bluuebunny/crossref_metadata_2025_split huggingface dataset:
0861 Beat Right, Sleep Tight: Pilot Study of Depression’s Role on Blood Pressure and Sleep in Older Adults with Insomnia
Authors: Sebastian Celestine , Costa Amy , McCrae Christina , Curtis Ashley 
Published: April 2024

Abstract

Introduction
Insomnia disorder and hypertension are common in aging adults, making older adults at increased risk for cardiovascular disease. A bidirectional relationship between insomnia symptoms and hypertension exists, but mechanisms underlying this association are not fully understood. Depressive symptoms have been linked to insomnia. Additionally, there is a known association between depression and hypertension, but investigations of non-invasive blood pressure metrics are limited, which limits conclusions regarding disease markers and potential targets for intervention. This pilot study tested whether blood pressure interacted with depressive symptoms in its association with sleep in older adults with insomnia.

Methods
Older adults with insomnia disorder (DSM-5 criteria plus sleep diary confirmation of &gt;30 minutes of sleep onset latency or wake time after sleep onset 3+ nights/7; N=38, Mage=68.5±6.4 years, 24 women) completed the Beck Depression Inventory-II (BDI-II), Insomnia Severity Index (ISI), and resting blood pressure reading. Multiple linear regressions tested if cardiovascular activity [pulse pressure (systolic BP – diastolic BP), systolic BP, diastolic BP] interacted with depressive symptoms in its association with insomnia severity, controlling for Body Mass Index and number of medications.

Results
Depressive symptoms interacted with systolic BP in its association with ISI (R2-change=.08, p=.02). Specifically, higher systolic BP was associated with worse insomnia severity only at highest levels of depression (BDI-II score=14.61; B=.12, p=.03).

Conclusion
Preliminary findings suggest higher levels of depression may exacerbate the relationship between higher systolic blood pressure and more severe insomnia symptoms in older adults. These results point to a dynamic interplay between autonomic nervous system dysregulation, peripheral vasoconstriction, and potentially neural circuits involved in emotional processing that mediate depressive symptoms. Prospective studies in larger samples are needed to untangle the temporal nature of this relationship. Additionally, it may be important to concurrently monitor depressive symptoms and blood pressure in older adulthood as well as evaluate whether behavioral interventions in depression (e.g., Cognitive Behavioral Therapy for Depression) may reduce systolic blood pressure and in turn improve insomnia severity in older adults.

Support (if any)
This research was made possible by an award (PI:Curtis) from the American Academy of Sleep Medicine Foundation, a foundation of the American Academy of Sleep Medicine.
0867 Machine Learning Analysis of Polysomnography Variables to Predict Hypertension
Authors: Chow Christine , Kang Hyojung , Logan Jeongok , Liu Xiaoyue , Kwon Younghoon 
Published: April 2024

Abstract

Introduction
Sleep plays an important role in the regulation of blood pressure (BP) and BP variability (BPV), both of which are associated with cardiovascular disease. However, studies in this area have typically focused on a single domain of sleep traits. We aimed to examine whether multidimensional sleep measures incorporating a wide array of polysomnography (PSG) data along with other patient characteristics can be used to predict hypertension and high BPV using a machine learning (ML) approach.

Methods
We retrieved patient characteristics and PSG data from a single academic sleep center. BP data with at least 3 measures within 1 year following PSG were used to determine hypertension (systolic BP ≥130 mmHg or on antihypertension medication) and high BPV (coefficient of variation &gt; 0.1). We used three commonly used supervised ML models including the logistic regression model, random forests, and eXtreme Gradient Boosting (XGBoost) to predict hypertension and high BPV. To improve the model performance by including the most predictive variables, we additionally conducted feature engineering and ran ML models using the selected variables from the process. We employed two variable reduction

methods
least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA).

Results
Among 2,827 patients, 2074 (73.4%) patients had hypertension and 1,188 patients (42%) had the high BPV group. Overall, the three models showed a good performance in predicting hypertension in which XGBoost performed the best in terms of accuracy (0.67 – 0.75), recall (0.72 – 0.96), precision (0.76 – 0.83), and AUC (0.68 – 0.70). Models built with LASSO-selected variables generally performed more favorably than models built with PCA-constructed features. However, the performance of the ML models to predict high BPV was low with an accuracy of 0.56, recall of 0.2, precision of 0.45, and AUC of 0.53 at best.

