Objective vs. subjective measurements of sleep in depressed insomniacs: first night effect or reverse first night effect?

A scoping review of the effect of chronic stretch training on sleep quality in people with sleep disorders

PURPOSE

The widespread and health-detrimental sleep disorders have resulted in stretching exercises being investigated as a non-drug solution for enhanced sleep quality. However, a comprehensive understanding of the impact of stretching exercises on individuals with sleep disorders is lacking.

METHODS

This scoping review systematically maps the existing literature and identifies research gaps on the impact of stretching exercises on sleep quality in individuals with sleep disorders.

RESULTS

Sixteen eligible studies were included, where the weighted mean changes indicate a positive trend in sleep quality improvement, ranging from trivial to very large magnitudes. However, concerning the individual study results only 5 out of 16 studies reported significant improvements. Notable enhancements include a small 1.22% overall sleep quality improvement, a large 6.51% reduction in insomnia severity, a large 8.88% increase in sleep efficiency, a moderate 4.36% decrease in sleep onset latency, a large 8.27% decrease in wake after sleep onset, and a very large 14.70% improvement in total sleep time. Trivial changes are noted in sleep duration (0.58%), sleep disturbance reduction (0.07%), and daytime dysfunction reduction (0.19%). Likely mechanisms for the improvement of sleep include autonomic nervous system modulation, muscle tension relief, cortisol regulation, enhanced blood circulation, and psychological benefits such as stress reduction and mood enhancement.

CONCLUSION

There is little evidence that stretching exercises positively impact sleep quality in individuals with sleep disorders. Additionally, further research is vital for designing optimal protocols, understanding of the long-term effects, and clarification of the mechanisms.

Polysomnographic parameters associated with cognitive function in patients with major depression and insomnia

OBJECTIVE

To examine whether objective sleep parameters are associated with cognitive function (CF) in patients with major depressive disorder (MDD) with chronic insomnia (CI) and whether the severity of these disorders is related to CF.

METHOD

Thirty patients with MDD with CI attending a tertiary care institution underwent two consecutive nights of polysomnographic (PSG) recording and a battery of neuropsychological tests, which included episodic memory, sustained attention, working memory, and executive function. The severity of MDD and CI was assessed by clinical scales. We examined the relationship between PSG parameters and CF, as well as whether the severity of the disorders is related to CF.

RESULTS

Linear regression analysis revealed that total sleep time (TST) was positively associated with higher learning and recall of episodic memory, as well as better attention. Slow-wave sleep (SWS) showed a positive association with better working memory. Furthermore, wake after sleep onset (WASO) was negatively associated with episodic memory and lower attention. No significant relationships were found between the severity of MDD or CI with CF.

CONCLUSION

Both sleep duration and depth are positively associated with several aspects of CF in patients with MDD with CI. Conversely, a lack of sleep maintenance is negatively related to CF in these patients. These findings could help identify modifiable therapeutic targets to reduce CF impairment.

How emotions impact sleep: A quantitative review of experiments

Although sleep and emotional processes are recognized as mutually dependent, the causal impact of emotions on sleep has been comparatively neglected. To appraise evidence for the causal influence of emotions on sleep, a meta-analysis of the existing experimental literature evaluated the strength, form, and context of experimental effects of emotion inductions on sleep parameters (k = 31). Quality of experiments was evaluated, and theoretically-relevant features were extracted and examined as moderating factors of observed effects (i.e., sleep parameter, design, sleep context, types of emotion inductions and emotions). Random-effect models were used to aggregate effects for each sleep parameter, while-mixed effect models examined moderators. There was a significant impact of emotion inductions on delayed sleep onset latency (D = 3.36 min, 95%CI [1.78, 4.94], g = 0.53), but not other parameters. There was little evidence of publication bias regarding sleep-onset latency effect, the studies overall were heterogeneous, sometimes of limited methodological quality, and could only detect moderate-to-large impacts. The findings supported the hypothesis that negative emotions delayed sleep onset, but evidence regarding other sleep parameters was inconclusive. The results call for more targeted investigation to disambiguate distinct features of emotions and their import for sleep.

First-night effect in insomnia disorder: a systematic review and meta-analysis of polysomnographic findings

Polysomnographic studies have been performed to investigate the first-night effect in insomnia disorder. However, these studies have revealed discrepant findings. This meta-analysis aimed to summarise and quantify the characteristics of the first-night effect in insomnia disorder. We performed a systematic search of the PubMed, Medline, EMBASE, Web of Science and PsycINFO databases to identify studies published through October 2019. A total of 11,862 articles were identified, and seven studies with eight independent populations were included in the meta-analysis. A total of 639 patients with insomnia disorder and 171 healthy controls underwent more than 2 consecutive nights of in-laboratory polysomnography. Pooled results demonstrated that both variables of sleep continuity and sleep architecture, other than slow-wave sleep were significantly altered in the first-night effect in insomnia disorder. Furthermore, the results indicated that patients with insomnia disorder had a disruption of sleep continuity in the first-night effect, including increased sleep onset latency and reduced total sleep time, compared to healthy controls. Overall, the findings show that patients with insomnia disorder experience the first-night effect, rather than reverse first-night effect, and the profiles of the first-night effect in patients with insomnia are different from healthy controls. These indicate that an adaptation night is necessary when sleep continuity and sleep architecture is to be studied in patients with insomnia disorder. More well-designed studies with large samples are needed to confirm the results.

Waking Up to the Issue! Research Inattention and Sex-Related Differences Warrant More Sleep Studies in Female Athletes

Understanding sleep patterns and behaviors of athletes is essential for developing targeted sleep-based interventions for implementation in practice. However, more than double the number of sleep studies have examined male athletes compared with female athletes, making the current understanding of sleep patterns, behaviors, and interventions among athletes disproportionately indicative of men. Consequently, this review demonstrates the need for more female-specific sleep data among athlete populations due to research inattention and sex-related differences. Specifically, this review identifies variations in sleep patterns and behaviors between male and female athletes, as well as physiological and lifestyle factors that potentially affect sleep patterns and behaviors across the lifespan, specifically in female athletes. In this regard, evidence suggests some female athletes experience longer sleep durations and better objective sleep quality, but similar or worse subjective sleep quality compared with male athletes. Additionally, scheduling training in the morning or throughout the day may benefit sleep in some female athletes. Considering sleep disorders, women may be at greater risk for insomnia and restless legs syndrome compared with men, which may be attributed to pregnancy, as well as a higher prevalence of anxiety and depressive symptoms, iron deficiency without anemia, and use of psychotropic medication among women. Finally, the menstrual cycle, menstrual disorders, oral contraceptive use, and the postpartum period have been shown to exert detrimental effects on sleep patterns and behaviors and should theoretically be considered when monitoring and managing sleep in female athletes.

Evaluating an under-mattress sleep monitor compared to a peripheral arterial tonometry home sleep apnea test device in the diagnosis of obstructive sleep apnea

STUDY OBJECTIVES

To evaluate whether or not the apnea-hypopnea index (AHI) from a peripheral arterial tonometry (PAT) home sleep apnea test (HSAT) is equivalent to the AHI provided by the mean of one, three, or seven nights from the Withings Sleep Analyzer (WSA) under-mattress device.

METHODS

We prospectively enrolled patients with suspected OSA in whom a PAT-HSAT was ordered. Eligible patients used the WSA for seven to nine nights. PAT data were scored using the device's intrinsic machine learning algorithms to arrive at the AHI using both 3% and 4% desaturation criteria for hypopnea estimations (PAT3%-AHI and PAT4%-AHI, respectively). These were then compared with the WSA-estimated AHI (WSA-AHI).

RESULTS

Of 61 patients enrolled, 35 completed the study with valid PAT and WSA data. Of the 35 completers 16 (46%) had at least moderately severe OSA (PAT3%-AHI ≥ 15). The seven-night mean WSA-AHI was 2.13 (95%CI =  - 0.88, 5.14) less than the PAT3%-AHI, but 5.64 (95%CI = 2.54, 8.73) greater than the PAT4%-AHI. The accuracy and area under the receiver operating curve (AUC) using the PAT3%-AHI ≥ 15 were 77% and 0.87 and for PAT4%-AHI ≥ 15 were 77% and 0.85, respectively. The one-, three-, or seven-night WSA-AHI were not equivalent to either the 3% or 4% PAT-AHI (equivalency threshold of ± 2.5 using the two one-sided t-test method).

