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

Actigraphy measures show sleep improvement after parathyroidectomy for primary hyperparathyroidism

IMPORTANCE

The symptoms of primary hyperparathyroidism are often subtle, such as fatigue, mood changes, and sleep disturbances. After parathyroidectomy, patients often report improvement in sleep and mood; however, objective data supporting these improvements is lacking.

OBJECTIVE

This prospective study uses standard measures to objectively and subjectively assess sleep in patients with primary hyperparathyroidism before and after parathyroidectomy.

DESIGN

A longitudinal prospective study was conducted over three one-week-long periods: pre-parathyroidectomy, 1-week post-parathyroidectomy, and three months post-parathyroidectomy. During each time point, patients wore an actigraphy device, recorded a sleep diary, and completed the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Depression Anxiety Stress Scale (DASS). Statistical analysis was performed using repeated measures models to compare the average measures among the three time points and test for trends over time.

SETTING

Single institution, tertiary care center.

PARTICIPANTS

Patients with primary hyperparathyroidism from ages 18 to 89 years old.

EXPOSURE

Parathyroidectomy between September 2020 and January 2024.

MAIN OUTCOMES AND MEASURES

Actigraphy data, consensus sleep diary, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Depression Anxiety Stress Scales - 21 Items (DASS).

RESULTS

Thirty-six patients were enrolled, and 34 patients completed the study. Actigraphy data showed a significant negative trend in average sleep latency (p = 0.045) and average time in bed (p = 0.046). Sleep diary data showed additional differences in the number of awakenings (p = 0.002), wake after sleep onset (p < 0.001), sleep quality (p < 0.001), and sleep efficiency (p = 0.02) among the three time points and/or as a significant negative trend. PSQI and ISI scores were significantly different among the three time points (p = 0.002 and p < 0.001, respectively) and also declined significantly over time (p = 0.008 and p = 0.007, respectively). DASS depression, anxiety, and stress scores were significantly different among the three time points (p < 0.001, p = 0.01, and p < 0.001, respectively), and stress also declined significantly over time (p = 0.005).

CONCLUSION AND RELEVANCE

This study represents the most extensive prospective study demonstrating objective and subjective sleep and mood improvement in patients with primary hyperparathyroidism after parathyroidectomy.

Effects of modafinil on nocturnal sleep patterns in patients with narcolepsy: A cohort study

BACKGROUND

Patients with narcolepsy often experience disturbed nighttime sleep. Modafinil is commonly prescribed for hypersomnolence, but its impacts on nocturnal sleep remain unclear. This study uses actigraphy to examine the effect of modafinil on both hypersomnolence and nocturnal sleep patterns in patients with narcolepsy.

METHODS

Prior to treatment, 87 patients with narcolepsy wore an actigraphy for 7-14 days to assess their nighttime sleep. After evaluation, they received a daily dose of 200-400 mg of modafinil in the morning and wore an actigraphy again six months after initiating treatment. Questionnaires, including the Epworth-Sleepiness-Scale (ESS), the Visual-Analogue-for-Hypersomnolence (VAS), and the Short-Form-36-Health-Survey (SF-36), were used to evaluate hypersomnolence and quality of life both before and after treatment. Paired t-tests and independent samples t-tests were used for pre- and post-treatment comparisons and subgroup analysis. We used the Pearson's correlation test to measure the correlations between the sleep parameters of the actigraphy and data of the questionnaires.

RESULTS

Improvements in hypersomnolence were noted following modafinil treatment, and we observed no significant deterioration in nocturnal sleep parameters by the actigraphy. The total number of awakenings by actigraphy significantly decreased (p = 0.005), especially in females (p = 0.008), while sleep onset latency significantly increased in children/adolescents (p = 0.014). Correlations were found between the sleep parameters of the actigraphy and ESS, VAS, and SF-36 scores.

CONCLUSION

Modafinil treatment may not worsen nighttime sleep in patients with narcolepsy. However, it should be administered with care in children and adolescents.

Association between sleep state misperception and bedtime behavior in patients with chronic insomnia

Previous studies on sleep state misperception have objectively evaluated sleep status in special environments using polysomnography. There is a paucity of data from studies that evaluated habitual sleep status in home environments. The present study aimed to investigate sleep state misperception in the home environment of patients with chronic insomnia using a lumbar-worn actigraphy to identify sleep habits associated with sleep state misperception severity. Thirty-one patients and 42 healthy volunteers were included in the insomnia and non-insomnia group, respectively. Participants recorded subjective assessments in sleep diaries, objective assessments with an actigraphy worn for 14 days, and self-assessments using questionnaires. Both groups had similar objective sleep ratings; however, insomnia group had significantly worse subjective ratings (total sleep time, wake after sleep onset, and sleep onset latency). A significant correlation was found between subjective and objective total sleep time scores in non-insomnia group but not in insomnia group. Insomnia group had earlier bedtimes, significantly longer bedtimes, and impaired daytime functioning (Sheehan Disability Scale score); additionally, they underestimated their total sleep time, particularly with earlier bedtimes and longer laying durations. Monitoring the sleep status and habits of individuals in home environments could be instrumental in identifying key points for targeted interventions on sleep hygiene and cognitive behavioral therapy for insomnia.

Insomnia Symptoms Are Associated with Measures of Functional Deterioration and Dementia Status in Adults with Down Syndrome at High Risk for Alzheimer's Disease

Background

While obstructive sleep apnea (OSA) and insomnia symptoms in neurotypical populations are associated with Alzheimer's disease (AD), their association with dementia in adults with Down syndrome (DS) remains less clear, even though these symptoms are prevalent and treatable in DS. Understanding their associations with AD-related dementia status, cognitive impairment, and functional deterioration may lead to interventions to slow decline or disease progression in adults with DS.

Objective

To characterize differences in OSA and insomnia symptom expression by dementia status, and to determine which sleep factors support dementia diagnosis.

Methods

Multimodal consensus conference was used to determine dementia status in 52 adults with DS (52.2 ± 6.4 years, 21 women). Cognitive impairment, adaptive behavior skills, and symptoms of OSA and insomnia were quantified using validated assessments for adults with DS and their primary informants.

Results

A sex by dementia status interaction demonstrated that older women with DS and dementia had more severe terminal insomnia but not OSA symptoms relative to older women with DS who were cognitively stable (CS). Greater insomnia symptom severity was associated with greater functional impairments in social and self-care domains adjusting for age, sex, premorbid intellectual impairment, and dementia status.

Conclusions

Insomnia symptoms are more severe in women with DS with dementia than in women with DS and no dementia, and regardless of dementia status or sex, more severe insomnia symptoms are associated with greater impairment in activities of daily living. These findings underscore the potential importance of early insomnia symptom evaluation and treatment in women with DS at risk of developing AD.

Metrology of two wearable sleep trackers against polysomnography in patients with sleep complaints

Sleep trackers are used widely by patients with sleep complaints, however their metrological validation is often poor and relies on healthy subjects. We assessed the metrological validity of two commercially available sleep trackers (Withings Activité/Fitbit Alta HR) through a prospective observational monocentric study, in adult patients referred for polysomnography (PSG). We compared the total sleep time (TST), REM time, REM latency, nonREM1 + 2 time, nonREM3 time, and wake after sleep onset (WASO). We report absolute and relative errors, Bland-Altman representations, and a contingency table of times spent in sleep stages with respect to PSG. Sixty-five patients were included (final sample size 58 for Withings and 52 for Fitbit). Both devices gave a relatively accurate sleep start time with a median absolute error of 5 (IQR -43; 27) min for Withings and -2.0 (-12.5; 4.2) min for Fitbit but both overestimated TST. Withings tended to underestimate WASO with a median absolute error of -25.0 (-61.5; -8.5) min, while Fitbit tended to overestimate it (median absolute error 10 (-18; 43) min. Withings underestimated light sleep and overestimated deep sleep, while Fitbit overestimated light and REM sleep and underestimated deep sleep. The overall kappas for concordance of each epoch between PSG and devices were low: 0.12 (95%CI 0.117-0.121) for Withings and VPSG indications 0.07 (95%CI 0.067-0.071) for Fitbit, as well as kappas for each VPSG indication 0.07 (95%CI 0.067-0.071). Thus, commercially available sleep trackers are not reliable for sleep architecture in patients with sleep complaints/pathologies and should not replace actigraphy and/or PSG.

[Sleep behavior after reverse shoulder replacement in comparison to a healthy control group : An exploratory cross-sectional study]

BACKGROUND

Individuals with shoulder pathologies frequently report sleep problems. Improving sleep quality is a treatment focus of shoulder arthroplasty. So far, it is unclear whether altered anatomy and biomechanics in reversed total shoulder arthroplasty affect sleep quality in the long term. In addition to a subjective evaluation, a reliable assessment can be obtained by recording objective sleep parameters. With the help of actigraphy, body movements are registered and divided into active and inactive phases by means of threshold values. Thanks to the valid correspondence with waking and sleeping phases, the calculation of objective sleep parameters is successful.

