bluuebunny/crossref_metadata_2025_split huggingface dataset:
0564 Sleep patterns of patients on home parenteral nutrition: a home-based observational study
Authors: Dashti Hassan , Godbole Meghna , Chen Angela , Mogensen Kris , Leong Aaron , Burns David , Winkler Marion , Saxena Richa , Compher Charlene 
Published: May 2022

Abstract

Introduction
Whereas home parenteral nutrition (HPN), a form of nutrition administered through a central venous catheter for patients with intestinal failure, is necessary for survival, the current standard practice for HPN is to administer infusions for approximately 12-hour periods overnight, coinciding with nighttime sleep. Patients supported with HPN often report poor sleep, however limited research has been conducted to objectively measure sleep patterns of HPN-dependent patients.

Methods
We aimed to characterize the sleep patterns of patients on HPN through 7-day actigraphy in a remote, home-based observational study. Sleep measures of clinical importance were derived from actigraphy including sleep duration, sleep efficiency, sleep onset latency, and wake after sleep onset. Participants also completed validated sleep surveys electronically.

Results
20 participants completed all study procedures [mean (standard deviation): age =51.6 (13.9), BMI =21.4 kg/m2 (4.6), 80% female]. The population median (interquartile range) for sleep duration, sleep efficiency, sleep onset latency, and wake after sleep onset was 6.9 (1.1) hours, 83.3 (7.8) %, 11.8 (7.1) minutes and 57.2 (39.9) minutes, respectively, and 55%, 60%, 35%, and 100% of participants did not meet the recommendations for these measures from the National Sleep Foundation. 65% of participants reported napping at least once during the 7-day period. Based on the Insomnia Severity Index, 70% of participants were classified as having sub-threshold or more severe insomnia. Based on the Pittsburgh sleep quality index, 85% were classified as having significant sleep disturbance.

Conclusion
Most HPN-dependent patients likely have disrupted sleep largely driven by difficulty maintaining sleep. The extent to which overnight HPN infusions contributed to poor sleep cannot be elucidated from this observational study. Addressing known factors that contribute to poor sleep and encouraging sleep hygiene and sleep interventions are imperative to improve the overall quality of life of patients requiring HPN.

Support (If Any)
Research reported in this publication was supported by the American Society for Parenteral and Enteral Nutrition (ASPEN) Rhoads Research Foundation.
0590 Factors Associated with Sleep Health in Young Women After Breast Cancer Treatment
Authors: Hwang Youri , Conley Samantha , Jeon Sangchoon , Redeker Nancy , Sanft Tara , Knobf Mary 
Published: May 2022

Abstract

Introduction
Poor sleep health adversely affects quality of life and prognosis in cancer survivors, yet there is limited evidence on sleep health in young women with breast cancer (YWBC). The purpose of this study was to identify sociodemographic, clinical, and psychosocial factors associated with sleep health.

Methods
We conducted a cross-sectional study. Eligible participants were women diagnosed with stage I-III breast cancer ≤ 50 years of age and within 5 years from primary cancer treatment. Sociodemographic, clinical, and psychosocial data were collected through an online survey. Sleep health and psychosocial data were assessed by the Pittsburgh Sleep Quality Index (PSQI), PROMIS depression and anxiety, and the McMaster Family Device General Functioning subscale. Data were analyzed with logistic regression. A PSQI cut-off score of &gt;8 was used to define poor sleep health based on the study data and the cancer sleep literature.

Results
The sample included 159 YWBC with a mean age of 43.6 years (SD=6.8), the majority of whom were non-Hispanic White (84%) and completed chemotherapy or radiotherapy (&gt;70%). Half of the participants were premenopausal at diagnosis and became peri- or postmenopausal after treatment. The mean global PSQI was 9.3 (SD=3.6) and 55% reported poor sleep health. About half of the participants slept &lt;7 hours per night, 87% spent &gt;15 minutes falling asleep, and 58% reported taking medication to sleep. Non-White underrepresented groups (OR=7.56, p&lt;.01), more severe night sweats (OR=9.00, p&lt;.001), no history of endocrine therapy (OR=2.73, p&lt;.05), more severe anxiety (OR=1.08, p&lt;.01) and depression (OR=1.06, p&lt;.05), and poorer family functioning (OR=3.78, p&lt;.001) were associated with poor sleep health.

