Sleep Profile Research Articles

A Comprehensive Examination of Severely Ill ME/CFS Patients.

One in four myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients are estimated to be severely affected by the disease, and these house-bound or bedbound patients are currently understudied. Here, we report a comprehensive examination of the symptoms and clinical laboratory tests of a cohort of severely ill patients and healthy controls. The greatly reduced quality of life of the patients was negatively correlated with clinical depression. The most troublesome symptoms included fatigue (85%), pain (65%), cognitive impairment (50%), orthostatic intolerance (45%), sleep disturbance (35%), post-exertional malaise (30%), and neurosensory disturbance (30%). Sleep profiles and cognitive tests revealed distinctive impairments. Lower morning cortisol level and alterations in its diurnal rhythm were observed in the patients, and antibody and antigen measurements showed no evidence for acute infections by common viral or bacterial pathogens. These results highlight the urgent need of developing molecular diagnostic tests for ME/CFS. In addition, there was a striking similarity in symptoms between long COVID and ME/CFS, suggesting that studies on the mechanism and treatment of ME/CFS may help prevent and treat long COVID and vice versa.

Sleep profile and the risk of cardiovascular events in patients undergoing percutaneous coronary intervention

ABSTRACT A significant proportion of patients with coronary artery disease (CAD) who undergo percutaneous coronary intervention (PCI) suffer from physical and mental disorders which lead to the decline of sleep profile. Sleep disorders are highly prevalent in these patients. But the effect of sleep on the outcomes of post-PCI patients remains unclear. We aim to examine the individual and joint effects of sleep quality and sleep duration on the risk of adverse cardiovascular events in post-PCI patients. We included 314 participants who were diagnosed with a first CAD and underwent PCI with drug-eluting stents and followed up for a mean duration of 341 days to assess major adverse cardiovascular events (MACEs). Sleep quality, based on the Pittsburgh Sleep Quality Index, was categorized as good (a score of ≤7) or poor (>7). Sleep duration was categorized into three classes: ≤ 5, 6–8 (reference group) and ≥ 9 hours per day. The log-rank test and the Cox regression model were used for data analysis. MACEs occurred in 26 (8.3%) patients. Subjects whose sleep duration was ≤ 5 hours per day had a shorter time to MACEs than those whose sleep duration was 6–8 hours (p = 0.036). A significantly increased risk for MACEs was observed for participants with a ≤ 5 hours sleep duration (HR = 2.18, 95% CI = 1.02–4.64) after adjustment for demographic and clinical confounders. Associations between long sleep duration (≥ 9 hours), sleep quality, or their joint effect and MACEs were not found. This suggests the importance of considering sleep loss when developing strategies to improve health outcomes of PCI patients. And further researches are needed to examine the effects of different aspects of sleep quality on the prognosis of PCI patients and explore the reasons that lead to the decline of sleep profile.

P11.03 Sleep analysis of accelerometer data from High Grade Glioma patients in the BrainWear study