CONCLUSIONS

The WSA derives estimates of the AHI unobtrusively over many nights, which may prove to be a valuable clinical tool. However, the WSA-AHI over- or underestimates the PAT-AHI in clinical use, and the appropriate use of the WSA in clinical practice will require further evaluation.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04778748.

Sleep quality and emotion recognition in individuals with and without internalizing psychopathologies

BACKGROUND AND OBJECTIVES

Separate lines of research indicate sleep quality may impact recognition of facial expressions in anxious or depressed individuals. This study examined facial emotion recognition ability in the context of self-perceived sleep quality and anxiety and depression symptom levels in individuals with and without internalizing psychopathologies.

METHODS

Seventy anxious and/or depressed patients and 24 demographically matched healthy controls completed the Pittsburgh Sleep Quality Index (PSQI), standard measures of anxiety and depression, and an Emotion Recognition Task comprising negative and positive facial expressions.

RESULTS

Analyses of variance results revealed patients reported worse sleep quality than controls. Linear mixed-effects models indicated that all participants demonstrated better emotion recognition abilities in identifying positive versus negative emotions. For reaction time, but not accuracy, regression results revealed significant individual differences, with worse sleep quality predicting slower reaction times for positive faces, specifically for happiness.

LIMITATIONS

The use of a subjective measure of sleep quality and a specific behavioral paradigm for emotion recognition may impact the generalizability of the findings.

CONCLUSIONS

Associations between task performance and emotional valence of facial expression implies that poor sleep quality, beyond internalizing symptom severity, may disrupt emotion processing.

Evaluating Prediction Models of Sleep Apnea From Smartphone-Recorded Sleep Breathing Sounds

Importance

Breathing sounds during sleep are an important characteristic feature of obstructive sleep apnea (OSA) and have been regarded as a potential biomarker. Breathing sounds during sleep can be easily recorded using a microphone, which is found in most smartphone devices. Therefore, it may be easy to implement an evaluation tool for prescreening purposes.

Objective

To evaluate OSA prediction models using smartphone-recorded sounds and identify optimal settings with regard to noise processing and sound feature selection.

Design, Setting, and Participants

A cross-sectional study was performed among patients who visited the sleep center of Seoul National University Bundang Hospital for snoring or sleep apnea from August 2015 to August 2019. Audio recordings during sleep were performed using a smartphone during routine, full-night, in-laboratory polysomnography. Using a random forest algorithm, binary classifications were separately conducted for 3 different threshold criteria according to an apnea hypopnea index (AHI) threshold of 5, 15, or 30 events/h. Four regression models were created according to noise reduction and feature selection from the input sound to predict actual AHI: (1) noise reduction without feature selection, (2) noise reduction with feature selection, (3) neither noise reduction nor feature selection, and (4) feature selection without noise reduction. Clinical and polysomnographic parameters that may have been associated with errors were assessed. Data were analyzed from September 2019 to September 2020.

Main Outcomes and Measures

Accuracy of OSA prediction models.

Results

A total of 423 patients (mean [SD] age, 48.1 [12.8] years; 356 [84.1%] male) were analyzed. Data were split into training (n = 256 [60.5%]) and test data sets (n = 167 [39.5%]). Accuracies were 88.2%, 82.3%, and 81.7%, and the areas under curve were 0.90, 0.89, and 0.90 for an AHI threshold of 5, 15, and 30 events/h, respectively. In the regression analysis, using recorded sounds that had not been denoised and had only selected attributes resulted in the highest correlation coefficient (r = 0.78; 95% CI, 0.69-0.88). The AHI (β = 0.33; 95% CI, 0.24-0.42) and sleep efficiency (β = -0.20; 95% CI, -0.35 to -0.05) were found to be associated with estimation error.

Conclusions and Relevance

In this cross-sectional study, recorded sleep breathing sounds using a smartphone were used to create reasonably accurate OSA prediction models. Future research should focus on real-life recordings using various smartphone devices.

Association Between Pre-Stroke Subjective Sleep Status and Post-Stroke Cognitive Impairment: A Nationwide Multi-Center Prospective Registry

BACKGROUND

Although sleep disorders significantly increase the risk of cognitive impairment, literature is relatively scarce regarding the impact of sleep status on cognitive function in patients with acute ischemic stroke (AIS). We seek to study the association between pre-stroke subjective sleep status and cognitive function at 3 months after stroke.

PATIENTS AND METHODS

Data were analyzed for 1,759 AIS patients from the Impairment of Cognition and Sleep after Acute Ischemic Stroke or Transient Ischemic Attack in Chinese Patients Study (ICONS). Pre-stroke subjective sleep status was assessed by the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). Greater sleep fragmentation was defined as waking up in the middle of the night or early morning ≥3 times a week. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA) at 3 months after stroke. Primary endpoint was the incidence of post-stroke cognitive impairment (PSCI) at 3 months after stroke. The association between subjective sleep status and PSCI was evaluated using multivariable logistic regression.

RESULTS

PSCI occurred in 52.1% at 3 months after stroke. Patients with very bad sleep quality before stroke were at increased risk of PSCI (OR, 2.11; 95% CI, 1.11-4.03; P=0.03). Subgroup analysis found that the association between very bad sleep quality and PSCI was more evident among patients with high school education or above (OR, 5.73; 95% CI, 1.92-17.10; P for interaction=0.02). In addition, patients with greater sleep fragmentation before stroke were also at higher risk of PSCI (OR, 1.55; 95% CI, 1.20-2.01; P<0.01). Similarly, subgroup analysis showed that the risk of PSCI was more pronounced among patients without employment (OR, 2.45; 95% CI, 1.59-3.77; P for interaction=0.01).

CONCLUSION

Very bad sleep quality and greater sleep fragmentation before stroke were identified as independent risk factors for PSCI at 3 months after stroke.

Sleep quality: An evolutionary concept analysis

AIM

To clarify the meaning of the concept sleep quality.

BACKGROUND

Sleep loss and sleep quality are global health concerns. Poor sleep quality has significant adverse health outcomes. A clarification of the term is necessary to inform patients and healthcare providers, promote consistent theoretical and operational definitions in research, and develop prevention and treatment strategies.

DESIGN

Concept analysis.

DATA SOURCES

Scientific literature from electronic databases (CINAHL, PsycINFO, PubMED, Web of Science, and JSTOR) and definitions from online dictionaries.

REVIEW METHODS

Rodgers' Evolutionary method was applied to guide the concept analysis to identify and determine the attributes, antecedents, and consequences.

RESULTS

Sleep quality is defined as an individual's self-satisfaction with all aspects of the sleep experience. Sleep quality has four attributes: sleep efficiency, sleep latency, sleep duration, and wake after sleep onset. Antecedents include physiological (e.g., age, circadian rhythm, body mass index, NREM, REM), psychological (e.g., stress, anxiety, depression), and environmental factors (e.g., room temperature, television/device use), and family/social commitments. Good sleep quality has positive effects such as feeling rested, normal reflexes, and positive relationships. Poor sleep quality consequences include fatigue, irritability, daytime dysfunction, slowed responses, and increased caffeine/alcohol intake.

CONCLUSIONS

Sleep quality is essential, and poor sleep quality contributes to disease and poor health outcomes. Given the extensive consequences of poor sleep quality, nurses and clinicians are vital in instructing the importance of good sleep.

