bluuebunny/crossref_metadata_2025_split huggingface dataset:
0497 Obstructive Sleep Apnea Prevalence in a Young Mixed Trauma Population with Post-traumatic Stress Disorder Symptoms
Authors: Jordan Amy , Cherian Darshana , Pan Maddie , Bruce Gemma , Schenker Maya , Zeng Liz , Felmingham Kim 
Published: April 2024

Abstract

Introduction
Disturbed sleep appears to play a role in post-traumatic stress disorder (PTSD) development and maintenance. The prevalence of obstructive sleep apnea (OSA, as defined as an AHI&gt;5 events/hr) has been reported to be up to 75% in individuals with PTSD (Zhang 2017). Most prior studies investigating OSA prevalence in PTSD have been conducted in military populations, who commonly have other risk factors for OSA such as being male, middle-aged and having high rates of substance use disorders. The aim of this study was to determine whether OSA is more common in individuals with PTSD symptoms exposed to non-military traumas as compared to individuals without PTSD symptoms.

Methods
125 participants interested in completing a sleep study completed a screening questionnaire measuring previous Criterion A trauma exposure (Life events checklist) and PTSD symptoms (PTSD symptom checklist for DSM-5, PCL-5), along with alcohol use and demographic information. A sub-set were recruited for a standard overnight polysomnography either in the sleep laboratory (Grael, Compumedics), or at home (Siesta, Compumedics). Sleep studies were scored blinded to questionnaire data by an independent sleep technician. Three symptom severity groups were compared, individuals with Likely PTSD (PCL-5 &gt;33 and Criterion A trauma exposure) Sub-Syndromal PTSD (PCL-5 15-33 and Criterion A trauma exposure) or No-PTSD (PCL-5 &lt; 15 and no intrusive symptoms).

Results
45 participants (31 female; aged 18-48 years) completed the polysomnography. 11 had likely PTSD, 10 Sub-Syndromal PTSD and 23 had No-PTSD. The 3 groups were comparable in age (25±7 years), sex (68% women) and BMI (24.2±4.5 kg/m2). In total, 6 participants had AHI &gt;5 events/hr; 3 in the Likely PTSD group, 2 in the Sub-Syndromal group and 1 in the No-OSA group. The mean AHI did not differ between groups (Likely PTSD = 5.1±7.7, Sub-Syndromal PTSD = 4.0±6.7, No-PTSD = 2.2±4.4 events/hr, p=.64).

Conclusion
Although the a priori sample size (n=26 in each group) has not yet been reached, these preliminary data indicate that the prevalence of OSA in a young mixed-trauma PTSD population is unlikely to be as high as has been observed previously. PTSD may only increase the risk for OSA in older/heavier individuals.

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University of Melbourne.
0499 Relationship Between RDW and Disease Burden in Obstructive Sleep Apnea
Authors: Abraham Stanley , Basist Madeleine , Duenas Sean , Dong Vincent , Rusk Sam , Nygate Yoav , Quintero Luis , Hahn Stella , Greenberg Harly , Talwar Arunabh 
Published: April 2024

Abstract

Introduction
Obstructive sleep apnea (OSA) has significant physiologic consequences. The Apnea-Hypopnea Index (AHI) is used to define severity, but AHI only reflects the rate of sleep-disordered breathing events and does not correlate well with clinical outcomes that arise from hypoxia. Percentage of cumulative time with oxygen saturation below 90% (T90) and hypoxic burden (HBI) more accurately reflect nocturnal hypoxia and may be more suitable correlates to morbidity associated with sleep apnea. Rising Red Cell Distribution Width (RDW) reflects dysregulation in erythrocyte homeostasis seen with metabolic derangements like oxidative stress and inflammation which has been shown to correlate with mortality in cardiovascular disease. Previous work demonstrates a linear relationship between RDW and AHI. We postulate there is a positive correlation between RDW, T90 and HBI.

Methods
A retrospective analysis of 1797 participants at Northwell with Home Sleep Apnea Testing or in-lab Polysomnography data and complete blood counts (CBC) within 6 months of the sleep study was performed. Subjects with chronic hypoxemia or hematologic conditions that may affect CBC were excluded. Ordinary least squares (OLS) regression was performed using RDW as the dependent variable and AHI, T90, HBI and mean saturation of peripheral oxygen (SpO2) as independent variables.

