An Official American Thoracic Society Statement: The Importance of Healthy Sleep. Recommendations and Future Priorities

Insomnia and sleep duration for kidney function: Mendelian randomization study

OBJECTIVES

Extensive researches highlight the detrimental impact of sleep disorders such as insomnia and insufficient sleep duration on kidney function. However, establishing a clear causal relationship between insomnia, sleep duration, and kidney function remains challenging. This study aims to estimate this relationship using Mendelian randomization (MR).

METHODS

Independent genetic variants strongly associated with insomnia (N = 462,341) and sleep duration (N = 460,099) were selected as instrumental variables from corresponding genome-wide association studies (GWAS). Kidney function parameters, including serum creatinine, estimated glomerular filtration rate by cystatin C (eGFRcys), acute renal failure (ARF), chronic renal failure (CRF), kidney injury molecule-1, neutrophil gelatinase associated lipocalin, microalbuminuria, cystatin C, and β2 microglobulin, were derived from GWAS databases. A two-sample MR study was conducted to assess the causal relationship between sleep disorders and kidney function, and multivariable MR was used to identify potential mediators. The inverse-variance weighted was used as the primary estimate.

RESULTS

MR analysis found robust evidence indicating that insomnia and short sleep duration were associated with an increased risk of elevated serum creatinine, regardless of adjusting for obesity. Causal links between sleep duration and eGFRcys or cystatin C were also identified. While genetically predicted insomnia and sleep duration were found to potentially impact ARF, CRF, microalbuminuria, and β2 microglobulin, the p-values in multivariable MR analysis became nonsignificant. No pleiotropy was detected.

CONCLUSIONS

This study demonstrates a causal impact of insomnia on the risk of elevated serum creatinine and a positive effect of sleep duration on serum creatinine, eGFRcys, and cystatin C. Our findings also suggest their potential indirect effects on ARF, CRF, microalbuminuria, and β2 microglobulin mediated by obesity.

State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset

Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an optimized, state-of-the-art approach using data from daily work in our university hospital sleep laboratory. Therefore, a machine learning algorithm was trained and evaluated on 3423 polysomnograms of people with various sleep disorders. The model architecture is a U-net that accepts 50 Hz signals as input. We compared this algorithm with models trained on publicly available datasets, and evaluated these models using our clinical dataset, particularly with regard to the effects of different sleep disorders. In an effort to evaluate clinical relevance, we designed a metric based on the error of the predicted arousal index. Our models achieve an area under the precision recall curve (AUPRC) of up to 0.83 and F1 scores of up to 0.81. The model trained on our data showed no age or gender bias and no significant negative effect regarding sleep disorders on model performance compared to healthy sleep. In contrast, models trained on public datasets showed a small to moderate negative effect (calculated using Cohen's d) of sleep disorders on model performance. Therefore, we conclude that state-of-the-art arousal detection on our clinical data is possible with our model architecture. Thus, our results support the general recommendation to use a clinical dataset for training if the model is to be applied to clinical data.

Exploring the association between sleep duration and cancer risk in middle-aged and older Chinese adults: observations from a representative cohort study (2011-2020)

BACKGROUND

This prospective cohort study aimed to investigate the relationship between sleep duration and cancer incidence among 9996 participants over a median follow-up period of 9 years.

METHODS

Participants without cancer at baseline were followed for over 88,790 person-years. The incidence of cancer and sleep duration was self-reported. The relationship between sleep duration and cancer incidence was analyzed using Cox proportional hazards models adjusted for various confounding factors, including age, gender, lifestyle factors, and comorbidities.

RESULTS

During the follow-up, 325 participants were diagnosed with incident cancer, resulting in an incidence rate of 20.49 per 1000 person-years. After adjusting for confounders, a total sleep duration of less than 6 h was significantly associated with an increased risk of cancer (HR: 1.27; 95% CI: 1.01-1.61). This association was particularly strong for cancers in the digestive and respiratory systems (HR: 1.41; 95% CI: 1.03-1.93). Longer sleep durations (> 9 h) showed a potential increase in cancer risk, but results were not consistently significant. Age-stratified analyses revealed a similar significant increase in cancer incidence among individuals aged 60 years or younger with less than 6 h of sleep per day, showing a 35% increase in overall cancer risk and an 83% increase in digestive and respiratory system cancer. No significant association was found between nocturnal sleep durations or daytime naps and cancer incidence. However, a significant interaction was observed between daytime naps longer than 30 min and cancer incidence in women (p = 0.041).

CONCLUSIONS

We observed that short sleep duration may increase the risk of cancer, particularly cancers in the digestive and respiratory systems. Additionally, while longer sleep durations might also increase cancer risk, this finding requires validation with larger sample sizes.

Effects of Cadmium and Lead Co-exposure on Sleep Status in Rural Areas Northwestern China

In this study, we explored how cadmium and lead co-exposure affects sleep status among residents of a polluted area and nature reserve in rural northwestern China. Cadmium and lead levels were measured using blood samples, and sleep status was evaluated using sleep questionnaires, with the main sleep indicators including sleep duration, sleep quality, bedtime, and staying up. Furthermore, cadmium-lead co-exposure levels were divided into three groups: high exposure, medium exposure, and low exposure. Subjects in the contaminated area had significantly higher exposure levels (p < 0.001) and more negative sleep indicators (p < 0.01). Significant differences were found for all four sleep indicators in the high exposure group compared to the low exposure group (p < 0.01). Moreover, the overall evaluation of sleep status with high cadmium-lead co-exposure had a negative impact. Our data suggest that cadmium-lead co-exposure has a negative effect on sleep status and may have a synergistic effect on sleep.

Sleep, anxiety, depression, and stress in critically ill patients: a descriptive study in a Portuguese intensive care unit

BACKGROUND

Sleep disorders are common among patients admitted to intensive care units (ICUs). This study aimed to assess the perceptions of sleep quality, anxiety, depression, and stress reported by ICU patients and the relationships between these perceptions and patient variables.

METHODS

This cross-sectional study used consecutive non-probabilistic sampling to select participants. All patients admitted for more than 72 hours of ICU hospitalization at a Portuguese hospital between March and June 2020 were asked to complete the "Richard Campbell Sleep Questionnaire" and "Anxiety, depression, and Stress Assessment Questionnaire." The resulting data were analyzed using descriptive statistics, Pearson's correlation coefficient, Student t-tests for independent samples, and analysis of variance. The significance level for rejecting the null hypothesis was set to α ≤0.05.

RESULTS

A total of 52 patients admitted to the ICU for at least 72 hours was recruited. The mean age of the participants was 64 years (standard deviation, 14.6); 32 (61.5%) of the participants were male. Approximately 19% had psychiatric disorders. The prevalence of self-reported poor sleep was higher in women (t[50]=2,147, P=0.037) and in participants with psychiatric problems, although this difference was not statistically significant (t[50]=-0.777, P=0.441). Those who reported having sleep disorders before hospitalization had a worse perception of their sleep.

CONCLUSIONS

Sleep quality perception was worse in female ICU patients, those with psychiatric disorders, and those with sleep alterations before hospitalization. Implementing early interventions and designing nonpharmacological techniques to improve sleep quality of ICU patients is essential.

The Effect of a Cognitive Dual Task on Gait Parameters among Healthy Young Adults with Good and Poor Sleep Quality: A Cross-Sectional Analysis

Background: Sleep quality is known to affect automatic and executive brain functions such as gait control and cognitive processing. This study aimed to investigate the effect of dual tasks on gait spatiotemporal parameters among young adults with good and poor sleep quality. Methods: In total, 65 young adults with a mean age of 21.1 ± 2.5 were assessed for gait analysis during single-task and dual-task conditions. The participants' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and gait was assessed using the BTS Gaitlab System. The participants were asked to walk at natural speed as a single-task condition, followed by walking while performing a cognitive task as a dual-task condition. The parameters assessed included the gait velocity (m/s), cadence (steps/min), step width (m), and stride length (m). The dual-task cost (DTC) on each gait parameter was calculated. The Mann-Whitney U test was used to compare the differences in the DTC on gait variables between the good and poor sleep quality groups and the Spearman correlation test was used to assess the correlation between total PSQI scores and the DTC. Results: At a significance level of p < 0.05, a significant difference in cadence between the two sleep quality groups was observed, in addition to a positive correlation between sleep quality and the DTC effect on gait mean velocity, cadence, and stride length. Our findings also revealed a greater DTC in participants with poorer sleep quality. Conclusions: These findings contribute to our perception of the significance of sleep quality in gait performance while multitasking in younger populations.