Conclusion
ML modeling of multiple PSG sleep features along with common patient characteristics was predictive of hypertension in patients undergoing PSG. PSG data may be better utilized in cardiovascular risk assessment beyond its role as a diagnostic tool for OSA assessment.

Support (if any)
Engineering in Medicine Grant (University of Virginia)
0869 Association Between Accelerometer-Measured Irregular Sleep Duration and Incidence of Obesity in Older Adults
Authors: Kianersi Sina , Potts Kaitlin , Wang Heming , Sofer Tamar , Noordam Raymond , Rutter Martin K , Redline Susan , Huang Tianyi 
Published: April 2024

Abstract

Introduction
Abnormal sleep duration is an established risk factor for obesity. However, the potential adverse effects of sleep's nightly variability, including fluctuations in duration, remain less explored. Irregular sleep duration may increase circadian disruption and subsequently contribute to metabolic alterations, behavioral and mood changes, and obesity development.

Methods
From 2013-2015, a subsample of the UK Biobank (UKB) participants wore accelerometers for a week. Our longitudinal study included 8,438 participants (mean age: 64 years) with ≥5 days of accelerometer data and repeated weight measurements who had BMI&lt; 30 kg/m2 at baseline. Irregular sleep duration was assessed by the within-person standard deviation (SD) of 7-night accelerometer-measured sleep duration. Weight was objectively measured at UKB center visits or extracted from UK general practice records at two timepoints. The baseline measurement was taken in a period spanning from two years before to one year after the accelerometer study. The follow-up measurement was obtained on average 3.6 years after the baseline measurement (interquartile range: 1.8-5.0) and at least 6 months after the accelerometer study. Poisson regression with robust error variance was used to estimate relative risk (RR) for incident obesity (BMI≥30 kg/m2) according to sleep duration-SD categories.

Results
A total of 419 participants developed obesity at the follow-up measurement. Compared with participants with a sleep duration-SD &lt; 30 minutes, the RR (95% CI) for incident obesity was 1.22 (0.86, 1.73) for 31-45 minutes, 1.60 (1.14, 2.26) for 46-60 minutes, and 2.01 (1.45, 2.80) for &gt;60 minutes (p-trend=0.0024), after adjusting for age, sex, race, and follow-up period. Additional adjustment for lifestyle (smoking, physical activity, diet, and alcohol use), co-morbidities (dyslipidemia, hypertension, and depression), and other sleep-related factors including average sleep duration resulted in a weaker but statistically significant association (RR comparing &gt;60 versus &lt; 30 min: 1.73; 95% CI: 1.24, 2.41). The association was similar in men and women (P-interaction in the fully-adjusted model=0.84).

Conclusion
Irregular sleep duration was associated with higher risk of incident obesity in older adults, independent of average sleep duration and other obesogenic behaviors.

Support (if any)
R01HL155395
0870 Association Between Narcolepsy and Cardiovascular Outcomes: A Matched Cohort Study Adjusting for Medication Use
Authors: Riaz Munaza , Kaufmann Christopher , Bhattacharjee Rakesh , Lo-Ciganic Wei-Hsuan , Wilson Debbie , Wickwire Emerson , Malhotra Atul , Park Haesuk 
Published: April 2024

Abstract

Introduction
Emerging research suggests that narcolepsy, a chronic disabling condition characterized by excessive daytime sleepiness, directly impacts the cardiovascular system, leading to increased risk of cardiovascular disease (CVD). Existing studies evaluating CVD risk among persons with narcolepsy (PWN) have not considered medications to treat the symptoms of narcolepsy (e.g., stimulants). We aimed to assess the real-world association of narcolepsy with CVD risk while accounting for medications.

Methods
We conducted a retrospective cohort study using 2005-2021 MarketScan® Commercial and Medicare Supplemental databases. Patients with newly diagnosed narcolepsy with ◻2 outpatient claims identified using International Classification of Diseases – Clinical Modification diagnosis codes were included (narcolepsy group). A comparison cohort of patients without narcolepsy and hypersomnia (non-narcolepsy group) was matched at a ratio of 1 up to 3 using propensity score (PS) matching based on baseline demographics, comorbidities, and medication use. After PS matching, we used multivariable Cox regression to compare the risks of CVD (i-e., stroke, atrial fibrillation, heart failure (HF), myocardial infarction (MI), or acute coronary syndrome) and major adverse cardiac events (MACE) (i-e., MI, ischemic stroke, HF, acute coronary syndrome, coronary artery bypass grafting, or percutaneous coronary intervention) between the two groups after controlling for baseline wake promoting agents and stimulants use, and post-index time-varying stimulants use. Follow-up continued until the occurrence of outcomes, end of enrollment, or December 31, 2021.