Conclusion
The findings suggest that poor sleep health is a significant clinical problem in YWBC. Sleep assessment, education, and appropriate referrals should be part of routine survivorship care. Social determinants of health such as race and ethnicity and family functioning warrant further investigation related to sleep health. Future studies are needed to confirm the relationships of sociodemographic and clinical factors, psychological symptoms, and family functioning with sleep health.

Support (If Any)
The Global Korean Nursing Foundation.
0600 The moderating effect of comorbid insomnia on the association of obstructive sleep apnea with mood, and with diabetes-related distress in adults with type 2 diabetes
Authors: Jeon Bomin , Luyster Faith , Sereika Susan , DiNardo Monica , Callan Judith , Chasens Eileen 
Published: May 2022

Abstract

Introduction
Previous findings showed that insomnia in persons with type 2 diabetes (T2D) may have a greater impact on mood disturbances than obstructive sleep apnea (OSA) and that insomnia contributed to the severity of diabetes-related distress. This study examined insomnia severity as a moderator of the association between OSA severity with mood, and with diabetes-related distress in adults with OSA and T2D.

Methods
This secondary analysis used pooled baseline data (N=240) from two independent randomized controlled trials that evaluating the efficacy of OSA and insomnia treatment in persons with T2D. OSA (apnea-hypopnea index [AHI] ≥ 5 events per hour) was determined by in-home ApneaLinkPlus®. Insomnia severity was measured by the Insomnia Severity Index, mood by the Profile of Mood States, and diabetes-related distress by the Problem Areas in Diabetes Scale. Possible moderator effect of insomnia severity was examined using hierarchical multiple linear regression analysis, controlling for demographic characteristics and restless leg syndrome (RLS).

Results
Participants were middle-aged (mean age ± SD [years] = 57.80 ± 10.17), White (65%), educated post high school (56.3%), evenly distributed by gender (49.6% female) and marital status (47.9%), with 34.3% reporting financial difficulty. Participants had poorly controlled diabetes (mean HbA1c ± SD [%] = 7.93 ± 1.62) and 15.5% reported symptoms of RLS. Insomnia severity had a moderating effect on the association between OSA severity and mood states (b = -.048, p = .017). Insomnia severity had no significant moderating effect on the relationship between OSA severity and diabetes-related distress (b = -.009, p = .458), but independently increased the level of diabetes-related distress (b =1.133, p &lt; .001).

Conclusion
Insomnia severity moderated the association between OSA severity and mood states in adults with OSA and T2DM. Counterintuitively, as OSA severity increased, the level of mood disturbances decreased depending on insomnia severity. In addition, insomnia was independently associated with diabetes-related distress. These findings suggest that insomnia may be the primary underlying sleep disorder which is associated with psychological factors in persons with T2D. Findings need further investigation because psychological factors are known to be associated with worse glycemic control.

Support (If Any)
The NIH funded the parent studies (R01-DK0960281; K24-NR016685) and the CTSI grants (UL1-RR024153; UL1-TR000005)
0607 Prevalence and Correlates of Sleep Disorders Among Users of a Consumer Sleep Technology
Authors: Gahan Luke , Gottlieb Elie , Aman Aman , Watson Nathaniel , Raymann Roy 
Published: May 2022

Abstract

Introduction
Sleep disorders constitute a major public health burden yet remain widely undiagnosed and untreated. The prevalence of diagnosed sleep disorders and associations with objectively measured sleep-wake dysfunction vary widely across populations. Here, we examined the self-reported prevalence and objective sleep architectural correlates of four sleep disorders in a large sample of individuals using a consumer sleep technology.

Methods
Data from 33,429 users (mean age: 44.6, 55.1% female) across 1,842,282 nights were included in the analysis from the PSG-validated SleepScore Mobile Application, which uses a non-contact, sonar-based method to objectively capture sleep-related metrics, and questionnaires to capture self-reported data. Subjective sleep disorder information was ascertained by asking users, “Which of the following sleep disorders has a healthcare professional diagnosed you with?” Linear regression was used for analysis, while age and gender were used as confounding variables, with the cohort reporting “None of the above” were used reference group for research purposes.