Abstract BACKGROUND Sleep disturbance is a common symptom in patients with high grade glioma (HGG). Existing self-reported and uni-dimensional data from questionnaires are of limited value. The observational phase 2 trial, BrainWear (ISRCTN 34351424) provides the first objective analysis of sleep in HGG patients. MATERIAL AND METHODS Patients with HGG were asked to wear an AX3 Axivity tri-axial accelerometer throughout treatment. The study employed a wear-as-long-as-possible approach to accelerometry data collection, and we used age-sex matched controls from the UK Biobank as comparators. Baseline was established as a 7 day period of wear prior to surgery or at least 7 days post-surgery. The dataset for this analysis consists of 21 patients with data at baseline and 15 patients during chemo-radiation. Only 16 of the 21 HGG patients at baseline were included for initial comparisons with healthy controls due to age limitations of the UK Biobank cohort for matching. Raw accelerometer data was processed using the GGIR package, with non-imputation of missing data, exclusion of days with <16 hours of wear time and removal of algorithm-identified problematic data. Mann-Whitney U-tests and unpaired T-tests were used to compare 7 sleep-related features between HGG patients and healthy controls at baseline, with choice of statistical test based on shapiro-wilk derived normality. Secondly, to assess changes in sleep in HGG patients across treatment period, K-means clustering of 5 sleep parameters, available longitudinally, was conducted to explore sleep behaviours at baseline (n = 21) and during chemo-radiation. RESULTS HGG patients (n = 16) exhibited greater daytime inactivity than healthy controls (n = 32) (p < 0.0001, 2.2 vs 0.5 hrs) and more variation in their 24 hour activity rhythm from day to day (p < 0.0001, 0.12 vs 0.18). We identified 5 sleep features which allowed us to cluster patients’ sleep behaviour, and most (62.5%) of HGG patients have a poor sleep profile. This sleep profile was characterised by an average of 5.4 hours of night-time sleep, 2.1 hours of daytime inactivity and disturbed sleep quality. However, evaluation of HGG patient sleep cluster designation at baseline and during chemoradiation, showed HGG patients with data at both timepoints (n = 9) demonstrate stability or improvement in sleep profile. CONCLUSION Patients with HGG have objective evidence of poor sleep compared to healthy matched controls. Further work will explore changes in sleep over time.

Dissociated profiles of sleep timing and sleep quality changes across the first and second wave of the COVID-19 pandemic

Previous work showed a significant impact of the COVID-19 pandemic on Italians’ sleep both during the first wave, when a total lockdown (TL) was imposed, and during the second wave, when a partial lockdown (PL) was mandated (autumn 2020). Here we complement these data by describing the profile of sleep across four time-points: the first and second lockdown (TL, PL) and the months preceding them (pre-TL, pre-PL).An online survey was completed by 214 participants (Mage = 36.78 ± 14.2 y; 159 F) during TL and again during PL. All sleep-related questions (including items of the Pittsburgh Sleep Quality Index) required a double answer, one referred to the current lockdown and one to the month preceding the lockdown.Bedtime and rise time were delayed in TL and then advanced in pre-PL and PL. Similarly, time in bed increased in TL and then decreased in pre-PL and PL. Sleep quality worsened in the two lockdowns compared to the preceding periods and the proportion of poor sleepers correspondingly increased in both lockdowns.Sleep habits and quality displayed different profiles across phases of the pandemic. Sleep timing was altered during the first lockdown and then returned towards baseline (likely due to normalized working schedules). Instead, sleep quality, which markedly worsened during both lockdowns, appears particularly sensitive to changes in life habits and psychological factors, independently of sleep habits. Our findings also point to a possible role of acute and chronic stress (experienced during the first and second wave, respectively) in modulating sleep changes across the pandemic waves.

Sleep Characteristics and Socio-Emotional Functioning of Gifted Children

ABSTRACT Objectives/Background Intellectual giftedness is characterized by an intellectual development superior to peers, while emotional and relational developments correspond to the age norms. Few empirical researches have investigated sleep profile of gifted children (GC) and its association with their well-being, all of which used IQ as the sole definition criteria for GC. This study aimed to investigate the interaction between giftedness and sleep on socio-emotional functioning. Participants The sample consisted of 32 GC (25 boys; mean age = 9.62, SD = 1.81) and 17 typically-developing children (TD: 13 boys; mean age = 10.23 years, SD = 1.95). Giftedness was identified using Renzulli’s three-factor definition of giftedness. Methods Children’s sleep and socio-emotional functioning were respectively assessed with the Children’s Sleep Habits Questionnaire and the Child Behavior Checklist, both completed by parents. Results Being in the GC group increased by 4.67 times the risk of having sleep problems and 14.12 times the risk of having maladaptive behaviors. Two-way ANOVA tests showed that sleep problems tended to moderate the relation between giftedness and adjustment difficulties so that the combination of giftedness and sleep problems appeared to be prejudicial to socio-emotional functioning. Conclusion Giftedness could be a risk factor for sleep disorders as well as adjustment difficulties. The present results support the importance of addressing sleep in the GC assessment to improve their well-being and eventually limit the negative impacts of sleep difficulties on emotional and behavioral functioning.

