bluuebunny/crossref_metadata_2025_split huggingface dataset:
0915 Comparison of In-person Versus Telehealth Positive Airway Pressure Set Up for Rural Veterans
Authors: Murray Benjamin , Seo Jiyeon , Bhattacharyya Sarathi , Mempin Roberto , Harris Brian , Smith Connor , Mitchell Michael , Lee Diane , Moghtaderi Isabel , Martin Jennifer , Gomez Alexander , Ryden Armand , Sarmiento Kathleen , Zeidler Michelle 
Published: May 2023

Abstract

Introduction
Traditionally, positive airway pressure (PAP) therapy is initiated in a face-to-face visit. This can be a barrier to accessing care for rural Veterans. The COVID-19 pandemic led to the implementation of telehealth PAP set-ups at two large VA sleep centers providing an opportunity to assess the effectiveness of telehealth versus face-to-face PAP initiation in rural Veterans.

Methods
We performed a retrospective cohort study of rural Veterans (defined by the Rural-Urban Commuting Areas system) to compare outcomes for those who initiated PAP with in-person visits prior to the COVID-19 pandemic to those who initiated PAP with telehealth during the COVID-19 pandemic. We assessed the days of PAP use, hours of PAP use and residual Apnea Hypopnea Index (AHI) at 30-day and 90-day intervals in these two groups. We excluded individuals who received a replacement device, and those who received PAP on or after June 14, 2021, due to a safety recall of PAP devices that may have affected use.

Results
PAP initiation data was available for 93 individuals, approximately half of whom were initiated on PAP in-person (n=46) and half by telehealth (n=47). There were no significant differences between the in-person and telehealth groups in terms of age, BMI, and AHI, which were 57.23±16 vs 60.67±14 (mean±SD), 31.81±5 vs 31.99±13, and 27.52±23/hr vs 28.85±22/hr respectively. The average number of days per month with PAP use at 30-day and 90-day intervals for in-person vs telehealth set-up was 17.59±11 vs 15.38±12 (p=0.36) and 15.54±13 vs 14.11±14 (p=0.60) respectively. The average number of hours of PAP use at 30-days and 90-days for in-person vs telehealth set-up was 3.25±3 vs 3.11±3 (p=0.82) and 3.15±3 vs 3.07±3 (p=0.90) respectively. The residual AHI at 30-days and 90-days for in-person vs telehealth set-up was 6.61±8/hr vs 5.25±6/hr (p=0.37) and 6.35±8/hr vs 7.68±11/hr (p=0.60)

Conclusion
In this cohort of rural Veterans, there were no significant differences in outcomes for those who initiated PAP therapy via telehealth when compared to in-person. This supports the feasibility of more widespread implementation of telehealth services for treatment of OSA in order to improve access without compromising patient outcomes.

Support (if any)
VA OCC FY21 RFA, VAGLAHS GRECC, K24HL143055
0916 Q4 no More: Optimizing Clincial Decision Support to Decrease Inpatient Sleep Disruptions
Authors: Kadura Sullafa , Eisner Lauren , Poulakis Alexander , Wielgus Oskar , Lin Jennifer 
Published: May 2023

Abstract

Introduction
Orders such as vital signs (VS) and neurological checks (NC) contain frequency options to help clinicians align workflows with patient needs. However, these clinical decision support (CDS) systems often default to around-the-clock, and clinicians may over-accept around-the-clock, leading to unnecessary sleep disruptions.

Methods
We added two radio buttons to VS/NC orders: q4 hour while awake (q4WA) and TID while awake (TIDWA). We gave presentations on CDS to inpatient neurology unit (INU) residents and staff pre-intervention. We sent reminders to INU residents to review and modify (when appropriate) around-the-clock orders via secure chat. We defined the pre-intervention period as six months before and the post-intervention period as six months following. Order frequencies and NC/VS performed from 11 pm–7 am were obtained via EHR. Pre- and post-intervention data were analyzed using interrupted time-series analysis (ITSA).