Results
The prevalence of reported disorders were “None of the above” (n=23,732,71.0%), sleep apnea/SDB (n=5,309, 15.9%), insomnia (n=3,968, 11.9%), RLS/PLM (n=2,295, 6.87%), or narcolepsy (n=266, 0.8%). Narcolepsy was associated with the greatest reduction in TST (ß=-23.6 mins, SE=3.475, p&lt;0.001) while insomnia was associated with smallest (ß=-5.7mins, SE=0.979, p&lt;0.001). Narcolepsy was associated with the greatest increase in WASO (ß=7.0 mins, SE=1.815, p&lt;0.001) while insomnia was associated with smallest (ß=2.2 mins, SE=0.511, p&lt;0.001). RLS/PLM was associated with the greatest increase in SOL (ß=3.9mins, SE=0.302, p&lt;0.001) while sleep apnea/SDB was associated with the smallest (ß=2.171 mins, SE=0.22, p&lt;0.001). Narcolepsy was associated with the greatest decrease in SE (ß=-3.05%, SE=0.5, p&lt;0.001) while insomnia was associated with smallest (ß=-1.42%, SE=0.1, p&lt;0.001).

Conclusion
Self-reported sleep disorders were associated with objectively poor sleep in a big data consumer sleep technology analysis. These findings suggest consumer sleep technologies may have value in screening for sleep disorders in the general population and may motivate these individuals to seek care in clinical sleep medicine settings.

Support (If Any)
0627 The Effects of Insomnia Therapy on Depression, Anxiety, and Daily Functioning in Individuals with Insomnia and Mild Cognitive Impairment
Authors: Morehouse Allison , O'Hora Kathleen , Hernandez Beatriz , Lazzeroni Laura , Zeitzer Jamie , Friedman Leah , Posner Donn , Kushida Clete , Yesavage Jerome , Goldstein-Piekarski Andrea 
Published: May 2022

Abstract

Introduction
Insomnia is common in older adults with and without mild cognitive impairment (MCI), and is associated with worse neuropsychiatric symptoms (NPS) and impaired daily functioning. Evidence suggests treating insomnia may resolve some of these difficulties in cognitively normal adults. However, little is known about the effects of improving sleep on these domains in older adults with MCI.

Methods
We examined whether MCI status moderates the improvements of a behavioral intervention for insomnia on NPS and daily functioning. 125 adults (mean age=69.18, 34.4% male) with insomnia (38 with MCI as determined by a Montreal Cognitive Assessment; MoCA score &lt; 26) completed the Insomnia Severity Index (ISI), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and five domains (activity, vigilance, intimacy, productivity, and social) of the Functional Outcomes of Sleep Questionnaire (FOSQ) before (BL) and after (ETX) completing either the behavioral, cognitive, or combined components of Cognitive Behavioral Therapy for Insomnia (CBT-I). Linear mixed effects models were used to determine the effect of MCI status, time, and an MCI-by-time interaction on NPS and daily functioning while covarying for sex.

Results
Treatment improved BDI (p&lt;0.001), BAI (p&lt;0.001), ISI (p&lt;0.001), productivity (p&lt;0.008), activity (p&lt;0.001), social functioning (p=0.014), and FOSQ total score (p=0.015) regardless of MCI status at ETX compared to BL. Treatment did not significantly improve vigilance (p=0.154) or intimacy (p=0.439). There was a significant MCI-by-time interaction for the FOSQ social domain (p=0.041) with MCI participants showing greater improvements in social functioning compared to non-MCI participants. There were no other significant MCI-by-time interactions.

Conclusion
These findings suggest insomnia therapy can similarly improve aspects of sleep-related daily functioning, insomnia severity, and NPS regardless of MCI. However, insomnia therapy may be more beneficial in improving social functioning for individuals with MCI.

Support (If Any)
NIMHR01MH101468-01; Mental Illness Research, Education, and Clinical Center (MIRECC) at the VAPAHCS
0641 Automated Detection of Isolated REM Sleep Behavior Disorder (iRBD) During Single Night In-Lab Video-Polysomnography (PSG) Using Computer Vision
Authors: Adaimi George , Gupta Niraj , Mottaghi Ali , Yeung Serena , Mignot Emmanuel , Alahi Alexandre , During Emmanuel 
Published: May 2022

Abstract

Introduction
At least 1% of adults aged 45 and above have isolated REM sleep behavior disorder (iRBD), a prodromal stage of a synucleinopathy, however a majority remains undiagnosed until they develop irreversible neuropathology. The gold-standard diagnostic procedure, the in-lab video-polysomnography (PSG), relies on complex rules for sleep staging and electromyography quantification which potentially lead to incorrect diagnoses. We tested a computer vision classifier for RBD versus other sleep conditions based on automated video analysis of body movements during a single-night in-lab PSG.