Results
OLS analysis revealed a statistically significant positive correlation between RDW and T90 (coef=.807 (CI 0.426,1.188), p-value=0.000034), HBI (coef=0.000033 (0.000019,0.000054), p-value=0.002)) and AHI (coef= 0.0062 (0.0028, 0.0097), p-value= 0.0004). A negative correlation was noted between mean SpO2 and RDW (coef=-0.047 (-0.078,-0.162), p-value=0.003).

Conclusion
There is a positive correlation with RDW and sleep apnea markers of disease burden, including T90, HBI, and mean SpO2. A 100% change in T90 (0 – 100%) in a patient will result in an increase in RDW by 0.8 and a 100% change in HBI (0 – 500 %min/hour) will result in an increase in RDW by 1.5. AHI was noted to poorly correlate with RDW. An AHI of 100 resulted in a 0.62 increase in RDW versus an AHI of 0. For the range of mean SpO2 observed (range 80 – 100%) the expected change in RDW is 0.94. This relationship requires further exploration in future studies.

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0501 Sleep Medicine Referrals in a High-Risk Obstetrics Population
Authors: Boyd Victoria , Shewnarain Kimberly Persaud , Oo Thae Aient Aient , Naik Sreelatha , Paglia Michael , Mackeen A Dhanya , Young Amanda , Grey Celia 
Published: April 2024

Abstract

Introduction
Obstructive sleep apnea (OSA) has traditionally been underdiagnosed and undertreated in pregnancy. Untreated OSA has been associated with adverse peripartum outcomes, such as hypertensive disorders of pregnancy, diabetes, cesarean delivery and NICU admissions. In August 2023, a taskforce from the Society of Anesthesia and Sleep Medicine and the Society for Obstetric Anesthesia and Perinatology published recommendations that pregnant patients with obesity, gestational or pre-existing diabetes, or hypertensive disorders of pregnancy be screened for OSA. Currently, our Maternal-Fetal Medicine (MFM) group only screens for OSA in the obese pregnant population on a conditional basis. It is unknown how many of these patients are screened for OSA and/or referred to sleep medicine for follow-up.

Methods
This is a cross-sectional retrospective study to characterize the 19,439 pregnancies from January 1, 2012-December 31, 2022 at a rural health system with five labor and delivery units that would meet criteria for screening for OSA and a sleep medicine referral. Patients were included if they were over 18, pregnant and had at least a hypertensive disorder of pregnancy, diabetes (pre-existing or gestational) or were obese. The Cochrane-Armitage trend test was used to evaluate the rates over the time-period.

Results
In the initial data review, we found that between 2012 and 2022, the practice grew considerably; there was an increase in the proportion of women with gestational diabetes (16.9-31.2%, p&lt; 0.01), obesity (75.0-75.2%, p&lt; 0.01) and a hypertensive disorder of pregnancy (22.9-25.8%, p&lt; 0.01). Despite the increase in sleep medicine referrals during pregnancy (0.4-1.1%, p&lt; 0.01) over the years, the overall referral rate to sleep medicine regardless of the selected peripartum co-morbidity remained low at 0.5-0.9%.

Conclusion
Less than 1% of patients at high-risk for OSA in pregnancy are being screened or tested for OSA. Based on the guidelines published in August 2023, these results establish a wide practice gap in our center. It is likely that this knowledge is generalizable to centers around the country. We conclude that there is a large opportunity to improve our maternal outcomes by connecting these at-risk patients with sleep medicine referrals to be screened and treated for OSA.

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0502 Impact of Excessive Daytime Sleepiness on Day-to-day Experience of Patients Suffering from Obstructive Sleep Apnea
Authors: Khan Anees , Waheed Sana , Rasul Ammar , Usama Muhammad , Usman Abira , woo Emily , Waheed Muazzam , Cheema Mustafa 
Published: April 2024

Abstract

Introduction
Today, excessive daytime sleepiness (EDS) is considered as one of the most frequently occurring clinical manifestations in patients with obstructive sleep apnea (OSA). According to the National Sleep Foundation 2000 Omnibus Sleep in America Poll: `a sizable proportion of adults (43%) report that they are so sleepy during the day that it interferes with their daily activities a few days per month or more; and, one out of five (20%) experience this level of daytime sleepiness at least a few days per week or more'.

