Shift Work and Sleep Disturbance in the Oil Industry.

BACKGROUND: Rotating shift work is common in high-hazard industries, despite documented associations with sleep disturbance and impairment. In the oil industry, where rotating and extended shift schedules are used to staff safety-sensitive positions, work intensification and increasing overtime rates have been broadly documented over the last few decades. Research on the impacts of these work schedules on sleep and health has been limited for this workforce. METHODS: We examined sleep duration and quality among rotating shift workers in the oil industry and explored associations between schedule characteristics, sleep, and health outcomes. We recruited hourly refinery workers from the West and Gulf Coast oil sector members of the United Steelworkers union. FINDINGS: Impaired sleep quality and short sleep durations were common and associated with health and mental health outcomes common among shift workers. Shortest sleep durations followed shift rotations. Early rise and start times were associated with shorter sleep duration and poorer sleep quality. Drowsiness and fatigue-related incidents were common. CONCLUSION/APPLICATION TO PRACTICE: We observed lower sleep duration and quality and increased overtime in 12-hour rotating shift schedules. These long workdays with early start times may reduce available hours for quality sleep; here they were associated with reduced exercise and leisure activity which correlated with good sleep. This safety-sensitive population appears severely impacted by poor sleep quality, which has broader implications for process safety management. Later start times, slower rotation, and a reconsideration of two-shift schedules are interventions to consider for improving sleep quality among rotating shift workers.

A Holistic Strategy for Classification of Sleep Stages with EEG.

Manual sleep stage scoring is usually implemented with the help of sleep specialists by means of visual inspection of the neurophysiological signals of the patient. As it is a very hectic task to perform, automated sleep stage classification systems were developed in the past, and advancements are being made consistently by researchers. The various stages of sleep are identified by these automated sleep stage classification systems, and it is quite an important step to assist doctors for the diagnosis of sleep-related disorders. In this work, a holistic strategy named as clustering and dimensionality reduction with feature extraction cum selection for classification along with deep learning (CDFCD) is proposed for the classification of sleep stages with EEG signals. Though the methodology follows a similar structural flow as proposed in the past works, many advanced and novel techniques are proposed under each category in this work flow. Initially, clustering is applied with the help of hierarchical clustering, spectral clustering, and the proposed principal component analysis (PCA)-based subspace clustering. Then the dimensionality of it is reduced with the help of the proposed singular value decomposition (SVD)-based spectral algorithm and the standard variational Bayesian matrix factorization (VBMF) technique. Then the features are extracted and selected with the two novel proposed techniques, such as the sparse group lasso technique with dual-level implementation (SGL-DLI) and the ridge regression technique with limiting weight scheme (RR-LWS). Finally, the classification happens with the less explored multiclass Gaussian process classification (MGC), the proposed random arbitrary collective classification (RACC), and the deep learning technique using long short-term memory (LSTM) along with other conventional machine learning techniques. This methodology is validated on the sleep EDF database, and the results obtained with this methodology have surpassed the results of the previous studies in terms of the obtained classification accuracy reporting a high accuracy of 93.51% even for the six-classes classification problem.

Acute mountain sickness and sleep disturbances differentially influence cognition and mood during rapid ascent to 3000 and 4050 m.