Hospitalized COVID-19 Patients Were Five Times More Likely to Suffer From Total Sleep Deprivation Compared to Non-COVID-19 Patients; an Observational Comparative Study

Objectives: Sleeping disorders are a common complaint in patients who suffer from an acute COVID-19 infection. Nonetheless, little is known about the severity of sleep disturbances in hospitalized COVID-19 patients, and whether these are caused by disease related symptoms, hospitalization, or the SARS-CoV-2 virus itself. Therefore, the aim of this study was to compare the quality and quantity of sleep in hospitalized patients with and without COVID-19, and to determine the main reasons for sleep disruption. Methods: This was an observational comparative study conducted between October 1, 2020 and February 1, 2021 at the pulmonary ward of an academic hospital in the Netherlands. This ward contained both COVID-19-positive and -negative tested patients. The sleep quality was assessed using the PROMIS-Sleep Disturbance Short Form and sleep quantity using the Consensus Sleep Diary. Patient-reported sleep disturbing factors were summarized. Results: A total of 79 COVID-19 patients (mean age 63.0, male 59.5%) and 50 non-COVID-19 patients (mean age 59.5, male 54.0%) participated in this study. A significantly larger proportion of patients with COVID-19 reported not to have slept at all (19% vs. 4% of non-COVID-19 patients, p = 0.011). The Sleep quality (PROMIS total score) and quantity (Total Sleep Time) did not significantly differ between both groups ((median PROMIS total score COVID-19; 26 [IQR 17-35], non-COVID-19; 23 [IQR 18-29], p = 0.104), (Mean Total Sleep Time COVID-19; 5 h 5 min, non-COVID-19 mean; 5 h 32 min, p = 0.405)). The most frequently reported disturbing factors by COVID-19 patients were; 'dyspnea', 'concerns about the disease', 'anxiety' and 'noises of other patients, medical staff and medical devices'. Conclusion: This study showed that both patients with and without an acute COVID-19 infection experienced poor quality and quantity of sleep at the hospital. Although the mean scores did not significantly differ between groups, total sleep deprivation was reported five times more often by COVID-19 patients. With one in five COVID-19 patients reporting a complete absence of night sleep, poor sleep seems to be a serious problem. Sleep improving interventions should focus on physical and psychological comfort and noise reduction in the hospital environment.

Diagnostic accuracy of oximetry for obstructive sleep apnea: a study on older adults in a home setting

OBJECTIVES

Owing to the fact that obstructive sleep apnea (OSA) is an underreported disease, the strategy used for the diagnosis of OSA has been extensively dissected to devise a simplified process that can be accessed by the public health services. Polysomnography (PSG) type I, the gold standard for the diagnosis of OSA, is expensive and difficult to access by low-income populations. In this study, we aimed to verify the accuracy of the oxyhemoglobin desaturation index (ODI) in comparison to the apnea-hypopnea index (AHI) using a portable monitor.

METHODS

We evaluated 94 type III PSG home test results of 65 elderly patients (69.21±6.94 years old), along with information, such as the body mass index (BMI) and sex, using data obtained from a clinical trial database.

RESULTS

A significant linear positive correlation (r=0.93, p<0.05) was observed between ODI and AHI, without any interference from sex, BMI, and positional component. The sensitivity of ODI compared to that of AHI increased with an increase in the severity of OSA, while the specificity of ODI in comparison to that of AHI was high for all degrees of severity. The accuracy of ODI was 80.7% for distinguishing between patients with mild and moderate apnea and 84.4% for distinguishing between patients with moderate and severe apnea.

CONCLUSION

The ODI values obtained in uncontrolled conditions exhibited high sensitivity for identifying severe apnea compared to the AHI values, and correctly identified the severity of OSA in more than 80% of the cases. Thus, oximetry is promising strategy for diagnosing OSA.

Reconstruction of Pulse Wave and Respiration from Wrist Accelerometer During Sleep

OBJECTIVE

Nocturnal recordings of heart rate and respiratory rate usually require several separate sensors or electrodes attached to different body parts -- a disadvantage for at-home screening tests and for large cohort studies. In this paper, we demonstrate that a state-of-the-art accelerometer placed at subjects' wrists can be used to derive reliable signal reconstructions of heartbeat (pulse wave intervals) and respiration during sleep.

METHODS

Based on 226 full-night recordings, we evaluate the performance of our signal reconstruction methodology with respect to polysomnography. We use a phase synchronization analysis metrics that considers individual heartbeats or breaths.

RESULTS

The quantitative comparison reveals that pulse-wave signal reconstructions are generally better than respiratory signal reconstructions. The best quality is achieved during deep sleep, followed by light sleep N2 and REM sleep. In addition, a suggested internal evaluation of multiple derived reconstructions can be used to identify time periods with highly reliable signals, particularly for pulse waves. Furthermore, we find that pulse-wave reconstructions are hardly affected by apnea and hypopnea events.

CONCLUSION

During sleep, pulse wave and respiration signals can simultaneously be reconstructed from the same accelerometer recording at the wrist without the need for additional sensors. Reliability can be increased by internal evaluation if the reconstructed signals are not needed for the whole sleep duration.

SIGNIFICANCE

The presented methodology can help to determine sleep characteristics and improve diagnostics and treatment of sleep disorders in the subjects' normal sleep environment.

Lactobacillus fermentum PS150 promotes non-rapid eye movement sleep in the first night effect of mice

The first night effect (FNE) is a type of sleep disturbance caused by an unfamiliar environment, which leads to difficulty falling asleep and reduced sleep duration. Previously, we reported that Lactobacillus fermentum PS150 (PS150) improves sleep conditions in a pentobarbital-induced sleep mouse model. In this study, we aimed to evaluate the effect of PS150 on the FNE in mice. Briefly, mice were implanted with electrodes and orally administered PS150 for four weeks, and then the FNE was induced by cage changing. Analysis of polysomnographic signals revealed that intervention with PS150 restored non-rapid eye movement (NREM) sleep length under the FNE. Compared to diphenhydramine, a commonly used sleep aid, PS150 had no unwanted side effects, such as rapid eye movement (REM) sleep deprivation and fragmented sleep. Moreover, temporal analysis revealed that PS150 efficiently reduced both sleep latency and time spent restoring normal levels of REM sleep. Taken together, these results suggest that PS150 efficiently ameliorates sleep disturbance caused by the FNE. Additionally, V3–V4 16S rRNA sequencing revealed significant increases in Erysipelotrichia, Actinobacteria, and Coriobacteriia in fecal specimens of the PS150-treated group, indicating that PS150 induces gut microbiota remodeling.

Wrist actigraphic approach in primary, secondary and tertiary care based on the principles of predictive, preventive and personalised (3P) medicine

Abstract

Sleep quality and duration as well as activity-rest-cycles at individual level are crucial for maintaining physical and mental health. Although several methods do exist to monitor these parameters, optimal approaches are still under consideration and technological development. Wrist actigraphy is a non-invasive electro-physical method validated in the field of chronobiology to record movements and to allow for monitoring human activity-rest-cycles. Based on the continuous recording of motor activity and light exposure, actigraphy provides valuable information about the quality and quantity of the sleep–wake rhythm and about the amount of motor activity at day and night that is highly relevant for predicting a potential disease and its targeted prevention as well as personalisation of medical services provided to individuals in suboptimal health conditions and patients. Being generally used in the field of sleep medicine, actigraphy demonstrates a great potential to be successfully implemented in primary, secondary and tertiary care, psychiatry, oncology, and intensive care, military and sports medicines as well as epidemiological monitoring of behavioural habits as well as well-being medical support, amongst others.

Prediction of disease development and individual outcomes

Activity-rest-cycles have been demonstrated to be an important predictor for many diseases including but not restricted to the development of metabolic, psychiatric and malignant pathologies. Moreover, activity-rest-cycles directly impact individual outcomes in corresponding patient cohorts.

Targeted prevention

Data acquired by actigraphy are instrumental for the evidence-based targeted prevention by analysing individualised patient profiles including light exposure, sleep duration and quality, activity-rest-cycles, intensity and structure of motion pattern.

Personalised therapy

Wrist actigraphic approach is increasingly used in clinical care. Personalised measurements of sedation/agitation rhythms are useful for ICU patients, for evaluation of motor fatigue in oncologic patients, for an individual enhancement of performance in military and sport medicine. In the framework of personalised therapy intervention, patients can be encouraged to optimise their behavioural habits improving recovery and activity patterns. This opens excellent perspectives for the sleep-inducing medication and stimulants replacement as well as for increasing the role of participatory medicine by visualising and encouraging optimal behavioural patterns of the individual.

Cognitive behavioral therapy for insomnia (CBT-i) in patients with fibromyalgia: a systematic review and meta-analysis

PURPOSE

We aimed to evaluate the effectiveness of CBT-i in patients with fibromyalgia in comparison with other non-pharmacological treatments.

METHODS

Randomized controlled trials assessing the effects of CBT-i in adults with fibromyalgia, published in English or Spanish, were eligible. Electronic searches were performed using PubMed, Scopus, The Cochrane Library, WebOfKnowledge and Psicodoc databases in March 2021. The main outcome measures were sleep efficiency and sleep quality. Secondary outcomes included pain, depression, and anxiety.