Results
Post-intervention, there was a significant decrease in q4 order frequencies (VS 15% and NC 17%,p&lt; 0.001) across the institution. Subgroup analysis of the INU revealed more significant reductions in q4 frequencies (VS 54% and NC 48%, p&lt; 0.001). Sleep-friendly orders significantly increased for VS and NC (0% to 6.7%, 0% to 7.8%). Sub-group analysis of the INU was again more profound, with sleep-friendly orders increasing from 0% to 16% for both VS and NC. Additionally, overnight VS and NC performed decreased by 11% and 17% post-intervention (p&lt; 0.001) at the institution, with a further reduction in the INU (45% and 35% decrease for VS and NC, p&lt; 0.001). The case-mix index was appropriately lower in the population with while awake orders (1.2749) versus around-the-clock orders (2.2684)

Conclusion
CDS modifications significantly increased sleep-friendly orders while reducing around-the-clock order frequencies and NC/VS completed overnight. These results were more profound on the INU, indicating that a combination of CDS changes, education, and chat reminders demonstrated a higher impact than CDS changes alone.

Support (if any)
0920 Enrichment and Patterns of Comorbidities in the Electronic Health Record of Patients with diagnosed Obstructive Sleep Apnea
Authors: Te Tue , Keenan Brendan , Veatch Olivia , Hubbard Rebecca , Pack Allan 
Published: May 2023

Abstract

Introduction
Obstructive Sleep Apnea (OSA) is the most common respiratory disorder of sleep and an independent risk factor for multiple other medical conditions related to poor quality of life and increased mortality and morbidity. The current study utilized the electronic health record (EHR) to examine relationships between OSA and common comorbidities within a large-scale dataset.

Methods
Cases with OSA and non-cases (controls) were defined using a validated EHR case identification algorithm, and matched based on age, sex, and observation period. We collapsed International Classification of Disease codes into PheCodes representing common etiologies and identified the top 20 most common comorbidities in the EHR among cases. We then compared overall and annual prevalence between matched cases and controls using conditional logistic regression. Latent class analysis (LCA) was used to identify subtypes of cases defined by specific combinations of comorbidities.

Results
Overall, 60,586 EHR-defined cases and 60,586 matched controls (from a total of 1,226,755 EHR-defined controls) were identified. Matched pairs had a median (IQR) age of 54 (45-63) years and 57.4% were males. BMI was higher in cases (median [IQR] = 35.9 [29.6, 41.0] kg/m2) than matched controls (28.0 [24.0, 32.0] kg/m2). Patients with OSA were at significantly greater risk of having each of the top PheCodes when compared to matched controls, with odds ratios ranging from 3.1 to 30.8 in the full matched set and 1.3 to 10.2 after controlling for BMI in the subset with available data. LCA identified 5 distinct subgroups based on comorbidities, labeled as High Comorbidity Burden, Cardiovascular Comorbidities, Depressive and Inflammatory Conditions, Low Comorbidity Burden, and Obesity and Cardiometabolic Dysregulation.

Conclusion
Our study demonstrates the power of leveraging the EHR to understand the relative health burden of OSA. In addition to showing enrichment for a number of comorbidities, we identified 5 subtypes defined by specific combinations of comorbidities in the EHR. These results could be informative for understanding likely disease outcomes and improved prevention and clinical care.

Support (if any)
National Research Service Awards (NRSA) T32 HL07713 National Institutes of Health (NIH) P01 HL094307
0922 Interference of racial and socioeconomic factors in the sleep of a large Brazilian city: lessons for comparisons between countries
Authors: Dokkedal-Silva Vinicius , Fernandes Guilherme , Tufik Sergio , Andersen Monica 
Published: May 2023

Abstract

Introduction
Investigation on the effects of racial and socioeconomic parameters on sleep has markedly increased along the years. The vast majority of these studies take place on countries in North America or Europe, thus making it necessary that new initiatives are conducted in developing nations. The objective of this study was to evaluate how race and socioeconomic factors influence sleep in the city of São Paulo, Brazil.

Methods
Health and sleep parameters of participants of the EPISONO (2007) study were assessed with validated questionnaires and a night of polysomnographic examination. Data regarding their self-identified race was collected during this protocol. Among the applied questionnaires, scores in the Critério de Classificação Econômica Brasil (CCEB) questionnaire were adopted in this analysis. General Linear Models were used to investigate the relationship between objective sleep parameters and the racial and socioeconomic classification according to the CCEB questionnaire.