Sleep Patterns Related to Emotion Dysregulation Among Adolescents and Young Adults.

Adolescents and young adults in the college setting often report poor sleep hygiene and quality. These sleep difficulties may be related to emotion dysregulation, which is highly relevant to broader adjustment. The current study aimed to empirically identify latent groups of healthy college students with distinct subjective sleep patterns and examine differences in emotion dysregulation between subgroups. College students (N = 476; Mage=19.38) completed the Adolescent Sleep-Wake Scale-Revised, Adolescent Sleep Hygiene Scale-Revised, and Difficulties in Emotion Dysregulation Scale. Most participants were White (78%), non-Hispanic/Latinx (85%), and female (77%). Latent profile analysis identified patterns of sleep with maximum likelihood estimation. Bolck-Croon-Hagenaars procedure evaluated differences in emotion dysregulation by class. A three-class model had optimal fit, Bayesian information criterion = 11,577.001, Bootstrapped Parametric Likelihood Ratio Test = -5,763.042, p < .001, entropy = .815. The three profiles identified were good sleep (overall high sleep quality and hygiene; n = 219), moderate sleep (low sleep quality with mix of low and high sleep hygiene; n = 221), and poor sleep (very low sleep quality and hygiene; n = 36). Those in the good sleep group (M = 68.06, SE = 1.5) reported significantly less emotion dysregulation than the moderate sleep group (M = 92.12, SE = 1.67; X2(2) = 98.34, p = .001) and the poor sleep group (M = 99.51, SE = 4.10; p < .001). The moderate and poor sleep groups did not significantly differ, X2(2) = 2.60, p = .11. Emotion dysregulation differed across three sleep profiles, with participants classified in the good sleep group reporting, on average, the lowest emotion dysregulation, compared to the moderate and poor sleep groups. These findings highlight contextual factors of sleep that may be clinically targeted to promote emotion regulation.

Subjective and objective sleep in young people with borderline personality disorder features.

Characterising sleep in young people (aged 15-25years) with borderline personality disorder (BPD) features is crucial given the association between BPD features and sleep disturbance, negative consequences of poor sleep, and normative developmental sleep changes that occur in this age group. The present study aimed to characterise the sleep profile of young people with BPD to determine whether this profile is non-normative and specific to BPD. Participants were 96 young people (40 with BPD features, 38 healthy individuals, and 18 young people seeking help for mental health difficulties without BPD). Sleep was measured subjectively (self-report questionnaires) and objectively (10days of actigraphy). Young people with BPD features reported poorer subjective sleep quality, greater insomnia symptoms and later chronotype than same-age healthy and clinical comparison groups. Young people with BPD features also displayed irregular sleep timing, later rise times, greater time in bed and longer sleep durations than healthy young people. Those with BPD features had superior sleep quality (greater sleep efficiency, less wake after sleep onset) and longer sleep durations than the clinical comparison group. Sleep profiles were similar across young people with BPD features with and without co-occurring depression. Overall, the findings revealed a subjective-objective sleep discrepancy and suggest that sleep-improvement interventions might be beneficial to improve subjective sleep in young people with BPD features.

Relationship Among Caregiver Mental Health, Infant and Toddler Sensory-Processing Profiles, and Occupations

Abstract Date Presented 04/13/21 The purpose of this study was to explore the relationship between caregiver mental illness, breastfeeding frequency and duration, and infant sleep and sensory profiles. Neurotypical infant–maternal dyads took part in the IDAHO Mom Study. The findings suggest that maternal mental health, actual or perceived, has an influence on sensory processing profiles in infants and toddlers. Primary Author and Speaker: Bryan M. Gee Additional Authors and Speakers: Rachel Allen-McHugh, Kelsey Huss Contributing Authors: Andrew Galvez, Taylor Pirillo, Sabrina DeHerrera, and Jessica Pottebaum

Androgen deprivation therapy and radiation for prostate cancer—cognitive impairment, sleep, symptom burden: a prospective study

ObjectivesThis paper (1) sought to compare sleep, mood and physical symptom profiles of men with prostate cancer (PCa) who experienced subjective and objective cancer-related cognitive impairment (CRCI) during the first...