RESULTS

Of 226 studies reviewed, five were included in the meta-analysis. CBT-i compared with non-pharmacological treatments showed no significant improvements in sleep efficiency (p = 0.05; standardized mean difference (SMD) [95% CI] 0.31 [-0.00 to 0.61]). CBT-i showed significant improvements in sleep quality (p = 0.009; SMD [95% CI] - 0.53 [-0.93 to -0.13]), pain (p = 0.002; SMD [95% CI] - 0.41 [-0.67 to -0.16]), anxiety (p = 0.001; SMD [95% CI] - 0.46 [-0.74 to 0.18]) and depression (p = 0.02; SMD [95% CI] - 0.33 [-0.61 to -0.05]), compared to non-pharmacological treatments. Effect sizes ranged from small to moderate.

CONCLUSIONS

CBT-i was associated with a significant improvement in sleep quality, pain, anxiety, and depression, although these results are retrieved from very few studies with only very low to low quality evidence. Trial registration: The review protocol was registered with PROSPERO (Record ID = CRD42016030161).IMPLICATIONS FOR REHABILITATIONCBT-i has been proven to improve sleep quality, pain, anxiety and depression, although with small effect sizes.Implementing hybrid CBT for pain and sleep or combining CBT and mindfulness may improve symptoms in people diagnosed with FM.This meta-analysis results highlight the need to enhance sleep management skills among people suffering from this health condition.

A Multi-Level Classification Approach for Sleep Stage Prediction With Processed Data Derived From Consumer Wearable Activity Trackers

Consumer wearable activity trackers, such as Fitbit are widely used in ubiquitous and longitudinal sleep monitoring in free-living environments. However, these devices are known to be inaccurate for measuring sleep stages. In this study, we develop and validate a novel approach that leverages the processed data readily available from consumer activity trackers (i.e., steps, heart rate, and sleep metrics) to predict sleep stages. The proposed approach adopts a selective correction strategy and consists of two levels of classifiers. The level-I classifier judges whether a Fitbit labeled sleep epoch is misclassified, and the level-II classifier re-classifies misclassified epochs into one of the four sleep stages (i.e., light sleep, deep sleep, REM sleep, and wakefulness). Best epoch-wise performance was achieved when support vector machine and gradient boosting decision tree (XGBoost) with up sampling were used, respectively at the level-I and level-II classification. The model achieved an overall per-epoch accuracy of 0.731 ± 0.119, Cohen's Kappa of 0.433 ± 0.212, and multi-class Matthew's correlation coefficient (MMCC) of 0.451 ± 0.214. Regarding the total duration of individual sleep stage, the mean normalized absolute bias (MAB) of this model was 0.469, which is a 23.9% reduction against the proprietary Fitbit algorithm. The model that combines support vector machine and XGBoost with down sampling achieved sub-optimal per-epoch accuracy of 0.704 ± 0.097, Cohen's Kappa of 0.427 ± 0.178, and MMCC of 0.439 ± 0.180. The sub-optimal model obtained a MAB of 0.179, a significantly reduction of 71.0% compared to the proprietary Fitbit algorithm. We highlight the challenges in machine learning based sleep stage prediction with consumer wearables, and suggest directions for future research.

Night-to-night variability in obstructive sleep apnea using peripheral arterial tonometry: a case for multiple night testing

STUDY OBJECTIVES

Night-to-night variability of obstructive sleep apnea severity (OSA) is considerable and may depend on the diagnostic modality used. We investigated the night-to-night variability using peripheral arterial tonometry (PAT).

METHODS

Home sleep apnea testing was performed in 51 patients during three consecutive nights using PAT. Patients referred to our sleep clinic were screened and prospectively recruited for this study. All recordings were automatically and manually scored according to the PAT scoring guidelines.

RESULTS

No systematic differences in pAHI were found between the nights. The night-to-night variability was comparable between manually and automatically scored data. PAT-derived apnea-hypopnea index (pAHI) varied in 35% of patients more than 10/h between the nights. The OSA severity of 24% of patients was misclassified when using one night compared to the average of all nights. On average, pAHI varied by 57% from night-to-night. The variability of pAHI could partially be explained by the variability of time spent in the supine position with more time supine leading to a higher pAHI. On measuring a subsequent night, 12-14% of patients spontaneously fulfilled the commonly accepted criteria for treatment success without any intervention.

CONCLUSIONS

With repeated recordings of PAT, we found no first night effect. However, there is considerable night-to-night variability similar to values found for polysomnography, which can partially be explained by the variability of time spent in the supine position. OSA severity was frequently misclassified due to the night-to-night variability. Our findings make a strong case for multiple testing in the diagnostic work-up of OSA patients.

No familiarization or 'first-night effect' evident when monitoring sleep using wrist actigraphy

Anecdotal reports suggest that the first night of sleep monitoring using a wrist-actigraphy monitor may result in impaired sleep when compared to subsequent nights, due to increased levels of anxiety and awareness of being monitored. This phenomenon has been seen in sleep laboratories with polysomnographic monitoring. However, this is yet to be established for wrist actigraphy monitoring in the research literature. A total of 240 healthy adult participants (177 male, 63 female; age range, 18-35 years) had their sleep monitored using wrist actigraphy over a period of five nights of 'normal' sleep (1,200 nights of data). Sleep variables including sleep latency, wake episodes, wake after sleep onset, awakenings per hour, time in bed, total sleep time and sleep efficiency % were evaluated across all nights of sleep. Comparisons were made using repeated measures ANOVAs, mean differences, range of mean differences, intraclass correlation coefficients (ICC) and Cohen's d effect sizes. There were no significant differences between the first night and subsequent nights for any of the measured sleep variables (p < .05) and all differences were associated with trivial effect sizes (d < 0.2). ICCs ranged from 0.35 to 0.62 (low to moderate). Despite claims of impaired sleep during the first night of sleep monitoring, our results indicate that a familiarization period may not be necessary when monitoring sleep in healthy participants using wrist actigraphy. However, the response is highly individual and further research is required to assess personality traits and responses to sleep monitoring.

Sleep Efficiency and Total Sleep Time in Individuals with Type 2 Diabetes with and without Insomnia Symptoms

There is increasing awareness of the high prevalence of insomnia symptoms in individuals with type 2 diabetes (T2D). Past studies have established the importance of measuring sleep parameters using measures of central tendency and variability. Additionally, subjective and objective methods involve different constructs due to the discrepancies between the two approaches. Therefore, this study is aimed at comparing the averages of sleep parameters in individuals with T2D with and without insomnia symptoms and comparing the variability of sleep parameters in these individuals. This study assessed the between-group differences in the averages and variability of sleep efficiency (SE) and total sleep time (TST) of 59 participants with T2D with and without insomnia symptoms. Actigraph measurements and sleep diaries were used to assess sleep parameter averages and variabilities calculated by the coefficient of variation across 7 nights. Mann-Whitney U tests were utilized to compare group differences in the outcomes. Validated instruments were used to assess the symptoms of depression, anxiety, and pain as covariates. Objective SE was found to be statistically lower on average (85.98 ± 4.29) and highly variable (5.88 ± 2.57) for patients with T2D and insomnia symptoms than in those with T2D only (90.23 ± 6.44 and 3.82 ± 2.05, respectively). The subjective average and variability of SE were also worse in patients with T2D and insomnia symptoms, with symptoms of depression, anxiety, and pain potentially playing a role in this difference. TST did not significantly differ between the groups on averages or in variability even after controlling for age and symptoms of depression, anxiety, and pain. Future studies are needed to investigate the underlying mechanisms of worse averages and variability of SE in individuals with T2D and insomnia symptoms. Additionally, prompting the associated risk factors of insomnia symptoms in individuals with T2D might be warranted.

An attempt to identify reproducible high-density EEG markers of PTSD during sleep

STUDY OBJECTIVES

We examined electroencephalogram (EEG) spectral power to study abnormalities in regional brain activity in post-traumatic stress disorder (PTSD) during sleep. We aimed to identify sleep EEG markers of PTSD that were reproducible across nights and subsamples of our study population.

METHODS

Seventy-eight combat-exposed veteran men with (n = 31) and without (n = 47) PTSD completed two consecutive nights of high-density EEG recordings in a laboratory. We performed spectral-topographical EEG analyses on data from both nights. To assess reproducibility, we used the first 47 consecutive participants (18 with PTSD) for initial discovery and the remaining 31 participants (13 with PTSD) for replication.