OBJECTIVES

The aims of the study were to investigate whether objective sleep parameters differ in persons with reversed total shoulder arthroplasty (RTSA) 1 year postoperatively compared to a healthy control group and to explore what the reasons are.

MATERIAL AND METHODS

The present work is an exploratory cross-sectional study with one measurement time point. 29 study participants (15 in the RTSA-group, 14 in the control group) collected objective sleep parameters and body position data during seven nights using actigraphy. The Mann-Whitney-U test was used for the mean comparison of sleep parameters. In addition, reasons for wakefulness were explored.

RESULTS AND CONCLUSIONS

The groups showed no significant differences in all objective sleep parameters with nearly identical sleep efficiency (p = 0.978). In the RTSA-group, 11% lay on the operated side and 65% on the back. This is just above the significance level compared to the control group with 45% in the supine position (p = 0.056). The increased use of the supine position could promote sleep-related medical conditions such as sleep apnoea and requires further research.

Quantifying the effects of sleep on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment

BACKGROUND

Despite the promise of wearable sensors for both rehabilitation research and clinical care, these technologies pose significant burden on data collectors and analysts. Investigations of factors that may influence the wearable sensor data processing pipeline are needed to support continued use of these technologies in rehabilitation research and integration into clinical care settings. The purpose of this study was to investigate the effect of one such factor, sleep, on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment and across a two-day wearing period.

METHODS

This was a secondary analysis of data collected during a prospective, longitudinal cohort study (n = 127 individuals, 62 with upper limb impairment and 65 without). Participants wore a wearable sensor on each wrist for 48 h. Five upper limb sensor variables were calculated over the full wear period (sleep included) and with sleep time removed (sleep excluded): preferred time, non-preferred time, use ratio, non-preferred magnitude and its standard deviation. Linear mixed effects regression was used to quantify the effect of sleep on each sensor variable and determine if the effect differed between people with and without upper limb impairment and across a two-day wearing period.

RESULTS

There were significant differences between sleep included and excluded for the variables preferred time (p < 0.001), non-preferred time (p < 0.001), and non-preferred magnitude standard deviation (p = 0.001). The effect of sleep was significantly different between people with and without upper limb impairment for one variable, non-preferred magnitude (p = 0.02). The effect of sleep was not substantially different across wearing days for any of the variables.

CONCLUSIONS

Overall, the effects of sleep on sensor-derived variables of upper limb accelerometry are small, similar between people with and without upper limb impairment and across a two-day wearing period, and can likely be ignored in most contexts. Ignoring the effect of sleep would simplify the data processing pipeline, facilitating the use of wearable sensors in both research and clinical practice.

Statistical analysis of actigraphy data with generalised additive models

There is a growing interest in the use of physical activity data in clinical studies, particularly in diseases that limit mobility in patients. High-frequency data collected with digital sensors are typically summarised into actigraphy features aggregated at epoch level (e.g., by minute). The statistical analysis of such volume of data is not straightforward. The general trend is to derive metrics, capturing specific aspects of physical activity, that condense (say) a week worth of data into a single numerical value. Here we propose to analyse the entire time-series data using Generalised Additive Models (GAMs). GAMs are semi-parametric models that allow inclusion of both parametric and non-parametric terms in the linear predictor. The latter are smooth terms (e.g., splines) and, in the context of actigraphy minute-by-minute data analysis, they can be used to assess daily patterns of physical activity. This in turn can be used to better understand changes over time in longitudinal studies as well as to compare treatment groups. We illustrate the application of GAMs in two clinical studies where actigraphy data was collected: a non-drug, single-arm study in patients with amyotrophic lateral sclerosis, and a physical-activity sub-study included in a phase 2b clinical trial in patients with chronic obstructive pulmonary disease.

Interventions for insomnia in cancer patients and survivors-a comprehensive systematic review and meta-analysis

BACKGROUND

Considering the persistent nature and higher prevalence of insomnia in cancer patients and survivors compared with the general population, there is a need for effective management strategies. This systematic review and meta-analysis aimed to comprehensively evaluate the available evidence for the efficacy of pharmacological and nonpharmacological interventions for insomnia in adult cancer patients and survivors.

METHODS

Following the PRISMA guidelines, we analyzed data from 61 randomized controlled trials involving 6528 participants. Interventions included pharmacological, physical, and psychological treatments, with a focus on insomnia severity and secondary sleep and non-sleep outcomes. Frequentist and Bayesian analytical strategies were employed for data synthesis and interpretation.

RESULTS

Cognitive-Behavioral Therapy for Insomnia (CBT-I) emerged as the most efficacious intervention for reducing insomnia severity in cancer survivors and further demonstrated significant improvements in fatigue, depressive symptoms, and anxiety. CBT-I showed a large postintervention effect (g = 0.86; 95% confidence interval [CI] = 0.57 to 1.15) and a medium effect at follow-up (g = 0.55; 95% CI = 0.18 to 0.92). Other interventions such as bright white light therapy, sleep medication, melatonin, exercise, mind-body therapies, and mindfulness-based therapies showed benefits, but the evidence for their efficacy was less convincing compared with CBT-I. Brief Behavioral Therapy for Insomnia showed promise as a less burdensome alternative for patients in active cancer treatment.

CONCLUSIONS

CBT-I is supported as a first-line treatment for insomnia in cancer survivors, with significant benefits observed across sleep and non-sleep outcomes. The findings also highlight the potential of less intensive alternatives. The research contributes valuable insights for clinical practice and underscores the need for further exploration into the complexities of sleep disturbances in cancer patients and survivors.

Validation of actigraphy sleep metrics in children aged 8 to 16 years: considerations for device type, placement and algorithms

BACKGROUND

Actigraphy is often used to measure sleep in pediatric populations, despite little confirmatory evidence of the accuracy of existing sleep/wake algorithms. The aim of this study was to determine the performance of 11 sleep algorithms in relation to overnight polysomnography in children and adolescents.

METHODS

One hundred thirty-seven participants aged 8-16 years wore two Actigraph wGT3X-BT (wrist, waist) and three Axivity AX3 (wrist, back, thigh) accelerometers over 24-h. Gold standard measures of sleep were obtained using polysomnography (PSG; Embletta MPRPG, ST + Proxy and TX Proxy) in the home environment, overnight. Epoch by epoch comparisons of the Sadeh (two algorithms), Cole-Kripke (three algorithms), Tudor-Locke (four algorithms), Count-Scaled (CS), and HDCZA algorithms were undertaken. Mean differences from PSG values were calculated for various sleep outcomes.

RESULTS

Overall, sensitivities were high (mean ± SD: 91.8%, ± 5.6%) and specificities moderate (63.8% ± 13.8%), with the HDCZA algorithm performing the best overall in terms of specificity (87.5% ± 1.3%) and accuracy (86.4% ± 0.9%). Sleep outcome measures were more accurately measured by devices worn at the wrist than the hip, thigh or lower back, with the exception of sleep efficiency where the reverse was true. The CS algorithm provided consistently accurate measures of sleep onset: the mean (95%CI) difference at the wrist with Axivity was 2 min (-6; -14,) and the offset was 10 min (5, -19). Several algorithms provided accurate measures of sleep quantity at the wrist, showing differences with PSG of just 1-18 min a night for sleep period time and 5-22 min for total sleep time. Accuracy was generally higher for sleep efficiency than for frequency of night wakings or wake after sleep onset. The CS algorithm was more accurate at assessing sleep period time, with narrower 95% limits of agreement compared to the HDCZA (CS:-165 to 172 min; HDCZA: -212 to 250 min).

CONCLUSION

Although the performance of existing count-based sleep algorithms varies markedly, wrist-worn devices provide more accurate measures of most sleep measures compared to other sites. Overall, the HDZCA algorithm showed the greatest accuracy, although the most appropriate algorithm depends on the sleep measure of focus.

Comparing actigraphy and diary to measure daily and average sleep in firefighters: a Bland-Altman analysis

STUDY OBJECTIVES

This study sought to examine the relationship between actigraphy and the Consensus Sleep Diary to contribute information on their concurrent validity in a sample of career firefighters.

METHODS

Sixty firefighters were recruited from a large, urban fire department in the southwest United States that utilizes a fire-based emergency medical services system and a 5/6 shift schedule. A total of 329 differences were recorded during participants' 6-day between-shift recovery period. Data was collected utilizing the two most common forms of sleep analysis in an outpatient setting, wrist actigraphy (Actiwatch-2) and the Consensus Sleep Diary. Nine major sleep indices were computed: wake time after sleep onset, total sleep time, sleep onset latency, sleep offset, in-bed time, lights-off time, out-of-bed time, wake time, and sleep efficiency.

RESULTS

Firefighters overestimated sleep efficiency and underestimated wake after sleep onset by values that were greater than the American Academy of Sleep Medicine a priori clinical significance thresholds. All indices showed very broad limits of agreement. For example, the 95% confidence interval for diary and actigraphic total sleep time estimates fell within a 4.7-hour range.