Sleep Characteristics Among Children with Idiopathic Generalized Epilepsy: A Polysomnography-Based Study.

This study was designed to describe the sleep profile in a cohort of children 5-15 y with idiopathic generalized epilepsy (IGE) using polysomnography (PSG) and Children's Sleep Habits Questionnaire (CSHQ) and Pittsburg Sleep Quality Index (PSQI). The controls included age- and gender-matched healthy controls. A total of 30 cases of IGE and matched 30 controls were enrolled in study. The global CSHQ score [58.8 (10.8) vs. 32.3 (4.1); p < 0.01] and PSQI score [2.4 (1.6) vs. 0.9(0.3); p < 0.01] was significantly higher among children with IGE as compared to controls. REM sleep duration was significantly lower and other parameters including AHI [2.8 (1.9, 4.6) vs. 2.6 (1.3, 2.9); p = 0.04], frequency of arousals [51.5 (36.7, 71.5) vs. 27 (24, 43); p < 0.01], percentage of oxygen desaturation > 4% [23.5 (8, 36.5) vs. 4 (2, 8); p < 0.01], were significantly higher among children with IGE when compared to controls. Children with IGE havesleep disturbances and alteration in sleep architecture. Theyshould be assessed and screened for sleep characteristics.

Statement of Retraction

This article refers to:Do Anxiety and Mood Vary among Disparate Sleep Profiles in Youth with Craniopharyngioma? A Latent Profile Analysis

Relationship between sleep respiration, architecture and childhood enuresis: Correlates between polysomnography and questionnaire.

Nocturnal enuresis (NE) and sleep-disordered breathing (SDB) are common in childhood. While the two disorders are linked, those links are still being clarified. This study compared sleep profiles and enuresis-related behaviours between children with NE and those without, who were referred to a tertiary sleep unit with suspected SDB, using the combination of polysomnography (PSG) and questionnaire. Continuous numerical data were analysed after adjusting for body mass index z-score. The study included 52 Children (39 boys, 13 girls) aged 5-14 years. Twenty-one had enuresis (10 monosymptomatic enuresis (MNE) and 11 non-monosymptomatic enuresis (NMNE)) and 31 did not have enuresis. The majority had comorbidities. On PSG, all children with NE had moderate obstructive sleep apnoea (OSA) compared to the control group which were of mild OSA. Children with NMNE had a higher percentage time in stage-3 non-REM sleep when compared to the non-enuretic and MNE groups (P < 0.05). On the questionnaire, more parents of the NE groups reported that their child was 'difficult to wake in the morning' (P < 0.05). In this heterogeneous population referred for suspected SDB, children with NE had moderate OSA, yet those with MNE had increased arousals and more often report difficulty waking than children with suspected SDB who do not wet, while children with NMNE exhibit changes in sleep architecture suggesting deeper sleep. These differences may impact treatment choices for children with enuresis.

Do Anxiety and Mood Vary among Disparate Sleep Profiles in Youth with Craniopharyngioma? A Latent Profile Analysis

