bluuebunny/crossref_metadata_2025_split huggingface dataset:
768 The Relationship Between Circadian Rhythm and Autism Spectrum Disorder Traits and Executive Function Across the Life Span
Authors: Smidt Stacey Elkhatib , Ghorai Arpita , Gehringer Brielle , Dow Holly , Smernoff Zoe , Taylor Sara , Rawot Eric , Langer Allison , Zhang Jing , Rader Daniel , Almasy Laura , Brodkin Edward , Bucan Maja 
Published: May 2021

Abstract

Introduction
Children and adults with autism spectrum disorder (ASD) often have sleep, circadian, and executive function impairments, which can affect daytime quality. Yet, the relationship between sleep or circadian traits and ASD traits is still unknown. Thus, we aimed to determine if sleep and circadian traits were associated with ASD traits, including executive function.

Methods
We studied data from participants with and without ASD enrolled in the family-based study Autism Spectrum Program of Excellence (ASPE), University of Pennsylvania. We used GGIR to analyze actigraphy-derived sleep and circadian traits from 250 participants (219 adults ages 18–87 years, mean 44.2 ± 17.3 years; 31 children ages 4–17 years, mean 11.3 ± 3.9 years). These traits were compared to ASD traits (social impairment and restricted/repetitive behavior via Social Responsiveness Scale, Second Edition) and executive function (Behavior Rating Inventory of Executive Function) using linear multivariate regression models adjusted for age, age2, and sex via Sequential Oligogenic Linkage Analysis Routines.

Results
In adults, earlier start time of the 10 hours of highest activity in a 24-hour day (M10 start time; p = 0.02), decreased robustness of the rest/activity rhythm (relative amplitude; p = 0.03), and increased intradaily variability of rest/activity rhythm (p = 0.04) were associated with more social impairment. In children, earlier M10 start time (p = 0.02) and decreased relative amplitude (p = 0.03) were associated with more social impairment. In adults, higher average 5-hour period of lowest activity in a 24-hour day (L5 average; p = 0.03), lower average 10-hour period of highest activity in a 24-hour day (M10 average; p = 0.005), earlier M10 start time (p = 0.02), decreased relative amplitude (p = &lt;0.001), increased intradaily variability (p = &lt;0.001) and decreased sleep efficiency (p = 0.04) were associated with increased executive function impairment. In children, earlier M10 start time (p = 0.006) and intradailty variability (p = 0.008) were associated with increased executive function impairment.

Conclusion
Circadian traits are significantly associated with ASD traits, including executive function, suggesting the importance of sleep-wake rhythm dysfunction in ASD.

Support (if any)
Anonymous donor; NIH T32HL07713; University of Pennsylvania’s Institute for Translational Medicine and Therapeutics
779 Effects of lifetime trauma exposure on the association between neighborhood safety and sleep
Authors: Alcántara Carmela , Diaz Sarah 
Published: May 2021

Abstract

Introduction
Greater perceived neighborhood safety (PNS) has been linked to better sleep quality and longer sleep duration. There is also evidence that past exposure to traumatic events may be associated with lower perceived personal safety and poor mental health. Yet, the moderating effects of lifetime trauma exposure on the association between PNS and sleep (duration & latency), has not been assessed.

Methods
We used cross-sectional data from 190 healthy NYC Latino adults. Lifetime trauma exposure was measured using the Life Events Checklist [LEC] (a count of traumatic events that happened to or were witnessed). In the first set of models, we regressed self-reported sleep duration in minutes (continuous), on PNS (safe vs. not safe), a single item scale, with three covariates (i.e. age, gender, education). In the second set, self-reported sleep latency in minutes, replaced sleep duration. To test for moderation, interaction terms—LEC x PNS—were added to covariate-adjusted models. In sensitivity analyses, regression models were re-run with adjustment for PTSD symptoms, and with short sleep duration (&lt;7hours) as the outcome.

Results
On average, participants were 37.9 years old (SE= 1.02), 65.8% female, 59.5% foreign-born, and 33.2% completed &lt; Bachelor’s degree. Overall, 43.68% slept &lt;7 hours and 83.68% were exposed to &gt;1 traumatic event in their lifetime. In adjusted models, each traumatic event (b= -2.95, SE = 1.34, p=0.03) was negatively associated with sleep duration. When PTSD symptoms was added, trauma was no longer statistically significant (b=-1.08, SE=1.02, p=0.18). However, each traumatic event exposure was associated with a 10% higher odds of short sleep duration (OR= 1.10, CI=1.02, 1.15), and this association remained significant with adjustment for PTSD symptoms. No interaction terms were significant. In models for sleep latency, there were no statistically significant main effects for LEC or interaction terms.