CONCLUSIONS

Firefighters receiving recovery sleep between tours demonstrated significantly large disagreements between their daily self-reported sleep and measured actigraphic sleep. Sleep findings from actigraphic and Consensus Sleep Diary sleep assessments in this population should be interpreted cautiously until each method is compared against other reliable sleep analysis methods. Currently it is unclear if clinicians are using properly validated tools when diagnosing shift work disorder or other sleep disorders in firefighters.

CITATION

Marmis R, McGoldrick-Ruth L, Kelly MR, Haynes PL. Comparing actigraphy and diary to measure daily and average sleep in firefighters: a Bland-Altman analysis. J Clin Sleep Med. 2024;20(4):497-503.

Feasibility and Acceptability of Using Wireless Limited Polysomnography to Capture Sleep Before, During, and After Hospitalization for Patients With Planned Cardiothoracic Surgery

BACKGROUND

Sleep disruption, a common symptom among patients requiring cardiovascular surgery, is a potential risk factor for the development of postoperative delirium. Postoperative delirium is a disorder of acute disturbances in cognition associated with prolonged hospitalization, cognitive decline, and mortality.

OBJECTIVE

The aim of this study was to evaluate the feasibility and acceptability of using polysomnography (PSG) to capture sleep in patients with scheduled cardiothoracic surgery.

METHODS

Wireless limited PSG assessed sleep at baseline (presurgery at home), postoperatively in the intensive care unit, and at home post hospital discharge. Primary outcomes were quality and completeness of PSG signals, and acceptability by participants and nursing staff.

RESULTS

Among 15 patients, PSG data were of high quality, and mean percentage of unscorable data was 5.5% ± 11.1%, 3.7% ± 5.4%, and 3.7% ± 8.4% for baseline, intensive care unit, and posthospitalization measurements, respectively. Nurses and patients found the PSG monitor acceptable.

CONCLUSIONS

Wireless, limited PSG to capture sleep across the surgical continuum was feasible, and data were of high quality. Authors of future studies will evaluate associations of sleep indices and development of postoperative delirium in this high-risk population.

Pediatric Insomnia

Insomnia is the most common sleep disorder among all ages; unfortunately, however, child and adolescent insomnia is infrequently addressed. Given the importance of adequate sleep for proper brain development, pediatric populations are particularly vulnerable to the negative effects of insomnia. Therefore, proper clinical assessment and treatment of pediatric insomnia is crucial. This article is the result of a comprehensive literature review and serves as a guide to the disorder and how it presents differently across child development.

A Protocol for Evaluating Digital Technology for Monitoring Sleep and Circadian Rhythms in Older People and People Living with Dementia in the Community

Sleep and circadian rhythm disturbance are predictors of poor physical and mental health, including dementia. Long-term digital technology-enabled monitoring of sleep and circadian rhythms in the community has great potential for early diagnosis, monitoring of disease progression, and assessing the effectiveness of interventions. Before novel digital technology-based monitoring can be implemented at scale, its performance and acceptability need to be evaluated and compared to gold-standard methodology in relevant populations. Here, we describe our protocol for the evaluation of novel sleep and circadian technology which we have applied in cognitively intact older adults and are currently using in people living with dementia (PLWD). In this protocol, we test a range of technologies simultaneously at home (7-14 days) and subsequently in a clinical research facility in which gold standard methodology for assessing sleep and circadian physiology is implemented. We emphasize the importance of assessing both nocturnal and diurnal sleep (naps), valid markers of circadian physiology, and that evaluation of technology is best achieved in protocols in which sleep is mildly disturbed and in populations that are relevant to the intended use-case. We provide details on the design, implementation, challenges, and advantages of this protocol, along with examples of datasets.

Associations of light exposure patterns with sleep among Dutch children: The ABCD cohort study

Light exposure affects the circadian system and consequently can affect sleep quality. Only few studies examined this relationship in children. We evaluated associations between light exposure patterns and sleep metrics in children. We measured the sleep parameters of 247 Dutch children, aged between 11 and 13 years and recruited from the ABCD cohort, using actigraphy and sleep records for 7 consecutive nights. Personal light exposures were measured with a light meter during the whole day and night. We applied generalized mixed-effects regression models, adjusted for possible confounders, to evaluate the associations of light exposure patterns on sleep duration, sleep efficiency and sleep-onset delay. In the models mutually adjusted for potential confounders, we found the amount of hours between the first time of bright light in the morning and going to sleep and the duration of bright light to be significantly associated with decreased sleep duration (in min; β: -2.02 [95% confidence interval: -3.84, -0.25], β: -8.39 [95% confidence interval: -16.70, -0.07], respectively) and with shorter sleep-onset delay (odds ratio: 0.88 [95% confidence interval: 0.80, 0.97], odds ratio: 0.40 [95% confidence interval: 0.19, 0.87], respectively). Increased light intensities at night were associated with decreased sleep duration (T2 β: -8.54 [95% confidence interval: -16.88, -0.20], T3 β: -14.83 [95% confidence interval: -28.04, -1.62]), while increased light intensities before going to bed were associated with prolonged sleep onset (odds ratio: 4.02 [95% confidence interval: 2.09, 7.73]). These findings further suggest that children may be able to influence their sleep quality by influencing the light exposure patterns during day and night.

A systematic review of the performance of actigraphy in measuring sleep stages

The accuracy of actigraphy for sleep staging is assumed to be poor, but examination is limited. This systematic review aimed to assess the performance of actigraphy in sleep stage classification of adults. A systematic search was performed using MEDLINE, Web of Science, Google Scholar, and Embase databases. We identified eight studies that compared sleep architecture estimates between wrist-worn actigraphy and polysomnography. Large heterogeneity was found with respect to how sleep stages were grouped, and the choice of metrics used to evaluate performance. Quantitative synthesis was not possible, so we performed a narrative synthesis of the literature. From the limited number of studies, we found that actigraphy-based sleep staging had some ability to classify different sleep stages compared with polysomnography.

Imputing missing sleep data from wearables with neural networks in real-world settings

Sleep is a critical component of health and well-being but collecting and analyzing accurate longitudinal sleep data can be challenging, especially outside of laboratory settings. We propose a simple neural network model titled SOMNI (Sleep data restOration using Machine learning and Non-negative matrix factorIzation [NMF]) for imputing missing rest-activity data from actigraphy, which can enable clinicians to better handle missing data and monitor sleep-wake cycles of individuals with highly irregular sleep-wake patterns. The model consists of two hidden layers and uses NMF to capture hidden longitudinal sleep-wake patterns of individuals with disturbed sleep-wake cycles. Based on this, we develop two approaches: the individual approach imputes missing data based on the data from only one participant, while the global approach imputes missing data based on the data across multiple participants. Our models are tested with shift and non-shift workers' data from three independent hospitals. Both approaches can accurately impute missing data up to 24 hours of long dataset (>50 days) even for shift workers with extremely irregular sleep-wake patterns (AUC > 0.86). On the other hand, for short dataset (~15 days), only the global model is accurate (AUC > 0.77). Our approach can be used to help clinicians monitor sleep-wake cycles of patients with sleep disorders outside of laboratory settings without relying on sleep diaries, ultimately improving sleep health outcomes.

Assessment and Management of Sleep Disturbances in Atopic Dermatitis: A Review

Atopic dermatitis (AD) is a chronic burdensome inflammatory skin disease with well-established cutaneous and systemic comorbidities and disease burden. AD particularly has profound impacts on sleep in individuals of all ages. Sleep disturbances (SDs) affect 6.2% of school-age children and 33-87.1% of adults with AD. This narrative review addresses the burden of SD in AD patients, as well as biological mechanisms of SD in AD, including biological clocks influencing sleep, inflammation, and behavior. Approaches for early detection, diagnosis, objective quantification, patient education, and management are reviewed. It is imperative to break the itch-scratch cycle to reduce SDs and improve quality of life in individuals with AD.