Assessing the Accuracy of Generative Conversational Artificial Intelligence in Debunking Sleep Health Myths: Mixed Methods Comparative Study With Expert Analysis

BACKGROUND

Adequate sleep is essential for maintaining individual and public health, positively affecting cognition and well-being, and reducing chronic disease risks. It plays a significant role in driving the economy, public safety, and managing health care costs. Digital tools, including websites, sleep trackers, and apps, are key in promoting sleep health education. Conversational artificial intelligence (AI) such as ChatGPT (OpenAI, Microsoft Corp) offers accessible, personalized advice on sleep health but raises concerns about potential misinformation. This underscores the importance of ensuring that AI-driven sleep health information is accurate, given its significant impact on individual and public health, and the spread of sleep-related myths.

OBJECTIVE

This study aims to examine ChatGPT's capability to debunk sleep-related disbeliefs.

METHODS

A mixed methods design was leveraged. ChatGPT categorized 20 sleep-related myths identified by 10 sleep experts and rated them in terms of falseness and public health significance, on a 5-point Likert scale. Sensitivity, positive predictive value, and interrater agreement were also calculated. A qualitative comparative analysis was also conducted.

RESULTS

ChatGPT labeled a significant portion (n=17, 85%) of the statements as "false" (n=9, 45%) or "generally false" (n=8, 40%), with varying accuracy across different domains. For instance, it correctly identified most myths about "sleep timing," "sleep duration," and "behaviors during sleep," while it had varying degrees of success with other categories such as "pre-sleep behaviors" and "brain function and sleep." ChatGPT's assessment of the degree of falseness and public health significance, on the 5-point Likert scale, revealed an average score of 3.45 (SD 0.87) and 3.15 (SD 0.99), respectively, indicating a good level of accuracy in identifying the falseness of statements and a good understanding of their impact on public health. The AI-based tool showed a sensitivity of 85% and a positive predictive value of 100%. Overall, this indicates that when ChatGPT labels a statement as false, it is highly reliable, but it may miss identifying some false statements. When comparing with expert ratings, high intraclass correlation coefficients (ICCs) between ChatGPT's appraisals and expert opinions could be found, suggesting that the AI's ratings were generally aligned with expert views on falseness (ICC=.83, P<.001) and public health significance (ICC=.79, P=.001) of sleep-related myths. Qualitatively, both ChatGPT and sleep experts refuted sleep-related misconceptions. However, ChatGPT adopted a more accessible style and provided a more generalized view, focusing on broad concepts, while experts sometimes used technical jargon, providing evidence-based explanations.

CONCLUSIONS

ChatGPT-4 can accurately address sleep-related queries and debunk sleep-related myths, with a performance comparable to sleep experts, even if, given its limitations, the AI cannot completely replace expert opinions, especially in nuanced and complex fields such as sleep health, but can be a valuable complement in the dissemination of updated information and promotion of healthy behaviors.

Poor Sleep Quality in Jamaican Adults With Sickle Cell Disease: Prevalence, Risk Factors, and Association With Quality of Life

Poor sleep and chronic illnesses have a bidirectional relationship where presence of one can worsen the other. Sickle cell disease (SCD) is associated with significant morbidity and early mortality. In this study, we examine sleep quality, its predictors, and its association with quality of life in Jamaican adults with SCD. This cross-sectional study evaluated 177 well adult SCD patients for sleep quality using The Pittsburgh Sleep Quality Index (PSQI) and quality of life using the Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me). Multiple linear regression models examined the predictors of poor sleep quality. The mean global PSQI score was 6.9 (SD 4.2) with 56.5% having poor sleep quality. Women had significantly worse scores for sleep efficiency (p 0.005), sleep latency (p 0.03) and higher use of sleeping medications (p 0.02). Those overweight/obese had significantly worse subjective sleep quality (p 0.001) and sleep efficiency (p 0.05). In multivariate regression analysis, overweight individuals had poorer sleep quality (OR: 2.9; 95% C.I.: 1.07, 7.88) than those with normal weight whereas those unemployed and looking for a job had lower prevalence of poor sleep quality (OR 0.2; 95% C.I.: 0.05, 0.77) compared to employed individuals. Participants with good sleep quality had significantly better functioning in all 5 domains of the ASCQ-Me. In conclusion, persons with SCD who are overweight or obese are at increased risk of poor sleep which can negatively affect quality of life. Patient populations and healthcare providers will need to manage the emerging burden of overweight/obesity.

A Soft Bioelectronic Patch for Simultaneous Respiratory and Cardiovascular Monitoring

Sleep is critical to maintaining physical and mental health. Measuring physiological parameters to quantify sleep quality without uncomfortable user experience remains highly desired but a challenge. Here, this work develops a soft bioelectronic patch to perform simultaneous respiration and cardiovascular monitoring during sleep in a wearable and non-invasive manner. The soft bioelectronic patch system is mainly composed of a pressure sensor, a flexible printed circuit for signal processing, and a soft thermoplastic urethane mold for assembling different functional modules. The soft bioelectronic patch holds a sensitivity of >0.12 V kPa-1 and a remarkable low-frequency response from 0.5 to 15 Hz. It is demonstrated to continuously monitor respiration and heartbeat during the whole night, which could be harnessed for sleep monitoring and obstructive sleep apnea-hypopnea syndrome diagnosis. The reported soft bioelectronic patch represents a simple and convenient platform technology for sleep study.

Causal association between sleep traits and autoimmune arthritis: Evidence from a bidirectional Mendelian randomization study

OBJECTIVE

To explore whether there is a genetic causal relationship between sleep traits and the risk of autoimmune arthritis (AA).

METHODS

Univariable and multivariable Mendelian randomization was employed using genome-wide association studies data to assess sleep traits' associations with AAs, including rheumatoid arthritis (RA), ankylosing spondylitis, and psoriatic arthritis. The inverse-variance weighted method served as the primary analysis, supplemented by the CAUSE method to improve power and mitigate false positives. Mediation Mendelian randomization was used to quantify direct and indirect effects.

RESULTS

Significant associations were shown between insomnia symptoms and increased risk of overall RA (odds ratio = 2.75, 95% confidence interval 1.45-5.22) and seronegative RA (odds ratio = 6.95, 95% confidence interval 2.47-19.56). CAUSE results revealed an association of insomnia symptoms with overall RA and seronegative RA, as well as the sleep duration with overall RA. After the adjustment for body mass index, alcohol status, smoking status, and physical activity levels, multivariable analyses revealed that genetic predisposition to insomnia symptoms and prolonged sleep duration showed independent negative associations with the risk of overall RA and seropositive RA. In the reversed multivariable analyses, a borderline negative association was shown in the overall RA-sleep duration and a positive association of seropositive RA with the risk of insomnia symptoms.

CONCLUSION

This study demonstrated a potential bidirectional causal relationship that genetic predisposition to insomnia symptoms and shorter sleep duration was associated with the risk of AA, especially RA. Genetic predisposition to RA was also associated with decreased sleep duration, as well as increased insomnia symptom risk.

Associations of Training and Academic Stress with Sleep in Dual-Career Collegiate Badminton Athletes: A Preliminary Study

Introduction

Poor sleep negatively impacts cognitive and physical functioning and affects athletic and academic achievement. "Dual-career" athletes emphasize the pursuit of academic excellence along with athletic performance.

Purpose

The study aimed to assess sleep characteristics and sleep quality in dual-career collegiate badminton athletes. Furthermore, the study explored associations between training and academic stress and sleep, providing a theoretical basis for better training and sleep programs for dual-career athletes.