ABSTRACT Introduction: Craniopharyngioma is a histologically benign brain tumor that arises in the suprasellar region affecting critical neurovascular structures including the hypothalamic-pituitary-adrenal axis and optic pathways. Children with craniopharyngioma often experience excessive daytime sleepiness which may be compounded by anxiety and depression. The current study investigated disparate sleep profiles to better understand psychological adjustment among children diagnosed with craniopharyngioma. Method: Actigraphs recorded nightly sleep data, including measures of sleep onset latency and wake after sleep onset, in a cohort of 80 youth between the ages of 2 and 20 years (median age = 9). Parent reports of behavioral and emotional functioning were included in the analysis. A latent profile analysis examined disparate sleep profiles, and a multinomial logistic regression examined differences of anxiety and depression among the sleep profiles. Results: The latent profile analysis revealed three sleep profiles: “variable sleepers” (48.3%), “consistently poor sleepers” (45.4%), and “night wakers” (6.4%). Consistently poor sleepers had lower rates of anxiety (g = .76; p = .009) and depression (g = .81; p = .003) than variable sleepers and had significantly lower rates of anxiety than night wakers (g = .52; p = .05); all other differences were nonsignificant (ps > .05). Discussion: Youth with craniopharyngioma who have nightly variations in sleep may have worse psychological functioning than those with more consistent, albeit poor, sleep patterns. Patients with craniopharyngioma who report variable sleep should be assessed for anxiety and depression to prevent and intervene on emotional difficulties that may be reciprocally related to sleep.

Sleep in Older Adults and Its Possible Relations With COVID-19.

Since the beginning of the COVID-19 pandemic, older adults have been found to be a highly vulnerable group, with a higher prevalence of severe cases and negative outcomes. Research has focused on the reasons why older adults are at greater risk; Sleep-related factors have been suggested as one possible explanation for this. An individual’s sleep pattern undergoes significant changes over the course of their life. In older adults a specific sleep profile can be observed, one characterized by advanced sleep timing, a morningness preference, longer sleep-onset latency, shorter overall sleep duration, increased sleep fragmentation, reduced slow-wave sleep and, increased wake time after sleep onset. Additionally, an increased prevalence of sleep disorders can be observed, such as obstructive sleep apnea and insomnia. Previous research has already linked sleep disorders (especially sleep apnea) with COVID-19, but few studies have focused specifically on the older population. We believe that the intrinsic sleep patterns of older adults, and the prevalence of sleep disorders in this population, may be important factors that could explain why they are at a greater risk of negative COVID-19 outcomes. In this review, we discuss the relationship between sleep and COVID-19 among older adults, focusing on three different aspects: (1) Sleep-related issues that might increase the likelihood of getting infected by SARS-COV-2; (2) Sleep disturbances that might increase the predisposition to worse COVID-19 prognosis and outcomes; and (3) COVID-19-related aspects affecting community-dwelling older adults, such as social isolation, quarantine, and home confinement, among others, that might impact sleep.

Using mobile wearables to establish sleep bioprofiles in newly diagnosed multiple myeloma (MM) patients.

