bluuebunny/crossref_metadata_2025_split huggingface dataset:
0955 Correlation Between CPAP Use and Symptoms of Depression, Anxiety, and Sleepiness in Patients with OSA
Authors: Singh Amitoj , Bradshaw Samuel , Niraula Rijesh , Meghpara Sanket , Keenan Lynn , Yan Yueki , DelRosso Lourdes 
Published: April 2024

Abstract

Introduction
Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder associated with poor health outcomes, including sleepiness, anxiety, and depression. This study aimed to further explore this relationship by looking at outcomes after treatment of OSA with continuous positive airway pressure (CPAP) therapy, using the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder 7 (GAD-7), and Epworth Sleepiness Scale (ESS) questionnaires respectively.

Methods
An observational longitudinal study in which the PHQ-9, GAD7, and ESS questionnaires were administered to adult patients diagnosed with OSA during the initial consultation and after three months of CPAP use. All patients had a diagnosis of OSA by a sleep study. Data collected included demographics, PSG data, and questionnaire results. Patients without follow-up or incomplete data were not included.

Results
One hundred patients were initially recruited. Thirty-five patients have completed data after three months. The mean±SD age was 50.9±15.4, BMI 36.5±8.9, 54% male and 46% female. Women were older 61.1±14 than men 46.5±14.9, p&lt; 0.001. The percent of CPAP adherence was 68.7±36.7, and hours used per day were 5.5±1.8. The PHQ-9 initially was 10.4±5.6 decreased to 5.32±5.3 p&lt; 0.001. GAD-7 initially 6.4±6.2 decreased to 4.29±4.8 p&lt; 0.001, ESS initially 11.1±5.5 decreased to 5.8±4.3 p&lt; 0.001. Neither age, BMI, or AHI correlated with compliance or hours used. The strongest negative correlation was between post-treatment GAD-7 and compliance (r= -0.45), followed by a mild negative correlation between PHQ-9 and compliance (r = -0.345). A mild positive correlation existed between the initial ESS and the AHI (r = 0.288). There were no statistical differences in questionnaire results between men and women.

Conclusion
The study demonstrates that daytime symptoms of sleepiness, depression, and anxiety improved in a cohort of patients with OSA and CPAP. The post-CPAP GAD-7 was moderately and negatively correlated with CPAP compliance percent use, while PHQ-9 was mildly negatively correlated. Initial ESS was mildly correlated with AHI, and although it improved, it was not correlated with compliance.

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0958 Prior Night Self-report and Behaviorally-assessed Sleep Duration Is Associated with the Pupillary Unrest Index
Authors: Taylor Maddison , Wescott Delainey , Klevens Alison , Franzen Peter , Roecklein Kathryn 
Published: April 2024

Abstract

Introduction
Excessive daytime sleepiness is experienced by approximately 5-10% of adults and 20-30% of older adults (Young et al., 2004). However, assessment of sleepiness has posed challenges, specifically lack of agreement between different assessments. While the construct of sleepiness hinges on insufficiently sleep, different assessments of sleepiness may conflate fatigue, mood, or anhedonia. This study tested whether physiological (Pupillary unrest) and subjectively assessed sleepiness were associated with prior night sleep duration. Results may allow subjective reports of sleepiness to be clarified with the potential to intervene more effectively.

Methods
Participants included 95 never depressed control (M age=38, SD=12) and individuals diagnosed with seasonal depression (M age=39, SD=12). We administrated the pupil sleepiness test, while the EYE-TRAC (R) 6000 tracked pupil diameter at 60Hz. The PUI was quantified as the cumulative change in pupil diameter (mm) over 1 minute. The average PUI over the full 11-minute protocol was calculated. Self-reported sleep duration was calculated as the difference between bedtime and waketime the night prior to the PUI. Self-report sleepiness was assessed via the Epworth Sleepiness Scale the week of the PUI assessment. A subset of participants had actigraphically-assessed sleep (n=47). We used multi-level models to account for repeated measures in winter and summer and included PUI testing time, diagnostic group, season, age, and gender as covariates. PUI was log transformed to account for skewness.

Results
The PUI was inversely associated with both self-report (b=-0.03, p=0.01) and actigraphy sleep duration (b=-0.00, p=0.02). Conversely, subjective sleepiness was not associated with either self-report sleep duration (b=-0.00, p=0.16) or actigraphy calculated sleep duration (b=-0.02, p=0.31).