Conclusion
We found a dose response in the negative association between lifetime exposure to trauma and sleep duration, but not sleep latency. Trauma history did not moderate the association between PNS and sleep. These results suggest that short sleep duration may be particularly sensitive to lifetime exposure to trauma independent of neighborhood safety. Future studies should replicate these results in population-based samples.
Support (if any):
789 Obstructive Sleep Apnea (OSA) and Vestibular Dysfunction in Patients with Traumatic Brain Injury (TBI)
Authors: Skop Karen , Bajor Laura , Swank Chad , Sevigny Mitch , Tallavajhula Sudha , Nakase-Richardson Risa , Miles Shannon 
Published: May 2021

Abstract

Introduction
Recent work has highlighted prevalent OSA after TBI. Vestibular dysfunction is also common and associated with adverse outcomes particularly in military personnel. Vestibular dysfunction has been identified in patients with moderate to severe OSA, yet the relationship remains unexplored in those with TBI. This study examined the relationship of vestibular dysfunction with OSA in a large cohort of Veterans and Military Service Members (V/SM) with documented TBI.

Methods
Data are secondary analyses from a five-center prospective observational cohort study of V/SM admitted for inpatient rehabilitation for TBI and enrolled in the VA TBI Model Systems. Participants completing study measures from 2015 to March of 2020 were included in analyses. Study measures includes the Centers for Disease and Control’s National Health and Nutrition Education Survey (NHANES, OSA item embedded) epidemiologic survey and Neurobehavioral Symptom Inventory (NSI). T-tests and chi-square tests compared patients with OSA to those without OSA on the vestibular subscale on the NSI.

Results
The sample was mostly male (93%), a mean of 38 years of age, and predominantly with mild (52%) or severe (41%) TBI. OSA was reported in 30.6% on the NHANES. Vestibular symptoms were more common among those with OSA (24%) compared to those without (12%) with a significant difference on the NSI Vestibular Total Score (3.84 vs 2.88 respectively; p&lt;0.001). Similar results were seen across all three NSI vestibular items (dizziness, balance difficulties, poor coordination).

Conclusion
Participants with TBI and comorbid OSA are more likely to endorse the presence and greater severity of vestibular symptoms compared to those without OSA. Future research is needed to improve understanding of the inter-relationship of OSA and vestibular dysfunction to inform clinical management.

Support (if any)
VA TBIMS & TBICoE (HT0014-19-C-0004), NIDILRR, North Texas TBI Model System (Grant #90DPTB0013), TIRR TBIMS (Grant #90DPTB0016)
793 Obstructive Sleep Apnea and Hypoventilation in Patients with Muscular Dystrophies: Analysis of 42 Polysomnogram Studies
Authors: Halani Pallav , Ahn Mihye , Vaughn Bradley , Ewing Travis , Fan Zheng 
Published: May 2021

Abstract

Introduction
Patients with muscular dystrophies (dystrophinopathy, congenital muscular dystrophy and limb-girdle muscular dystrophy) are at greater risk of obstructive sleep apnea (OSA). However, few studies have examined if they are also at risk for hypoventilation and its relationship with OSA. We hypothesize that these two conditions occur independently of each other as an impaired ventilator drive and diaphragm weakness.

Methods
Retrospective review of diagnostic polysomnograms (PSG) in a tertiary care facility over 15 years was conducted. The polysomnography included either end tidal CO2 or transcutaneous CO2 measurements. Descriptive data analysis was performed on results described. We computed Pearson correlation coefficients to examine the relationships between PSG indices and other parameters. Pearson’s Chi-squared test with Yates’ continuity correction is used to test if hypoventilation is independent from OSA.

Results
42 PSG studies in patients with muscular dystrophies were included after excluding 2 studies due to insufficient sleep duration. The average age at the time of study was 14.2 yrs with 41 being male and average BMI of 24.1. 64% of the group met the definition for OSA with average AHI 8.0. 36% of the group met the criteria for hypoventilation, and 33% patients with hypoventilation did not have OSA. Chi squared analysis (p=1.0) shows that hypoventilation is independent of OSA.