Results
1,008 participants of the EPISONO were included (mean age=42.3 years; 574 women). Class C Blacks had greater total sleep time (TST) than Class A Whites, while Class C Asians presented less TST. Indigenous participants had reduced wake after sleep onset (WASO) time when sided to Whites and, similarly, Class D Blacks presented lower WASO compared to Class A Whites. Arousal index was lower in Class B and C individuals when comparing to Class A individuals and higher in Class C Blacks when compared to Class A Whites.

Conclusion
The variety of results when comparing socioeconomic and racial factors highlights the richness of the interplay between these parameters. While some findings are similar to those of North American and European studies, there are differences underlining the necessity of evaluating the socioeconomic and racial background of each population cautiously. Future research on sleep patterns of the Brazilian population concerning the effect of race and socioeconomic status is essential and a promising frontier of investigation to be explored.

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.
0924 Poor sleep regularity is widespread among first-year medical students
Authors: Marquardt Matthew , Fisher Fielding , Grandner Michael , Khan Meena 
Published: May 2023

Abstract

Introduction
Poor sleep health is widespread within healthcare and is notoriously neglected during residency; however, little is known about sleep quality during the pre-clinical years of medical school. Sleep regularity is increasingly recognized as a key driver for sleep quality and health. This study sought to determine the prevalence of and the factors that contribute to irregular sleep among first-year medical students.

Methods
A one-time, 130-item survey was distributed to the first year medical school class three months into the first semester. Quantitative and open-text questions asked about various sleep health related topics, including sleep regularity across weekdays (WDs) and weekends (WEs) for the past two weeks. Likert scale responses were treated as continuous data and reported as mean ± standard deviation. Means for WD and WE times were compared using paired t-tests. Statistical significance was considered a p-value ≤0.05.

Results
Out of 209 medical students in the first-year class, 58% (n=121) completed the sleep irregularity items on the survey. Demographics mirrored those of the whole class: 46% male, 54% female, and average age 23.5. The differences between WD and WE times for getting into bed (1.03 hours ± 0.90 hours), falling asleep (0.92 ± 0.80 hours), waking up (1.62 ± 0.84 hours), and getting out of bed (1.89 ± 0.93 hours) were significant (p&lt; 0.001). Furthermore, 49.3% of participants reported significant bedtime or wake time variability (&gt;3 hours difference from one day to another) at least once per week during the past 3 months. This occurred despite respondents expressing a strong belief in the importance of sleep consistency (7.1 ± 2.25 on a 10-point Likert scale; 0=Strongly Disagree, 5=Neutral, 10=Strongly Agree).

Conclusion
Poor sleep regularity is widespread during the first year of medical school. While students are aware of the importance of consistent bedtimes and wake times, they rarely follow this knowledge suggesting that external factors encountered during medical school such as poorly balanced academic workloads or stress might be to blame. Future studies should seek to better understand the factors contributing to poor sleep regularity in medical school and develop interventions to help students address any barriers.

Support (if any)
0925 Population Health and Data Analytics as an Opportunity for Improving Care Quality in Sleep Medicine
Authors: Stothard Ellen , Hickey Mark , Wertz Adam 
Published: May 2023

Abstract

Introduction
The volume and diversity of sleep-related and quality of life complaints in sleep medicine has increased through improved availability of data from wearables and public education on sleep health. Future shifts away from quantity and towards quality-based compensation by insurance payors will require practices to understand and actively monitor population health and outcomes data and implement data-driven practices to improve diagnostic efficiency. Currently, prevalence and population health data benchmarks are incomplete or absent in many aspects of sleep disorders treatment. The integrated care model of sleep medicine, with board-certified primary sleep physicians, an in-house Positive Airway Pressure (PAP) Therapy clinic and certified sleep medicine Dentist, is uniquely positioned to improve care by characterizing the impact of clinical decision-making on care cost and quality.

Methods
Population health data was gathered in the course of patient care in the integrated care model. Baseline/Diagnostic Home Sleep Apnea Test (HSAT) results from 2018-2021 were included. Diagnostic severity was categorized based on AASM treatment guidelines. Matched therapy visits were included from PAP Therapy Initiation or Compliance visit and treatment outcomes, as well as non-PAP treatments for sleep-disordered breathing, Oral Appliance (OA) and Inspire Therapy.