Conclusion
The current findings suggest the PUI is correlated with sleep duration the prior night, but subjective reports of sleepiness is not. This indicates that sleep duration may be a mechanism contributing to excessive physiological daytime sleepiness. Individuals reporting greater sleepiness may be actually experiencing fatigue, anhedonia, or depressed mood; overlapping but distinct constructs with unique etiological considerations. Future work should work to examine how different sleep parameters may be differentially related to sleepiness and fatigue constructs, and to determine if using the PUI to match intervention strategies is clinically advantageous.

Support (if any)
NIH
0960 Unraveling Sleep EEG-ECG Interactions in Major Depression: Preliminary Results of a Coherence Analysis
Authors: Azad Mohammad Hasan , Robillard Rebecca , Higginson Caitlin , Lina Jean-Marc , Forouzanfar Mohamad 
Published: April 2024

Abstract

Introduction
In addition to common sleep disturbances, major depression involves intricate interactions between the cardiovascular and central nervous systems, underscoring the multidimensional nature of its pathophysiology. This study investigates how brain and heart activity interact across sleep states and brain topography in the context of depression.

Methods
Simultaneous sleep electrocardiograms (ECG) and electroencephalograms (EEG: F3, C3, and O1) were extracted from the polysomnograms of 50 individuals diagnosed with major depression and 50 controls. Following artifact removal, a coherence metric based on cross-power spectral density between the ECG and EEG was developed to characterize brain-heart connections in the 0.015-4 Hz delta and 4-8 Hz theta bands. Statistical analysis including bootstrapping, t-tests, analysis of variance, and multiple comparison tests were utilized to identify significant differences in brain-heart coherence between the depressed and healthy groups.

Results
Preliminary results show that, in NREM sleep within the theta band, individuals with depression showed significantly higher mean of ECG-EEG coherence values (MCV) compared to healthy controls across all EEG channels. MCVs for the depression and control group respectively were: 0.576±0.014 vs. 0.563±0.014 in F3, 0.545 ± 0.006 vs. 0.540±0.008 in C3, and 0.574±0.014 vs. 0.563±0.012 in O1 (p&lt; 0.0001). No significant group difference was observed during REM sleep. Furthermore, irrespective of depression status, the MCV in O1 was significantly higher in NREM compared to REM sleep for the full spectrum between the delta and theta bands (p&lt; 0.00001). In contrast, MCV in F3 and C3 did not significantly differ between NREM and REM sleep. In the delta band, regardless of depression status, the MCV was significantly lower in C3 compared to F3 and O1 during NREM sleep, but during REM sleep MCV was significantly higher in C3 than in O1 (p&lt; 0.0001).

Conclusion
The higher brain-heart coherence linked to theta activity during NREM sleep we observed in people with depression may suggest stronger interactions between autonomic and cortical arousal. This could be one of the factors worsening sleep during depression. Beyond generating new insights about pathophysiological mechanisms underlying the high comorbidity between sleep, cardiovascular, and mental disorders, this may inform further work to identify multi-systemic biomarkers of depression.

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0962 Reciprocal Interactions Between Sleep and Mental Health: A Structural Equation Analysis in a Digital Cohort
Authors: Julien Coelho , Pécune Florian , D'Incau Emmanuel , Sagaspe Patricia , Levavasseur Yannick , De Sevin Etienne , Micoulaud-Franchi Jean-Arthur , Philip Pierre 
Published: April 2024

Abstract

Introduction
New digital tools constitute an opportunity in understanding the interactions between sleep health and mental health. Structural equation analysis applied to these e-cohort allows to study the bidirectional associations between these dimensions. Thus, we aimed to study the reciprocal interactions between behaviors (duration, temporality, regularity) and sleep health (insomnia and somnolence) and mental health (anxiety and depression).

Methods
Digital cohort of 3000 participants invited to complete weekly self-questionnaires over 17 days on their sleep health (Epworth and ISI), their mental health (PHQ-9 and PHQ-2) as well as sleep diaries which made it possible to calculate their sleep behaviors (duration, median, and regularity index). The interaction analysis used a longitudinal structure equation model.

Results
The average age of the participants was 51 years (68% women). The average sleep duration was 7h24, the median sleep time was 3h30 in the morning, the regularity index was 84/100. Among them, 57% reported insomnia (ISI≥15), 41% reported drowsiness (ESS≥11), 19% reported anxiety (PHQ-2≥3) and 18% reported depression (PHQ-9≥15). Sleep behaviors were associated with sleep health and mental health cross-sectionally. Longitudinal structural equation modeling shows bidirectional associations between sleep health behaviors and mental health.