Tailored lighting intervention (TLI) for improving sleep-wake cycles in older adults living with dementia

Introduction: Sleep disturbance is a hallmark of Alzheimer's disease and related dementias, and caregiver stress caused by patients' nighttime wandering, injuries, and agitation are frequently at the root of decisions to move them to assisted living facilities, where typically dim institutional lighting can further exacerbate their sleep problems. This study explored the effects of a circadian-effective lighting intervention on actigraphic sleep measures and subjective assessments of sleep disturbance, depression, and sleep-disturbed behaviors. Methods: Fourteen older adult (≥60 years) participants (11 females, mean age = 84.1 [SD 8.9]), all diagnosed with moderate to severe dementia and sleep disturbance, were recruited from 3 assisted living and memory care facilities. Following a crossover, placebo-controlled design, 3 different lighting modes were used to deliver high levels of circadian stimulus to the participants' eyes for two 8-week intervention periods in a counter balanced order with a 4-week washout between the study's 2 conditions (dim light control vs. active intervention). Actigraphy and questionnaire data were collected over 7-day assessment periods that preceded (baseline weeks 1 and 9) and concluded (post-intervention week 9 and 22) the intervention periods. Actigraphic outcomes included sleep duration, sleep time, sleep efficiency, sleep start time, and sleep end time. Subjective assessments included the Cornell Scale for Depression in Dementia (CSDD), Pittsburgh Sleep Quality Index (PSQI), and Sleep Disorders Inventory (SDI) instruments. Results: Under the active condition, sleep duration significantly (p = 0.018) increased and sleep start time significantly (p = 0.012) advanced after the intervention compared to baseline. Also under the active condition, PSQI (p = 0.012), CSDD (p = 0.007), Sleep Disorders Inventory frequency (p = 0.015), and SDI severity (p = 0.015) scores were significantly lower after the intervention compared to baseline. Discussion: This study demonstrates that a circadian-effective lighting intervention delivering bright days and dark nights improves measures of sleep and mood in dementia patients living in controlled environments.

Association between electroencephalogram-based sleep characteristics and physical health in the general adult population

We examined the associations between electroencephalogram (EEG)-based sleep characteristics and physical health parameters in general adults via a cross-sectional study recruiting 100 volunteers aged 30-59 years. Sleep characteristics were measured at home using a portable multichannel electroencephalography recorder. Using the k-means +  +  clustering method, according to 10 EEG-based parameters, participants were grouped into better (n = 39), middle (n = 46), and worse (n = 15) sleep groups. Comparing 50 physical health parameters among the groups, we identified four signals of difference (P < 0.05), including systolic (sBP) and diastolic blood pressure (dBP), γ-glutamyl transpeptidase (γ-GTP), and serum creatinine, where sBP reached a Bonferroni-corrected threshold (P < 0.001). The sBP was higher by 7.9 (95% confidence interval 1.9-13.9) and 15.7 (7.3-24.0) mmHg before adjustment and 5.4 (- 0.1-10.9) and 8.7 (1.1-16.3) mmHg after adjustment for age, sex, body mass index, smoking, drinking habits, and 3% oxygen desaturation index in the middle and worse sleep groups, respectively, than in the better group. As another approach, among 500 combinations of EEG-based and physical health parameters, there were 45 signals of correlation, of which 4 (N1% and sBP, dBP, γ-GTP, and triglycerides) reached a Bonferroni-corrected threshold (P < 0.0001). Thus, EEG-based sleep characteristics are associated with several physical health parameters, particularly sBP.

Sleep-wake state discrepancy among cancer survivors with insomnia symptoms

PURPOSE

To evaluate the discrepancy and correlation between sleep-wake measures (i.e., time in bed (TIB), total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE%)) reported on sleep diary and measured by actigraphy among cancer survivors with insomnia symptoms; and examine the influences of sociodemographic and clinical variables on these measurement differences.

METHODS

A heterogenous sample of cancer survivors with insomnia symptoms (n = 120; M age = 63.7 ± 10.1; female = 58.3%) was included. Seven consecutive days of sleep diary and actigraphic data were obtained along with information on demographic, sleep, and mental health symptoms. Bland-Altman plot, Pearson correlation coefficient, concordance correlation coefficient, and mixed linear model approach were used to conduct the analysis.

RESULTS

Self-reported TIB, SOL, and WASO were longer than measured by actigraphy (TIB: 8.6 min. (95% CI, 3.7, 13.5; p < .001); SOL: 14.8 min. (95% CI, 9.4, 20.2; p < .0001); and WASO: 20.7 min. (95% CI, 9.4, 20.2; p < .0001), respectively); and self-reported TST and SE% were shorter than measured by actigraphy (TST: 6.8 min. (95% CI, -18.7, 5.13); and SE%: 0.7% (95%CI, -3.0, 2.0), respectively), but were not statistically significant. Sex, higher insomnia severity, and poor sleep quality were associated with discrepancy between several sleep-wake measures.

CONCLUSION

Subjective and objective sleep-wake measures may present discrepant finding among cancer survivors with symptoms of insomnia. Future research is needed to validate appropriate sleep-wake assessment, and better understand factors that influence the discrepancy that exists between measures among this population.

CLINICAL TRIAL REGISTRATION

Clinical trials identifier: NCT03810365. Date of registration: January 14, 2019.

Current Considerations in the Diagnosis and Treatment of Circadian Rhythm Sleep-Wake Disorders in Children

Circadian Rhythm Sleep-Wake Disorders (CRSWDs) are important sleep disorders whose unifying feature is a mismatch between the preferred or required times for sleep and wakefulness and the endogenous circadian drives for these. Their etiology, presentation, and treatment can be different in pediatric patients as compared to adults. Evaluation of these disorders must be performed while viewed through the lens of a patient's comorbid conditions. Newer methods of assessment promise to provide greater diagnostic clarity and critical insights into how circadian physiology affects overall health and disease states. Effective clinical management of CRSWDs is multimodal, requiring an integrated approach across disciplines. Therapeutic success depends upon appropriately timed nonpharmacologic and pharmacologic interventions. A better understanding of the genetic predispositions for and causes of CRSWDs has led to novel clinical opportunities for diagnosis and improved therapeutics.

The European Insomnia Guideline: An update on the diagnosis and treatment of insomnia 2023

Progress in the field of insomnia since 2017 necessitated this update of the European Insomnia Guideline. Recommendations for the diagnostic procedure for insomnia and its comorbidities are: clinical interview (encompassing sleep and medical history); the use of sleep questionnaires and diaries (and physical examination and additional measures where indicated) (A). Actigraphy is not recommended for the routine evaluation of insomnia (C), but may be useful for differential-diagnostic purposes (A). Polysomnography should be used to evaluate other sleep disorders if suspected (i.e. periodic limb movement disorder, sleep-related breathing disorders, etc.), treatment-resistant insomnia (A) and for other indications (B). Cognitive-behavioural therapy for insomnia is recommended as the first-line treatment for chronic insomnia in adults of any age (including patients with comorbidities), either applied in-person or digitally (A). When cognitive-behavioural therapy for insomnia is not sufficiently effective, a pharmacological intervention can be offered (A). Benzodiazepines (A), benzodiazepine receptor agonists (A), daridorexant (A) and low-dose sedating antidepressants (B) can be used for the short-term treatment of insomnia (≤ 4 weeks). Longer-term treatment with these substances may be initiated in some cases, considering advantages and disadvantages (B). Orexin receptor antagonists can be used for periods of up to 3 months or longer in some cases (A). Prolonged-release melatonin can be used for up to 3 months in patients ≥ 55 years (B). Antihistaminergic drugs, antipsychotics, fast-release melatonin, ramelteon and phytotherapeutics are not recommended for insomnia treatment (A). Light therapy and exercise interventions may be useful as adjunct therapies to cognitive-behavioural therapy for insomnia (B).

Sleep regularity and mortality: a prospective analysis in the UK Biobank

Background

Irregular sleep-wake timing may cause circadian disruption leading to several chronic age-related diseases. We examined the relationship between sleep regularity and risk of all-cause, cardiovascular disease (CVD), and cancer mortality in 88,975 participants from the prospective UK Biobank cohort.

Methods

The sleep regularity index (SRI) was calculated as the probability of an individual being in the same state (asleep or awake) at any two time points 24 hr apart, averaged over 7 days of accelerometry (range 0-100, with 100 being perfectly regular). The SRI was related to the risk of mortality in time-to-event models.

Results

The mean sample age was 62 years (standard deviation [SD], 8), 56% were women, and the median SRI was 60 (SD, 10). There were 3010 deaths during a mean follow-up of 7.1 years. Following adjustments for demographic and clinical variables, we identified a non-linear relationship between the SRI and all-cause mortality hazard (p [global test of spline term]<0.001). Hazard ratios, relative to the median SRI, were 1.53 (95% confidence interval [CI]: 1.41, 1.66) for participants with SRI at the 5th percentile (SRI = 41) and 0.90 (95% CI: 0.81, 1.00) for those with SRI at the 95th percentile (SRI = 75), respectively. Findings for CVD mortality and cancer mortality followed a similar pattern.

Conclusions

Irregular sleep-wake patterns are associated with higher mortality risk.

Funding

National Health and Medical Research Council of Australia (GTN2009264; GTN1158384), National Institute on Aging (AG062531), Alzheimer's Association (2018-AARG-591358), and the Banting Fellowship Program (#454104).

Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data

BACKGROUND

Patient-generated health data are important in the management of several diseases. Although there are limitations, information can be obtained using a wearable device and time-related information such as exercise time or sleep time can also be obtained. Fitbits can be used to acquire sleep onset, sleep offset, total sleep time (TST), and wakefulness after sleep onset (WASO) data, although there are limitations regarding the depth of sleep and satisfaction; therefore, the patient's subjective response is still important information that cannot be replaced by wearable devices.