Results
134,967 patients (34,562 PWN and 100,405 non-narcolepsy; mean age 40±16.78 years and 62% female) were identified. The crude incidence of CVD was 1.50 and 0.85 per 100 person-years for narcolepsy and non-narcolepsy groups, respectively. After controlling for baseline and time-varying covariates, PWN was associated with a 93% higher CVD risk compared to non-narcolepsy group (adjusted hazard ratio (aHR), 1.93; 95% confidence interval (95% CI), 1.75-2.13). Similarly, PWN was associated with a 97% higher MACE risk compared to non-narcolepsy group (aHR,1.97; 95%CI, 1.72-2.26).

Conclusion
In this PS-matched cohort study, PWN experienced increased risk of developing CVD or MACE relative to propensity-matched patients without narcolepsy after controlling for baseline medication use (stimulant and wake promoting agent), and post-index time-varying stimulant use.

Support (if any)
Sleep Research Society Foundation (23-FRA-001).
0871 Sleep Disturbance and Disability Severity After Stroke Hospitalization
Authors: Gonzalez Alvis , Jurado Ammie , Aguirre Jennifer , Shechter Ari 
Published: April 2024

Abstract

Introduction
Stroke survivors frequently report sleep disturbance and feelings of not being back to where they were, physically, prior to their event. Post-stroke sleep disturbance may be a factor related to sub-optimal recovery.

Methods
Data came from the Reactions to Acute Care and Hospitalizations (ReACH) Stroke-Sleep Study, an observational cohort assessing the relationship of sleep with secondary cardiovascular risk in the year following stroke or transient ischemic attack (TIA). Data were collected using self-reported questionnaires at 1 month and chart reviews. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI), with a score &gt;5 indicating poor sleep quality. Insomnia symptoms were assessed with a single item from the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5): “In the past month, how much were you bothered by trouble falling or staying asleep?” with a rating of “moderately,” “quite a bit,” or “extremely” indicating presence of insomnia symptoms. Degree of disability was assessed using the Simplified Modified Rankin Scale Questionnaire (smRSq), with presence of disability defined as smRSq score &gt;2. Binary logistic regression was used to analyze the relationships between presence of poor sleep and insomnia, separately, with presence of disability at 1-month post-hospitalization. Analyses were adjusted for age, gender, race/ethnicity, and stroke severity (NIH Stroke Scale).

Results
The sample included n=436 participants (mean [SD] age=60.2 [15.5] y, 52% Hispanic/Latino, 59% female). Fifty-six percent of participants reported poor sleep quality, 27% reported presence of insomnia symptoms, and 23% reported presence of disability at 1 month. Poor global sleep quality (vs. good sleep) was significantly associated with presence of disability (adjusted OR: 2.45, 95% CI: 1.48-4.04, p&lt; 0.001). Insomnia (vs. no or mild symptoms) was also significantly associated with presence of disability (adjusted OR: 2.40, 95% CI: 1.50-3.85, p&lt; 0.001).

Conclusion
More than half of participants reported poor sleep quality, and over a quarter reported insomnia symptoms, 1 month after stroke hospitalization. Compared to those without sleep problems, individuals with sleep disturbance had nearly 2.5 times higher odds of disability. While causal relationships cannot be concluded based on this cross-sectional analysis, findings suggest that sleep may play a role in stroke survivors’ outcomes and recovery.

Support (if any)
R01HL141494
0873 Impact of Obstructive Sleep Apnea Treatment on Mortality in Atrial Fibrillation Patients
Authors: Sattani Ashrine , Karca Ayla , Naik Sreelatha , Suryanarayanana Manoj , Tejwani Dimple 
Published: April 2024

Abstract

Introduction
The intricate relationship between atrial fibrillation (AF) and obstructive sleep apnea (OSA) has garnered attention due to its potential impact on morbidity and mortality. This study explores the characteristics of individuals with both AF and OSA, aiming to shed light on associated outcomes.

Methods
Utilizing data from the Geisinger Health System (2007-2023), we focused on cardiology patients with AF. Inclusion criteria comprised age &gt; 18, AF and OSA diagnosis, and polysomnography with an apnea-hypopnea index (AHI) &gt; 5. Data collected included age, gender, body mass index (BMI), mean AHI, oxygen desaturation index (ODI), ablation, cardioversion rates, and electrophysiology (EP) clinic follow-ups.