Conclusion
The demonstration of these reciprocal interactions confirms the importance of the joint assessment and management of sleep and mental health behaviors and health in digital interventions aimed at modifying them. New interventional studies are awaited to confirm these results in the general population but also in subgroups of individuals at risk.

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0966 Mood in OSA Patients with Different Chronotypes with and Without Chronic Pain
Authors: Weber Amberlee , Weingarten Jeremy , Dubrovsky Boris , Cunningham John 
Published: April 2024

Abstract

Introduction
Mood has been related to chronotype, OSA and pain, although no studies have examined these three variables simultaneously. This study analyzes depression symptoms in relationship to self-reported sleep timing, PSG-determined AHI and the presence of chronic pain conditions (CPC) in patients referred for OSA evaluation.

Methods
From patients tested between 08/2017 and 04/2021, 360 (210 women) were selected based on self-reported sleep time criteria, no shift work, no significant cardiac, pulmonary, neurological, endocrine or psychiatric history except depression/anxiety; 78 had CPC (e.g., fibromyalgia, arthritis, sciatica, musculoskeletal pain and similar). Self-reported sleep times defined typical chronotype (TC, asleep 10pm-12am, wake-up 6-9am), early and late chronotypes (EC, LC, earlier or later than TC); those not clearly meeting these criteria or reporting &lt; 6hr or &gt;10hr of usual sleep were excluded. The Center for Epidemiologic Studies Depression Scale-Revised (CESDR) was an outcome; explanatory variables were AHI, chronotypes (EC, TC, LC), CPC; covariates were age, sex, BMI.

Results
EC (n=115), TC (n=163) and LC (n=82) were unrelated to CPC (chi-square=1.1, p=0.58). Older age (M=48.5±15.7) was predictive of lower CESDR (F=17.5, p&lt; 0.001). AHI (M=14.6±21.0) was unrelated to CESDR (F=1.6, p=0.21) and did not interact with CPC or chronotypes. CPC presence predicted higher CESDR (F=8.1, p=0.004). Chronotypes predicted CESDR (F=7.8, p&lt; 0.001) without significant interaction with CPC. LC/CPC-absent group had higher CESDR (M=20.7±18.9) relative to EC/CPC-absent (M=11.5±11.3, p&lt; 0.001) and TC/CPC-absent (M=10.1±10.6, p&lt; 0.001, Bonferroni post-hoc). Among CPC-present patients, CESDR did not significantly differ between EC (M=17.5±14.5), TC (M=16.3±10.3) and LC (M=22.9±17.3).

Conclusion
In this sample, there was no relationship between OSA and depression symptoms. In patients without CPC, late self-reported sleep time was associated with higher depression symptoms, relative to early and typical sleep times. However, in patients with CPC, CESDR scores did not reach significant difference between chronotypes, apparently due to the overall elevation of depression symptoms in these patients.

Support (if any)
none
0968 Perceived Stress and Worry Mediate the Link Between Sleep Quality and Immune Function
Authors: Lueke Niloufar , Assar Arash , Desai Vedant , Diaz Kayla , Jung Aena , LeBlanc Izabella , Lueke Adam 
Published: April 2024

Abstract

Introduction
Given that college students have an increased risk for spreading infection (White et al., 2003), it is important to examine factors that influence the immune functioning of this population. The present work examined the effect of sleep quality on the immune function of college students. Sleep problems are highly prevalent among college students (Kloss et al., 1011). Poor sleep quality has been shown to be related to reduced immune function (Irwin, 2015), and among college students, it has been linked to a multitude of negative outcomes, including heightened perceived stress (Veeramachaneni et al., 2019). Not only does poor sleep predict stress levels (Wu et al., 2015), but worry is a common cognitive reaction to stress (Borkovec et al., 1998). Worry has also been associated with reduced immune function (Brosschot et al., 2006). Based on this evidence, the present work proposed a serial mediation model, in which sleep quality (X) was modeled to increase perceived stress (M1), which in turn, increases worry (M2), thereby resulting in a decreased in immune function (Y).

Methods
Participants were 391 undergraduate students (68.3% female; Mage = 19.19, SDage = ±2.03) who completed scales related to sleep quality, perceived stress, worry, and immune function.