Conclusion
Sleep disordered breathing is common in patients with muscular dystrophy. This study supports that OSA and CO2 retention may be independent processes.
Support (if any):
797 Obstructive Sleep Apnea is a Risk Factor for Sudden Unexplained Death in Epilepsy (SUDEP)
Authors: Soontornpun Atiwat , Andrews Noah , Bena James , Grigg-Damberger Madeleine , Foldvary-Schaefer Nancy 
Published: May 2021

Abstract

Introduction
Epilepsy is associated with a substantial risk of morbidity and mortality, including sudden unexplained death in epilepsy (SUDEP). Prior data demonstrated a possible association between obstructive sleep apnea (OSA) based on nocturnal oximetry oxyhemoglobin saturation index (ODI) and risk of SUDEP. We aimed to evaluate the relationship between PSG-defined OSA and SUDEP risk using the revised SUDEP Risk Inventory (rSUDEP-7).

Methods
We identified adults with epilepsy who underwent PSG between January 2004 and December 2016 at Cleveland Clinic. OSA was defined as an apnea-hypopnea index (AHI) ≥5 and moderate-to-severe OSA as an AHI ≥ 15. SUDEP risk was determined by the rSUDEP-7. The higher the rSUDEP-7 score, the greater the risk for SUDEP. Associations between rSUDEP-7 score and OSA groups (AHI&gt;15 vs. &lt;15) used Wilcoxon rank sum tests, and multivariable linear models adjusting for age, sex, BMI, and smoking status. Spearman correlations measured relationships between rSUDEP-7 score with AHI and ODI.

Results
214 patients were identified; 134 (62.6%) had OSA, moderate-to-severe in 75 (35%). Those with AHI≥15 were older and more likely to have: pharmacoresistant epilepsy, nocturnal seizures, higher BMI, and longer epilepsy duration (all p&lt;0.05). Median rSUDEP-7 score was 1(0,3), and &gt; 35% had rSUDEP-7 score of &gt; 3. Patients with moderate-to-severe OSA had higher rSUDEP-7 than those with AHI&lt;15 (p=0.001). Higher AHI and ODI positively correlated with rSUDEP-7 (p=0.002 and p=0.016) while SpO2 nadir negatively correlated with rSUDEP-7 (p=0.007). After adjustment, those with AHI≥15 had mean rSUDEP-7 score 1.14 points (95%CI 0.55–1.72, p&lt;0.001) higher than those with AHI&lt;15.

Conclusion
Epilepsy patients with moderate-to-severe OSA, have higher risk of SUDEP based on the rSUDEP-7. Our findings provide further support for routine screening of OSA in epilepsy populations.
Support (if any):
798 Diffusion tensor imaging as a potential biomarker of sleep dysfunction in warfighters with chronic, severe, traumatic brain injury
Authors: Kent Werner J , Gerstenslager Brian , Yeh Ping-Hong , Srikanchana Rujirutana , Kenney Kimbra , Ollinger John 
Published: May 2021

Abstract

Introduction
Traumatic brain injury (TBI) plagues service members in times of war and training. Diagnosis and management of TBI remain challenging, with many suffering from sleep disorders. We hypothesized that TBI-related damage to the hypothalamus, a master regulator of breathing and sleep, could be related to post-TBI obstructive sleep apnea (OSA) and serve as a pathophysiological biomarker for a subpopulation of OSA patients.

Methods
This was a retrospective study of warfighters with TBI from the National Intrepid Center of Excellence (NICoE). Subjects were identified by severe TBI on neuroimaging and compared against a control group without TBI. All subjects underwent screening polysomnography (PSG). MRI was acquired via 3T scanner. The hypothalamus was automatically segmented using a diffeomorphic algorithm. DTI scalar values were analyzed with scalar t-tests between subjects and controls. Generalized linear modeling with DTI scalar values was used to predict AHI in subjects.

Results
6 subjects and 61 controls were identified. There was significant sleep dysfunction amongst TBI subjects (mean apnea-hypopnea index (AHI) 5.1+/-6.6 events/hour; mild OSA incidence 33.3%; Pittsburgh Sleep Quality Index (PSQI) mean 13.3+/-2.6). Radial diffusivity (RD), axial diffusivity (AD) and mean diffusivity (MD) were significantly higher among subjects (control RD 9.64x10^-10+/-7.54x10^-11 m^2/s, subject RD 1.13x10^-9+/-1.20x10^-10m^2/s, p = 0.023; control AD 1.32x10^-9+/-7.64x10^-11m^2/s, subject AD 1.50x10^-9+/-1.43x10^-10m^2/s, p = 0.029; control MD 1.08x10^-9+/-7.43x10^-11m^2/s, subject MD 1.25x10^-9+/-1.34x10^-10m^2/s, p = 0.025). There were no differences in age or body-mass index. Generalized linear modeling with diffusivity measures as predictors of AHI in subjects was not significant.