Methods
Raw PSG video recordings of 60 iRBD patients (mean 67 years, 78% males) and 100 controls (mean 65, 65% males) were selected from the Stanford Sleep Center database. Our pipeline involved three main steps: movement detection, feature extraction, and RBD recognition. The recordings between lights off and lights on were 7 to X hours in duration with some interspersed short movements. For every recording, short video segments that contain movements were first extracted using background subtraction. Additional features, such as sleep-onset time and wake-up time, were used to filter out noisy segments that did not involve patients being asleep. Next, I3D, a state-of-the-art method for action recognition, was used to derive a feature vector of 2048 features from every extracted segment. RBD diagnosis could be considered as an action recognition task in which ‘RBD’ was the action category to be classified. For every recording, the feature vectors for every segments were averaged, resulting in one feature vector per subject. With 160 PSG video recordings, this resulted in a dataset of 160 feature vectors that were used to train a multi-layer perceptron (MLP) for RBD recognition.

Results
Leave-one-out cross-validation (LOOC) procedure was used for evaluation achieving 91.9% accuracy, with a 78.3% sensitivity and 100% precision.

Conclusion
We tested the feasibility and performance of a new diagnostic paradigm for RBD solely based on single-night video analysis of PSG. Our results suggest that a machine learning model can detect and distinguish the characteristics of movements related to RBD versus other sleep disorders and normal sleep. Larger studies in heterogeneous datasets are needed to validate these findings.

Support (If Any)
Google
0648 Decreased Slow-Wave Sleep May Exacerbate Anxiety in Individuals with Low Anxiety
Authors: Games Margaux , Goldstein Elena , Palermo Emma , Costello Samantha , Owens Kendall , Goldschmied Jennifer 
Published: May 2022

Abstract

Introduction
Evidence suggests that individuals with generalized anxiety disorder exhibit decreases in slow-wave sleep (SWS). Because SWS has been shown to be modifiable, it is imperative to better understand the relationship between symptoms of anxiety and amount of SWS to inform treatment development. This study aimed to explore the relationship between anxiety and SWS, and to investigate the impact of slow-wave sleep disruption on state anxiety.

Methods
Twenty-seven participants’ (mean age 30.9) were recruited as part of an ongoing study examining the relationship between SWS and depression. Participants spent two nights in the laboratory: baseline (BL) and slow-wave disruption (SWD), where SWS was disrupted using auditory stimulation. Anxiety was measured using the State-Trait Anxiety Inventory (STAI). Both trait and state anxiety (BL, SWD) measures were collected. Repeated measures ANOVA was used to determine the impact of SWD on state anxiety.

Results
Participants’ trait anxiety scores were significantly correlated with percent N3, such that greater anxiety was associated with less N3 (r = -0.43; p&lt;0.05). Individuals were then categorized as either high-anxiety (HA) or low-anxiety (LA) by median split (M=46.5). Results of the repeated measures showed a significant main effect of group (F=43.963; p&lt;0.001), with HA individuals showing greater state anxiety than LA individuals. A significant interaction of group*condition was also found (F(1,24)=4.703; p=0.40). LA participants showed a significant increase in state anxiety following SWD (t=-2.539; p=0.028), while HA participants showed no change.

Conclusion
The current findings replicate previous research showing that anxious individuals have a reduced amount of SWS and demonstrate that decreases in SWS may exacerbate anxiety in individuals with low anxiety. Further, this work suggests that individuals with high anxiety may be more resilient to changes in anxiety state than individuals with low anxiety when SWS is reduced.

Support (If Any)
Goldschmied: K23MH118580 (NIMH)
0669 The Role Of Hypersomnolence In Depression: Results From A Longitudinal Study Of The American General Population
Authors: Ohayon Maurice , Pakpour Amir , Cote Marie Lise 
Published: May 2022

Abstract

Introduction
Insomnia symptoms have often been pointed out as an important factor for the relapse and/or the maintenance of depression. However, the contribution of hypersomnolence in depression is less studied and the conclusions are unclear. Our aim is to examine the association between hypersomnolence and depression in the US general population.