RESULTS

In the discovery analysis, compared with non-PTSD participants, PTSD participants exhibited (1) reduced delta power (1-4 Hz) in the centro-parietal regions during nonrapid eye movement (NREM) sleep and (2) elevated high-frequency power, most prominent in the gamma band (30-40 Hz), in the antero-frontal regions during both NREM and rapid eye movement (REM) sleep. These findings were consistent across the two study nights, with reproducible trends in the replication analysis. We found no significant group differences in theta power (4-8 Hz) during REM sleep and sigma power (12-15 Hz) during N2 sleep.

CONCLUSIONS

The reduced centro-parietal NREM delta power, indicating reduced sleep depth, and the elevated antero-frontal NREM and REM gamma powers, indicating heightened central arousal, are potential objective sleep markers of PTSD. If independently validated, these putative EEG markers may offer new targets for the development of sleep-specific PTSD diagnostics and interventions.

Effects of Passiflora incarnata Linnaeus on polysomnographic sleep parameters in subjects with insomnia disorder: a double-blind randomized placebo-controlled study

The purpose of the present double-blind randomized placebo-controlled clinical study was to investigate the effects of Passionflower on polysomnographic sleep parameters in subjects with insomnia disorder. A total number 110 adult participants (mean age = 40.47 ± 11.68, Female = 53.6%) met the inclusion criteria of insomnia disorder according to the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders). After randomization, patients received either the Passionflower extract or the placebo for 2 weeks. Patients underwent an overnight polysomnography and completed sleep diaries, Insomnia Severity Index, and Pittsburgh Sleep Quality Index. Within group comparisons were analyzed with paired t-tests or Wilcoxon's signed rank tests, and between-group comparisons were analyzed with independent t-tests or Mann-Whitney U Tests, as appropriate. Total sleep time (TST) was significantly increased in the Passionflower group compared with placebo (Passionflower vs placebo, 23.05 ± 54.26 vs -0.16 ± 53.12; P = 0.049). Sleep efficiency and wake after sleep onset (WASO) significantly improved after 2 weeks in the Passionflower group but there was no difference compared with the placebo group. The current study demonstrated the positive effects of Passionflower on objective sleep parameters including TST on polysomnography in adults with insomnia disorder. Further study is needed to investigate the clinical efficacy of Passionflower on insomnia.

Sleep, a Governor of Morbidity in PTSD: A Systematic Review of Biological Markers in PTSD-Related Sleep Disturbances

BACKGROUND

Sleep disturbances (SD) are the most impactful and commonly reported symptoms in post-traumatic stress disorder (PTSD). Yet, they are often resistant to primary PTSD therapies. Research has identified two distinct SDs highly prevalent in PTSD; insomnia and nightmares. Those who report SDs prior to a traumatic event are at greater risk for developing PTSD; highlighting that sleep potentially plays a role in PTSD's pathology. To further understand the pathobiological mechanisms that lead to the development of PTSD, it is first imperative to understand the interplay which exists between sleep and PTSD on a biological level. The aim of this systematic review is to determine if biological or physiological markers are related to SD in PTSD.

METHODS

A systematic literature search was conducted on the electronic databases; Medline, Embase, AMED and PsycINFO, using Medical Subject Headings and associated keywords.

RESULTS

Sixteen studies were included in the final analyses. Physiological makers of autonomic function, and biochemical markers of HPA-axis activity; inflammatory processes; and trophic factor regulation were related to the severity of SDs in PTSD.

CONCLUSION

These findings add to the growing literature base supporting a central focus on sleep in research aiming to define the pathophysiological processes which result in PTSD, as well as emphasising the importance of specifically targeting sleep as part of a successful PTSD intervention strategy. Resolving SDs will not only reduce PTSD symptom severity and improve quality of life but will also reduce all-cause mortality, hospital admissions and lifetime healthcare costs for those with PTSD. Limitations of the current literature are discussed, and key recommendations future research must adhere to are made within.

Alcohol use disorder and sleep disturbances: a feed-forward allostatic framework

The development of alcohol use disorder (AUD) involves binge or heavy drinking to high levels of intoxication that leads to compulsive intake, the loss of control in limiting intake, and a negative emotional state when alcohol is removed. This cascade of events occurs over an extended period within a three-stage cycle: binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation. These three heuristic stages map onto the dysregulation of functional domains of incentive salience/habits, negative emotional states, and executive function, mediated by the basal ganglia, extended amygdala, and frontal cortex, respectively. Sleep disturbances, alterations of sleep architecture, and the development of insomnia are ubiquitous in AUD and also map onto the three stages of the addiction cycle. During the binge/intoxication stage, alcohol intoxication leads to a faster sleep onset, but sleep quality is poor relative to nights when no alcohol is consumed. The reduction of sleep onset latency and increase in wakefulness later in the night may be related to the acute effects of alcohol on GABAergic systems that are associated with sleep regulation and the effects on brain incentive salience systems, such as dopamine. During the withdrawal/negative affect stage, there is a decrease in slow-wave sleep and some limited recovery in REM sleep when individuals with AUD stop drinking. Limited recovery of sleep disturbances is seen in AUD within the first 30 days of abstinence. The effects of withdrawal on sleep may be related to the loss of alcohol as a positive allosteric modulator of GABAA receptors, a decrease in dopamine function, and the overactivation of stress neuromodulators, including hypocretin/orexin, norepinephrine, corticotropin-releasing factor, and cytokines. During the preoccupation/anticipation stage, individuals with AUD who are abstinent long-term present persistent sleep disturbances, including a longer latency to fall asleep, more time awake during the night, a decrease in slow-wave sleep, decreases in delta electroencephalogram power and evoked delta activity, and an increase in REM sleep. Glutamatergic system dysregulation that is observed in AUD is a likely substrate for some of these persistent sleep disturbances. Sleep pathology contributes to AUD pathology, and vice versa, possibly as a feed-forward drive to an unrecognized allostatic load that drives the addiction process.

Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors

BACKGROUND

It has become possible for the new generation of consumer wristbands to classify sleep stages based on multisensory data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic parameters, including total sleep time, wake time, sleep efficiency (SE), and the ratio of each sleep stage. Nevertheless, its accuracy in measuring sleep stage transitions remains unknown.

OBJECTIVE

This study aimed to examine the accuracy of Fitbit Charge 2 in measuring transition probabilities among wake, light sleep, deep sleep, and rapid eye movement (REM) sleep under free-living conditions. The secondary goal was to investigate the effect of user-specific factors, including demographic information and sleep pattern on measurement accuracy.

METHODS

A Fitbit Charge 2 and a medical device were used concurrently to measure a whole night's sleep in participants' homes. Sleep stage transition probabilities were derived from sleep hypnograms. Measurement errors were obtained by comparing the data obtained by Fitbit with those obtained by the medical device. Paired 2-tailed t test and Bland-Altman plots were used to examine the agreement of Fitbit to the medical device. Wilcoxon signed-rank test was performed to investigate the effect of user-specific factors.

RESULTS

Sleep data were collected from 23 participants. Sleep stage transition probabilities measured by Fitbit Charge 2 significantly deviated from those measured by the medical device, except for the transition probability from deep sleep to wake, from light sleep to REM sleep, and the probability of staying in REM sleep. Bland-Altman plots demonstrated that systematic bias ranged from 0% to 60%. Fitbit had the tendency of overestimating the probability of staying in a sleep stage while underestimating the probability of transiting to another stage. SE>90% (P=.047) was associated with significant increase in measurement error. Pittsburgh sleep quality index (PSQI)<5 and wake after sleep onset (WASO)<30 min could be associated to significantly decreased or increased errors, depending on the outcome sleep metrics.

CONCLUSIONS

Our analysis shows that Fitbit Charge 2 underestimated sleep stage transition dynamics compared with the medical device. Device accuracy may be significantly affected by perceived sleep quality (PSQI), WASO, and SE.