Participants and Methods

In this study, 15 dual-career collegiate badminton athletes were recruited, and 12 subjects (male n = 8, female n = 4, mean age 20.3 ± 1.7) completed the questionnaire. Repeated measurements were taken monthly in the spring semester from March to August 2021. The questionnaire assessed sleep quality and daytime sleepiness by the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Score (ESS). Moreover, we collected average training, study time per week, and monthly sports competitions and academic tests to quantify participants' training and academic stress.

Results

An average of 36.1% of dual-career athletes reported poor sleep and 25.0% had excessive daytime sleepiness. Overall, a significant positive correlation existed between PSQI scores and weekly study hours (r = 0.308, p = 0.009). Significant positive correlations were found between the four stressors and PSQI (August: r = 0.868, p < 0.001; July: r = 0.573, p = 0.026) or ESS scores (March: r = -0.678, p = 0.015; August: r = 0.598, p = 0.040) for specific months. Hierarchical linear modeling (HLM) analysis identified that lower study and training hours predict better sleep quality.

Conclusion

Dual-career collegiate badminton athletes had a higher prevalence of poor sleep and daytime sleepiness, and daytime sleepiness did not result in better sleep quality; study and training hours had the greatest effect on the sleep quality of dual-career collegiate badminton athletes.

Insomnia and sleep-disordered breathing in FKRP-related limb-girdle muscular dystrophy R9. The Norwegian LGMDR9 cohort study (2020)

Limb-girdle muscular dystrophy R9 (LGMDR9) is a progressive and disabling genetic muscle disease. Sleep is relevant in the patient care as it impacts on health, functioning, and well-being. LGMDR9 may potentially affect sleep by physical or emotional symptoms, myalgia, or sleep-disordered breathing (SDB) through cardiorespiratory involvement. The objective was to investigate the occurrence of insomnia and unrecognized or untreated SDB in LGMDR9, associated factors, and relationships with fatigue and health-related quality of life (HRQoL). All 90 adults in a Norwegian LGMDR9 cohort received questionnaires on sleep, fatigue, and HRQoL. Forty-nine of them underwent clinical assessments and 26 without mask-based therapy for respiration disorders additionally underwent polysomnography (PSG) and capnometry. Among 77 questionnaire respondents, 31% received mask-based therapy. The prevalence of insomnia was 32% of both those with and without such therapy but was significantly increased in fatigued respondents (54% vs 21%). Insomnia levels correlated inversely with mental HRQoL. Among 26 PSG candidates, an apnea-hypopnea index (AHI) ≥ 5/h was observed in 16/26 subjects (≥ 15/h in 8/26) with median 6.8 obstructive apneas and 0.2 central apneas per hour of sleep. The AHI was related to advancing age and an ejection fraction < 50%. Sleep-related hypoventilation was detected in one subject. Fatigue severity did not correlate with motor function or nocturnal metrics of respiration or sleep but with Maximal Inspiratory Pressure (r = - 0.46). The results indicate that insomnia and SDB are underrecognized comorbidities in LGMDR9 and associated with HRQoL impairment and heart failure, respectively. We propose an increased attention to insomnia and SDB in the interdisciplinary care of LGMDR9. Insomnia and pulmonary function should be examined in fatigued patients.

Sex and Sleep Disruption as Contributing Factors in Alzheimer's Disease

Alzheimer's disease (AD) affects more women than men, with women throughout the menopausal transition potentially being the most under researched and at-risk group. Sleep disruptions, which are an established risk factor for AD, increase in prevalence with normal aging and are exacerbated in women during menopause. Sex differences showing more disrupted sleep patterns and increased AD pathology in women and female animal models have been established in literature, with much emphasis placed on loss of circulating gonadal hormones with age. Interestingly, increases in gonadotropins such as follicle stimulating hormone are emerging to be a major contributor to AD pathogenesis and may also play a role in sleep disruption, perhaps in combination with other lesser studied hormones. Several sleep influencing regions of the brain appear to be affected early in AD progression and some may exhibit sexual dimorphisms that may contribute to increased sleep disruptions in women with age. Additionally, some of the most common sleep disorders, as well as multiple health conditions that impair sleep quality, are more prevalent and more severe in women. These conditions are often comorbid with AD and have bi-directional relationships that contribute synergistically to cognitive decline and neuropathology. The association during aging of increased sleep disruption and sleep disorders, dramatic hormonal changes during and after menopause, and increased AD pathology may be interacting and contributing factors that lead to the increased number of women living with AD.

Factors Affecting Medical Residents' Decisions to Work After Call

BACKGROUND

Accreditation Council for Graduate Medical Education (ACGME) work-hour restrictions (WHRs) are intended to improve patient safety by reducing resident fatigue. Compliance with ACGME WHRs is not universal.

PURPOSE

The purpose of this study was to identify factors that influence residents' decisions to take a postcall day (PCD) off according to ACGME WHRs.

METHODS

Residents (N = 433) at one university were emailed a link to a survey in 2019. The survey included demographic details and a Discrete Choice Experiment examining influences on resident decisions to take a PCD off.

RESULTS

One hundred seventy-five residents (40.4%) responded to the survey; 113 residents (26%) completed the survey. Positive feedback from attending physicians about taking PCDs off in the past had the greatest impact on respondents' decisions to take a PCD off, increasing the probability by 27.3%, followed by chief resident comments about the resident looking tired (16.6% increase), and having never heard their attendings comment about PCDs off as either positive or negative (13.9% increase). Factors that had the largest effect on decreasing the probability of taking a PCD were negative feedback about taking PCDs off (14.3% decrease), continuity of care concerns (10.8% decrease), and whether the resident was looking forward to an assignment (7.9% decrease).

CONCLUSIONS

The most important influencer of residents' decisions to take a PCD off was related to feedback from their attending physicians, suggesting that compliance with WHRs can be improved by focusing on the residency program's safety culture.

Recommendations for clinical management of excessive daytime sleepiness in obstructive sleep apnoea - A Delphi consensus study

STUDY OBJECTIVE

Excessive daytime sleepiness is common with obstructive sleep apnoea and can persist despite efforts to optimise primary airway therapy. The literature lacks recommendations regarding differential diagnosis and management of excessive daytime sleepiness in obstructive sleep apnoea. This study sought to develop expert consensus statements to bridge the gap between existing literature/guidelines and clinical practice.

METHODS

A panel of 10 international experts was convened to undertake a modified Delphi process. Statements were developed based on available evidence identified through a scoping literature review, and expert opinion. Consensus was achieved through 3 rounds of iterative, blinded survey voting and revision to statements until a predetermined level of agreement was met (≥80 % voting "strongly agree" or "agree with reservation").

RESULTS

Consensus was achieved for 32 final statements. The panel agreed excessive daytime sleepiness is a patient-reported symptom. The importance of subjective/objective evaluation of excessive daytime sleepiness in the initial evaluation and serial management of obstructive sleep apnoea was recognised. The differential diagnosis of residual excessive daytime sleepiness in obstructive sleep apnoea was discussed. Optimizing airway therapy (eg, troubleshooting issues affecting effectiveness) was addressed. The panel recognised occurrence of residual excessive daytime sleepiness in obstructive sleep apnoea despite optimal airway therapy and the need to evaluate patients for underlying causes.

CONCLUSIONS

Excessive daytime sleepiness in patients with obstructive sleep apnoea is a public health issue requiring increased awareness, recognition, and attention. Implementation of these statements may improve patient care, long-term management, and clinical outcomes in patients with obstructive sleep apnoea.

Bifidobacterium breve CCFM1025 Improves Sleep Quality via Regulating the Activity of the HPA Axis: A Randomized Clinical Trial

Psychobiotics, a newly identified category of probiotics primarily targeting the gut-brain axis, exhibit tremendous potential in improving sleep quality. In this study, the clinical trial was registered in advance (identifier: NO. ChiCTR2300067806). Forty participants who were diagnosed with stress-induced insomnia were chosen and randomly divided into two groups: one received CCFM1025 at a dose of 5 × 109 CFU (n = 20), while the other was administered a placebo (n = 20), over a period of four weeks. The results revealed that compared to the placebo group (pre: M = 10.10, SD = 2.292; post: M = 8.650, SD = 2.793; pre vs. post: F (1, 38) = 15.41, p = 0.4316), the CCFM1025-treated group exhibited a significant decrease in Pittsburgh Sleep Quality Index (PSQI) scores from baseline (pre: M = 11.60, SD = 3.169; post: M = 7.750, SD = 3.697, F (1, 38) = 15.41, p = 0.0007). Furthermore, the administration of CCFM1025 was associated with a more pronounced reduction in stress marker concentrations. This effect could potentially be linked to changes in serum metabolites induced by the probiotic treatment, notably daidzein. In conclusion, B. breve CCFM1025 demonstrates promise as a psychobiotic strain for enhancing sleep quality.