OBJECTIVE

To effectively use patient-generated health data related to time such as sleep, it is first necessary to understand the characteristics of the time response recorded by the user. Therefore, the aim of this study was to analyze the characteristics of individuals' time perception in comparison with wearable data.

METHODS

Sleep data were acquired for 2 weeks using a Fitbit. Participants' sleep records were collected daily through chatbot conversations while wearing the Fitbit, and the two sets of data were statistically compared.

RESULTS

In total, 736 people aged 30-59 years were recruited for this study, and the sleep data of 543 people who wore a Fitbit and responded to the chatbot for more than 7 days on the same day were analyzed. Research participants tended to respond to sleep-related times on the hour or in 30-minute increments, and each participant responded within the range of 60-90 minutes from the value measured by the Fitbit. On average for all participants, the chat responses and the Fitbit data were similar within a difference of approximately 15 minutes. Regarding sleep onset, the participant response was 8 minutes and 39 seconds (SD 58 minutes) later than that of the Fitbit data, whereas with respect to sleep offset, the response was 5 minutes and 38 seconds (SD 57 minutes) earlier. The participants' actual sleep time (AST) indicated in the chat was similar to that obtained by subtracting the WASO from the TST measured by the Fitbit. The AST was 13 minutes and 39 seconds (SD 87 minutes) longer than the time WASO was subtracted from the Fitbit TST. On days when the participants reported good sleep, they responded 19 (SD 90) minutes longer on the AST than the Fitbit data. However, for each sleep event, the probability that the participant's AST was within ±30 and ±60 minutes of the Fitbit TST-WASO was 50.7% and 74.3%, respectively.

CONCLUSIONS

The chatbot sleep response and Fitbit measured time were similar on average and the study participants had a slight tendency to perceive a relatively long sleep time if the quality of sleep was self-reported as good. However, on a participant-by-participant basis, it was difficult to predict participants' sleep duration responses with Fitbit data. Individual variations in sleep time perception significantly affect patient responses related to sleep, revealing the limitations of objective measures obtained through wearable devices.

The relationship between sleep quality and daytime dysfunction among college students in China during COVID-19: a cross-sectional study

Objective

College Students' sleep quality and daytime dysfunction have become worse since the COVID-19 outbreak, the purpose of this study was to explore the relationship between sleep quality and daytime dysfunction among college students during the COVID-19 (Corona Virus Disease 2019) period.

Methods

This research adopts the form of cluster random sampling of online questionnaires. From April 5 to 16 in 2022, questionnaires are distributed to college students in various universities in Fujian Province, China and the general information questionnaire and PSQI scale are used for investigation. SPSS26.0 was used to conduct an independent sample t-test and variance analysis on the data, multi-factorial analysis was performed using logistic regression analysis. The main outcome variables are the score of subjective sleep quality and daytime dysfunction.

Results

During the COVID-19 period, the average PSQI score of the tested college students was 6.17 ± 3.263, and the sleep disorder rate was 29.6%, the daytime dysfunction rate was 85%. Being female, study liberal art/science/ engineering, irritable (due to limited outdoor), prolong electronic entertainment time were associated with low sleep quality (p < 0.001), and the occurrence of daytime dysfunction was higher than other groups (p < 0.001). Logistics regression analysis showed that sleep quality and daytime dysfunction were associated with gender, profession, irritable (due to limited outdoor), and prolonged electronic entertainment time (p < 0.001).

Conclusion

During the COVID-19 epidemic, the sleep quality of college students was affected, and different degrees of daytime dysfunction have appeared, both are in worse condition than before the COVID-19 outbreak. Sleep quality may was inversely associated with daytime dysfunction.

Novel treatment based on acceptance and commitment therapy versus cognitive behavioral therapy for insomnia: A randomized comparative effectiveness trial in women veterans

OBJECTIVE

This randomized comparative effectiveness trial evaluated a novel insomnia treatment using acceptance and commitment therapy (ACT) among women veterans. Participants received either the acceptance and the behavioral changes to treat insomnia (ABC-I) or cognitive behavioral therapy for insomnia (CBT-I). The primary objectives were to determine whether ABC-I was noninferior to CBT-I in improving sleep and to test whether ABC-I resulted in higher treatment completion and adherence versus CBT-I.

METHOD

One hundred forty-nine women veterans with insomnia disorder (Mage = 48.0 years) received ABC-I or CBT-I. The main sleep outcomes were Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and sleep efficiency (SE) by actigraphy (objective) and sleep diary (subjective). Measures were collected at baseline, immediate posttreatment, and 3-month posttreatment follow-up. Treatment completion and adherence were assessed during the interventions.

RESULTS

Both interventions improved all sleep outcomes from baseline to immediate posttreatment and 3-month posttreatment follow-up. At immediate posttreatment, ABC-I was statically noninferior for sleep diary SE and objective SE, but noninferiority was not statistically confirmed for ISI or PSQI total scores. At 3-month posttreatment follow-up, ABC-I was noninferior for all four of the key outcome variables. There was not a statistically significant difference between the number of participants who discontinued CBT-I (11%) versus ABC-I (18%; p = .248) before completing treatment. ABC-I was superior to CBT-I for some adherence metrics.

CONCLUSIONS

Overall, ABC-I was similar in effectiveness compared to CBT-I for the treatment of insomnia and may improve adherence to some behavioral elements of treatment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Sleep Quality of Family Caregivers of Children With Tracheostomies or Home Ventilators: A Scoping Review

Family caregivers of children with tracheostomies or home ventilators are more likely to experience poor sleep quality when undertaking the full responsibility of caring for fragile children. This scoping review aimed to identify the sleep quality, related factors, and their impact on the health of family caregivers of children with tracheostomies or home ventilators. The included studies (N = 16) were retrieved through PubMed, CINAHL, Cochrane Library, Embase, PsycINFO, and Web of Science. Family caregivers' sleep were low in quality, frequently disturbed, and insufficient. Their sleep quality was related to fatigue, anxiety, depression, family functioning, and health-related quality of life. The sleep disturbing factors were classified as child, caregiver, or environment-related, which were mutually interrelated. This review emphasizes the need to develop nursing interventions to both improve the sleep quality of family caregivers and the health of children with tracheostomies or home ventilators based on an in-depth understanding of the family's context.

Association between Acute Respiratory Distress Syndrome Due to COVID-19 and Long-Term Sleep and Circadian Sleep-Wake Disorders

Current studies agree on the impact of sleep and circadian rest-activity rhythm alterations in acute respiratory distress syndrome (ARDS) survivors. However, research on the duration of this impact is scarce. In this study, we evaluate the impact of ARDS on the sleep and circadian rest-activity rhythm of COVID-19 survivors twelve months after hospital discharge. This is a prospective study including COVID-19 survivors with and without ARDS during hospitalization. Data was collected four and twelve months after hospital discharge. The interventions included one-week wrist actigraphy and a home sleep apnea test (HSAT), and evaluations were conducted according to the Pittsburgh sleep quality index (PSQI), Epworth sleepiness scale (ESS), and insomnia severity index (ISI). Fifty-two patients were evaluated (ARDS = 31 and non-ARDS = 21); they had a median age of 49.0 [39.0;57.2] years and 53.8% were male. After twelve months, 91.3% presented poor sleep quality, 58.7% presented insomnia, 50% presented daytime somnolence, and 37% presented comorbid insomnia and obstructive sleep apnea (COMISA). No significant improvement was observed in relation to sleep or the circadian rest-activity rhythm between four and twelve months. A tendency of poor sleep quality, insomnia, daytime somnolence, and COMISA was observed. Finally, there was no significant impact on the circadian rest-activity rhythm between four and twelve months or between the groups.

Nightmares and Sleep Disturbances in Children with PTSD: A Polysomnographic and Actigraphy Approach Evaluation

RATIONALE

Sleep disturbances (insomnia and nightmare symptoms) are the most sensitive and persistent symptoms of pediatric post-traumatic stress disorder (PTSD). Untreated, these sleep disturbances (SD) associated with PTSD are predictive of PTSD persistence and increased psychiatric complications. The aim of this study was to evaluate sleep and circadian rhythms in children with PTSD under both laboratory and ecological conditions in comparison with a control population and to test for the first time the hypothesis that SD and circadian rhythms are positively correlated with PTSD severity and its comorbidities.

METHOD

This prospective pilot study evaluated PTSD, SD (insomnia, nightmares), and sleep-wake rhythms in 11 children with PTSD (aged 3-18), compared with the age and sex-matched control groups. Assessment of PTSD and subjective and objective measures of sleep and sleep-wake rhythms (questionnaires, 24-h in-laboratory video-polysomnography, 15-day at-home actigraphy recording) were performed between 1 and 6 months after the traumatic event.