Results
20% of 8531 Diagnostic HSAT results were non-diagnostic for sleep apnea, 35% were Mild, 21% Moderate and 24% Severe. Of non-diagnostic tests, 81% had no sleep apnea treatment associated. Of Mild diagnostic tests, 49% had associated PAP initiation or compliance, 9% had associated OA, and 42% had no treatment associated. The relationship between diagnostic severity and associated treatment was significant (Χ2 &lt; 0.0001). Further, Moderate and Severe resulting diagnostic tests had no associated treatment in 24% and 28% of cases, respectively.

Conclusion
Sleep medicine patients are commonly symptomatic and often have major quality of life complaints. Yet as these data demonstrate, there is a substantial proportion of patients who do not have an associated treatment after a positive diagnostic home sleep apnea test. Future studies should include additional demographic and follow up data to better understand care pathways both for patients who receive a positive diagnostic test but pursue alternative treatment methods, as well as more complicated non-diagnostic sleep disorders patients.

Support (if any)
0927 The Evolution of Costs for Telehealth versus In-person PAP Initiation for Patients with Sleep Apnea over the COVID Pandemic
Authors: Jambulingam Nikita , Sarmiento Kathleen , Gomez Alexander , Huynh Angela , Sanders Elizabeth , Smith Connor , Mitchell Michael , Lee Diane , Ryden Armand , Martin Jennifer , Zeidler Michelle 
Published: May 2023

Abstract

Introduction
During the COVID pandemic, at the San Francisco VA Healthcare System (VASFHS), positive airway pressure (PAP) set-up visits transitioned from in person to a mix of in person and telehealth for patients newly diagnosed sleep apnea. As part of a larger study examining the clinical outcomes resulting from telehealth versus in-person PAP initiation, we performed a cost analysis of these two treatment pathways within VASFHS.

Methods
The telehealth pathway included mailing of PAP machines to patients (initially from VASFHS and later through a centralized national distributor), with follow-up video/phone education by respiratory therapists (RTs) and registered sleep technicians (RSTs). We used a bottom-up analysis to examine the total variable direct cost of telehealth versus in-person PAP initiation at various points through the COVID pandemic for patients newly diagnosed with sleep apnea at VASFHS.

Results
The total variable direct cost of telehealth PAP initiation was $49.66 per patient mid-pandemic (Feb-Dec 2020) compared to $31.02 per patient post-pandemic (Oct-Dec 2022). The total variable direct cost of in-person PAP initiation was $16.76 per patient pre-pandemic (Jan-Dec 2019) compared to $22.71 per patient post-pandemic. The reduction in costs (37.5%) for telehealth PAP initiation mid- to post-pandemic was due to 25% less RT/RST time required and elimination of PAP shipping costs as PAP distribution became nationally centralized. The increase in costs (35.5%) for in-person PAP initiation pre- to post-pandemic was largely due to elimination of group PAP initiation sessions (33.3% more RT/RST time required for individual PAP initiation). Post-pandemic, telehealth PAP initiation cost was 36.6% more than in-person due to 25% more RT/RST time required and five times as much troubleshooting help required for the telehealth pathway.

Conclusion
With integration of telehealth for PAP initiation, as RT/RSTs gained more expertise with this interface through the pandemic and as distribution of PAP machines/supplies became centralized, costs were significantly reduced, making telehealth a financially sustainable workflow. Future cost analysis can evaluate if group rather than individual telehealth PAP initiation would yield additional cost savings, placing it on par with the cost of in-person PAP initiation.

Support (if any)
VA OCC FY21 RFA, VAGLAHS GRECC, K24HL143055
0928 The Self-Reported Practice of Light Exposure Recommendations in the Morning, Daytime, Evening, and Nighttime
Authors: Gottlieb Elie , Gahan Luke , Wilson Samantha , Watson Nathaniel F , Raymann Roy 
Published: May 2023

Abstract

Introduction
While it is well known that ocular light strongly entrains the central circadian clock, there has been a lack of evidence-based recommendations for daytime, evening, and nighttime light exposure for healthy adults. Recently, an expert consensus report with recommendations for light exposure has been published. Although the general population is likely not yet acquainted with these recommendations, we examined the self-reported practice of daily and nightly light exposure based on these published guidelines.