Results
Among 29,000 patient encounters, 2,971 unique patients met inclusion criteria. 64% were male, with a mean age of 74.9 for deceased patients versus 68.1 for the alive cohort (p &lt; 0.001). Deceased patients had a higher mean BMI (35.8 vs. 34.3, p = 0.003) and AHI (27 vs. 25, p = 0.0143). Oxygen desaturation was observed in 34% of deceased patients compared to 28% in the alive cohort (p &lt; 0.0001). Ablation and cardioversion did not significantly impact mortality. The all-cause mortality rate was 12.7%.

Conclusion
Analysis revealed that prolonged hypoxia increased mortality risk in AF and OSA patients. Although higher AHI was noted in deceased patients, its clinical significance was limited. We also found that ablation and cardioversion did not improve mortality. Effective OSA treatment in AF patients can potentially improve outcomes. Further studies are necessary to determine if reducing oxygen burden reduces mortality in this population.

Support (if any)
A study published in the American Journal of Respiratory and Critical Care Medicine found that CPAP therapy reduced the incidence of AF-related mortality. The data from over 10,000 patients, demonstrated that those receiving effective sleep apnea interventions, such as CPAP, exhibited a 35% reduction in all-cause mortality compared to untreated counterparts. This research highlights the potential life-saving benefits of addressing sleep-disordered breathing in the management of AF.
0875 The Impact of Non-compliance with CPAP Therapy on Mortality in Atrial Fibrillation Patients
Authors: Sattani Ashrine , Naik Sreelatha , Suryanarayanana Manoj , Tejwani Dimple 
Published: April 2024

Abstract

Introduction
Atrial Fibrillation (AF) patients commonly experience comorbidities such as sleep apnea, emphasizing the need for effective management strategies. This study investigates the association between non-compliance with Continuous Positive Airway Pressure (CPAP) therapy and increased mortality in AF patients.

Methods
Utilizing data from the Geisinger Health System (2007-2023), we focused on cardiology patients with AF. Inclusion criteria comprised age &gt; 18, AF and OSA diagnosis, and polysomnography with an apnea-hypopnea index (AHI) &gt; 5. Data collected included age, gender, body mass index (BMI), mean AHI, adherence within 1st three months of starting CPAP therapy, Medicare adherence percentage, and CAI.

Results
Among 29,000 patient encounters, 2,971 unique patients met inclusion criteria. We chart reviewed 100 patients by looking at compliance reports within the first three months of CPAP use. Mean adherence time within the first three months was 5 hours 39 minutes for the alive cohort vs 4 hours 9 minutes for the patients that died (p=0.02). Mean Medicare medical adherence percentage for alive cohort was 73% vs 71% for the patients that died (p=0.361). Deceased patients had higher association of having AHI &gt; 5 (p=0.016). Mean CAI for the alive cohort was 0.81 vs 0.62 for the deceased cohort (p=0.912). All-cause mortality rate was 12.7%.

Conclusion
Our findings underscore the critical impact of CPAP compliance on mortality outcomes in AF patients. Non-compliance with CPAP therapy within the first three months of use and AHI &gt;5 emerged as a significant predictor of increased mortality, emphasizing the need for targeted interventions to enhance adherence in this population. The implications of our study extend beyond mortality, encompassing broader cardiovascular outcomes and healthcare utilization. Studies have established the relationship between AF and sleep apnea. Sleep apnea, prevalent in up to 50% of AF patients, exacerbates the arrhythmia's progression and increases the risk of cardiovascular events. While CPAP therapy has demonstrated efficacy in ameliorating the cardiovascular impact of sleep apnea, limited research has explored its effect on mortality in AF patients. Studies examining CPAP therapy's impact on AF outcomes have primarily focused on surrogate markers such as AF recurrence and symptom severity.

Support (if any)
0878 Particulate Matter Exposure Is a Driving Factor of Oxygen Desaturation in Blacks with Central Sleep Apnea
Authors: Gallop Erin-Leigh , Blanc Judite , Oliveira Bruno , Elvariste Stessie , Chung Debbie , Scott Sadeaqua , Thompson Michelle , Seixas Azizi , Jean-Louis Girardin 
Published: April 2024

Abstract

Introduction
Exposure to particulate matter (PM) in the home environment is a modifiable risk factor for oxidative stress, a common and burdensome symptom of Central Sleep Apnea (CSA), a condition characterized by the brain temporarily not sending signals to the muscles that control breathing during sleep. Although previous research has established a greater likelihood of adverse health outcomes given environmental exposure, the effects of specific air pollutants have not been distinguished from other neighborhood factors. Moreover, recommendations to reduce exposure to PM have not been included in CSA treatment. This study aims to contribute to the development of predictive models that account for the impact of environment on severity of CSA symptoms among Black Americans.