The impact of acute mountain sickness (AMS) and sleep disturbances on mood and cognition at two altitudes relevant to the working and tourist population is unknown. Twenty unacclimatized lowlanders were exposed to either 3000 m (n = 10; 526 mmHg) or 4050 m (n = 10; 460 mmHg) for 20 h in a hypobaric chamber. AMS prevalence and severity was assessed using the Environmental Symptoms Questionnaire (ESQ) and an AMS-C score ≥ 0.7 indicated sickness. While sleeping for one night both at sea level (SL) and high altitude (HA), a wrist motion detector was used to measure awakenings (Awak, events/h) and sleep efficiency (Eff, %). If Eff was ≥85%, individuals were considered a good sleeper (Sleep+). Mood and cognition were assessed using the Automated Neuropsychological Assessment Metric and Mood Scale (ANAM-MS). The ESQ and ANAM-MS were administered in the morning both at SL and after 20 h at HA. AMS severity (mean ± SE; 1.82 ± 0.27 vs. 0.20 ± 0.27), AMS prevalence (90% vs. 10%), depression (0.63 ± 0.23 vs. 0.00 ± 0.24) Awak (15.6 ± 1.6 vs. 10.1 ± 1.6 events/h), and DeSHr (38.5 ± 6.3 vs. 13.3 ± 6.3 events/h) were greater (p < 0.05) and Eff was lower (69.9 ± 5.3% vs. 87.0 ± 5.3%) at 4050 m compared to 3000 m, respectively. AMS presence did not impact cognition but fatigue (2.17 ± 0.37 vs. 0.58 ± 0.39), anger (0.65 ± 0.25 vs. 0.02 ± 0.26), depression (0.63 ± 0.23 vs. 0.00 ± 0.24) and sleepiness (4.8 ± 0.4 vs. 2.7 ± 0.5) were greater (p < 0.05) in the AMS+ group. The Sleep- group, compared to the Sleep+ group, had lower (p < 0.05) working memory scores (50 ± 7 vs. 78 ± 9) assessed by the Sternberg 6-letter memory task, and lower reaction time fatigue scores (157 ± 17 vs. 221 ± 22), assessed by the repeated reaction time test. Overall, AMS, depression, DeSHr, and Awak were increased (p < 0.05) at 4050 m compared to 3000 m. In addition, AMS presence impacted mood while poor sleep impacted cognition which may deteriorate teamwork and/or increase errors in judgement at HA.

Sleep Disturbance and Metabolic Dysfunction: The Roles of Adipokines.

Adipokines are a growing group of peptide or protein hormones that play important roles in whole body metabolism and metabolic diseases. Sleep is an integral component of energy metabolism, and sleep disturbance has been implicated in a wide range of metabolic disorders. Accumulating evidence suggests that adipokines may play a role in mediating the close association between sleep disorders and systemic metabolic derangements. In this review, we briefly summarize a group of selected adipokines and their identified function in metabolism. Moreover, we provide a balanced overview of these adipokines and their roles in sleep physiology and sleep disorders from recent human and animal studies. These studies collectively demonstrate that the functions of adipokine in sleep physiology and disorders could be largely twofold: (1) adipokines have multifaceted roles in sleep physiology and sleep disorders, and (2) sleep disturbance can in turn affect adipokine functions that likely contribute to systemic metabolic derangements.

Predictors of dream enactment behavior among medical students: The case of the University of Gondar, Ethiopia.

INTRODUCTION: Dream enactment behavior is one of the features of rapid eye movement sleep behavior disorder. It might be a manifestation of neurodegenerative diseases and can lead to fall associated injuries. There is no evidence of dream enactment behavior and its associated factors in Ethiopia. Hence, this study targeted to pinpoint the predictors of dream enactment behavior among Medical students at the University of Gondar. METHODS: The cross-sectional survey was carried out at the University of Gondar among Medical students selected by simple random sampling technique from Dec 2020 to Feb 2021. We used a structured pretested questionnaire to collect the data and dream enactment behavior was evaluated using rapid eye movement sleep behavior disorder single question. Descriptive statistics were computed, and determinant factors were identified using binary logistic regression model. In the final model, explanatory variables with a p<0.05 were considered as predictors (statistically significant) of the dream enactment behavior. The strength of association was determined using adjusted odds ratio (AOR) with its 95% CI. RESULTS: Four-hundred and twelve students took part in the study with 97.4% response rate. The mean age of participants was 20.82(±1.88) years and 291(70.63%) were males. The prevalence of dream enactment was 34.47% (95% CI: 30.02-39.20). Daytime sleepiness score (AOR = 1.104; 95% CI: 1.053-1.160), age (AOR = 1.15; 95% CI: 1.019-1.290), monthly pocket money (AOR = 0.9991; 95% CI: 0.9985-0.9997), alcohol drink (AOR = 2.71; 95% CI: 1.076-6.846), and perceived stress (AOR = 3.854; 95% CI: 1.802-8.242) were statistically significant factors of dream enactment behavior. CONCLUSIONS: In this study, the magnitude of dream enactment behavior was high which was significantly associated with daytime sleepiness score, age, monthly pocket money, alcohol drink, and perceived stress all of which are modifiable except age. The University of Gondar has to plan a strategy to avert the condition via the prevention of the determinant factors. Students need to reduce stress and avoid alcohol drink. We strongly urge forthcoming scholars to ascertain association of dream enactment and academic performance of university students.