RESULTS

Children with PTSD had higher sleep fragmentation (increased wake-after-sleep onset, increased number of sleep stage changes) compared to controls, with a change in sleep microarchitecture (micro-arousal index at 14.8 versus 8.2, p = 0.039). Sleep fragmentation parameters correlated with PTSD symptomatology, insomnia, and post-traumatic nightmare severity. The within-group comparison revealed a better sleep architecture in the controlled (sleep laboratory) than in the ecological condition (at home) (total sleep time 586 versus 464 min, p = 0.018).

CONCLUSIONS

Sleep and rhythm disturbances are strongly associated with PTSD in children. The assessment of SD in children with PTSD should be carried out systematically and preferentially under ecological conditions, and management of SD should integrate the environment (environmental design, psycho-education for the children and their parents) more fully into therapy focused on sleep and trauma.

Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing

GOAL AND AIMS

Commonly used actigraphy algorithms are designed to operate within a known in-bed interval. However, in free-living scenarios this interval is often unknown. We trained and evaluated a sleep/wake classifier that operates on actigraphy over ∼24-hour intervals, without knowledge of in-bed timing.

FOCUS TECHNOLOGY

Actigraphy counts from ActiWatch Spectrum devices.

REFERENCE TECHNOLOGY

Sleep staging derived from polysomnography, supplemented by observation of wakefulness outside of the staged interval. Classifications from the Oakley actigraphy algorithm were additionally used as performance reference.

SAMPLE

Adults, sleeping in either a home or laboratory environment.

DESIGN

Machine learning was used to train and evaluate a sleep/wake classifier in a supervised learning paradigm. The classifier is a temporal convolutional network, a form of deep neural network.

CORE ANALYTICS

Performance was evaluated across ∼24 hours, and additionally restricted to only in-bed intervals, both in terms of epoch-by-epoch performance, and the discrepancy of summary statistics within the intervals.

ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES

Performance of the trained model applied to the Multi-Ethnic Study of Atherosclerosis dataset.

CORE OUTCOMES

Over ∼24 hours, the temporal convolutional network classifier produced the same or better performance as the Oakley classifier on all measures tested. When restricting analysis to the in-bed interval, the temporal convolutional network remained favorable on several metrics.

IMPORTANT SUPPLEMENTAL OUTCOMES

Performance decreased on the Multi-Ethnic Study of Atherosclerosis dataset, especially when restricting analysis to the in-bed interval.

CORE CONCLUSION

A classifier using data labeled over ∼24-hour intervals allows for the continuous classification of sleep/wake without knowledge of in-bed intervals. Further development should focus on improving generalization performance.

The potential of biomarkers for diagnosing insomnia: Consensus statement of the WFSBP Task Force on Sleep Disorders

OBJECTIVES

Thus far, the diagnosis of insomnia is based on purely clinical criteria. Although a broad range of altered physiological parameters has been identified in insomniacs, the evidence to establish their diagnostic usefulness is very limited. Purpose of this WFSBP Task Force consensus paper is to systematically evaluate a series of biomarkers as potential diagnostic tools for insomnia.

METHODS

A newly created grading system was used for assessing the validity of various measurements in establishing the diagnosis of insomnia; these measurements originated from relevant studies selected and reviewed by experts.

RESULTS

The measurements with the highest diagnostic performance were those derived from psychometric instruments. Biological measurements which emerged as potentially useful diagnostic instruments were polysomnography-derived cyclic alternating pattern, actigraphy, and BDNF levels, followed by heart rate around sleep onset, deficient melatonin rhythm, and certain neuroimaging patterns (mainly for the activity of frontal and pre-frontal cortex, hippocampus and basal ganglia); yet, these findings need replication, as well as establishment of commonly accepted methodology and diagnostic cut-off points. Routine polysomnography, EEG spectral analysis, heart rate variability, skin conductance, thermoregulation, oxygen consumption, HPA axis, and inflammation indices were not shown to be of satisfactory diagnostic value.

CONCLUSIONS

Apart from psychometric instruments which are confirmed to be the gold standard in diagnosing insomnia, six biomarkers emerge as being potentially useful for this purpose.

Concordance of objective and subjective measures of sleep in children with neurodevelopmental conditions: A systematic review and meta-analysis

The purpose of this systematic review and meta-analysis is to delineate the concordance of objective and subjective measures of sleep in children with neurodevelopmental conditions (NDCs). A systematic literature search identified 31 studies that compare objective and subjective estimates of sleep parameters in autism, ADHD or rare genetic syndromes associated with intellectual disability. The meta-analyses revealed smaller mean differences and larger correlations indicative of greater concordance for parameters associated with sleep scheduling compared to parameters associated with sleep duration and night awakenings. Relative to objective measures, subjective measures produced: 1) greater estimates of total sleep time, sleep efficiency and time in bed; and 2) lower estimates of wake after sleep onset and number of night awakenings. Subgroup analyses also revealed differences in concordance between measurement comparison types (e.g., stronger correlations between actigraphy and sleep diaries, compared to actigraphy and questionnaires) and NDC diagnostic groups. The results predominantly replicate concordance trends observed in typically-developing samples, although some NDC-specific patterns of concordance were identified. This indicates that objective and subjective sleep measures retain broadly similar properties across populations, although researchers and clinicians should be cautious of the impact of NDC-related characteristics on sleep parameter estimates. These findings should inform sleep assessment design and the interpretation of sleep parameter estimates in NDCs, increasing the rigour of sleep parameter description across research and clinical settings.

A standardized workflow for long-term longitudinal actigraphy data processing using one year of continuous actigraphy from the CAN-BIND Wellness Monitoring Study

Monitoring sleep and activity through wearable devices such as wrist-worn actigraphs has the potential for long-term measurement in the individual's own environment. Long periods of data collection require a complex approach, including standardized pre-processing and data trimming, and robust algorithms to address non-wear and missing data. In this study, we used a data-driven approach to quality control, pre-processing and analysis of longitudinal actigraphy data collected over the course of 1 year in a sample of 95 participants. We implemented a data processing pipeline using open-source packages for longitudinal data thereby providing a framework for treating missing data patterns, non-wear scoring, sleep/wake scoring, and conducted a sensitivity analysis to demonstrate the impact of non-wear and missing data on the relationship between sleep variables and depressive symptoms. Compliance with actigraph wear decreased over time, with missing data proportion increasing from a mean of 4.8% in the first week to 23.6% at the end of the 12 months of data collection. Sensitivity analyses demonstrated the importance of defining a pre-processing threshold, as it substantially impacts the predictive value of variables on sleep-related outcomes. We developed a novel non-wear algorithm which outperformed several other algorithms and a capacitive wear sensor in quality control. These findings provide essential insight informing study design in digital health research.

Actigraphic characterization of sleep and circadian phenotypes of PER3 gene VNTR genotypes

The molecular circadian timing system involves genes known as "clock genes," such as the PER3 gene. Studies have demonstrated associations among a repeat polymorphism (VNTR) of the PER3 gene with chronotypes, with the occurrence of circadian rhythm disorders and with sleep homeostasis phenotypes. The aim of this study was to investigate, by actigraphy, sleep and circadian rhythm profiles of people with different genotypes for the VNTR polymorphism of the PER3 gene. We genotyped 467 individuals (46,39% male) for the PER3 VNTR polymorphism. The mean age of the participants was 21.84 ± 2.64, ranging from 18 to 30 y old. Actigraphy data were collected from a subsample of 81 subjects with PER3 4-repeats homozygous (PER34/4) or 5-repeats homozygous (PER35/5) genotypes from April to June of 2021. From this sample, 48 PER34/4 and 33 PER35/5 subjects wore a wrist actigraph between 12 and 19 d. The sleep onset (weekdays, p = 0.015; weekend, p = 0.022) and offset (weekdays, p = 0.004; weekend, p = 0.041) of the PER35/5 group occurred later than the PER34/4 group. Similar results were observed for the mid-sleep phase of weekdays (MSW) (p = 0.008) and free days (MSF) (p = 0.019), and for the mid-sleep phase corrected for sleep debt accumulated over the week (MSFsc) (p = 0.024). Despite the phase differences found between the PER34/4 and PER35/5 groups, no differences were found in sleep duration and social jet lag. However, the PER34/4 group presented, on average, a longer sleep rebound on the days off when compared to the PER35/5 (p = 0.002). The PER35/5 group showed lower interdaily stability (IS) (p = 0.032) and higher daily activity rhythm variability (IV) (p = 0.035). The findings of the present study revealed associations between the PER3 gene, sleep, and circadian rhythms. In general, we found that the gene is associated with the expression of sleep timing and duration and to the phase of the activity rhythm. The experiments carried out here occurred in the COVID-19 pandemic scenario, which should be considered as an environmental element with potential effects on the results obtained.