Assessing the Association of Self-Reported Sleep Duration and Metabolic Syndrome Among Middle-Aged and Older Adults in China from the China Health and Retirement Longitudinal Survey

Objectives: We aim to investigate the correlation between sleep and metabolic syndrome (MS) among a community population 45 years of age and older in China. Methods: A cross-sectional analysis of 9096 participants from China health and longitudinal study was carried out. MS was defined by consensus criteria. Sleep durations were assessed by self-reported questionnaire. Odds ratio (OR) and 95% confidence intervals (CIs) for MS were obtained using multivariable-adjusted regression analysis. Results: Long habitual daytime sleep had a positive influence on MS (OR = 1.50, 95% CI = 1.10-2.06). For elderly, short daytime sleep significantly increased risk of MS (OR = 2.14, 95% CI = 1.25-3.67). Females with long daytime sleep was associated with increased risk of MS (OR = 1.54, 95% CI = 1.04-2.29). Conclusions: Daytime sleep significantly increased risk of MS for middle-aged and elderly Chinese. The hazard role of daytime sleep on MS was various between age and sex groups. Results of this study needed to be verified by future longitudinal studies.

Multi-channel EEG-based sleep staging using brain functional connectivity and domain adaptation

Objective.Sleep stage recognition has essential clinical value for evaluating human physical/mental condition and diagnosing sleep-related diseases. To conduct a five-class (wake, N1, N2, N3 and rapid eye movement) sleep staging task, twenty subjects with recorded six-channel electroencephalography (EEG) signals from the ISRUC-SLEEP dataset is used.Approach.Unlike the exist methods ignoring the channel coupling relationship and non-stationarity characteristics, we developed a brain functional connectivity method to provide a new insight for multi-channel analysis. Furthermore, we investigated three frequency-domain features: two functional connectivity estimations, i.e. synchronization likelihood (SL) and wavelet-based correlation (WC) among four frequency bands, and energy ratio (ER) related to six frequency bands, respectively. Then, the Gaussian support vector machine (SVM) method was used to predict the five sleep stages. The performance of the applied features is evaluated in both subject dependence experiment by ten-fold cross validation and subject independence experiment by leave-one-subject-out cross-validation, respectively.Main results.In subject dependence experiment, the results showed that the fused feature (fusion of SL, WC and ER features) contributes significant gain the performance of SVM classifier, where the mean of classification accuracy can achieve 83.97% ± 1.04%. However, in subject-independence experiment, the individual differences EEG patterns across subjects leads to inferior accuracy. Five typical domain adaptation (DA) methods were applied to reduce the discrepancy of feature distributions by selecting the optimal subspace dimension. Results showed that four DA methods can significantly improve the mean accuracy by 1.89%-5.22% compared to the baseline accuracy 57.44% in leave-one-subject-out cross-validation.Significance.Compared with traditional time-frequency and nonlinear features, brain functional connectivity features can capture the correlation between different brain regions. For the individual EEG response differences, domain adaptation methods can transform features to improve the performance of sleep staging algorithms.

Multi-task learning for arousal and sleep stage detection using fully convolutional networks

Objective.Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential for the diagnosis of sleep disorders, as frequent and excessive occurrences of arousals disrupt sleep stage patterns and lead to poor sleep quality, negatively impacting physical and mental health. Polysomnography is a traditional method for arousal and sleep stage detection that is time-consuming and prone to high variability among experts.Approach. In this paper, we propose a novel multi-task learning approach for arousal and sleep stage detection using fully convolutional neural networks. Our model, FullSleepNet, accepts a full-night single-channel EEG signal as input and produces segmentation masks for arousal and sleep stage labels. FullSleepNet comprises four modules: a convolutional module to extract local features, a recurrent module to capture long-range dependencies, an attention mechanism to focus on relevant parts of the input, and a segmentation module to output final predictions.Main results.By unifying the two interrelated tasks as segmentation problems and employing a multi-task learning approach, FullSleepNet achieves state-of-the-art performance for arousal detection with an area under the precision-recall curve of 0.70 on Sleep Heart Health Study and Multi-Ethnic Study of Atherosclerosis datasets. For sleep stage classification, FullSleepNet obtains comparable performance on both datasets, achieving an accuracy of 0.88 and an F1-score of 0.80 on the former and an accuracy of 0.83 and an F1-score of 0.76 on the latter.Significance. Our results demonstrate that FullSleepNet offers improved practicality, efficiency, and accuracy for the detection of arousal and classification of sleep stages using raw EEG signals as input.

Sleep and critical illness: a review

Critical illness and stays in the Intensive Care Unit (ICU) have significant impact on sleep. Poor sleep is common in this setting, can persist beyond acute critical illness, and is associated with increased morbidity and mortality. In the past 5 years, intensive care clinical practice guidelines have directed more focus on sleep and circadian disruption, spurring new initiatives to study and improve sleep complications in the critically ill. The global SARS-COV-2 (COVID-19) pandemic and dramatic spikes in patients requiring ICU level care also brought augmented levels of sleep disruption, the understanding of which continues to evolve. This review aims to summarize existing literature on sleep and critical illness and briefly discuss future directions in the field.

Psychosocial and health stressors during the COVID-19 pandemic and their association with sleep quality

OBJECTIVE

We investigated how psychosocial and health stressors and related cognitive-affective factors were differentially associated with sleep quality during the early months of the COVID-19 pandemic.

METHODS AND MEASURES

Adults living in Florida (n = 2,152) completed a Qualtrics survey in April-May 2020 (Wave 1). Participants (n = 831) were reassessed one month later (Wave 2; May-June 2020). At Wave 1, participants reported their level of physical contact with someone they care about, presence of a pre-existing chronic disease, employment status, loneliness, health worry, and financial distress. At Wave 2, participants rated their quality of sleep and insomnia symptoms.

RESULTS

Loneliness, but not health worry or financial distress, directly predicted worse sleep quality. Lack of physical contact was indirectly associated with worse sleep quality via greater levels of loneliness. Further, results showed the presence of a pre-existing chronic disease was associated with both greater health worry and worse sleep quality.

CONCLUSION

Loneliness was the sole cognitive-affective predictor of worse sleep quality when controlling for other psychosocial factors. As expected, adults living with a chronic disease reported impaired sleep quality. Understanding the processes influencing sleep quality during a significant time of stress is important for identifying risk factors, informing treatment, and improving sleep health beyond the pandemic.

Current status and prospects of automatic sleep stages scoring: Review

The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment.

Assessing the Feasibility of Replacing Subjective Questionnaire-Based Sleep Measurement with an Objective Approach Using a Smartwatch

In order to ensure sufficient recovery of the human body and brain, healthy sleep is indispensable. For this purpose, appropriate therapy should be initiated at an early stage in the case of sleep disorders. For some sleep disorders (e.g., insomnia), a sleep diary is essential for diagnosis and therapy monitoring. However, subjective measurement with a sleep diary has several disadvantages, requiring regular action from the user and leading to decreased comfort and potential data loss. To automate sleep monitoring and increase user comfort, one could consider replacing a sleep diary with an automatic measurement, such as a smartwatch, which would not disturb sleep. To obtain accurate results on the evaluation of the possibility of such a replacement, a field study was conducted with a total of 166 overnight recordings, followed by an analysis of the results. In this evaluation, objective sleep measurement with a Samsung Galaxy Watch 4 was compared to a subjective approach with a sleep diary, which is a standard method in sleep medicine. The focus was on comparing four relevant sleep characteristics: falling asleep time, waking up time, total sleep time (TST), and sleep efficiency (SE). After evaluating the results, it was concluded that a smartwatch could replace subjective measurement to determine falling asleep and waking up time, considering some level of inaccuracy. In the case of SE, substitution was also proved to be possible. However, some individual recordings showed a higher discrepancy in results between the two approaches. For its part, the evaluation of the TST measurement currently does not allow us to recommend substituting the measurement method for this sleep parameter. The appropriateness of replacing sleep diary measurement with a smartwatch depends on the acceptable levels of discrepancy. We propose four levels of similarity of results, defining ranges of absolute differences between objective and subjective measurements. By considering the values in the provided table and knowing the required accuracy, it is possible to determine the suitability of substitution in each individual case. The introduction of a "similarity level" parameter increases the adaptability and reusability of study findings in individual practical cases.

