Large Body Movements on Video-Polysomnography are Associated with Daytime Dysfunction in Children with Restless Sleep Disorder

Restless sleep disorder (RSD) is a newly defined sleep related movement disorder characterized by large muscle movements (LMM) in sleep. We examined the sleep study, clinical characteristics, and daytime functioning in children with RSD and compared them to children with Periodic Limb Movement Disorder (PLMD) or Restless Legs Syndrome (RLS). Video polysomnography from 47 children with restless sleep was retrospectively reviewed for LMM and age- and sex- matched to 34 children with PLMD and 12 children with RLS. Data examined included PSG characteristics, ferritin, Pediatric Quality of Life (PedsQL), and Epworth Sleepiness Scores (ESS). Fourteen children met the clinical criteria for RSD with a LMM index of 5 or more per hour of sleep . Mean ESS was elevated in RSD patients compared to either the PLMD or RLS groups though the result did not reach statistical significance (RSD = 10.20 ± 6.81, PLMD = 6.19 ± 4.14, RLS = 6.25 ± 4.90). The PedsQL score was significantly decreased in the RLS group compared to RSD and was reduced overall in all three groups (PedsQL Total RSD= 70.76 ± 18.05, PLMD = 57.05 ± 20.33, RLS = 53.24 ± 16.97). Serum ferritin values were similar in all three groups (RSD= 26.89 ± 10.29, PLMD = 33.91 ± 20.31, RLS = 23.69 ± 12.94 ng/mL, P= NS). Children with RSD demonstrate increased daytime sleepiness compared to PLMD or RLS and all three disease groups decreased quality of life. Further studies are needed to examine long term consequences of RSD.

New uses of Melatonin as a Drug, a Review

Melatonin is a simple compound with a proper chemical name N-acetyl-5-methoxy tryptamine and known as a hormone controlling circadian rhythm. Humans produce melatonin at night which is the reason for sleeping in the night and awakening over the day. Melatonin interacts with melatonin receptors MT1 and MT2 but it was also revealed that melatonin is a strong antioxidant and it also has a role in regulation of cell cycle. Currently, melatonin is used as a drug for some types of sleep disorder but the recent research points to the fact that melatonin can also serve for the other purposes including prophylaxis or therapy of lifestyle diseases, cancer, neurodegenerative disorders and exposure to chemicals. This review summarizes basic facts and direction of the current research on melatonin. The actual literature was scrutinized for the purpose of this review.

A clinical trial to evaluate the dayzz smartphone app on employee sleep, health, and productivity at a large US employer

Sleep deficiency is a hidden cost of our 24–7 society, with 70% of adults in the US admitting that they routinely obtain insufficient sleep. Further, it is estimated that 50–70 million adults in the US have a sleep disorder. Undiagnosed and untreated sleep disorders are associated with diminished health for the individual and increased costs for the employer. Research has shown that adverse impacts on employees and employers can be mitigated through sleep health education and sleep disorder screening and treatment programs. Smartphone applications (app) are increasingly commonplace and represent promising, scalable modalities for such programs. The dayzz app is a personalized sleep training program that incorporates assessment of sleep disorders and offers a personalized comprehensive sleep improvement solution. Using a sample of day workers affiliated with a large institution of higher education, we will conduct a single-site, parallel-group, randomized, waitlist control trial. Participants will be randomly assigned to either use the dayzz app throughout the study or receive the dayzz app at the end of the study. We will collect data on feasibility and acceptability of the dayzz app; employee sleep, including sleep behavioral changes, sleep duration, regularity, and quality; employee presenteeism, absenteeism, and performance; employee mood; adverse and safety outcomes; and healthcare utilization on a monthly basis throughout the study, as well as collect more granular daily data from the employee during pre-specified intervals. Our results will illuminate whether a personalized smartphone app is a viable approach for improving employee sleep, health, and productivity. Trial registration: ClinicalTrials.gov Identifier: NCT04224285.

Sleep Disorders During Pregnancy and Postpartum: A Systematic Review

This study aimed to asses previous research results about bio-physiological alterations during pregnancy and postpartum, and make clear outlook about prevalence and related factors of sleep disorders during pregnancy and postpartum. In this review, the articles that published from 2000 to 2019 were reviewed. Related articles were searched from databases in English language. After evaluation of inclusion and exclusion criteria, articles were chosen and reviewed based on the University of York strategies. Sleep disorders in present study were classified according to the International Classification of Sleep Disorders-3. The search revealed 4449 articles, after evaluating and assessing qualified articles, finally 56 article selected to review. According to the results of this review, The prevalence of sleep disorders was almost 76%–97% in whole pregnancy. The most common sleep disorders included central disorders of hyper somnolence (waking up in the middle of the night, daytime sleepiness, sleeplessness) or insomnia, sleep-related movement disorders (restless legs syndrome), sleep related breathing disorders (obstructive sleep apnea), and parasomnia. In addition, sleep disorder may continue 3–12 months postpartum (33.2%). Sleep disorders induced by physiological processes (fetal movement, excessive weight gain, male sex of the fetus, and multiparty), health-related risks (metabolism disorders, cardiovascular diseases, and mood disorders), and physical or sexual abuse in childhood. In addition, these disorders could have maternal outcomes that can be greatest trigger to postpartum psychiatric disorders and fetal outcomes that have harmful sequences during childhood (sexual, fertility, emotional, and cognitive problems). Health care providers should evaluate the mothers’ sleep quality because sleep disorder leads to harmful consequences in fetuses and children.