Can mindfulness-based interventions improve outcomes in cognitive-behavioural therapy for chronic insomnia disorder in the general population? Systematic review and meta-analysis

Cognitive-behavioural therapy for insomnia (CBT-I) is the recommended first-line therapy for adults with chronic insomnia disorder (ID), which is characterized by hyperarousal. Mindfulness-based interventions (MBIs) are protocols aimed at stress reduction based on non-judgmental attention control in the present moment. However, MBIs have been increasingly used without a clear scientific basis. The objective of this analysis was to examine if MBIs could be useful as a component of the CBT-I therapeutic system through a systematic review and meta-analysis of randomized controlled trials (RCTs) and non-randomized studies (NRS) searched in PubMed, PsycINFO, Cochrane and WoS. The Insomnia Severity Index (ISI) was the primary outcome, while the Pittsburgh Sleep Quality Index (PSQI) and a composite sleep variable (CSV) were secondary outcomes. Thirteen articles corresponding to nine studies (three pragmatic RCTs, three explanatory RCTs and three NRS) were included. The omnibus test found that MBIs had a small to medium effect size on ISI nearing signification when comparing active control groups in the pretest-posttest period [Δ = 0.44, p = 0.07], a medium, non-significant, effect size on PSQI [Δ = 0.52, p = 0.18], and a significant though small effect size on CSV [Δ = 0.05, p < 0.01]. No heterogeneity was found. The analysis could not demonstrate that MBIs, combined with CBT-I components in some studies, positively affected ID in the general adult population. This was probably due to the lack of pragmatic designs and suitable measuring instruments. Recommendations are made for designing further studies to address these issues.

Sleep Regularity and Mortality: A Prospective Analysis in the UK Biobank

Background

Irregular sleep-wake timing may cause circadian disruption leading to several chronic age-related diseases. We examined the relationship between sleep regularity and risk of all-cause, cardiovascular disease (CVD), and cancer mortality in 88,975 participants from the prospective UK Biobank cohort.

Methods

The sleep regularity index (SRI) was calculated as the probability of an individual being in the same state (asleep or awake) at any two time points 24 hours apart, averaged over 7-days of accelerometry (range 0-100, with 100 being perfectly regular). The SRI was related to the risk of mortality in time-to-event models.

Findings

The mean sample age was 62 years (SD, 8), 56% were women, and the median SRI was 60 (SD, 10). There were 3010 deaths during a mean follow-up of 7.1 years. Following adjustments for demographic and clinical variables, we identified a non-linear relationship between the SRI and all-cause mortality hazard (p [global test of spline term] < 0·001). Hazard Ratios, relative to the median SRI, were 1·53 (95% confidence interval [CI]: 1·41, 1·66) for participants with SRI at the 5th percentile (SRI = 41) and 0·90 (95% CI: 0·81, 1·00) for those with SRI at the 95th percentile (SRI = 75), respectively. Findings for CVD mortality and cancer mortality followed a similar pattern.

Conclusions

Irregular sleep-wake patterns are associated with higher mortality risk.

Funding

National Health and Medical Research Council of Australia (GTN2009264; GTN1158384), National Institute on Aging (AG062531), Alzheimer's Association (2018-AARG-591358), and the Banting Fellowship Program (#454104).

Sleep and mental health in recruit paramedics: a 6-month longitudinal study

STUDY OBJECTIVES

To explore potential relationships and longitudinal changes in sleep and mental health in recruit paramedics over the first 6 months of work, and whether sleep disturbances pre-emergency work predict future mental health outcomes.

METHODS

Participants (N = 101, 52% female, Mage = 26 years) completed questionnaires prior to (baseline), and after 6 months of emergency work to assess for symptoms of insomnia, obstructive sleep apnea, post-traumatic stress disorder (PTSD), depression, anxiety, and trauma exposure. At each timepoint, participants also completed a sleep diary and wore an actigraph for 14 days to assess sleep patterns. Correlations between baseline sleep and mental health were conducted and changes in these variables across timepoints were examined using linear mixed models. Hierarchical regressions assessed whether sleep at baseline predicted mental health at follow-up.

RESULTS

Insomnia and depression symptoms, and total sleep time increased while sleep onset latency decreased across the first 6 months of emergency work. Participants experienced an average of 1 potentially traumatic event during the 6-month period. Baseline insomnia predicted increased depression symptoms at the 6-month follow-up, while baseline wake after sleep onset predicted follow-up PTSD symptoms.

CONCLUSION

Results highlight an increase in insomnia and depression across the initial months of emergency work, while sleep disturbances before emergency work were identified as potential risk factors for the development of depression and PTSD among paramedics in their early career. Screening and early interventions targeting poor sleep at the beginning of emergency employment may assist in reducing the risk of future mental health outcomes in this high-risk occupation.

Exploring physical and biological manifestations of burnout and post-traumatic stress disorder symptoms in healthcare workers: a scoping review protocol

INTRODUCTION

The COVID-19 pandemic has strained the mental and physical well-being of healthcare workers (HCW). Increased work-related stress and limited resources have increased symptoms of anxiety, depression, insomnia and post-traumatic stress disorder (PTSD) in this population. Stress-related disorders have been strongly associated with long-term consequences, including cardiometabolic disorders, endocrine disorders and premature mortality. This scoping review aims to explore available literature on burnout, PTSD, and other mental health-associated symptoms in HCW to synthesise relationships with physiological and biological biomarkers that may be associated with increased risk of disease, creating an opportunity to summarise current biomarker knowledge and identify gaps in this literature.

METHODS AND ANALYSIS

This scoping review uses the Arksey and O'Malley six-step scoping review methodology framework. The research team will select appropriate primary sources using a search strategy developed in collaboration with a health sciences librarian. Three reviewers will initially screen the title and abstracts obtained from the literature searches, and two reviewers will conduct independent reviews of full-text studies for inclusion. The research team will be reviewing literature focusing on which burnout and/or PTSD-associated physiological and biological biomarkers have been studied, the methodologies used to study them and the correlations between the biomarkers and HCW experiencing burnout/PTSD. Data extraction forms will be completed by two reviewers for included studies and will guide literature synthesis and analysis to determine common themes.

ETHICS AND DISSEMINATION

This review does not require ethical approval. We expect results from this scoping review to identify gaps in the literature and encourage future research regarding improving biological and physiological biomarker research in HCW. Preliminary results and general themes will be communicated back to stakeholders. Results will be disseminated through peer-reviewed publications, policy briefs and conferences as well as presented to stakeholders to an effort to invest in HCW mental and physical health.

Issues and opportunities of digital phenotyping: ecological momentary assessment and behavioral sensing in protecting the young from suicide

Digital phenotyping refers to the collection of real-time biometric and personal data on digital tools, mainly smartphones, and wearables, to measure behaviors and variables that can be used as a proxy for complex psychophysiological conditions. Digital phenotyping might be used for diagnosis, clinical assessment, predicting changes and trajectories in psychological clinical conditions, and delivering tailored interventions according to individual real-time data. Recent works pointed out the possibility of using such an approach in the field of suicide risk in high-suicide-risk patients. Among the possible targets of such interventions, adolescence might be a population of interest, since they display higher odds of committing suicide and impulsive behaviors. The present work systematizes the available evidence of the data that might be used for digital phenotyping in the field of adolescent suicide and provides insight into possible personalized approaches for monitoring and treating suicidal risk or predicting risk trajectories. Specifically, the authors first define the field of digital phenotyping and its features, secondly, they organize the available literature to gather all the digital indexes (active and passive data) that can provide reliable information on the increase in the suicidal odds, lastly, they discuss the challenges and future directions of such an approach, together with its ethical implications.

High-resolution daily profiles of tissue adrenal steroids by portable automated collection

Rhythms are intrinsic to endocrine systems, and disruption of these hormone oscillations occurs at very early stages of the disease. Because adrenal hormones are secreted with both circadian and ultradian periods, conventional single-time point measurements provide limited information about rhythmicity and, crucially, do not provide information during sleep, when many hormones fluctuate from nadir to peak concentrations. If blood sampling is attempted overnight, then this necessitates admission to a clinical research unit, can be stressful, and disturbs sleep. To overcome this problem and to measure free hormones within their target tissues, we used microdialysis, an ambulatory fraction collector, and liquid chromatography-tandem mass spectrometry to obtain high-resolution profiles of tissue adrenal steroids over 24 hours in 214 healthy volunteers. For validation, we compared tissue against plasma measurements in a further seven healthy volunteers. Sample collection from subcutaneous tissue was safe, well tolerated, and allowed most normal activities to continue. In addition to cortisol, we identified daily and ultradian variation in free cortisone, corticosterone, 18-hydroxycortisol, aldosterone, tetrahydrocortisol and allo-tetrahydrocortisol, and the presence of dehydroepiandrosterone sulfate. We used mathematical and computational methods to quantify the interindividual variability of hormones at different times of the day and develop "dynamic markers" of normality in healthy individuals stratified by sex, age, and body mass index. Our results provide insight into the dynamics of adrenal steroids in tissue in real-world settings and may serve as a normative reference for biomarkers of endocrine disorders (ULTRADIAN, NCT02934399).