A narrative review of the pathophysiology and impacts of insufficient and disrupted sleep

Background

Despite substantial ramifications of insufficient sleep on mental and physical health and general well-being, many individuals are unaware of what constitutes sufficient sleep, or of the short- and long-term extent of sleep deficiency effects, including those that may not be perceived as fatigue.

Objectives and procedures

This review describes the physiology of sleep, defines healthy standards, reviews the pathophysiology and health hazards of acute and chronic sleep insufficiency, and offers concepts for improving individual sleep hygiene. Online databases were searched to extract literature pertaining to sleep, sleep insufficiency, fatigue, and health, with emphasis on literature published in the preceding 5 years.

Results

The detrimental effects of acute and chronic sleep loss vary in their range and impact. Individuals often obtain a substandard quantity of sleep, a problem that is poorly recognized by individuals and society. This lack of recognition perpetuates a culture in which sleep insufficiency is accepted, resulting in serious and substantial negative impacts on mental and physical health.

Conclusion and clinical relevance

Sleep management is one of the most fundamental and changeable aspects of personal health. Improving awareness of the important physiological roles of sleep, healthy sleep habits, and the consequence of insufficient sleep is essential in promoting general well-being and mental and physical health.

Sleep quality in patients with non-functioning pituitary adenoma: impact of replacement therapies with an emphasis on the time of hydrocortisone

PURPOSE

Sleep disturbances are widespread and associated with pituitary diseases, even those under long-term therapeutic management. The aim of this study was to investigate sleep quality in patients with non-functioning pituitary adenoma (NFPA) and determine the factors that might influence sleep quality, including the detailed features of replacement therapy.

METHODS

Eighty-two patients with NFPA and 82 age- and gender-matched control subjects were included. Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Scale (HADS) and International Physical Activity Questionnaire (IPAQ) were used.

RESULTS

In the NFPA group, 57.3% of patients had decreased sleep quality, compared to 35.4% in the control group (p=0.005). Although there was no relationship between the presence of hydrocortisone replacement and sleep quality (p>0.05), a strong positive correlation was observed between PSQI and morning hydrocortisone replacement time in patients with secondary adrenal insufficiency (r=0.834, p<0.001). Diabetes insipidus was found to be significantly higher in the group with decreased sleep quality (p=0.01). Moreover, there was a negative correlation between PSQI and IGF-1 in patients with NFPA (r=-0.259, p=0.01). A multivariate logistic regression model revealed that depression score and free T4 level in the upper half of the normal limit influence the sleep quality of patients with NFPA.

CONCLUSION

Our study indicated the presence of depression, and a free T4 level in the upper half of the normal range have an impact on the sleep quality of patients with NFPA. The time of hydrocortisone replacement might be important factor for improved sleep quality in patients with secondary adrenal insufficiency.

Sleep Apnea, Obesity, and Diabetes - an Intertwined Trio

PURPOSE OF REVIEW

To synthesize the existing literature regarding the complex interplay between sleep disturbance, obesity, and diabetes. The review emphasizes the three pillars of health being diet, exercise, and sleep, with the notion that if one is ignored, then the other two could suffer.

RECENT FINDINGS

Sleep deprivation is associated with incident obesity, perhaps mediated by dysregulation in leptin and ghrelin - hormones important in regulation of appetite. Sleep apnea is very common particularly among obese people with type 2 diabetes mellitus. Treatment of sleep apnea has clear symptomatic benefits although its impact on long-term cardiometabolic health is less clear. Sleep disturbance may be an important modifiable risk for patients at risk of cardiometabolic disease. An assessment of sleep health may be an important component of the comprehensive care of patients with obesity and diabetes mellitus.

Wearable sensing, big data technology for cardiovascular healthcare: current status and future prospective

ABSTRACT

Wearable technology, which can continuously and remotely monitor physiological and behavioral parameters by incorporated into clothing or worn as an accessory, introduces a new era for ubiquitous health care. With big data technology, wearable data can be analyzed to help long-term cardiovascular care. This review summarizes the recent developments of wearable technology related to cardiovascular care, highlighting the most common wearable devices and their accuracy. We also examined the application of these devices in cardiovascular healthcare, such as the early detection of arrhythmias, measuring blood pressure, and detecting prevalent diabetes. We provide an overview of the challenges that hinder the widespread application of wearable devices, such as inadequate device accuracy, data redundancy, concerns associated with data security, and lack of meaningful criteria, and offer potential solutions. Finally, the future research direction for cardiovascular care using wearable devices is discussed.

The prevalence and risk factors of sleep disturbances in surgical patients: A systematic review and meta-analysis

Determining the prevalence and risk factors related to sleep disturbance in surgical patients would be beneficial for risk stratification and perioperative care planning. The objectives of this systematic review and meta-analysis are to determine the prevalence and risk factors of sleep disturbances and their associated postoperative complications in surgical patients. The inclusion criteria were: (1) patients ≥18 years old undergoing a surgical procedure, (2) in-patient population, and (3) report of sleep disturbances using a validated sleep assessment tool. The systematic search resulted in 21,951 articles. Twelve patient cohorts involving 1497 patients were included. The pooled prevalence of sleep disturbances at preoperative assessment was 60% (95% Confidence Interval (CI): 50%, 69%) and the risk factors for postoperative sleep disturbances were a high preoperative Pittsburgh sleep quality index (PSQI) score indicating preexisting disturbed sleep and anxiety. Notably, patients with postoperative delirium had a higher prevalence of pre- and postoperative sleep disturbances and high preoperative wake after sleep onset percentage (WASO%). The high prevalence of preoperative sleep disturbances in surgical patients has a negative impact on postoperative outcomes and well-being. Further work in this area is warranted.

The long-term and short-term effects of ambient air pollutants on sleep characteristics in the Chinese population: big data analysis from real world by sleep records of consumer wearable devices

Several studies on long-term air pollution exposure and sleep have reported inconsistent results. Large-scale studies on short-term air pollution exposures and sleep have not been conducted. We investigated the associations of long- and short-term exposure to ambient air pollutants with sleep in a Chinese population based on over 1 million nights of sleep data from consumer wearable devices. Air pollution data including particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃) were collected from the Ministry of Ecology and Environment. Short-term exposure was defined as a moving average of the exposure level for different lag days from Lag0 to Lag0-6. A 365-day moving average of air pollution was regarded as long-term exposure. Sleep data were recorded using wearable devices from 2017 to 2019. The mixed-effects model was used to evaluate the associations. We observed that sleep parameters were associated with long-term exposure to all air pollutants. Higher levels of air pollutant concentrations were associated with longer total sleep and light sleep duration, shorter deep sleep duration, and decreases in wake after sleep onset (WASO), with stronger associations of exposures to NO₂ and CO [a 1-interquartile range (IQR) increased NO₂ (10.3 μg/m³) was associated with 8.7 min (95% CI: 8.08 to 9.32) longer sleep duration, a 1-IQR increased CO (0.3 mg/m³) was associated with 5.0 min (95% CI: - 5.13 to - 4.89) shorter deep sleep duration, 7.7 min (95% CI: 7.46 to 7.85) longer light sleep duration, and 0.5% (95% CI: - 0.5 to - 0.4%) lower proportion of WASO duration to total sleep]. The cumulative effect of short-term exposure on Lag0-6 is similar to long-term exposure but relatively less. Subgroup analyses indicated generally greater effects on individuals who were female, younger (< 45 years), slept longer (≥ 7 h), and during cold seasons, but the pattern of effects was mixed. We supplemented two additional types of stratified analyses to reduce repeated measures of outcomes and exposures while accounting for individual variation. The results were consistent with the overall results, proving the robustness of the overall results. In summary, both short- and long-term exposure to air pollution affect sleep, and the effects are comparable. Although people tend to have prolonged total sleep duration with increasing air pollutant concentrations, their sleep quality might remain poor because of the reduction in deep sleep.

