleep stage and sleep position) snoring sound-related factors on snoring sound parameters in temporal, intensity, and frequency domains. MethodsThis study included 83 adult snorers (mean ± SD age: 42.2 ± 11.3 yrs; male gender: 59%) who underwent an overnight polysomnography (PSG) and simultaneous sound recording, from which a total of 131,745 snoring events were extracted and analyzed. Data on both between-individual and within-individual factors were extracted from the participants’ PSG reports. ResultsGender did not have any significant effect on snoring sound parameters. The fundamental frequency (FF; coefficient = −0.31; P = 0.02) and dominant frequency (DF; coefficient = −12.43; P < 0.01) of snoring sounds decreased with the increase of age, and the second formant increased (coefficient = 22.91; P = 0.02) with the increase of BMI. Severe obstructive sleep apnea (OSA; AHI ≥30 events/hour), non-rapid eye movement sleep stage 3 (N3), and supine position were all associated with more, longer, and louder snoring events (P < 0.05). Supine position was associated with higher FF and DF, and lateral decubitus positions were associated with higher formants. ConclusionsWithin the limitations of the current patient profile and included factors, AHI was found to have greater effects on snoring sound parameters than the other between-individual factors. The included within-individual factors were found to have greater effects on snoring sound parameters than the between-individual factors under study.

Effects of CPAP treatment on electroencephalographic activity in patients with obstructive sleep apnea syndrome during deep sleep: Preliminary findings of a cross-sectional study.

Study objectives: To investigate whether electroencephalographic (EEG) activities during non-rapid eye movement sleep stage 3 (N3) in obstructive sleep apnea syndrome (OSAS) patients were changed with continuous positive airway pressure (CPAP) treatment.Methods: A cross-sectional study of EEG activity during N3 sleep was conducted in 15 patients with moderate to severe OSAS without and with CPAP treatment compared to 15 normal controls. The amplitude, and absolute and relative power of delta, theta, alpha and beta waves as well as the absolute power ratio of slow to fast EEG waves (i.e., absolute power of delta and theta waves/absolute power of alpha and beta waves) and the spectral power density of 0-30Hz EEG activities were analyzed.Results: CPAP significantly increased N3 sleep, the absolute and relative powers, amplitudes of delta and theta waves, and absolute power ratio of slow to fast EEG waves, but decreased relative alpha and beta powers during N3 sleep. However, there were no significant differences in those parameters between the OSAS patients with CPAP treatment and normal controls.Conclusions: CPAP prolongs N3 sleep and increases the power and amplitude of slow EEG waves during N3 sleep, which indicates an improvement in sleep quality and further provides evidence for recommendation of CPAP treatment for OSAS patients.

Fast Sleep Stage Classification Using Cascaded Support Vector Machines with Single-Channel EEG Signals.

Long-term sleep stage monitoring is very important for the diagnosis and treatment of insomnia. With the development of wearable electroencephalogram (EEG) devices, we developed a fast and accurate sleep stage classification method in this study with single-channel EEG signals for practical applications. The original sleep recordings were collected from the Sleep-EDF database. The wavelet threshold denoising (WTD) method and wavelet packet transformation (WPT) method were applied as signal preprocessing to extract six kinds of characteristic waves. With a comprehensive feature system including time, frequency, and nonlinear dynamics, we obtained the sleep stage classification results with different Support Vector Machine (SVM) models. We proposed a novel classification method based on cascaded SVM models with various features extracted from denoised EEG signals. To enhance the accuracy and generalization performance of this method, nonlinear dynamics features were taken into consideration. With nonlinear dynamics features included, the average classification accuracy was up to 88.11% using this method. In addition, with cascaded SVM models, the classification accuracy of the non-rapid eye movement sleep stage 1 (N1) was enhanced from 41.5% to 55.65% compared with the single SVM model, and the overall classification time for each epoch was less than 1.7 s. Moreover, we demonstrated that it was possible to apply this method for long-term sleep stage monitor applications.