8040 Background: Passive monitoring using wearables can objectively measure sleep over extended time periods. MM patients (PTs) are susceptible to fluctuating sleep patterns due to pain and dexamethasone (dex) treatment. In this prospective study, we remotely monitored sleep patterns on 40 newly diagnosed MM (NDMM) PTs while administering electronic PT reported outcome (ePRO) surveys. The study aim was to establish sleep bioprofiles during therapy and correlate with ePROs. Methods: Eligible PTs for the study had untreated NDMM and assigned to either Cohort A – PTs &lt; 65 years or Cohort B – PTs ≥ 65 years. PTs were remotely monitored for sleep 1-7 days at baseline [BL] and continuously up to 6 therapy cycles. PTs completed ePRO surveys (EORTC - QLQC30 and MY20) at BL and after each cycle. Sleep data and completed ePRO surveys were synced to Medidata Rave through Sensorlink technology. Associations between sleep measurement trends and QLQC30 scores were estimated using a linear mixed model with a random intercept. Results: Between Feb 2017 - Sep 2019, 40 PTs (21 M and 19 F) were enrolled with 20 in cohort A (mean 54 yrs, 41-64) and 20 in cohort B (mean 71 yrs, 65-82). Regimens included KRd 14(35%), RVd 12(30%), Dara-KRd 8(20%), VCd 5(12.5%), and Rd 1(2.5%). Sleep data was compiled among 23/40 (57.5%) PTs. BL mean sleep was 578.9 min/24 hr for Cohort A vs. 544.9 min/24 hr for Cohort B (p = 0.41, 95% CI -51.5, 119.5). Overall median sleep trends changed for cohort A by -6.3 min/24 hr per cycle (p = 0.09) and for cohort B by +0.8 min/24 hr per cycle (p = 0.88). EPRO data trends include global health +1.5 score/cycle (p = 0.01, 95% CI 0.31, 3.1), physical +2.16 score/cycle (p &lt; 0.001, 95% CI 1.26, 3.07), insomnia -1.6 score/cycle (p = 0.09, 95% CI [-3.47, 0.26]), role functioning +2.8 score/cycle (p = 0.001, 95% CI 1.15, 4.46), emotional +0.3 score/cycle (p = 0.6, 95% CI -0.73, 1.32), cognitive -0.36 score/cycle (p = 0.44, 95% CI -1.29,0.56), and fatigue -0.36 score/cycle (p = 0.4, 95% CI -1.65, 0.93). No association between sleep measurements and ePRO were detected. Difference in sleep on dex days compared to all other days during the sample cycle period for cohort A was 81.4 min/24 hr (p = 0.004, 95% CI 26, 135) and for cohort B was 37.4 min/24 hr (p = 0.35, 95% CI -41, 115). Conclusions: Our study provides insight into wearable sleep monitoring in NDMM. Overall sleep trends in both cohorts do not demonstrate significant gains or losses, and these trends fit with HRQOL ePRO insomnia responses. Upon further examination, we demonstrate objective differences (younger PTs) in intra-cyclic sleep measurements on dex days compared to other cycle days (less sleep by &gt; 1 hr). For older patients, less variation in sleep profiles was detected during dex days, possibly due to higher levels of fatigue or longer sleep duration. Sleep is an integral part of well-being in the cancer patient. Future studies should continue to characterize sleep patterns as it relates to HRQOL.

Sleep profile predicts the cognitive decline of mild-moderate Alzheimer's disease patients.

To investigate the association between sleep and cognitive decline of patients with mild-moderate Alzheimer's disease. Observational, prospective study, including consecutive patients diagnosed with mild-moderate Alzheimer's disease. Cerebrospinal fluid was collected for amyloid-beta, total-tau, and phospho-tau levels determination. Also, overnight polysomnography was performed, followed by neuropsychological evaluations at baseline and after 12 months of follow-up. Principal component analysis revealed two profiles of patients in terms of sleep: one with a propensity to deepen the sleep (deep sleepers) and the other with a propensity to spend most of the time in the lighter sleep stage (light sleepers). The cohort included 125 patients with a median [IQR] of 75.0 [72.0;80.0] years. Deep and light sleepers did not present differences in relation to the cerebrospinal fluid pathological markers and to the cognitive function at the baseline. However, there was a significant difference of -1.51 (95% CI: -2.43 to -0.59) in the Mini-mental state examination after 12 months of follow-up. Accordingly, sleep depth and cognitive decline presented a dose-response relationship (p-for-trend = 0.02). Similar outcomes were observed in relation to the processing speed (Stroop words test, p-value = 0.016) and to the executive function (Verbal fluency test, p-value = 0.023). Considering the increased cognitive decline presented by light sleepers, the sleep profile may have a predictive role in relation to the cognitive function of patients with mild-moderate Alzheimer's disease. The modifiable nature of sleep sets this behavior as a possible useful intervention to prevent a marked cognitive decline. Role of Hypoxia Ans Sleep Fragmentation in Alzheimer's Disease. and Sleep Fragmentation. Completed. NCT02814045.