Methods
This longitudinal study was carried out in eight states in the U.S. A total of 12,218 subjects were interviewed by phone during the first wave (W1) and 10,931 at the second wave (W2) three years apart. The analyses included only the subjects who participated in the 2 waves (N=10,931). Hypersomnolence symptoms and Major Depressive Disorder (MDD) were assessed according to DSM-5 criteria.

Results
At W1, 27.2% (95% CI 26.4%-28.0%) of the sample had at least one hypersomnolence symptoms listed in the DSM5 occurring at least 3 days per week. This prevalence at W2 was 26.4% (95% CI 25.6%-27.2%). The incidence of DSM5 hypersomnolence symptoms was 20.5% which represents a yearly incidence of 5.8%. For MDD, the prevalence was 5.1% (95% CI 4.7%-5.5%) and 4.2% (95% CI 3.8%-4.6%) in W1 and W2, respectively. At W1, 54.2% of participants with a MDD also had hypersomnolence. At W2, 50.7% of MDD subjects also reported hypersomnolence. After adjusting for age, gender and medical conditions, persistent hypersomnolence (i.e., reported at both interviews) predicted incident MDD (i.e., absent at the first interview but present at the follow-up) with a relative risk of 2.0 (95% CI 1.5-2.8). Similarly, persistent hypersomnolence predicted persistent MDD with a relative risk of 3.8 (95% CI 2.5-5.8). After adjusting for the presence of insomnia, persistent hypersomnolence remained a strong predictor for persistent MDD (RR: 2.4) but not for incident MDD.

Conclusion
Hypersomnolence, especially when it is persistent, is an important contributing factor for persistent MDD. While the presence of insomnia mitigates the predictive value of hypersomnolence in incident MDD, it had little effect on the association between persistent hypersomnolence and persistent MDD.

Support (If Any)
0685 Sleep, mental health and socioeconomic factors concomitantly influence the risk in tobacco consumption
Authors: Dokkedal-Silva Vinícius , Fernandes Guilherme , Morelhão Priscila , Pires Gabriel , Rowlett James , Galduróz José Carlos , La Berro ís , Tufik Sergio , Andersen Monica 
Published: May 2022

Abstract

Introduction
Extensive evidence points that sleep, psychiatric symptoms and sociodemographic factors separately affect the risk involved in substance use. Due to the well-known relationship between these 3 pillars, an investigation of the combined effect of this factors on substance use is necessary. The objective of this study was to build a model including the 3 factors simultaneously and their effect on risk in substance use.

Methods
Volunteers of the EPISONO (2007) study underwent assessment through validated questionnaires concerning their general health and a night of polysomnographic examination. For this study, scores in the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) were evaluated considering responses to questionnaires concerning sleep, psychiatric symptoms, and socioeconomic parameters, as well as polysomnographic findings. A structured equation modelling (SEM) protocol was conducted to build a theoretical model in which variables pertaining to the 3 factors of interest (sleep, mental health and socioeconomic influence) could have their simultaneous effect on substance use measured.

Results
793 participants of the EPISONO were included (mean age=43.4 years; 452 women). Significant effects were found for the tobacco consumption model. Subjective sleep quality (SSQ), psychiatric symptoms (PS) and socioeconomic status (SES) influenced the ASSIST score for tobacco consumption. Influence of PS on tobacco consumption was also mediated by SSQ. Models for other substances assessed in the ASSIST questionnaire, such as alcohol, did not find any statistically significant effect.

Conclusion
The lack of significance of models for alcohol and other substances may be related to the nature of our sample, in which not many individuals presented a substantial risk of substance involvement that could be detected by the ASSIST questionnaire. However, in the model for tobacco consumption, subjective sleep quality, socioeconomic status and psychiatric symptoms exerted an effect on tobacco consumption risk, with psychiatric symptoms having their influence mediated by self-perceived sleep quality.

Support (If Any)
Our studies are supported by Associação Fundo de Incentivo à Pesquisa (AFIP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Finance Code 001 to GLF) and Conselho Nacional de Desenvolvimento Científico Tecnológico (CNPq – Grant #141445/2021-1 to GLF); S.T. and M.L.A. received CNPq fellowships.