Subjective sleep assessment compared to polysomnography in mechanically ventilated critically ill ICU patients

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

Secular trends of sleep-wake patterns in Hong Kong preschoolers

OBJECTIVE

To evaluate the secular trends of sleep-wake patterns of Hong Kong preschool children.

METHODS

Kindergartens from the four geographical regions of Hong Kong were randomly invited to take part in a sleep survey in 2012 and again in 2018. The parent-completed questionnaire provided information on socioeconomic status (SES), children's, and parental sleep-wake patterns. Secular trends and risk factors associated with short sleep duration in preschoolers were explored.

RESULTS

A sample of 5048 preschool children was included in the secular comparison, with 2306 and 2742 from the 2012 and 2018 surveys, respectively. A higher percentage of children in 2018 (41.1% vs 26.7%, p < 0.001) did not achieve the recommended sleep duration. During the survey years, sleep duration decreased by 13 ([95%CI: 18.5 to -8.1]) and 18 min ([95%CI: 23.6 to -12.2]) on weekdays and weekends, respectively. The overall trend of nap decrease was not significant. Sleep onset latency significantly increased on both weekdays (6 min [95%CI: 3.5 to 8.5]) and weekends (7 min [95%CI: 4.7 to 9.9]). Children's sleep duration was positively correlated with parental sleep duration with a correlation coefficient ranging from 0.16 to 0.27 (p < 0.001).

CONCLUSIONS

A significant proportion of Hong Kong preschool children did not achieve the recommended amount of sleep. A downward secular trend in sleep duration was observed during the survey period. Public health measures to improve sleep duration in preschool children should be a high priority.

The association between multidimensional sleep health and migraine burden among patients with episodic migraine

STUDY OBJECTIVES

Using the Sleep Regularity, Satisfaction, Alertness, Timing, Satisfaction, and Duration (Ru-SATED) sleep health framework, we examined the association between multidimensional sleep health and headache burden in a cohort of 98 adults with episodic migraine.

METHODS

Participants wore wrist actigraphs and completed twice-daily electronic diaries regarding sleep, headaches, and other health habits for 6 weeks. We calculated separate composite sleep health scores from diary and actigraphy assessed measures using the Ru-SATED framework. We used adjusted multivariable linear regression models to examine the association between composite sleep health scores and headache frequency, duration, and pain intensity.

RESULTS

Among 98 participants (mean age: 35 ± 12 years; 87.8% female), 83 had healthy ranges in ≥ 3 sleep dimensions. In models adjusted for age, sex, menopausal status, physical activity and alcohol intake, good sleep health was associated with fewer headache days/month (actigraphy: 3.1 fewer days; 95% confidence interval: 0.9, 5.7; diary: 4.0 fewer days; 95% confidence interval: 1.1, 6.9). Results did not change substantively with further adjustment for stress and depressive symptoms. We did not observe an association between sleep health and headache duration or intensity, respectively.

CONCLUSIONS

Among patients with episodic migraine, good multidimensional sleep health, but not the majority of singular dimensions of sleep, is associated with approximately 3-4 fewer headache days/month. In addition, there was no association with headache duration or intensity. These findings highlight the importance of assessing multiple dimensions of sleep and suggest that improving sleep health may be a potential clinical strategy to reduce headache frequency.

CITATION

Yoo A, Vgontzas A, Chung J, et al. The association between multidimensional sleep health and migraine burden among patients with episodic migraine. J Clin Sleep Med. 2023;19(2):309-317.

The Architecture of Early Childhood Sleep Over the First Two Years

INTRODUCTION

The architecture and function of sleep during infancy and early childhood has not been fully described in the scientific literature. The impact of early sleep disruption on cognitive and physical development is also under-studied. The aim of this review was to investigate early childhood sleep development over the first two years and its association with neurodevelopment.

METHODS

This review was conducted according to the 2009 PRISMA guidelines. Four databases (OVID Medline, Pubmed, CINAHL, and Web of Science) were searched according to predefined search terms.

RESULTS

Ninety-three studies with approximately 90,000 subjects from demographically diverse backgrounds were included in this review. Sleep is the predominant state at birth. There is an increase in NREM and a decrease in REM sleep during the first two years. Changes in sleep architecture occur in tandem with development. There are more studies exploring sleep and early infancy compared to mid and late infancy and early childhood.

DISCUSSION

Sleep is critical for memory, learning, and socio-emotional development. Future longitudinal studies in infants and young children should focus on sleep architecture at each month of life to establish the emergence of key characteristics, especially from 7-24 months of age, during periods of rapid neurodevelopmental progress.

Sleep quality and quantity determined by polysomnography in mechanically ventilated critically ill patients randomized to dexmedetomidine or placebo

BACKGROUND

Abnormal sleep is commonly observed in the ICU and is associated with delirium and increased mortality. If sedation is necessary, it is often performed with gamma-aminobutyric acid agonists such as propofol or midazolam leading to an absence of restorative sleep. We aim to evaluate the effect of dexmedetomidine on sleep quality and quantity.

METHODS

Thirty consecutive patients were included. The study was conducted as a double-blinded, randomized, placebo-controlled trial with two parallel groups: 20 patients were treated with dexmedetomidine, and 10 with placebo. Two 16 h of polysomnography recordings were done for each patient on two consecutive nights. Patients were randomized to dexmedetomidine or placebo after the first recording, thus providing a control recording for all patients. Dexmedetomidine was administered during the second recording (6 p.m.-6 a.m.).

OBJECTIVE

To compare the effect of dexmedetomidine versus. placebo on sleep - quality and quantity.

PRIMARY OUTCOME

Sleep quality, total sleep time (TST), Sleep efficiency (SE), and Rapid Eye Movement (REM) sleep determined by Polysomnography (PSG).

SECONDARY OUTCOME

Delirium and daytime function determined by Confusion Assessment Method of the Intensive Care Unit and physical activity. Alertness and wakefulness were determined by RASS (Richmond Agitation and Sedation Scale).

RESULTS

SE were increased in the dexmedetomidine group by; 37.6% (29.7;45.6 95% CI) versus 3.7% (-11.4;18.8 95% CI) (p < .001) and TST were prolonged by 271 min. (210;324 95% CI) versus 27 min. (-82;135 95% CI), (p < .001). No significant difference in REM sleep, delirium physical activity, or RASS score was found except for RASS night two.

CONCLUSION

Total sleep time and sleep efficiency were significantly increased, without elimination of REM sleep, in mechanically ventilated ICU patients randomized to dexmedetomidine, when compared to a control PSG recording performed during non-sedation/standard care.

Sleep staging in the ICU with heart rate variability and breathing signals. An exploratory cross-sectional study using deep neural networks

Introduction: To measure sleep in the intensive care unit (ICU), full polysomnography is impractical, while activity monitoring and subjective assessments are severely confounded. However, sleep is an intensely networked state, and reflected in numerous signals. Here, we explore the feasibility of estimating conventional sleep indices in the ICU with heart rate variability (HRV) and respiration signals using artificial intelligence methods Methods: We used deep learning models to stage sleep with HRV (through electrocardiogram) and respiratory effort (through a wearable belt) signals in critically ill adult patients admitted to surgical and medical ICUs, and in age and sex-matched sleep laboratory patients Results: We studied 102 adult patients in the ICU across multiple days and nights, and 220 patients in a clinical sleep laboratory. We found that sleep stages predicted by HRV- and breathing-based models showed agreement in 60% of the ICU data and in 81% of the sleep laboratory data. In the ICU, deep NREM (N2 + N3) proportion of total sleep duration was reduced (ICU 39%, sleep laboratory 57%, p < 0.01), REM proportion showed heavy-tailed distribution, and the number of wake transitions per hour of sleep (median 3.6) was comparable to sleep laboratory patients with sleep-disordered breathing (median 3.9). Sleep in the ICU was also fragmented, with 38% of sleep occurring during daytime hours. Finally, patients in the ICU showed faster and less variable breathing patterns compared to sleep laboratory patients Conclusion: The cardiovascular and respiratory networks encode sleep state information, which, together with artificial intelligence methods, can be utilized to measure sleep state in the ICU.