Conclusion
Using a diffeomorphic algorithm to define the hypothalamus reveals significantly elevated scalar DTI measures in chronic, severe TBI compared to controls. DTI differences in the hypothalamus are a novel finding and possibly underlie part of the pathophysiology of TBI. Although this may have potential to serve as a biomarker in severe TBI patients with sleep disorders, these initial data do not support a relationship between DTI and AHI, despite high incidence of OSA and subjective sleep dysfunction. Future studies with more subjects may better elucidate the changes in hypothalamic DTI after TBI for clinical outcomes analysis.

Support (if any)
This work was supported by grant 130132 from USAMRMC.
800 Similarities of Sleep Macrostructure in Cognitively Normal Elderly and Patients with Traumatic Brain Injury
Authors: Williams Ellita , Mullins Anna , Bubu Omonigho , Kam Korey , Parekh Ankit , Blanc Judite , Donley Tiffany , Briggs Anthony , Rogers April , Seixas Azizi , Rapoport David , Ayappa Indu , Jean-Louis Giardin , Dams-O’Conner Kristen , Varga Andrew 
Published: May 2021

Abstract

Introduction
The stability of sleep architecture and breathing across nights can depend on factors relating to the integrity of the nervous system. Traumatic brain injury (TBI) represents a sudden-onset dysfunction of the nervous system while normal aging is associated with more gradual changes to the nervous system. While normal aging and history of TBI are both associated with sleep complaints, less is known about the stability of sleep physiology variables in these populations. Therefore, the aims of our study are to determine which sleep variables have greater night-to-night stability in separate populations of individuals with TBI and in cognitively normal older individuals.

Methods
All volunteers completed 2 consecutive in-laboratory nocturnal polysomnograms (NPSG). The TBI sample (N=35) comprised 71% women and 26% men (average age of 47.3 years). The cognitively normal older sample (N=78) included 74% women and 25% men (average age of 66.4 years). Descriptive statistics and intra-class correlations (ICCs) were calculated for sleep macrostructure variables (total sleep time (TST), sleep efficiency (SE), arousal index (ArI), rapid eye movement (REM), non-REM 1 & 2 (N1, N2), slow-wave sleep (SWS)), and sleep apnea including stage-specific apneas (i.e., AHI4%, AHI3A).

Results
Among volunteers with TBI, ICCs for sleep architecture variables were: TST (0.68), SE (0.65), ArI (0.92), %SWS (0.77), %REM (0.50), %N1 (0.83), %N2 (0.62). ICC’s for sleep apnea variables were: AHI4% (0.86), AHI3A (0.86), REM AHI4% (0.63), REM AHI3A (0.65). Among cognitively normal older volunteers, ICCs for sleep architecture variables were: TST (0.26), SE (0.29), ArI (0.80), %SWS (0.68), %REM (0.39), %N1 (0.66), %N2 (0.49). ICC’s for sleep apnea variables were: AHI4% (0.91), AHI3A (0.92), REM AHI4% (0.85), REM AHI3A (0.83). All ICCs were statistically significant in both groups, except for %N1 among cognitively normal older volunteers.

Conclusion
In both populations, ICC’s for arousal index were greater than for TST or SE. Likewise, ICC’s were higher in %SWS and %N1 than for %N2 or %REM. Breathing variables were more stable than architecture variables. REM-specific breathing variables showed comparatively less consistency, possibly the product of lower ICC’s for %REM sleep versus other sleep stages.

Support (if any)
5T32HL129953-04, R01AG056682, R01AG066870, R21AG059179, 1RF1NS115268-01, K24HL109156, P30AG059303, P30AG066512, AASM 231-BS-20, R25HL105444
809 Innovative electronic sleep mitigation tool for medical trainees
Authors: Tran Danielle , Nelson Kaz , Irfan Muna 
Published: May 2021

Abstract

Introduction
The ACGME (Accreditation Council for Graduate Medical Education) has been advocating for training of medical learners in sleep and fatigue mitigation, in attempt to enhance their wellbeing. While some educational programs include a one-time sleep didactic, prone to being overlooked, there is need for an educational resource which can be accessible to the learners throughout their training span. The trainees’ needs and readiness to learn may vary from time to time, therefore, continued access to educational resources can be very beneficial.