Agreement between actigraphic and polysomnographic measures of sleep in adults with and without chronic conditions: A systematic review and meta-analysis

Wrist actigraphy (ACT) may overestimate sleep and underestimate wake, and the agreement may be lower in people with chronic conditions who often have poor sleep and low activity levels. The purpose of this systematic review is to compare the agreement between ACT and polysomnographic (PSG) measures of sleep in adults without chronic conditions and sleep complaints (healthy) and with chronic conditions. We conducted a systematic review and meta-analysis using PRISMA guidelines. We searched PubMed, OVIDEMBASE, OVIDMEDLINE, OVIDPsycINFO, CENTRAL, CINAHL, ClinicalTrials.gov, International Clinical Trials Registry, and Open Grey. We included 96 studies with a total of 4134 participants, of whom 762 (18.4) were healthy adults and 724 (17.5%) were adults with chronic conditions. Among adults with chronic conditions, ACT overestimated TST, compared to PSG [M = 22.42 min (CI 95%: 11.92, 32.91 min)] and SE [M = 5.21% (CI 95%: 1.41%-9.00%)]. ACT underestimated SOL [M = -7.70 min (CI 95%: -15.22, -0.18 min)], and WASO [M = -10.90 min (CI 95%: -26.01, 4.22 min)]. These differences were consistently larger between ACT and PSG sleep measures compared to healthy adults. Research is needed to better understand factors that influence the agreement between ACT and PSG among people with chronic conditions.

Relation between ambulatory actigraphy and laboratory polysomnography in insomnia practice and research

Actigraphy is increasingly used in practice and research studies because of its relative low cost and decreased subject burden. How multiple nights of at-home actigraphy compare to one independent night of in-laboratory polysomnography (PSG) has not been examined in people with insomnia. Using event markers (MARK) to set time in bed (TIB) compared to automatic program analysis (AUTO) has not been systematically evaluated. Subjects (n = 30) meeting DSM-5 criteria for insomnia and in-laboratory PSG sleep efficiency (SE) of <85% were studied. Subjects were free of psychiatric, sleep or circadian disorders, other chronic conditions and medications that effect sleep. Subjects had an in-laboratory PSG, then were sent home for 7 nights with Philips Actiwatch Spectrum Plus. Data were analysed using Philips Actiware version 6. Using the mean of seven nights, TIB, total sleep time (TST), SE, sleep-onset latency (SOL) and wake after sleep onset (WASO) were examined. Compared to PSG, AUTO showed longer TIB and TST and less WASO. MARK only differed from PSG with decreased WASO. Differences between the PSG night and the following night at home were found, with better sleep on the first night home. Actigraphy in people with insomnia over seven nights is a valid indicator of sleep compared to an independent in-laboratory PSG. Event markers increased the validity of actigraphy, showing no difference in TIB, TST, SE and SOL. AUTO was representative of SE and SOL. Increased SE and TST without increased TIB suggests possible compensatory sleep the first at night home after in-laboratory PSG.

The first night effect during polysomnography, and patients' estimates of sleep quality

We surveyed patients the next morning after in-laboratory polysomnography (PSG) to compare the first night effect (FNE) and reverse first night effect (RFNE) in different sleep disorders. A questionnaire was given to 852 patients with insomnia (n = 171), restless legs syndrome (n = 186), obstructive sleep apnea (n = 369), simple snoring (n = 54), REM sleep behavior disorder (n = 39), and hypersomnia (n = 33). FNE was seen in 48.9%, 30.5% slept as usual, and 20.6% had RFNE. The highest incidences of FNE were seen in OSA, simple snoring, hypersomnia, and in men. We propose to use these findings as a reference when interpreting nocturnal in-laboratory PSG results.

Single-use suvorexant for treating insomnia during overnight polysomnography in patients with suspected obstructive sleep apnea: a single-center experience

Purpose

Although patients with suspected obstructive sleep apnea (OSA) might suffer difficulty in falling asleep during overnight polysomnography (PSG), standard hypnotics to obtain sleep during PSG have not been established. The aim of this study was to investigate the safety and efficacy of a new hypnotic agent, suvorexant, a dual orexin receptor antagonist, for insomnia in suspected OSA patients during in-laboratory PSG.

Patients and methods

An observational study was conducted during PSG for 149 patients with suspected OSA who had no insomnia at home. Patients with difficulty in falling asleep during PSG were optionally permitted to take single-use suvorexant. Patients with residual severe insomnia (>1 hour) after taking suvorexant were permitted to take an add-on use zolpidem. Clinical data and sleep questionnaire results were analyzed between a no insomnia group (without hypnotics) and an insomnia group (treated with suvorexant).

Results

Among 84 patients who experienced insomnia during PSG and required hypnotics (the insomnia group; treated with suvorexant), 44 (52.4%) achieved sufficient subjective sleep with single-use of suvorexant, while the other 40 (47.6%) required suvorexant plus zolpidem. An apnea hypopnea index (AHI) of ≥5 was observed in 144 out of 149 patients with predominantly obstructive respiratory events. Among those patients, 70.8% in the no insomnia group and 63.1% in the insomnia group had severe OSA. Regarding both subjective sleep time and morning mood, significant differences between the no insomnia group and the insomnia group were not observed. No patient taking suvorexant had an adverse event, such as delirium or falling.

Conclusion

Single-use suvorexant seems to be a safe and effective (but mild) hypnotic agent for suspected OSA patients with insomnia during in-laboratory PSG.

Eszopiclone for insomnia

BACKGROUND

Insomnia is a major public health issue affecting between 6% to 10% of the adult population in Western countries. Eszopiclone is a hypnotic drug belonging to a newer group of hypnotic agents, known as new generation hypnotics, which was marketed as being just as effective as benzodiazepines for this condition, while being safer and having a lower risk for abuse and dependence. It is the aim of the review to integrate evidence from randomised controlled trials and to draw conclusions on eszopiclone's efficacy and safety profile, while taking methodological features and bias risks into consideration.

OBJECTIVES

To assess the efficacy and safety of eszopiclone for the treatment of insomnia compared to placebo or active control.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled trials (CENTRAL), MEDLINE, Embase, PsycINFO, PSYNDEX and registry databases (WHO trials portal, ClinicalTrials.gov) with results incorporated from searches to 10 February 2016. To identify trials not registered in electronic databases, we contacted key informants and searched reference lists of identified studies. We ran an update search (21 February 2018) and have placed studies of interest in awaiting classification/ongoing studies. These will be incorporated into the next version of the review, as appropriate.

SELECTION CRITERIA

Parallel group randomised controlled trials (RCTs) comparing eszopiclone with either placebo or active control were included in the review. Participants were adults with insomnia, as diagnosed with a standardised diagnostic system, including primary insomnia and comorbid insomnia.

DATA COLLECTION AND ANALYSIS

Two authors independently extracted outcome data; one reviewer assessed trial quality and the second author cross-checked it.

MAIN RESULTS

A total of 14 RCTs, with 4732 participants, were included in this review covering short-term (≤ 4 weeks; 6 studies), medium-term (> 4 weeks ≤ 6 months; 6 studies) and long-term treatment (> 6 months; 2 studies) with eszopiclone. Most RCTs included in the review included participants aged between 18 and 64 years, three RCTs only included elderly participants (64 to 85 years) and one RCT included participants with a broader age range (35 to 85 years). Seven studies considered primary insomnia; the remaining studies considered secondary insomnia comorbid with depression (2), generalised anxiety (1), back pain (1), Parkinson's disease (1), rheumatoid arthritis (1) and menopausal transition (1).Meta-analytic integrations of participant-reported data on sleep efficacy outcomes demonstrated better results for eszopiclone compared to placebo: a 12-minute decrease of sleep onset latency (mean difference (MD) -11.94 min, 95% confidence interval (CI) -16.03 to -7.86; 9 studies, 2890 participants, moderate quality evidence), a 17-minute decrease of wake time after sleep onset (MD -17.02 min, 95% CI -24.89 to -9.15; 8 studies, 2295 participants, moderate quality evidence) and a 28-minute increase of total sleep time (MD 27.70 min, 95% CI 20.30 to 35.09; 10 studies, 2965 participants, moderate quality evidence). There were no significant changes from baseline to the first three nights after drug discontinuation for sleep onset latency (MD 17.00 min, 95% CI -4.29 to 38.29; 1 study, 291 participants, low quality evidence) and wake time after sleep onset (MD -6.71 min, 95% CI -21.25 to 7.83; 1 study, 291 participants, low quality evidence). Adverse events during treatment that were documented more frequently under eszopiclone compared to placebo included unpleasant taste (risk difference (RD) 0.18, 95% CI 0.14 to 0.21; 9 studies, 3787 participants), dry mouth (RD 0.04, 95% CI 0.02 to 0.06; 6 studies, 2802 participants), somnolence (RD 0.04, 95% CI 0.02 to 0.06; 8 studies, 3532 participants) and dizziness (RD 0.03, 95% CI 0.01 to 0.05; 7 studies, 2933 participants). According to the GRADE criteria, evidence was rated as being of moderate quality for sleep efficacy outcomes and adverse events and of low quality for rebound effects and next-day functioning.