Methods
Data were collected from 168 Blacks (69% female and 31% male, Mage 47.60 ±16.459yrs) that were enrolled in two NIH-funded community-based sleep studies, ESSENTIAL and MOSAIC. Sleep environment PM levels were assessed objectively with the IQAir device for a period of 7 days. During the same period, SleepImage ring devices were used to measure the number of paused breathing events during a sleep period and a score was generated based on the qualifying events of oxygen desaturation. Analyses of correlation matrices were conducted to explore the associations between CSA and PM exposure. Descriptive statistics were analyzed, and a regression analysis was performed to understand the association between CSA and PM. Analyses were performed using SPSS29.

Results
Exposure to PM 2.5 (fine inhalable particles with diameters measuring 2.5 micrometers and smaller) was highly correlated with Central Sleep Apnea (sAHI Central), with at least 10 qualifying events of 3% oxygen desaturation (r(165)=.465,p&lt;.001) and 4% oxygen desaturation (r(165)=.473,p=&lt;.001) during a sleep period. Regression analysis further revealed significant association between PM 2.5 and sAHI Central [β= .032; p&lt; .001]. The model adjusted for age, sex, and an existing Sleep Apnea diagnosis.

Conclusion
Findings suggest that exposure to PM is a driving factor in oxygen desaturation in Blacks. These findings present an opportunity to influence population health by contextualizing the relationship between CSA and environmental factors among Black Americans.

Support (if any)
R01AG067523, R01HL142066, and T32HL166609-02
0879 Investigating Family Sleep Health in Native Hawaiian and Pacific Islander Communities
Authors: Gilles Allyson , Kavapalu Olivia 
Published: April 2024

Abstract

Introduction
Native Hawaiian/Pacific Islander (NHPI) populations have significantly elevated risk for cardiometabolic diseases, which are linked mechanistically to sleep deficiencies. Research suggests that sleep deficiencies are highly prevalent among NHPI adults, including short sleep, insomnia symptoms, and elevated risk factors for OSA (obesity). Although adult sleep practices often begin during childhood, little research has examined sleep among NHPI families. As sleep significantly relates to sociocultural factors (stress, socioeconomics, family dynamics), this study aimed to identify sleep health parameters that affect family members’ sleep and determine community methods to improve sleep.

Methods
NHPI adolescents and adults(N=34; 33.3% female) from Utah and Hawaii participated in six online focus groups. Discussed sleep-related topics were duration, sufficiency, environment, routines, household rules/dynamics, beliefs/practices, and disorders. Health-related topics discussed included cardiometabolic disease, stress, technology use, work schedules, and health attitudes/goals. Mixed method data were analyzed using constant comparison approach.

Results
Participants (adolescent mean age of 15.3 years; adult mean age of 39.4 years) reported an average household of 5.5 members(73.3% included children). Few participants regularly slept in a different home from family members(13.3%). Reported annual household income was $75,000+ by 48% of participants. Education level was 53.3% GED/high school, 43.3% some college/bachelor's degree, and 3.3% master’s degree. Adolescents reported adverse sleep-related factors, including sleep timing, chores, shared sleeping space and noise, sport/school schedules, and sleep insufficiency from homework and sleep onset worry. Adult-focused adverse sleep health repercussions included childcare, temperature, technology use in bed, community/extended family event frequency, financial strain, working multiple jobs, dietary challenges, and social beliefs/practices related to Polynesian culture. Community members identified religious practices, family-driven efforts, changing cultural perception of sleep, and targeting youth as ways to address intergenerational transmission of sleep health values and behaviors.

Conclusion
Findings reveal feasible areas that community members of all ages can utilize to improve sleep health across generations like limit setting at bedtime, utilizing strong community-driven ties (Polynesian cultural values, religious practices), and enhancing existing familial structure. Future research should address significant barriers to improving sleep health (socioeconomics, environmental influences, extracurricular events, sleep perception) that seem unsurmountable.

Support (if any)
Health Studies Fund, Department of Family and Preventive Medicine, University of Utah