Methods
Online survey data were collected from 168 participants through convenience sampling (age range: 25-80, mean age: 58.9 + 12.6 years, 55% female). The practice of expert, consensus-based light recommendations was assessed with 4 items on an 8-point frequency scale ranging from “Never” to “Every day of the week”. The scale covered 1) indoor daytime light recommendations, 2) indoor evening light recommendations, 3) nighttime light recommendations for the sleep environment, and 4) an additional morning-specific question.

Results
Within the first hour after waking up, the majority of respondents (53%) reported never receiving exposure to at least 15 minutes of sunlight or simulated bright light, with only 16% reporting exposure every day of the week. Throughout the daytime, 54% of respondents reported receiving consistent natural indoor light or sunlight every day of the week, and 8% reported never receiving any. During the evening, 47% of respondents reported never dimming lights and avoiding bright light starting at least 3 hours before bedtime. However, 24% reported avoiding bright light sources before bedtime every day of the week. While sleeping, nearly 80% of respondents reported keeping their bedroom as dark as possible, no brighter than natural moonlight, every day of the week, with only 10% reporting never doing so.

Conclusion
Self-reported practice of recently published light recommendations was poor for both morning and evening light exposure. These findings suggest that sleep and circadian health campaigns should focus on the importance of bright light in the morning upon awakening, and of dimmed light in the late evening before bedtime.

Support (if any)
SleepScore Labs
0932 Sleep Difficulties: Prevalence, relationship with psychological outcomes, and interindividual differences in student-athletes
Authors: Charest Jonathan , Cook Jesse , Werthner Penny , Samuels Charles 
Published: May 2023

Abstract

Introduction
Mental health issues are a leading cause of decreased academic and athletic performances when left untreated. Recently, the International Olympic Committee (IOC) and the National Collegiate Athletic Association (NCAA) have highlighted the fundamental importance of mental health among young athletes. Sleep represents a core feature of mental health, and student-athletes represent a vulnerable population for sleep restriction and disruption due to the demands of their courseload and training schedule. This investigation was performed to identify differences in sleep and mental health across gender, race/ethnicity, and sport type.

Methods
Data were obtained throughout the academic semester from Canadian institutions, with student-athletes completing the Athlete Sleep Screening Questionnaire (ASSQ), General Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire (PHQ-9). ASSQ captured sleep and circadian health, while GAD-7 and PHQ-9 assessed anxiety and depressive symptoms, respectively. Linear regression determined gender, race/ethnicity, and sport type differences across ASSQ sleep problems score, ASSQ sleep items, GAD-7 score, PHQ-9 score, and PHQ-9 item #9 (suicidal ideation).

Results
Final sample (N=559) was 53.0% female, 79.1% white, comprised of young individual (Mean Age = 18.9 ± 3.21), and included student-athletes from basketball, field-hockey, football, ice-hockey, soccer, volleyball, track & field and swimming. Females reported more overall sleep difficulties (p=0.01), medication use (p=0.04) and WASO (p=0.001) compared to males. Females also reported higher anxiety (p &lt; 0.0001), depression (p&lt; 0.0001), and suicidal ideation (p=0.03). Significant variance in total sleep time (TST) (p=0.001) and sleep satisfaction (p=0.04) was observed across race/ethnicity, with student-athletes identifying as Black or African American reporting the lowest TST, while Asian or Pacific Islander student-athletes reported the lowest sleep satisfaction. Significant variance in sleep difficulties score (p&lt; 0.0001), TST (p &lt; 0.0001), and satisfaction (p&lt; 0.0001), as well as anxiety (p &lt; 0.0001) and depression (p&lt; 0.0001) was observed across sport type. Football student-athletes reported the highest sleep difficulties score, and lowest TST satisfaction. Field-hockey student-athletes reported the highest anxiety and depression.

Conclusion
Results suggest that sleep and mental health challenges present differently across gender, race/ethnicity, and sport type. Clarifying these unique and specific challenges to student-athlete sleep and mental health is necessary to enhance and personalize interventions.

Support (if any)
Mitacs #IT23469