773 The relationship between personality and sleep: Subjective cognition as a mediator

Abstract Introduction Research has found relationships between sleep quality and personality traits. Poor subjective sleep quality has been observed within individuals scoring high in Neuroticism and low in Conscientiousness. Personality traits have also been associated with cognitive functioning and the link being worse cognition and poor sleep quality is established. However, less is known regarding the role of cognitive functioning in the relationship between personality and sleep quality, particularly in aging populations. This study investigated whether subjective cognition acted as a mediator between individual personality traits and subjective sleep quality in middle-aged and older adults. Methods Middle-aged and older adults (N=269; Mage= 64.5, SD=7.8; 123 women/146 men) who were cognitively healthy completed an online survey through Qualtrics measuring demographics, personality (Big Five Inventory-10; BFI-10), self-reported sleep (Pittsburgh Sleep Quality Index; PSQI), and subjective everyday cognition (Cognitive Failures Questionnaire; CFQ). Separate mediation analyses using SPSS PROCESS macro [and testing for indirect effects using 5,000 bootstrapped samples and 95% Confidence Interval (CI) and controlling for conditional associations among all pathways] examined whether subjective everyday cognition (CFQ scores) mediated the relationship between different personality traits (BFI-10 Conscientiousness and Neuroticism scores) and self-reported sleep (PSQI-Total Score), controlling for age and sex. Results Neuroticism and PSQI-Total Score was partially mediated by CFQ. There was a significant association between Neuroticism and total PSQI (total effect=0.588, SE=0.110, p&amp;lt;0.001). There were positive associations between Neuroticism and CFQ (a-path effect=2.765, SE=0.383, p&amp;lt;0.001) and CFQ and PSQI (b-path effect=0.068, SE=0.017, p&amp;lt;0.001). The indirect effect was significant (effect=0.187, SE=0.054, 95% CI=0.088 to 0.301). There was no association between Conscientiousness and PSQI-Total Score (total effect=-0.123, SE=0.133, p=0.358), therefore mediation analysis (testing of CFQ as a mediator) was discontinued. Conclusion In middle-aged and older adults, subjective everyday cognition mediates the relationship between Neuroticism personality trait and self-reported sleep quality. Individuals scoring higher in Neuroticism report worse subjective sleep quality as their subjective cognitive failures increase. Findings underscore the interacting roles of personality and everyday cognition on perceived sleep. Clinicians should consider individual personality profiles (via personality assessments) and subjective everyday cognitive ratings for a better understanding of the factors impacting middle-aged and older adults’ sleep profiles. Support (if any):

745 Association of Longitudinal Sleep Profiles with Cognitive Functioning in Bipolar Disorder

Abstract Introduction Emerging evidence suggests that some cognitive deficits in bipolar disorder may be attributed to sleep disturbance. However, current findings are limited by cross sectional analyses or longitudinal studies with sparse follow up on sleep quality. The current study examined longitudinal profiles of sleep as predictors of cognitive performance across a series of domains to better understand how sleep disturbance may impact in bipolar patients. Methods 241 bipolar disorder and 103 control participants had their sleep measured at baseline, 6- and 12-months using the Pittsburgh Sleep Quality Index (PSQI). Individuals with a “poor” categorical PSQI sleep rating (PSQI total score &amp;gt;5) at all time points were categorized as “Poor Sleepers” (n = 134). Those rated “good” at each time point were “Healthy Sleepers” (n = 107), and those with at least one discrepant sleep rating at any time point were labeled “Unstable Sleepers” (n = 103). Cognitive performance was assessed at 12-months, testing domains of memory, processing speed, and executive function. ANOVAs controlling for demographics, mood symptom severity, and diagnostic group examined effects of sleep profiles on cognitive function. Results Main effects for sleep group were found for the California Verbal Learning Test across all short and long delay recall conditions (F’s 4.45 – 5.8, p &amp;lt;.02 for all). The poor sleep group performed the worst, while no main effects for diagnosis were observed. Main effects of sleep group were found for time conditions of the Trail making task (F = 4.18, p = .016), but not for errors. Conclusion Sleep quality was more strongly related to verbal and visual memory than bipolar diagnosis, with weaker effects for executive function. Some cognitive domains in bipolar disorder may be more closely related to sleep disturbance than endogenous factors. Future studies should explore how improvements in sleep functioning relate to neurocognitive outcomes, and whether cognitive performance varies as a function of sleep instability independent of mood instability. Support (if any) Support: Heinz C. Prechter Bipolar Research Fund at the University of Michigan Depression Center, the Department of Veterans Affairs (IK2-CX001501; PI: Boland), the VISN 4 MIRECC, and National Institute of Mental Health (K23MH118580; PI: Goldschmied).