Narcolepsy and Idiopathic Hypersomnia

Narcolepsy types 1 and 2 and idiopathic hypersomnia are primary Central Nervous System (CNS) disorders of hypersomnolence characterized by profound daytime sleepiness and/or excessive sleep need. Onset of symptoms begins typically in childhood or adolescence, and children can have unique presentations compared with adults. Narcolepsy type 1 is likely caused by immune-mediated loss of orexin (hypocretin) neurons in the hypothalamus; however, the causes of narcolepsy type 2 and idiopathic hypersomnia are unknown. Existing treatments improve daytime sleepiness and cataplexy but there is no cure for these disorders.

Delayed sleep-wake phase disorder and its related sleep behaviors in the young generation

Delayed sleep-wake phase disorder (DSWPD) is a sleep disorder in which the habitual sleep-wake timing is delayed, resulting in difficulty in falling asleep and waking up at the desired time. Patients with DSWPD frequently experience fatigue, impaired concentration, sleep deprivation during weekdays, and problems of absenteeism, which may be further complicated by depressive symptoms. DSWPD is typically prevalent during adolescence and young adulthood. Although there are no studies comparing internationally, the prevalence of DSWPD is estimated to be approximately 3% with little racial differences between Caucasians and Asians. The presence of this disorder is associated with various physiological, genetic and psychological as well as behavioral factors. Furthermore, social factors are also involved in the mechanism of DSWPD. Recently, delayed sleep phase and prolonged sleep duration in the young generation have been reported during the period of COVID-19 pandemic-related behavioral restrictions. This phenomenon raises a concern about the risk of a mismatch between their sleep-wake phase and social life that may lead to the development of DSWPD after the removal of these restrictions. Although the typical feature of DSWPD is a delay in circadian rhythms, individuals with DSWPD without having misalignment of objectively measured circadian rhythm markers account for approximately 40% of the cases, wherein the psychological and behavioral characteristics of young people, such as truancy and academic or social troubles, are largely involved in the mechanism of this disorder. Recent studies have shown that DSWPD is frequently comorbid with psychiatric disorders, particularly mood and neurodevelopmental disorders, both of which have a bidirectional association with the pathophysiology of DSWPD. Additionally, patients with DSWPD have a strong tendency toward neuroticism and anxiety, which may result in the aggravation of insomnia symptoms. Therefore, future studies should address the effectiveness of cognitive-behavioral approaches in addition to chronobiological approaches in the treatment of DSWPD.

The curious case of the Zzz's

Excessive daytime sleepiness is a common presenting symptom that may present a diagnostic challenge for the sleep medicine clinician. We present a case of an adolescent female with excessive daytime sleepiness and "sleep attacks" who was evaluated using a 2-week sleep log, wrist actigraphy, baseline polysomnogram, and Multiple Sleep Latency Test. Multiple Sleep Latency Test results noted a short mean sleep latency without sleep onset rapid eye movement periods, concerning for possible central disorders of hypersomnolence. However, actigraphy data noted a habitual bedtime of midnight or later, resulting in less than recommended total sleep time for her age on weekdays with extended sleep periods on the weekends. The most unique actigraphy finding was exposure to ambient light throughout most overnight sleep periods. When actigraphy results were discussed with the patient, she revealed recent onset of severe anxiety with fear of sleeping in the dark. This case highlights the importance of thorough clinical evaluation, and careful interpretation of objective tests, when evaluating for causes of excessive daytime sleepiness.

CITATION

Dang L, Kanney ML, Hsu DP. The curious case of the Zzz's. J Clin Sleep Med. 2023;19(5):1009-1012.

Exploring Physical and Biological Manifestations of Burnout and Post-Traumatic Stress Disorder Symptoms in Healthcare Workers: A Scoping Review Protocol

Introduction

The COVID-19 pandemic has strained the mental and physical well-being of healthcare workers (HCW). Increased work-related stress and limited resources has increased symptoms of anxiety, depression, insomnia, and post-traumatic stress disorder (PTSD) in this population. Stress-related disorders have been strongly associated with long-term consequences including cardiometabolic disorders, endocrine disorders and premature mortality. This scoping review aims to explore available literature on burnout, PTSD, and other mental health-associated symptoms in HCW to synthesize relationships with physiological and biological biomarkers that may be associated with increased risk of disease, creating an opportunity to summarize current biomarker knowledge and identify gaps in this literature.

Methods and Analysis

This scoping review uses the Arksey and O'Malley six-step scoping review methodology framework. The research team will select appropriate primary sources using a search strategy developed in collaboration with a health sciences librarian. Three reviewers will initially screen the title and abstracts obtained from the literature searches, and two reviewers will conduct independent reviews of full-text studies for inclusion. The research team will be reviewing literature focusing on which burnout and/or PTSD-associated physiological and biological biomarkers have been studied, the methodologies used to study them and the correlations between the biomarkers and HCW experiencing burnout/PTSD. Data extraction forms will be completed by two reviewers for included studies and will guide literature synthesis and analysis to determine common themes.

Ethics and Dissemination

This review does not require ethical approval. We expect results from this scoping review to identify gaps in the literature and encourage future research regarding improving biologic and physiologic biomarker research in HCW. Preliminary results and general themes will be communicated back to stakeholders. Results will be disseminated through peer-reviewed publications, policy briefs, and conferences, as well as presented to stakeholders to an effort to invest in HCW mental and physical health.

Strengths and Limitations of This Study

This will be the first scoping review to assess the current understanding of the biologic and physiological impact of burnout on healthcare workers. The target population is restricted to healthcare workers; however, identified research gaps may be used to guide future studies in other high-burnout occupations and industries.This scoping review will be guided by the Arksey and O'Malley six-step methodological framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review checklist.Both peer reviewed manuscript and pre-prints/abstracts will be evaluated, but studies that have not been peer reviewed will be notated in the summary table. Conference abstracts are excluded.Preliminary and final themes and results identified by this scoping review will be communicated to stakeholders, including hospital staff and HCW, to ensure agreement with our interpretation and to convey knowledge gained with our population of interest.This review will advance the field's current understanding of mechanisms connecting the burnout and pathogenic stress to biologic and physiologic outcomes in healthcare workers and provide researchers with gaps in the literature to inform opportunities for future research.

Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

Characterization of sleep among deaf individuals

OBJECTIVES

Numerous health disparities are documented in deaf population research, but few empirical sleep assessments exist for this under-served population, despite knowledge that sleep contributes to physical and mental health disparities. We sought to document subjective and objective sleep in deaf adults with cross-sectional and prospective measures.

METHODS

Twenty deaf participants completed validated sleep and mental health questionnaires, 2-weeks of nightly sleep diaries and continuous wrist-worn actigraphy monitoring, and 1-week of nightly, reduced-montage EEG recordings.

RESULTS

Questionnaire data suggest high prevalence of insomnia (70%), poor sleep (75%), daytime sleepiness (25%) and nightmares (20%) among participants. Strong correlations were found between depression and sleep quality, fear of sleep, and insomnia severity (p's < .005). Objective sleep assessments suggest elevated wake after sleep onset and low sleep efficiency and sleep duration.

CONCLUSIONS

The prevalence of sleep disturbance recorded from self-report and objective sleep measures provides preliminary evidence of sleep health disparity among deaf adults.

Insomnia with objective short sleep duration in community-living older persons: A multifactorial geriatric health condition

BACKGROUND

Insomnia or poor sleep quality with objective short sleep duration (hereafter referred to as ISSD) has been identified as a high-risk phenotype among middle-aged persons. We evaluated the prevalence and clinical correlates of ISSD among community-living older persons.

METHODS

In 3053 men from the Osteoporotic Fractures in Men Sleep Study (MrOS; average age 76.4 ± 5.5 years) and 3044 women from the Study of Osteoporotic Fractures (SOF; average age 83.6 ± 3.8 years), we evaluated the prevalence of ISSD (trouble getting to sleep within 30 minutes, waking up in the middle of the night or early morning, and/or taking a medication to help with sleep ≥3 times per week and actigraphy-estimated sleep duration <6 h). Using separate logistic regression models in men and women, we evaluated the cross-sectional associations between predisposing, precipitating, and perpetuating factors for ISSD, as compared with normal sleep (no insomnia and actigraphy-estimated sleep duration of 6-9 h).

RESULTS

Overall, 20.6% of older men and 12.8% of older women had insomnia with short sleep duration. Multiple predisposing, precipitating, and perpetuating factors were cross-sectionally associated with ISSD in both men and women. In multivariable models that adjusted for predisposing factors (demographics, multimorbidity, obesity), precipitating (depression, anxiety, central nervous system-active medication use, restless legs syndrome) and perpetuating (napping, falls) factors were significantly associated with ISSD in men and women (adjusted odds ratios ranging 1.63-4.57).

CONCLUSIONS

In this cross-sectional study of community-living older men and women, ISSD was common and associated with multiple predisposing, precipitating, and perpetuating factors, akin to a multifactorial geriatric health condition. Future work should examine causal pathways and determine whether the identified correlates represent modifiable risk factors.