AUTHORS' CONCLUSIONS

Eszopiclone appears to be an efficient drug with moderate effects on sleep onset and maintenance. There was no or little evidence of harm if taken as recommended. However, as certain patient subgroups were underrepresented in RCTs included in the review, findings might not have displayed the entire spectrum of possible adverse events. Further, increased caution is required in elderly individuals with cognitive and motor impairments and individuals who are at increased risk of using eszopiclone in a non-recommended way.

Use of Actigraphy for the Evaluation of Sleep Disorders and Circadian Rhythm Sleep-Wake Disorders: An American Academy of Sleep Medicine Systematic Review, Meta-Analysis, and GRADE Assessment

INTRODUCTION

The purpose of this systematic review is to provide supporting evidence for a clinical practice guideline on the use of actigraphy.

METHODS

The American Academy of Sleep Medicine commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies that compared the use of actigraphy, sleep logs, and/or polysomnography. Statistical analyses were performed to determine the clinical significance of using actigraphy as an objective measure of sleep and circadian parameters. Finally, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence for making recommendations.

RESULTS

The literature search resulted in 81 studies that met inclusion criteria; all 81 studies provided data suitable for statistical analyses. These data demonstrate that actigraphy provides consistent objective data that is often unique from patient-reported sleep logs for some sleep parameters in adult and pediatric patients with suspected or diagnosed insomnia, circadian rhythm sleep-wake disorders, sleep-disordered breathing, central disorders of hypersomnolence, and adults with insufficient sleep syndrome. These data also demonstrate that actigraphy is not a reliable measure of periodic limb movements in adult and pediatric patients. The task force provided a detailed summary of the evidence along with the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use considerations.

Validity of Consumer Activity Wristbands and Wearable EEG for Measuring Overall Sleep Parameters and Sleep Structure in Free-Living Conditions

Consumer sleep tracking technologies offer an unobtrusive and cost-efficient way to monitor sleep in free-living conditions. Technological advances in hardware and software have significantly improved the functionality of the new gadgets that recently appeared in the market. However, whether the latest gadgets can provide valid measurements on overall sleep parameters and sleep structure such as deep and REM sleep has not been examined. In this study, we aimed to investigate the validity of the latest consumer sleep tracking devices including an activity wristband Fitbit Charge 2 and a wearable EEG-based eye mask Neuroon in comparison to a medical sleep monitor. First, we confirmed that Fitbit Charge 2 can automatically detect the onset and offset of sleep with reasonable accuracy. Second, analysis found that both consumer devices produced comparable results in measuring total sleep duration and sleep efficiency compared to the medical device. In addition, Fitbit accurately measured the number of awakenings, while Neuroon with good signal quality had satisfactory performance on total awake time and sleep onset latency. However, measuring sleep structure including light, deep, and REM sleep remains to be challenging for both consumer devices. Third, greater discrepancies were observed between Neuroon and the medical device in nights with more disrupted sleep and when the signal quality was poor, but no trend was observed in Fitbit Charge 2. This study suggests that current consumer sleep tracking technologies may be immature for diagnosing sleep disorders, but they are reasonably satisfactory for general purpose and non-clinical use.

The first night effect in multiple sclerosis patients undergoing home-based polysomnography

BACKGROUND

The first night effect (FNE) is a polysomnography (PSG) habituation effect in the first of several consecutive in-laboratory PSGs (I-PSGs). The FNE is caused by the discomfort provoked by electrodes and cables and the exposure to an unfamiliar environment. A reverse FNE (RFNE) with an improved sleep in the first night is characteristic of insomnia, presumably because the video PSG in the sleep laboratory leads to a decrease in the negatively toned cognitive activity. Therefore, two or more I-PSGs are required for an accurate diagnosis. Although the FNE is well documented in I-PSG, little is known about the FNE and the RFNE in home-based PSGs (H-PSGs).

METHODS

This is a retrospective analysis of a recently published cross-sectional study using H-PSG. Sixty-three consecutive patients suffering from multiple sclerosis (MS) were investigated by two consecutive H-PSGs without video. The differences between the first and second H-PSGs were analyzed. The patients were classified into four subgroups: no sleep disorder, insomnia, sleep-related breathing disorders (SRBDs), and periodic limb movement disorder or restless legs syndrome (PLMD/RLS).

RESULTS

MS patients suffering from insomnia showed no RFNE. MS patients with SRBD or PLMD/RLS showed no reduced sleep efficiency but significantly less slow wave sleep. Furthermore, SRBD patients showed significantly less non-rapid eye movement (NREM) sleep, and PLMD/RLS patients were significantly awake longer in the first night after sleep onset (increased wake-after-sleep-onset time) and showed a higher rapid eye movement (REM) latency.

CONCLUSION

SRBD and PLMD/RLS patients showed a significant FNE. Two consecutive H-PSGs are required in these patients to obtain a precise hypnogram even in the ambulatory field. In MS patients suffering from insomnia, no RFNE was found, and in insomnia patients one H-PSG seems to be sufficient.

[The role of subjective methods for the evaluation of sleep quality]

AIM

To assess the accuracy of questions evaluating the quality and duration of sleep.

MATERIAL AND METHODS

Target population included residents of St. Petersburg, who participated in the epidemiological study ESSE-RF. Out of 1417 participants, 136 individuals agreed to undergo additional sleep evaluation, and 49 subjects underwent polysomnography study for objective sleep evaluation. All participants were interviewed for subjective sleep assessment (standard questionnaires and Pittsburgh sleep quality index questionnaire).

RESULTS

One third of the participants evaluated sleep quality in the lab worse than at home. Their sleep duration was 1,5h shorter than in those who reported sleep quality to be as good as at home. However, the majority of participants slept in the sleep lab more than at home for the previous month. Moreover, 59% subjects reported sleep disturbances. Sleep duration during night in the lab was 6.6 [3; 9] - vs. 7 [3; 10] hours as assessed by PSG and by subjective report, respectively (p=0,06). At the same time, usual average sleep duration was 8 [5; 10] hours (p=0.005), and average sleep duration during last month - 7 [5; 9] hours.

CONCLUSION

One third of subjects report worse sleep in the laboratory compared to the usual nights and it is associated with their subjective shorter sleep duration. Subjective assessment of sleep duration and sleep onset time is appropriate for sleep evaluation during the last night, unlike subjective assessment of awakenings after sleep onset. Average self-reported sleep duration depends on the question formulation.

Potential Underestimation of Sleep Apnea Severity by At-Home Kits: Rescoring In-Laboratory Polysomnography Without Sleep Staging

STUDY OBJECTIVES

Home sleep apnea testing (HSAT) is increasingly available for diagnosing obstructive sleep apnea (OSA). One key limitation of most HSAT involves the lack of sleep staging, such that the respiratory event index is calculated using the total recording time (TRT) rather than total sleep time (TST).

METHODS

We performed a retrospective analysis of n = 838 diagnostic polysomnography (PSG) nights from our center; n = 444 with OSA (4% rule, apneahypopnea index (AHI) ≥ 5), and n = 394 with AHI < 5. We recalculated the AHI using time in bed (TIB) instead of TST, to assess the predicted underestimation risk of OSA severity.

RESULTS

Of all the patients with OSA, 26.4% would be reclassified as having less severe or no OSA after recalculating the AHI using TIB rather than TST. Of the n = 275 with mild OSA, 18.5% would be reclassified as not having OSA. The risk of underestimation was higher in those with moderate or severe OSA. Of the n = 119 moderate OSA cases, 40.3% would be reclassified as mild, and of the n = 50 severe OSA cases, 36.0% would be reclassified as moderate. Age strongly correlated with the degree of underestimation of the AHI, because age was significantly correlated with time awake during PSG.

CONCLUSIONS

The risk of sleep apnea underestimation is predicted to be substantial in a tertiary sleep center population. Phenotyping errors included risk of falsely negative results (from mild to normal), as well as category errors: moderate or severe moving to mild or moderate severity, respectively. Clinicians should recognize this underestimation limitation, which directly affects diagnostic phenotyping and thus therapeutic decisions.

COMMENTARY

A commentary on this article appears in this issue on page 531.