Sympathetic neural responses to sleep disorders and insufficiencies.

Short sleep duration and poor sleep quality are associated with cardiovascular risk, and sympathetic nervous system (SNS) dysfunction appears to be a key contributor. The present review will characterize sympathetic function across several sleep disorders and insufficiencies in humans, including sleep deprivation, insomnia, narcolepsy, and obstructive sleep apnea (OSA). We will focus on direct assessments of sympathetic activation, e.g., plasma norepinephrine and muscle sympathetic nerve activity, but include heart rate variability (HRV) when direct assessments are lacking. The review also highlights sex as a key biological variable. Experimental models of total sleep deprivation and sleep restriction are converging to support several epidemiological studies reporting an association between short sleep duration and hypertension, especially in women. A systemic increase of SNS activity via plasma norepinephrine is present with insomnia and has also been confirmed with direct, regionally specific evidence from microneurographic studies. Narcolepsy is characterized by autonomic dysfunction via both HRV and microneurographic studies but with opposing conclusions regarding SNS activation. Robust sympathoexcitation is well documented in OSA and is related to baroreflex and chemoreflex dysfunction. Treatment of OSA with continuous positive airway pressure results in sympathoinhibition. In summary, sleep disorders and insufficiencies are often characterized by sympathoexcitation and/or sympathetic/baroreflex dysfunction, with several studies suggesting women may be at heightened risk.

Mortality associated with nonrestorative short sleep or nonrestorative long time-in-bed in middle-aged and older adults.

Associations of sleep duration with human health could differ depending on whether sleep is restorative. Using data from 5804 participants of the Sleep Heart Health Study, we examined the longitudinal association of sleep restfulness combined with polysomnography-measured total sleep time (TST) or time in bed (TIB), representing different sleeping behaviors, with all-cause mortality. Among middle-aged adults, compared with restful intermediate TST quartile, the lowest TST quartile with feeling unrested was associated with higher mortality (hazard ratio [HR], 1.54; 95% confidence interval [CI] 1.01-2.33); the highest TST quartile with feeling rested was associated with lower mortality (HR, 0.55; 95% CI 0.32-0.97). Among older adults, the highest TIB quartile with feeling unrested was associated with higher mortality, compared with restful intermediate TIB quartile (HR, 1.57; 95% CI 1.23-2.01). Results suggest a role of restorative sleep in differentiating the effects of sleep duration on health outcomes in midlife and beyond.

Delayed Sleep-Wake Phase Disorder: Can Polysomnography Be Useful?

BACKGROUND: Delayed sleep-wake phase disorder (DSWPD) is a chronic condition with a multifactorial etiology that primarily affects adolescents, significantly influencing their quality of life. In clinical practice, the contribution of intrinsic and behavioral factors is difficult to determine. The aim of our study was to compare data from clinical interviews, sleep diaries, actigraphy, and nocturnal polysomnography (PSG) in a cohort of adolescents with DSWPD and to assess psychiatric/neurodevelopmental comorbidity. METHODS: Thirty-one patients (22 male; mean age 15.4 ± 2.2 years, range 12 to 19 years) with a diagnosis of DSWPD based on detailed history, sleep diary, and actigraphy underwent nocturnal polysomnography (PSG) and neurological, psychological, and psychiatric examination. RESULTS: Attention-deficit/hyperactivity disorder (ADHD) was present in 14 cases (45%), specific learning difficulties in nine (29%), and mood disorder (anxiety/depression) in 16 patients (52%). PSG revealed sleep-onset delay in only 12 (38%) cases. No differences in clinical data or psychiatric comorbidity between the group with sleep delay and the group with normal sleep onset were detected. Decreased total sleep time, sleep efficiency, rapid eye movement (REM) sleep, and prolonged REM sleep latency were observed in patients with delayed sleep onset. CONCLUSIONS: PSG showed delayed sleep timing in only 38% of patients with a diagnosis of DSWPD based on diagnostic criteria of the International Classification of Sleep Disorders. We suggest that PSG can provide useful information regarding the prevailing etiology (biological versus behavioral) if dim light melatonin onset testing is not available.

Effect of Hibiscus syriacus Linnaeus extract and its active constituent, saponarin, in animal models of stress-induced sleep disturbances and pentobarbital-induced sleep.