Methods
An electronic tool was created on Coggle, comprising of educational resources and content on the basic tenets of sleep quality, regulation, effects of deprivation and strategies to mitigate these effects. Links to free resources made available by AASM, such as “Choose Sleep,” were also included. The sleep resources were then incorporated in the overall continuum of Graduate Medical Education (GME) resources available to trainees, and was advertised in newsletters, incorporated in orientations (n=324) and wellness sessions (n=254). The GME Institutional Quality of Life data was obtained in 2018–2019 and in 2020 to ascertain baseline and post-intervention measures of wellness, workload and burn-out in trainees.

Results
Data collected in 2020, after introduction of Coggle, demonstrated: 1) A 4% increase of residents (n=1041) would rate their workload as “just right.” 2) A 9% increase of residents (n=1040) said their personal health and wellbeing was “very good” and “good.” 3) A 12% decrease of residents (n=1040) said they felt burned out at work. 4) A 5% decrease of residents (n=1037) said they felt they had become more calloused towards people since they first started training.

Conclusion
The analysis of learners’ feedback demonstrated that access to sleep training resources on a continuous, on-demand basis improved trainees’ personal health and wellbeing. The positive impact was sustained despite unprecedented stress caused by the COVID-19 pandemic. Future steps include: 1) Moving the electronic tool to a more advanced platform with analytical capabilities. 2) Obtaining longitudinal data to assess the impact of the electronic tool on medical trainees’ sleep parameters. 3) Sharing the electronic tool with other organizations to improve wellbeing of all medical trainees and health professionals.
Support (if any):
810 How much does it really cost? Barriers, Bottlenecks and Billing in Sleep Diagnostics
Authors: Jambulingam Nikita , Stretch Robert , Butz David , Zeidler Michelle 
Published: May 2021

Abstract

Introduction
Utilization rates of home sleep apnea tests (HSATs) versus in-lab polysomnograms (PSGs) vary greatly among healthcare institutions. HSATs can provide expanded testing capacity and offload operational bottlenecks in sleep labs, however, the financial benefit of this is not well quantified. Comparison of testing utilization and profitability between institutions can provide greater insight into decisions regarding sleep lab operations and expansion.

Methods
We analyzed profitability of HSATs and PSGs in 2018–2019 at two separate institutions with vastly different operational constraints and healthcare delivery models: Greater Los Angeles VA Healthcare System (GLA-VAHS) and University of California Los Angeles Health System (UCLA-HS). Both institutions own and operate independent sleep labs and offer HSATs for the diagnosis of sleep apnea. Profitability was calculated using contribution margin (CM) which factors out high fixed costs of healthcare infrastructure. CM was calculated by subtracting variable direct costs from revenue.

Results
The non-diagnostic HSAT rate was higher at GLA-VAHS compared to UCLA-HS (30.5% versus 13.1%). At both GLA-VAHS and UCLA-HS, HSATs were more profitable than PSGs on a per-unit basis (CM 47% for HSATs and 29% for PSGs at GLA-VAHS vs. 78% and 66% at UCLA-HS, respectively). Comparing the two institutions, PSGs were 14.8 times more profitable and HSATs were two times more profitable at UCLA-HS versus GLA-VAHS. When analyzed on a per-day basis, HSATs were more profitable at GLA-VAHS but PSGs were more profitable at UCLA-HS.

Conclusion
Reimbursement rates significantly impact institutional decisions to expand utilization of HSATs versus PSGs. Due to higher per-unit reimbursement rates, non-governmental and larger academic institutions may opt to aggressively expand sleep lab capacity. However, risks and benefits of such a strategy should be taken into account in light of changing market patterns and declining reimbursement rates for PSGs. Despite the seemingly higher profitability at the current time, future market volatility in PSG profitability may cause delayed amortization of costs for PSGs at large academic and private institutions compared to the relatively lower cost of expanding HSAT capacity. It may be beneficial for all types of institutions, regardless of current reimbursement rates, to expand HSAT capacity concomitantly with sleep lab expansion to mitigate financial risk.
Support (if any):