Results
A serial mediation model tested whether perceived stress (M1) and worry (M2) sequentially mediated the relation between poor sleep quality (X) and immune functioning (Y). A 95% bias-corrected confidence interval based on 5,000 bootstrap samples indicated that the indirect effect of perceived stress alone (i.e., X→M1→Y) was non-significant (indirect effect = .05, SE = .03, 95% CI [-.00, .11]). Likewise, the indirect effect through worry alone (i.e., X→M2→Y) was also non-significant (indirect effect = .01, SE = .01, 95% CI [-.01, .11]). Lastly, and as hypothesized, poor sleep quality was an indirect significant predictor of immune functioning through perceived stress and worry, in a sequential manner (i.e., X→M1→ M2→Y; indirect effect = .04, SE = .02, 95% CI [.01, .07]).

Conclusion
Findings demonstrate the importance of college students’ sleep in relation to both their mental health and subsequent immune functioning, rendering sleep as an important target for preventative intervention.

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0969 Predicting Differences Between Objective and Subjective Sleep Parameters with Mental Health Questionnaires
Authors: Marsolek Mason , Emert Sarah , Dietch Jessica , Tucker Emme , Taylor Daniel 
Published: April 2024

Abstract

Introduction
Differences between objectively and subjectively measured sleep can vary widely between participants and these differences may depend on individual characteristics, including mental health. The severity of mental health symptoms may be beneficial in assessing the magnitude of discrepancies between participants’ objective and subjective data. This secondary data analysis examined the predictivity of validated measures of post-traumatic stress symptoms, anxiety symptoms, and depressive symptoms on differences between sleep electroencephalogram (EEG) and actigraphy with sleep diary data.

Methods
Adults in the community (N=80; Mage=32.65 years, 63% female, 88.8% White) completed the Post-Traumatic Stress Disorder Checklist, State-Trait Anxiety Inventory, Quick Inventory of Depressive Symptomatology, and seven days of sleep assessment via sleep diaries, actigraphy, and EEG. The mean absolute value of differences between the sleep diary, actigraphy, and EEG data was calculated for total sleep time, time in bed (TIB), sleep efficiency, sleep onset latency (SOL), wakefulness after sleep onset, terminal wakefulness, and number of awakenings. Stepwise linear regression was used to examine whether the anxiety, post-traumatic stress, and depressive symptom scores were significant predictors of the objective-subjective differences between these sleep parameters.

Results
Depressive symptoms significantly predicted differences between EEG and sleep diary data for SOL, F(1,72)=9.958, p=.002, R2=0.121. Anxiety symptoms significantly predicted differences between actigraphy and sleep diary data for SOL, F(1,69)=6.335, p=.014, R2=0.084. Anxiety and post-traumatic stress symptoms significantly predicted differences between actigraphy and sleep diary data for TIB, F(2,70)=10.355, p&lt;.001, R2=.228, βQIDS=0.62, βPCL=-.42.

Conclusion
Anxiety, post-traumatic stress, and depressive symptoms significantly predicted EEG and actigraphy objective-subjective differences for SOL and TIB. To better assess whether these variations are due to measurement type or if there are individual characteristics responsible for the discrepancies (i.e., sleep state misperception, symptom of mental health), a larger sample with more longitudinal data is needed. Additionally, future studies may focus on clinical samples. For instance, SOL and TIB variations may be indicative of mental health concerns (i.e., hyperarousal, anxiety, depression).

Support (if any)
National Institutes of Health/National Institute of Allergy and Infectious Disease (R01AI128359-01), the Foundation for Rehabilitation Psychology, and the General Sleep Corporation.
0970 Real-world Use of Solriamfetol for Excessive Daytime Sleepiness in Patients Reporting Anxiety or Depression
Authors: Kallweit Ulf , Benes Heike , Burghaus Lothar , Eglit Graham , Abeynayake Iresha , Floam Samantha , Parks Gregory , Winter Yaroslav 
Published: April 2024

Abstract

Introduction
Psychiatric comorbidities are common in patients with excessive daytime sleepiness (EDS) from narcolepsy or obstructive sleep apnea (OSA). Real-world efficacy and safety data of wake promoting agents in these populations is limited. Solriamfetol (Sunosi®), a dopamine/norepinephrine reuptake inhibitor that activates TAAR1 and 5HT1A receptors, is approved to treat EDS associated with narcolepsy or OSA. Solriamfetol clinical trials excluded and the prescribing information caution against use in patients with severe psychiatric comorbidities, so limited data exists for this population. Here we describe real world use of solriamfetol in German patients with narcolepsy or OSA who self-reported depression/anxiety (yes/no response) at baseline.

Methods
We performed a retrospective chart review (SURWEY) using data from German physicians who prescribed solriamfetol to patients with EDS associated with narcolepsy or OSA and at a stable dose for ≥6 weeks. Comorbidities, including anxiety/depression, were documented with background information at baseline.