Treatment of sleep disorders promotes the long-term use of commercially available sleep inducers that have several adverse effects, including addiction, systemic fatigue, weakness, loss of concentration, headache, and digestive problems. Therefore, we aimed to limit these adverse effects by investigating a natural product, the extract of the Hibiscus syriacus Linnaeus flower (HSF), as an alternative treatment. In the electric footshock model, we measured anxiety and assessed the degree of sleep improvement after administering HSF extract. In the restraint model, we studied the sleep rate using PiezoSleep, a noninvasive assessment system. In the pentobarbital model, we measured sleep improvement and changes in sleep-related factors. Our first model confirmed the desirable effects of HSF extract and its active constituent, saponarin, on anxiolysis and Wake times. HSF extract also increased REM sleep time. Furthermore, HSF extract and saponarin increased the expression of cortical GABAA receptor α1 (GABAAR α1) and c-Fos in the ventrolateral preoptic nucleus (VLPO). In the second model, HSF extract and saponarin restored the sleep rate and the sleep bout duration. In the third model, HSF extract and saponarin increased sleep maintenance time. Moreover, HSF extract and saponarin increased cortical cholecystokinin (CCK) mRNA levels and the expression of VLPO c-Fos. HSF extract also increased GABAAR α1 mRNA level. Our results suggest that HSF extract and saponarin are effective in maintaining sleep and may be used as a novel treatment for sleep disorder. Eventually, we hope to introduce HSF and saponarin as a clinical treatment for sleep disorders in humans.

Sleep Problems and Circadian Functioning in Children and Adolescents With Autism Spectrum Disorder.

BACKGROUND: Sleep problems are a prevalent comorbidity in autism spectrum disorder (ASD) with a multifactorial basis in which circadian misalignment has been described. METHODS: A cross-sectional study was conducted including 52 children and adolescents with ASD (9.85 ± 3.07) and 27 children and adolescent controls with normal intellectual functioning (8.81 ± 2.14). They were matched for age, sex, and body mass index, and all were drug-naïve. An ambulatory circadian monitoring device was used to record temperature and motor, body position, sleep, and light intensity. RESULTS: Individuals with ASD presented longer sleep-onset latency, lower sleep efficiency, and decreased total sleep time and tended to be more sedentary and have less exposure to light. They also showed lower amplitude, low interdaily stability, and a different pattern of wrist temperature across the day, with a midpoint of sleep that did not concur with sleep midpoint indicated by the rest of circadian parameters. CONCLUSIONS: The sleep problems observed in this sample resemble those reported previously, with the exception of nocturnal awakenings which did not show differences. The ambulatory circadian monitoring device enabled measurement of circadian parameters such as temperature which, until now, were scarcely described in children with ASD and could be used to better understand sleep and circadian system in ASD.

Cerebellar malfunction and postoperative sleep disturbances after general anesthesia: a narrative review.

The cerebellum is widely regarded as a brain region involved in motor processing, non-motor processing, and even sleep-wake cycles. Cerebellar dysfunction may cause changes in the sleep-wake cycle, leading to sleep disturbances. At present, there is limited research on its effect on postoperative sleep after general anesthesia, despite the suspicion of its implication in postoperative sleep disturbances. With this review, we aim to provide a clear and comprehensive review of the cerebellar activity during the normal sleep-wake cycle, the correlation between cerebellar dysfunction and postoperative sleep disturbances, and the effects of general anesthesia on cerebellar dysfunction. Future large-scale multicenter trials are needed to objectively support the present results, identify the initial cerebellar dysfunction to prevent postoperative sleep disturbances, and develop new therapeutic measures targeting sleep disturbances with possible far-reaching implications for neurodegenerative diseases in general.

A Multicenter Study of Patient Acceptability of the IBD Disk Tool and Patient-Reported Disabilities.