A novel approach using actigraphy to quantify the level of disruption of sleep by in-home polysomnography: the MrOS Sleep Study: Sleep disruption by polysomnography

BACKGROUND

The "first-night effect" of polysomnography (PSG) has been previously studied; however, the ability to quantify the sleep disruption level has been confounded with the use of PSG on all nights. We used actigraphy to quantify disruption level and examined characteristics associated with disruption.

METHODS

Totally, 778 older men (76.2 ± 5.4 years) from a population-based study at six US centers underwent one night of in-home PSG. Actigraphy was performed on the PSG night and three subsequent nights. Actigraphically measured total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), and sleep onset latency (SOL) from the PSG night and subsequent nights were compared. Linear regression models were used to examine the association of characteristics and sleep disruption.

RESULTS

On average, sleep on the PSG night was worse than the following night (p < 0.05, TST 21 ± 85 min less, SE 2.3 ± 11.3% less, WASO 4.9 ± 51.8 min more, SOL 6.6 ± 56.2 min more). Sleep on the PSG night was significantly worse than that two and three nights later. Characteristics associated with greater sleep disruption on the PSG night included older age, higher apnea-hypopnea index, worse neuromuscular function, and more depressive symptoms. Minorities and men with excessive daytime sleepiness slept somewhat better on the PSG night.

CONCLUSIONS

Among older men, there was sleep disruption on the PSG night, which may lead to sleep time underestimation. The increase of sleep on the night after the PSG suggests that data from the second monitoring may overestimate sleep.

Sleep Assessment in Large Cohort Studies with High-Resolution Accelerometers

Accelerometry can be a practical replacement for polysomnography in large observational studies. This review discusses the need for sleep characterization in large observational studies, exemplified by the practices of the ongoing German National Cohort study. After brief descriptions of the physical principles and state-of-the-art accelerometer devices and an overview of public data analysis algorithms for sleep-wake differentiation, we demonstrate that the spectral properties of acceleration data provide additional features that can be exploited. This leads to a periodogram-based sleep detection algorithm. Finally, we address issues of data handling and quality assurance in large cohort studies.

Subjective sleep complaints indicate objective sleep problems in psychosomatic patients: a prospective polysomnographic study

OBJECTIVE

To elucidate the relationship between subjective complaints and polysomnographical parameters in psychosomatic patients.

METHOD

A convenience sample of patients from a psychosomatic inpatient unit were classified according to the Pittsburgh Sleep Quality Index (PSQI) as very poor sleepers (PSQI >10, n=80) and good sleepers (PSQI <6, n=19). They then underwent a polysomnography and in the morning rated their previous night's sleep using a published protocol (Deutschen Gesellschaft für Schlafforschung und Schlafmedizin morning protocol [MP]).

RESULTS

In the polysomnography, significant differences were found between very poor and good sleepers according to the PSQI with respect to sleep efficiency and time awake after sleep onset. When comparing objective PSG and subjective MP, the polysomnographical sleep onset latency was significantly positively correlated with the corresponding parameters of the MP: the subjective sleep onset latency in minutes and the subjective evaluation of sleep onset latency (very short, short, normal, long, very long) were positively correlated with the sleep latency measured by polysomnography. The polysomnographical time awake after sleep onset (in minutes) was positively correlated with the subjective time awake after sleep onset (in minutes), evaluation of time awake after sleep onset (seldom, normal often), and subjective restfulness. The polysomnographical total sleep time (TST) was positively correlated with the subjective TST. Conversely, the polysomnographical TST was negatively correlated with the evaluation of TST (high polysomnographical TST was correlated with the subjective evaluation of having slept short or normal and vice versa). The polysomnographical sleep efficiency was positively correlated with subjective feeling of current well-being in the morning and subjective TST and negatively with subjective restfulness, subjective sleep onset latency, subjective evaluation of sleep onset latency, and evaluation of time awake after sleep onset.

CONCLUSION

The data suggest that, in general, patients selected from the extremes of reported very poor sleepers and good sleepers have different amounts of sleep when measured in the laboratory, and that in general, the amount and timing of sleep in the laboratory are quite well perceived and reported by these groups. The data came from psychosomatic patients and suggest that even in this patient group, respective sleep complaints are more than just the expression of general somatization or lamenting.

Periodic leg movement (PLM) monitoring using a distributed body sensor network

Wireless sensors networks represent the architecture of choice for distributed monitoring due to the ease of deployment and configuration. We developed a distributed sleep monitoring system which combines wireless inertial sensors SP-10C by Sensoplex controlled by a custom smartphone application as an extension of the polysomnographic (PSG) monitor SOMNOscreen plus from Somnomedics. While existing activity monitors are wired to the SOMNOscreen, our system allows the use of wireless inertial sensors to improve user's comfort during sleep. The system is intended for monitoring of periodic leg movements (PLM) and user's activity during sleep. Wireless sensors are placed on ankle and toes of the foot in a customized sock. An Android app communicates with wireless sensors over Bluetooth Smart (BTS) link and streams 3D accelerometer values, 4D unit quaternion values and timestamps. In this paper we present a novel method of synchronization of data streams from PSG and inertial sensors, and original method of detection of PLM events. The system was tested using five experiments of simulated PLM, and achieved 96.51% of PLM detection accuracy.

Identifying Insomnia in Early Pregnancy: Validation of the Insomnia Symptoms Questionnaire (ISQ) in Pregnant Women

STUDY OBJECTIVES

Although a substantial number of pregnant women report symptoms of insomnia, few studies have used a validated instrument to determine the prevalence in early gestation. Identification of insomnia in pregnancy is vital given the strong connection between insomnia and the incidence of depression, cardiovascular disease, or immune dysregulation. The goal of this paper is to provide additional psychometric evaluation and validation of the Insomnia Symptom Questionnaire (ISQ) and to establish prevalence rates of insomnia among a cohort of pregnant women during early gestation.

METHODS

The ISQ was evaluated in 143 pregnant women at 12 weeks gestation. The internal consistency and criterion validity of the dichotomized ISQ were compared to traditional measures of sleep from sleep diaries, actigraphy, and the Pittsburgh Sleep Quality Index using indices of sensitivity, specificity, positive and negative predictive value (PPV, NPV), and likelihood ratio (LR) tests.

RESULTS

The ISQ identified 12.6% of the sample as meeting a case definition of insomnia, consistent with established diagnostic criteria. Good reliability was established with Cronbach α = 0.86. The ISQ had high specificity (most > 85%), but sensitivity, PPV, NPV, and LRs varied according to which sleep measure was used as the validating criterion.

CONCLUSIONS

Insomnia is a health problem for many pregnant women at all stages in pregnancy. These data support the validity and reliability of the ISQ to identify insomnia in pregnant women. The ISQ is a short and cost-effective tool that can be quickly employed in large observational studies or in clinical practice where perinatal women are seen.

COMMENTARY

A commentary on this article appears in this issue on page 593.

Sleep quality, arousal and pain thresholds in migraineurs: a blinded controlled polysomnographic study

BACKGROUND

Our aim was to compare subjective and objective sleep quality and arousal in migraine and to evaluate the relationship between sleep quality and pain thresholds (PT) in controls, interictal, preictal and postictal migraine.

METHODS

Polysomnography and PT (to pressure, heat and cold) measurements were done in 34 healthy controls and 50 migraineurs. Subjective sleep quality was assessed by sleep diaries, Epworth sleepiness scale, Karolinska sleep questionnaire and Pittsburgh sleep quality index. Migraineurs who had their sleep registration more than 48 h from an attack were classified as interictal while those who were less than 48 h from an attack were classified as either preictal or postictal.

RESULTS

Migraineurs reported more insomnia and other sleep-related symptoms than controls, but the objective sleep differences were smaller and we found no differences in daytime sleepiness. Interictal migraineurs had more awakenings (p=0.048), a strong tendency for more slow-wave sleep (p=0.050), lower thermal pain thresholds (TPT) (heat pain thresholds p=0.043 and cold pain thresholds p=0.031) than controls. Migraineurs in the preictal phase had shorter latency to sleep onset than controls (p=0.003). Slow-wave sleep correlated negatively with pressure PT and slow bursts correlated negatively with TPT.

CONCLUSION

Lower PT in interictal migraineurs seems related to increased sleep pressure. We hypothesize that migraineurs on the average suffer from a relative sleep deprivation and need more sleep than healthy controls. Lack of adequate rest might be an attack-precipitating- and hyperalgesia-inducing factor.