Qualitative Findings for Supporting Newly Graduated Nurse and Teacher Sleep During Their First Year

BACKGROUND

New graduate role transition for nurses and teachers is stressful. Poor adaptation may manifest as insomnia, which has implications for the new professionals, their employers, and the public served. This study examines factors that impact new graduate sleep, with the aim of identifying perceived helps and hindrances to sleep-during-transition.

METHODS

Targeted content analysis of transcripts from a larger longitudinal mixed methods study comparing new graduate sleep during their first year of practice. Study participants (N = 21) answered questions in the final interview regarding the most positive and negative impact(s) on sleep during the transition year. Transcripts were analyzed and compared based on the new graduate sleep typology (i.e., Got Better, Got Worse, Stayed Varied) which emerged from the parent study.

FINDINGS

Most participants, regardless of sleep type, identified a person/group as most positively impacting sleep. They identified work thoughts, stress/anxiety, people, work hours/sleep schedules, and environmental factors as negatively impacting sleep. Work thoughts and stress/anxiety were mentioned together and most frequently by participants in all three sleep types.

CONCLUSION/APPLICATIONS TO PRACTICE

This study provided insight into new graduate nurse and teacher sleep during transition. Support persons and/or groups may be essential regardless of sleep type. Thought management/stress mitigation strategies and good sleep hygiene may also improve the sleep experiences of these new professionals. Occupational health nurses can support sleep-during-transition among new nurses and teachers by acting as sleep advocates. They may also identify a need for medical intervention and/or sleep specialists and should promote fatigue risk mitigating policies.

Prevalence of sleep disorders among first responders for medical emergencies: A meta-analysis

Background

Shift work and irregular work schedules among first responders have been associated with physical and psychological problems such as sleep disorders. We conducted the first meta-analysis to explore and estimate the prevalence of sleep disorders among first responders for medical emergencies.

Methods

We searched four databases: Web of Science, Psych Info, CINAHL, and PubMed. The Generalized Linear Mixed model (GLMM) was used to estimate the prevalence estimates of sleep disorders in R software and the DerSimonian-Lard random-effects model in Comprehensive Meta-Analysis was used to explore associated comorbidities for OSA and insomnia, presented as odds ratios (ORs) and confidence intervals (CIs). The Cochran's Q, τ², and the statistics were used to assess heterogeneity and the moderator analysis was conducted to identify moderator variables.

Results

Twenty-eight studies with 100 080 first responders were included from the total of 1119 studies retrieved from the databases. The prevalence rates for sleep disorders were 31% (95% CI = 15%-53%) for shift work disorder (SWD), 30% (95% CI = 18%-46%) for obstructive sleep apnea (OSA), 28% (95% CI = 19%-39%) for insomnia, 28% (95% CI = 24%-33%) for excessive daytime sleepiness (EDS), 2% (95% CI = 1%-4%) for restless leg syndrome, and 1% (95% CI = 0%-5%) for narcolepsy. Anxiety (OR = 2.46; 95% CI = 1.99%-3.03%), cardiovascular disease (CVD) (OR = 2.03; 95% CI = 1.43-2.88), diabetes mellitus (DM) (OR = 1.93; 95% CI = 1.41-2.65), depression (OR = 1.89; 95% CI = 1.01-3.56), gastroesophageal reflux disease (GERD) (OR = 1.83; 95% CI = 150-2.22), and post-traumatic stress disorder (PTSD) (OR = 1.78; 95% CI = 1.33-2.39) were associated with OSA. Depression (OR = 9.74; 95% CI = 4.67-20.3), anxiety (OR = 9.22; 95% CI = 3.81-22.3), and PTSD (OR = 7.13; 95% CI = 6.27-8.10) were associated with insomnia. Age, gender, first responders, continent, study quality, study design, and assessment tool were significant moderator variables for OSA, insomnia, and EDS.

Conclusions

This meta-analysis found a substantially high prevalence of sleep disorders including SWD, OSA, insomnia, and EDS among first responders for medical emergencies. Early assessment and management of sleep disorders among first responders is necessary to promote good, quality sleep to help prevent anxiety, depression, CVD, DM, GERD, and PTSD.

Acculturation and depression are associated with short and long sleep duration among Mexican Americans in NHANES 2005-2018

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Length of time in the US was associated with long sleep duration.

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Individuals who speak majority English had higher odds of short sleep duration.

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Depression severity was linked to short and long sleep duration.

Acculturation and depression are linked to poor sleep quality and sleep problems that may explain ongoing health disparities for Hispanics/Latinos. We examined the associations of acculturation, depression, and sleep duration among the Mexican American population. We used a multinomial logistic regression model on cross-sectional data from the 2005–2018 National Health and Nutrition Examination Survey on 4,700 Mexican American adults aged ≥18 years old. The outcome of sleep duration was operationalized as short (≤6 h), optimal (7–8 h), and long (≥9 h). Acculturation was constructed using years living in the U.S. and language(s) spoken at home (majority Spanish, English and Spanish equally, majority English). Depression severity was assessed using the 9-item Patient Health Questionnaire. Covariates included gender, age, marital status, income, and U.S. citizenship. Speaking majority English (Adjusted Odds Ratio (AOR) = 1.23; 95% Confidence Interval (CI) = 1.00–1.52) and mild (AOR = 1.63; 95%CI = 1.32–2.01), moderate (AOR = 1.94; 95%CI = 1.43–2.63), and moderately severe/severe (AOR = 2.58; 95%CI = 1.72–3.88) levels of depression were significantly associated with short sleep duration. Living in the U.S. for ≥10 years (AOR = 1.61; 95%CI = 1.17–2.23) and moderately severe/severe depression (AOR = 2.30; 95%CI = 1.34–3.93) were significantly associated with long sleep duration. Our results provide additional evidence of a link between acculturation, depression, and short and long sleep duration among the Mexican American population. Understanding the sleep health of this population is important for informing future public health interventions and research. Additional investigation into the relationship between acculturation/depression and other sleep health measures among this population is warranted.

Sleep Quality Worsens While Perceived Stress Improves in Healthcare Workers over Two Years during the COVID-19 Pandemic: Results of a Longitudinal Study

The purpose of the study was to measure changes in sleep quality and perceived stress and their interrelationships in a sample of healthcare workers two years post the COVID-19 pandemic. Using a cohort design, data were collected from frontline healthcare workers (FLHCW, n = 70) and non-frontline healthcare workers (NFLHCW, n = 74) in April 2020 (T1) and in February 2022 (T2). The Pittsburgh Sleep Quality Index (PSQI) and the Perceived Stress Scale (PSS-10) were administered at both time points. There were no differences in sleep quality or perceived stress between FLHCW and NFLHCW at either timepoint. For the entire sample, the PSQI scores at T2 were significantly higher than at T1 (7.56 ± 3.26 and 7.25 ± 3.29, respectively) (p = 0.03, Cohen’s d = 0.18). PSS-10 scores at T2 were significantly lower than at T1 (19.85 ± 7.73 and 21.13 ± 7.41, respectively) (p = 0.001, Cohen’s d = 0.78). Baseline sleep quality PSQI (T1) was a significant predictor for changes in sleep quality. During the initial months of the outbreak of the COVID-19 pandemic, poor sleep quality and perceived stress were common for healthcare workers. Two years into the pandemic, the perceived stress was reduced, but sleep quality worsened.

Sleep and Professional Burnout in Nurses, Nursing Technicians, and Nursing Assistants During the COVID-19 Pandemic

BACKGROUND

The COVID-19 pandemic may trigger sleep disorders and burnout in nursing professionals.

PURPOSE

This study was designed to describe the occurrence of sleep disorders and burnout in a nursing team during the COVID-19 pandemic and to identify the associated factors.