BACKGROUND: IBD, both Crohn's disease and ulcerative colitis, is associated with significant functional disability. Gastrointestinal symptoms alone are not the sole purpose of the interaction between patients and providers. In order to ascertain patients' disabilities, we utilized the recently developed IBD Disk to help determine their functional concerns and initiate relevant conversation. We aimed to ascertain patient acceptability and their major disabilities. PATIENTS AND METHODS: In this multicenter study, IBD patients at their outpatient visit were given the paper version of the IBD Disk. Patients were asked to score their level of disability for each item of the IBD Disk. The completed scores were then shared with their healthcare provider to act as a focus of discussion during the consultation. Patients and clinicians were also asked to provide informal qualitative feedback as to the benefits of the IBD Disk and areas for improvement. RESULTS: A total of 377 (female 60%) patients completed the questionnaires over the study period. Patient acceptability scored on a 0-10 Likert scale was excellent. All patients scored all domains of disability. Sleep, energy, and joint pain were the highest scoring domains of the IBD Disk, scoring higher than digestive symptoms. Clinicians and patients agreed that the IBD Disk allowed for ease of communication about disability symptoms and relevance to their day-to-day functioning. CONCLUSION: The IBD Disk is a novel easy-to-use tool to assess the functional disability of patients. We next plan to utilize it in the form of an electronic app internationally and in relation to treatment commencement and escalation.

Worst Pain Severity Profiles of Oncology Patients Are Associated With Significant Stress and Multiple Co-Occurring Symptoms.

Little is known about the associations between pain, stress, and co-occurring symptoms in oncology patients. Purpose was to identify subgroups of patients with distinct worst pain profiles and evaluate for differences among the subgroups in demographic and clinical characteristics, as well as stress and symptom scores. Oncology outpatients (n = 1305) completed questionnaires prior to their second or third chemotherapy cycle. Worst pain intensity was assessed 6 times over 2 chemotherapy cycles using a 0 to 10 numeric rating scale. The 371 patients (28.4%) who had ≤1 occurrence of pain over the 6 assessments were classified as the None class. For the remaining 934 patients whose data were entered into the latent profile analysis, 3 distinct worst pain profiles were identified (ie Mild [12.5%], Moderate [28.6%], Severe [30.5%]). Compared to None class, Severe class had fewer years of education and a lower annual income; were less likely to be employed and married; less likely to exercise on a regular basis, had a higher comorbidity burden, and a worse functional status. Compared to None class, Severe class reported higher levels of general, disease-specific, and cumulative life stress and lower levels of resilience, as well as higher levels of depressive symptoms, anxiety, fatigue, sleep disturbance, and cognitive dysfunction. This study is the first to identify distinct worst pain profiles in a large sample of oncology patients receiving chemotherapy and associated risk factors. PERSPECTIVE: Unrelieved pain remains a significant problem for oncology patients receiving chemotherapy. High levels of stress and co-occurring symptoms contribute to a more severe pain profile in these patients.

Sleep Disturbance in Individuals at Clinical High Risk for Psychosis.

INTRODUCTION: Disturbed sleep is a common feature of psychotic disorders that is also present in the clinical high risk (CHR) state. Evidence suggests a potential role of sleep disturbance in symptom progression, yet the interrelationship between sleep and CHR symptoms remains to be determined. To address this knowledge gap, we examined the association between disturbed sleep and CHR symptoms over time. METHODS: Data were obtained from the North American Prodrome Longitudinal Study (NAPLS)-3 consortium, including 688 CHR individuals and 94 controls (mean age 18.25, 46% female) for whom sleep was tracked prospectively for 8 months. We used Cox regression analyses to investigate whether sleep disturbances predicted conversion to psychosis up to >2 years later. With regressions and cross-lagged panel models, we analyzed longitudinal and bidirectional associations between sleep (the Pittsburgh Sleep Quality Index in conjunction with additional sleep items) and CHR symptoms. We also investigated the independent contribution of individual sleep characteristics on CHR symptom domains separately and explored whether cognitive impairments, stress, depression, and psychotropic medication affected the associations. RESULTS: Disturbed sleep at baseline did not predict conversion to psychosis. However, sleep disturbance was strongly correlated with heightened CHR symptoms over time. Depression accounted for half of the association between sleep and symptoms. Importantly, sleep was a significant predictor of CHR symptoms but not vice versa, although bidirectional effect sizes were similar. DISCUSSION: The critical role of sleep disturbance in CHR symptom changes suggests that sleep may be a promising intervention target to moderate outcome in the CHR state.

Risk Factors and Brain Metabolic Mechanism of Sleep Disorders in Autoimmune Encephalitis.