A Sleep Stage Classification Algorithm of Wearable System Based on Multiscale Residual Convolutional Neural Network

Sleep disorder is a serious public health problem. Unobtrusive home sleep quality monitoring system can better open the way of sleep disorder-related diseases screening and health monitoring. In this work, a sleep stage classification algorithm based on multiscale residual convolutional neural network (MRCNN) was proposed to detect the characteristics of electroencephalogram (EEG) signals detected by wearable systems and classify sleep stages. EEG signals were analyzed in each epoch of every 30 seconds, and then 5-class sleep stage classification, wake (W), rapid eye movement sleep (REM), and nonrapid eye movement sleep (NREM) including N1, N2, and N3 stages was outputted. Good results (accuracy rate of 92.06% and 91.13%, Cohen’s kappa of 0.7360 and 0.7001) were achieved with 5-fold cross-validation and independent subject cross-validation, respectively, which performed on European Data Format (EDF) dataset containing 197 whole-night polysomnographic sleep recordings. Compared with several representative deep learning methods, this method can easily obtain sleep stage information from single-channel EEG signals without specialized feature extraction, which is closer to clinical application. Experiments based on CinC2018 dataset also proved that the method has a good performance on large dataset and can provide support for sleep disorder-related diseases screening and health surveillance based on automatic sleep staging.

Sleep Quality Improvement Enhances Neuropsychological Recovery and Reduces Blood Aβ42/40 Ratio in Patients with Mild–Moderate Cognitive Impairment

Background and objectives: Alzheimer’s disease is a progressive brain degeneration and is associated with a high prevalence of sleep disorders. Amyloid β peptide-42/40 (Aβ42/40) and Tau-pT181 are the core biomarkers in cerebrospinal fluid and blood. Accumulated data from studies in mouse models and humans demonstrated an aberrant elevation of these biomarkers due to sleep disturbance, especially sleep-disordered breathing (SDB). However, it is not clear if sleep quality improvement reduces the blood levels of Ab42/40 ratio and Tau-pT181 in Alzheimer’s disease patients. Materials and Methods: In this prospective study, a longitudinal analysis was conducted on 64 patients with mild–moderate cognition impairment (MCI) due to Alzheimer’s disease accompanied by SDB. Another 33 MCI cases without sleep-disordered breathing were included as the control group. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) score system. Neuropsychological assessments were conducted using the Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Clinical Dementia Rating (CDR), 24-h Hamilton Rating Scale for Depression (HRSD-24), and Hamilton Anxiety Rating Scale (HAMA) scoring systems. Aβ42, Aβ40, and Tau-pT181 protein levels in blood specimens were measured using ELISA assays. All patients received donepezil treatment for Alzheimer’s disease. SDB was managed with continuous pressure ventilation. Results: A significant correlation was found among PSQI, HRSD-24, HAMA, Aβ42/40 ratio, and Tau-pT181 level in all cases. In addition, a very strong and negative correlation was discovered between education level and dementia onset age. Compared to patients without SDB (33 non-SD cases), patients with SDB (64 SD cases) showed a significantly lower HRSD-24 score and a higher Aβ42/40 ratio Tau-pT181 level. Sleep treatment for patients with SDB significantly improved all neuropsychological scores, Aβ42/40 ratio, and Tau-pT181 levels. However, 11 patients did not completely recover from a sleep disorder (PSQI > 5 post-treatment). In this subgroup of patients, although HAMA score and Tau-pT181 levels were significantly reduced, MoCA and HRSD-24 scores, as well as Aβ42/40 ratio, were not significantly improved. ROC analysis found that the blood Aβ42/40 ratio held the highest significance in predicting sleep disorder occurrence. Conclusions: This is the first clinical study on sleep quality improvement in Alzheimer’s disease patients. Sleep quality score was associated with patient depression and anxiety scores, as well as Aβ42/40 ratio and Tau-pT181 levels. A complete recovery is critical for fully improving all neuropsychological assessments, Aβ42/40 ratio, and Tau-pT181 levels. Blood Aβ42/40 ratio is a feasible prognostic factor for predicting sleep quality.