METHODS

A cross-sectional approach was used. The questionnaire was administered via the Internet. All of the participants were nursing professionals who had provided care during the COVID-19 pandemic, and data were collected between June and August 2020. Sociodemographic and work characterization instruments, the Jenkins Sleep Scale, and the Maslach Burnout Inventory were used.

RESULTS

Five hundred seventy-two nursing professionals (nurses, nursing technicians, and nursing assistants) responded. Slightly over one quarter (26.4%) presented a sleep disorder, and 17.3% presented burnout. Professional category was a factor found to be associated with having a sleep disorder. Moreover, a lower prevalence both of disorders and of starting to use sleep medication was found among nurses than nursing assistants. Moreover, an association was found between having a high level of emotional exhaustion burnout and being a nursing technician, having a higher number of patients needing care, and starting to use sleep medication. The level of burnout related to depersonalization was significantly higher for nursing assistants, those with a weekly workload of 50 hours or more, and those starting to use sleep medication. Furthermore, burnout related to personal accomplishment was significantly higher in those starting to use sleep medication. Among the participants with sleep disorders, according to Jenkins Sleep Scale results, all of the participants presented a high or moderate level of emotional exhaustion and a high level of burnout related to personal accomplishment.

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

The findings indicate that the incidence of sleep disorders and burnout were high among nursing professionals during the COVID-19 pandemic and mainly related with starting to use sleep medication. The results demonstrate the importance of detecting and assessing the frequency of sleep disorders and professional exhaustion. Interventions that aim to improve sleep quality and working conditions for these professionals should be developed.

Sleep and behavioral problems in preschool-age children with Down syndrome

Sleep is a major concern, especially in people with Down Syndrome (DS). Beyond Obstructive Sleep Apnea, a number of other sleep difficulties have been reported in children with DS, such as delayed sleep onset, night-time awakenings, and early morning awakenings. The detrimental effect of sleep difficulties seems to contribute to and exacerbate the cognitive and behavioral outcomes of DS. Although the screening for sleep disorders is recommended early in age in DS, only a few studies have evaluated the sleep profile in preschool-age children with DS. The aim of the current study was to assess the association between sleep disturbances and behavioral problems in a group of preschool-age children with DS, by means of a feasible and easy-to-administer parent-report questionnaires. Seventy-one preschool-age children with DS, ranging in age from 3 to 5.11 years, were included in this retrospective study. Sleep disturbances were evaluated by means of the Sleep Disturbance Scale for Children, while emotional and behavioral problems by means of the Child Behavior Checklist. Sleep breathing disorders were the most frequent sleep difficulties reported by parents. Moreover, children with clinical scores in total sleep problems exhibited elevation of psychopathological symptoms, namely Total problems, Affective problems, Anxiety problems, Pervasive Developmental Problems, and Attention Deficit/Hyperactivity Problems. The identification of the broader connection between sleep difficulties and emotional and behavioral problems in preschool-age children with DS leads to important considerations for intervention.

What are the respiratory health research priorities in Alberta, Canada? A stakeholder consultation

OBJECTIVE

The Respiratory Health Strategic Clinical Network (RHSCN) was launched to facilitate respiratory and sleep health through implementation of innovative, patient-centred, evidence-informed coordinated services in Alberta. In collaboration with project partners, the RHSCN aimed to determine the respiratory research priorities for Alberta.

DESIGN

The four phases of this research prioritisation project were (1) identifying research questions from stakeholders, (2) determining which research questions had been answered in existing literature, (3) prioritising unanswered questions and (4) finalising the priorities through an inperson workshop.

SETTING

The study occurred in Alberta, Canada over a 2-year period beginning in March 2017.

PARTICIPANTS

A total of 448 patients, clinicians and other stakeholders consented to participate in the survey.

RESULTS

A total of 595 possible questions were submitted, with 343 unique questions identified. Of the questions, 94 were out of scope, 155 answered by existing literature and 10 were combined with others, while 83 were determined to be unanswered in the literature. Stakeholders were surveyed again to prioritise the remaining 83 questions and they were reviewed by the project's Steering Committee (clinicians and patients). At the inperson workshop, the Steering Committee identified 17 research topics as priority areas for respiratory and sleep research in Alberta.

CONCLUSION

A stakeholder-led research prioritisation process identified optimal clinical management/follow-up, equitable access to services, and management of social, psychological and mental health issues related to respiratory/sleep health as priority research areas.

Sleep Deficiency in Young Children

There is growing public health concern about the high prevalence of sleep deficiency in early childhood and the associated risk for sleep-associated poor health outcomes, including metabolic, cardiovascular, and mental health. The recent shift to conceptualize sleep health as a multidimensional construct, influenced by socioecological factors, highlights the potential role of sleep in health disparities. Understanding the development of sleep health and the emergence of sleep disorders in early life is a current priority in pediatric sleep research. Future behavioral sleep interventions should consider the multiple socioecological influences on children's sleep health and be tested using inclusive sampling methods.

Determinants of Sleep Disorders and Occupational Burnout among Nurses: A Cross-Sectional Study

Background: The aim of the study was to assess the determinants of the sleep disorders that occur among nurses working in a shift system by assessing the influence of sociodemographic factors, the impact of shift work, and the occurrence of occupational burnout. Methods: The study included 300 nurses who work shifts in the Silesian Region (Poland). The research was conducted using standardized research tools: the Karolinska Sleepiness Scale (KSS), the Epworth Sleepiness Scale (ESS), the Athens Insomnia Scale (AIS), and the Maslach Burnout Inventory (MBI). Results: Among the sociodemographic factors, in the KSS analysis, sleep disorders were most common in men (CI: 0.038; p < 0.001), in divorced individuals (CI: 1.436; p = 0.045), and in individuals who were overweight (CI: 1.927; p = 0.026). Multiple linear regression showed that sleep disorders (p < 0.001) were an independent predictor of MBI among nurses who worked shifts. Conclusions: Sleep disturbances affect the burnout of nurses who work shifts.

Dexmedetomidine and sleep quality in mechanically ventilated critically ill patients: study protocol for a randomised placebo-controlled trial

INTRODUCTION

Sleep deprivation, which is a common complication in the intensive care unit (ICU), is associated with delirium and increased mortality. Sedation with gamma-aminobutyric acid agonists (propofol, benzodiazepine) results in significant disturbance of the sleep architecture. Dexmedetomidine is a lipophilic imidazole with an affinity for α₂-adrenoceptors and it has sedative and analgesic properties. It has been reported to enhance sleep efficiency, thus sedate while preserving sleep architecture.

METHODS AND ANALYSIS

Thirty consecutive patients are planned to be included, at the Department of Anesthesia and Intensive Care at the Hospital of Southwest Jutland, Denmark. The study is a double-blinded, randomised, controlled trial with two parallel groups (2:1 allocation ratio). Screening and inclusion will be done on day 1 from 8:00 to 16:00. Two 16 hours PSG (polysomnography) recording will be done starting at 16:00 on day 1 and day 2. Randomisation is performed if the first recording is of acceptable quality, otherwise the patient is excluded before randomisation. Dexmedetomidine/placebo will be administered during the second recording from 18:00 on day 2 to 6:00 on day 3.

PRIMARY ENDPOINT

Improvement of total sleep time and sleep quality of clinical significance determined by PSG.

SECONDARY ENDPOINTS

Sleep phases determined by PSG. Daytime function and delirium determined by Confusion Assessment Method-ICU. Alertness and wakefulness determined by Richmonde Agitation Sedation Scale. The objective is to compare the effect of dexmedetomidine versus placebo on sleep quality in critical ill mechanically ventilated patients.

ETHICS AND DISSEMINATION

The trial investigate the potential benefit of dexmedetomidine on clinically relevant endpoints. If a beneficial effect is shown, this would have a large impact on future treatment of mechanically ventilated critically ill patients. Publication in peer-reviewed journal are plannedand the study has been approved by the National Committee on Health Research Ethics (ID:S-20180214).

TRIAL REGISTRATION NUMBER

EudraCT (2017-001612-11DK) and Danish National Committee on Health Research Ethics (ID:S-20180214). The study related to pre-results.