Background: Sleep disorders (SDs) in autoimmune encephalitis (AE) have received little attention and are poorly understood. We investigated the clinical characteristics, risk factors, and cerebral metabolic mechanism of SD in AE. Methods: Clinical, laboratory, and imaging data were retrospectively reviewed in 121 consecutively patients with definite AE. The risk factors for SD in AE were estimated by logistic regression analysis. Group comparisons based on 18F-fluorodeoxy-glucose positron emission tomography (18F-FDG-PET) data were made between patients with and without SD, to further analyze potential brain metabolic mechanism of SD in AE. Results: A total of 52.9% patients (64/121) with SD were identified. The multivariate logistic model analysis showed that smoking [odds ratio (OR), 6.774 (95% CI, 1.238-37.082); p = 0.027], increased Hamilton Depression scale (HAMD) score [OR, 1.074 (95% CI, 1.002-1.152); p = 0.045], hyperhomocysteinemia [OR, 2.815 (95% CI, 1.057-7.496); p = 0.038], elevated neuron-specific enolase (NSE) level [OR, 1.069 (95% CI, 1.007-1.135); p = 0.03] were independently correlated with higher risk of SD in AE patients. Contrastingly, high MoCA score [OR, 0.821 (95% CI, 0.752-0.896); p < 0.001] was associated with lower risk of SD in AE subjects. Compared to controls, AE patients had less total sleep time, less sleep efficiency, longer sleep latency, more wake, higher percent of stage N1, lower percent of stage N3 and rapid eye movement, and more arousal index in non-rapid eye movement sleep (p < 0.05 for all). Voxel-based group comparison analysis showed that, compared to patients without SD, patients with SD had increased metabolism in the basal ganglia, cerebellum, brainstem, median temporal lobe, thalamus, and hypothalamus [p < 0.05, false discovery rate (FDR) corrected]; decreased metabolism in superior frontal gyrus, medial frontal gyrus, and posterior cingulate cortex (p < 0.001, uncorrected). These results were confirmed by region of interest-based analysis between PET and sleep quality. Conclusion: Smoking, increased HAMD score, hyperhomocysteinemia, and elevated NSE level were correlated with higher risk of SD. High MoCA score was associated with lower risk of SD in AE subjects. Moreover, a widespread metabolic network dysfunction may be involved in the pathological mechanism of SD in AE.

Automatic Cyclic Alternating Pattern (CAP) analysis: Local and multi-trace approaches.

The Cyclic Alternating Pattern (CAP) is composed of cycles of two different electroencephalographic features: an activation A-phase followed by a B-phase representing the background activity. CAP is considered a physiological marker of sleep instability. Despite its informative nature, the clinical applications remain limited as CAP analysis is a time-consuming activity. In order to overcome this limit, several automatic detection methods were recently developed. In this paper, two new dimensions were investigated in the attempt to optimize novel, efficient and automatic detection algorithms: 1) many electroencephalographic leads were compared to identify the best local performance, and 2) the global contribution of the concurrent detection across several derivations to CAP identification. The developed algorithms were tested on 41 polysomnographic recordings from normal (n = 8) and pathological (n = 33) subjects. In comparison with the visual CAP analysis as the gold standard, the performance of each algorithm was evaluated. Locally, the detection on the F4-C4 derivation showed the best performance in comparison with all other leads, providing practical suggestions of electrode montage when a lean and minimally invasive approach is preferable. A further improvement in the detection was achieved by a multi-trace method, the Global Analysis-Common Events, to be applied when several recording derivations are available. Moreover, CAP time and CAP rate obtained with these algorithms positively correlated with the ones identified by the scorer. These preliminary findings support efficient automated ways for the evaluation of the sleep instability, generalizable to both normal and pathological subjects affected by different sleep disorders.

Sleep and Association With Cardiovascular Risk Among Midwestern US Firefighters.