The curious incident of the dog in the nighttime: The effects of pet-human co-sleeping and bedsharing on sleep dimensions of children and adolescents

BackgroundPets are often thought to be detrimental to sleep. Up to 75% of households with children have a pet, and 30-50% of adults and children regularly share their bed with their pets. Despite these high rates, few studies have examined the effect of pet-human co-sleeping on pediatric sleep. This study compared subjective and objective sleep in youth who never, sometimes, or frequently co-slept with pets. MethodsChildren (N = 188; aged 11-17 years; M = 13.25 years) and their parents answered standardized sleep questionnaires assessing timing, duration, onset latency, awakenings, and sleep quality. Children completed a home polysomnography (PSG) sleep study for one night and wore an actigraph for two weeks accompanied with daily sleep diary. Based on reported frequency of bedsharing with pets, children were stratified into three co-sleeping groups: never (65.4%), sometimes (16.5%), frequently (18.1%). ResultsOverall, 34.6% of children reported co-sleeping with their pet sometimes or frequently. Results revealed largely identical sleep profiles across co-sleeping groups; findings were congruent across sleep measurement (subjective: child, parent report; objective: PSG, actigraphy). Effect sizes indicated that frequent co-sleepers had the highest overall subjective sleep quality, but longest PSG onset-latency compared to the sometimes group. ConclusionsCo-sleeping with pets was prevalent in one third of children. Sleep dimensions were similar regardless of how frequently children reported sharing their bed with their pet. Future research should examine dyadic measurement of co-sleepers to derive causal evidence to better inform sleep recommendations.

Sleep Disorders and Psychological Profile in Oral Cancer Survivors: A Case-Control Clinical Study.

Simple SummarySleep disorders have been increasingly investigated in several medical illnesses as their presence may affect patients’ quality of life. However, the research examining sleep disorders in oral cancer is relatively weak. Indeed, the majority of the available studies present a cross-sectional or retrospective designs. Moreover, very few of them have evaluated quality of sleep in oral cancer survivors (OC survivors). We aimed to carry out a case-control study with the purpose to investigate sleep disorders and mood impairment in 50 OC survivors. Our research has shown that quality of sleep is significantly affected in OC survivors compared to a healthy population and that OC survivors suffers from higher levels of anxiety and depression. Our results may suggest that an appropriate assessment of quality of sleep and psychological profile should be performed in OC survivors as a prompt treatment for both sleep and mood disorders is crucial for the overall improvement of patients’ quality of life.Quality of sleep (QoS) and mood may impair oral cancer survivors’ wellbeing, however few evidences are currently available. Therefore, we aimed to assess the prevalence of sleep disorders, anxiety and depression among five-year oral cancer survivors (OC survivors). 50 OC survivors were compared with 50 healthy subjects matched for age and sex. The Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the Hamilton Rating Scales for Depression and Anxiety (HAM-D, HAM-A), the Numeric Rating Scale (NRS), the Total Pain Rating Index (T-PRI) were administered. The global score of the PSQI, ESS, HAM-A, HAM-D, NRS, T-PRI, was statistically higher in the OC survivors than the controls (p-value: <0.001). QoS of OC survivors was significantly impaired, especially with regard to some PSQI sub-items as the subjective sleep quality, sleep latency and daytime dysfunction (p-value: 0.001, 0.029, 0.004). Moreover, poor QoS was negatively correlated with years of education (p-value: 0.042 *) and positively correlated with alcohol consumption (p-value: 0.049 *) and with the use of systemic medications (p-value: 0.044 *). Sleep disorders and mood disorders are common comorbidities in OC survivors; therefore, early assessment and management before, during and after treatment should be performed in order to improve the quality of life of OC survivors.