Results
Of the 154 patients, n=48 (31.2%) reported anxiety and/or depression (OSA, n=23/83 [27.7%], narcolepsy, n=25/71 [35.2%]). Most patients (≥85%) reported no additional psychiatric, neurological, or sleep disorder. Regardless of primary etiology, baseline mean±SD Epworth Sleepiness Scale (ESS) scores were generally similar in patients with (OSA, 16.0±2.8; narcolepsy, 17.9±3.6) and without (OSA, 16.0±3.3; narcolepsy, 17.5±2.9) anxiety/depression. Overall, mean±SD decreases in ESS scores were 4.6±3.2 and 5.2±3.6 with and without anxiety/depression, respectively; and similar in OSA (5.2±3.1 vs 5.5±3.9), narcolepsy (3.9±3.2 vs 4.9±3.3). Ninety percent of patients achieved ≥2-point reduction in ESS scores from baseline and patients (≥89%) and physicians (≥91%) reported improvement in EDS with solriamfetol, which were both similar across primary etiologies and anxiety/depression presence. Anxiety/depression data was not collected at follow-up. Common adverse events were headache, insomnia, and decreased appetite, which generally occurred at similar rates regardless of reported anxiety/depression.

Conclusion
These real-world data describe solriamfetol treatment outcomes in narcolepsy or OSA patients who did and did not self-report anxiety/depression. Regardless of anxiety/depression, ESS scores improved, and most patients and physicians reported improved EDS. Our findings are consistent with clinical trial results and suggest that solriamfetol is effective in managing EDS symptoms in this population regardless of common psychiatric comorbidities.

Support (if any)
Axsome Therapeutics, Jazz Pharmaceuticals, Pharmanovia
0973 Romantic Partnership Mitigates the Influence of Anxiety and Mood on Sleep Disturbance in Full-Service Sex Workers
Authors: Tiani Alaina , Ramos Stephen , Du Bois Steff 
Published: April 2024

Abstract

Introduction
In the United States, an estimated 1-2 million full-service sex workers (FSSW) face notable physical and mental health challenges, including increased depression, anxiety, and sleep difficulties as compared to the general population (Ramos et al., 2022). The "partnership-health associations" concept suggests that romantic relationships may protect mental and physical well-being (Du Bois et al., 2021). Notably, a recent study found no significant health outcome differences between partnered and non-partnered FSSW at the univariate level (Du Bois et al., 2023). This secondary analysis aims to explore whether partnership buffers the link between mood, anxiety, and sleep disturbance among FSSW.

Methods
83 FSSW completed the Patient Reported Outcomes Measure Information System-29 (PROMIS-29) online from November 2019-February 2020. Four moderation analyses, utilizing PROCESS, examined anxiety and depression as predictor variables and global sleep disturbance score as an outcome, with partnership status (partnered versus non-partnered) as the moderating variable.

Results
The sample was primarily white (81.9%), non-Hispanic (77.1%), and cisgender female (66.3%), with a mean age of 28.01 (±4.25) years. The overall model for partnership status as a moderator of the association between anxiety and sleep disturbance was significant (F(3, 79)=17.65,p&lt;.001,R2=.40). The interaction effect showed a significant link between increased anxiety and sleep disturbance for both non-partnered FSSW (b=0.88,SE=0.13,t(79)=6.74, p&lt;.001) and partnered FSSW (b=0.35,SE=0.14,t(79)=2.48,p&lt;.05), with a more pronounced association for non-partnered FSSW. Similarly, the overall model for the association between depression and sleep disturbance was significant (F(3, 79)=12.50,p&lt;.001,R2=.32). The interaction effect indicated a significant link between increased depression and sleep disturbance for both non-partnered FSSW (b=0.75,SE=0.13,t(79)=5.61,p&lt;.001) and partnered FSSW (b=0.34,SE=0.15,t(79)=2.18,p&lt;.05), with a more pronounced association for non-partnered individuals.

Conclusion
Analyzing mental-physical health associations at a multivariable level provides a nuanced understanding that partnership may protect against unfavorable mood, anxiety, and sleep health associations in FSSW. Future studies should include a larger sample size and explore specific underlying mechanisms by which romantic partnership relates to a protective effect of low mood and high anxiety on sleep, both in FSSW and other groups who experience health inequities.

Support (if any)
American Psychological Foundation, The Drs. Rosalee G. and Raymond A. Weiss Research and Program Innovation Grant