Introduction: Cardiovascular disease is the leading cause of on-duty fatalities among U.S. firefighters. Research has demonstrated that many modifiable risk factors are contributors to the high prevalence of cardiometabolic risk factors. The current study aimed to assess whether sleep is associated with cardiometabolic risk factors among Indianapolis firefighters. The findings could support improving sleep hygiene in this population. Material and Methods: This cross-sectional study was conducted from the baseline data of eligible firefighters enrolled in "Feeding America's Bravest", a Mediterranean diet lifestyle intervention within the Indiana Fire Departments. Participants' sleep quality was categorized as "good" (≤ 8 points) or "bad" (>8 points) by a sleep quality questionnaire based on some questions from Pittsburgh Sleep Quality Index. In addition, firefighters' sleep duration was stratified based on the number of hours slept per night (≤6 as "short sleep" or >6 hours as normal). Linear and logistic regression models were used to examine the association of sleep with cardiometabolic risk factors. Results: A total of 258 firefighters were included. Bad sleepers had higher weight, greater waist circumference, higher body mass index (BMI), and increased body fat (all p<0.01) compared to good sleepers. Similarly, participants with short sleep duration were heavier (p<0.02), had greater BMI (p<0.02) and increased body fat (p<0.04) compared with participants with normal sleep duration. Both bad and short sleepers had a higher prevalence of hypertension and obesity (p <0.05). Conclusions: Our study supports that both sleep quality and quantity are associated with cardiometabolic risk among firefighters.

Sleep, Pain, and Cognition: Modifiable Targets for Optimal Perioperative Brain Health.

The prevention of perioperative neurocognitive disorders is a priority for patients, families, clinicians, and researchers. Given the multiple risk factors present throughout the perioperative period, a multicomponent preventative approach may be most effective. The objectives of this narrative review are to highlight the importance of sleep, pain, and cognition on the risk of perioperative neurocognitive disorders and to discuss the evidence behind interventions targeting these modifiable risk factors. Sleep disruption is associated with postoperative delirium, but the benefit of sleep-related interventions is uncertain. Pain is a risk factor for postoperative delirium, but its impact on other postoperative neurocognitive disorders is unknown. Multimodal analgesia and opioid avoidance are emerging as best practices, but data supporting their efficacy to prevent delirium are limited. Poor preoperative cognitive function is a strong predictor of postoperative neurocognitive disorder, and work is ongoing to determine whether it can be modified to prevent perioperative neurocognitive disorders.

Sleep Disruption Worsens Seizures: Neuroinflammation as a Potential Mechanistic Link.

Sleep disturbances, such as insomnia, obstructive sleep apnea, and daytime sleepiness, are common in people diagnosed with epilepsy. These disturbances can be attributed to nocturnal seizures, psychosocial factors, and/or the use of anti-epileptic drugs with sleep-modifying side effects. Epilepsy patients with poor sleep quality have intensified seizure frequency and disease progression compared to their well-rested counterparts. A better understanding of the complex relationship between sleep and epilepsy is needed, since approximately 20% of seizures and more than 90% of sudden unexpected deaths in epilepsy occur during sleep. Emerging studies suggest that neuroinflammation, (e.g., the CNS immune response characterized by the change in expression of inflammatory mediators and glial activation) may be a potential link between sleep deprivation and seizures. Here, we review the mechanisms by which sleep deprivation induces neuroinflammation and propose that neuroinflammation synergizes with seizure activity to worsen neurodegeneration in the epileptic brain. Additionally, we highlight the relevance of sleep interventions, often overlooked by physicians, to manage seizures, prevent epilepsy-related mortality, and improve quality of life.

Effects of Cognitive Behavioral Therapy on Pain and Sleep in Adults with Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

The objective of this study was to systematically review the literature on the effects of cognitive behavioral therapy (CBT) on insomnia and pain in patients with traumatic brain injury (TBI). PubMed, Embase, the Cochrane Library, Cumulative Index to Nursing and Allied Health, and Web of Science databases were searched. Outcomes, including pain, sleep quality, and adverse events, were investigated. Differences were expressed using mean differences (MDs) with 95% confidence intervals (CIs). The statistical analysis was performed using STATA 16.0. Twelve trials with 476 TBI patients were included. The included studies did not indicate a positive effect of CBT on pain. Significant improvements were shown for self-reported sleep quality, reported with the Pittsburgh Self-Reported Sleep Quality Index (MD, -2.30; 95% CI, -3.45 to -1.15; P < 0.001) and Insomnia Severity Index (MD, -5.12; 95% CI, -9.69 to -0.55; P = 0.028). No major adverse events related to CBT were reported. The underpowered evidence suggested that CBT is effective in the management of sleep quality and pain in TBI adults. Future studies with larger samples are recommended to determine significance. This trial is registered with PROSPERO registration number CRD42019147266.