Methods
Inclusion criteria The articles identified, were screened by title and abstract, and selected for full text review if they met the following inclusion criteria. 1)OSA and EDS should be primary or secondary outcomes and not incidental findings. 2)Studies showing clinical manifestations of EDS in patients with OSA such as problems with vigilance, cognitive function, memory, concentration, and mood; deterioration in school and/or job performance and productivity, social relationships, and driving skills Exclusion criteria Those articles and or studies were excluded from our analysis that included: 1)Patients who did not undergo the polysomnography.2)Patients who had pure or mainly central sleep apneas, co-morbidities, terminal illness 2)Patients with other causes of fatigue or excessive daytime sleepiness 3)Patients from pediatrics

Results
Our search strategy yielded 770 citations. Irrelevant papers were excluded by title and abstract review, leaving 72 manuscripts that were identified from the comprehensive database search. We read the titles of these articles specifically identify papers that looked at EDS and its impact on day to day life of patients suffering from. This eventually yielded the selection of 5 number of articles from their respective databases.

Conclusion
All of the included studies point towards a growing evidence that there is a strong correlation between EDS and OSA and how EDS affects the course of disease. Some negative effects of OSA are reduced productivity, cognitive dysfunction, frequent awakenings, disrupted sleep, irritability, judgment error and increased accident rates. OSA related EDS is related to neurocognitive function. Therefore, patients often have difficulty in concentrating and paying attention for long periods of time. Fine-motor coordination also gets affected.

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0504 Unraveling the Relationships Between Chronic Illness, Healthcare Access, and Obstructive Sleep Apnea in Nigeria
Authors: Olaoye Olatunji , Bolarinwa Oladimeji , Alatishe-Muhammad Bilqis , Saka Kafayat , Yakubu Bisola , Sotome anuoluwa , Adejumo Oluwatobiloba , Suberu Anavami , Oluwatoyin Aishat , Babs-Lawal Muhibat , Munirdeen Abdulrahman , Malomo Victor , Ademola Suliyat , Adewale Maryam , Babayanju Hikmat , Olaoye Olanrewaju 
Published: April 2024

Abstract

Introduction
Diagnosing Obstructive Sleep Apnea (OSA) in the wider population in Sub-Saharan Africa is challenging, while co-morbidity with other chronic illnesses and Cardiovascular disease is still unestablished. For the few individuals with established sleep disorders and chronic illness, poor health-seeking behaviour has contributed to this gap. This population-based survey assessed associations between chronic illness, healthcare access and OSA in Nigeria

Methods
A cross-sectional study was conducted among 2388 respondents in North Central Nigeria using the STOP-BANG Questionnaire (ESQ) tool and Epworth Sleepiness Scale (ESS). A multistage sampling technique was used. Data collected was analyzed using SPSS IBM V.23. Descriptive and inferential statistics to test associations between categorical variables were analyzed. The level of statistical significance was set at p&lt; 0.05 at 95% confidence level Ethical approval (ERC/MOH/2023/11/164) was obtained from the Ethical Review Committee of the Kwara State Ministry of Health.

Results
Of 2388 respondents, 683 (28.6%) were less than 50 years old, and 18.2% reported chronic illness, with hypertension being the most reported (59.1%). About 92% of those with chronic illness were on medications, and only 40.7% accessed hospital follow-up. About a third (33.3%) reported that the chronic illness affected their daily work and activities. Following medical measurement, 8.5% were underweight, 21.2% overweight, and 11.4% obese. About 16.6% had elevated diastolic blood pressure, while 21.9% had elevated systolic blood pressure. Of the respondents who reported sleep problems, SBQ classified 50% of them as having moderate to high risk of OSA (p&lt; 0.001). There were significantly higher risks of sleepiness and OSA among the respondents who reported having chronic illness in both ESS (p=0001) and SBQ (p&lt; 0.0001) scales. Similarly, high blood pressure and obesity were significantly associated with a high risk of sleepiness and OSA in SBQ (p=0.001) and ESS(p=0.004) scales respectively. The SBQ scale also revealed a significantly lower health facility utilization rate among respondents with a high risk of sleepiness (p&lt; 0.001)

Conclusion
There is a higher risk of sleepiness and OSA among the Nigerian population with chronic illness, many of whom have low healthcare access. This poses the danger of undiagnosed and iceberg phenomena in diagnosing OSA in low-resource settings.

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0506 Practice Patterns of Sleep Disorders Diagnoses in a Statewide Health System: An Electronic Health Record Analysis
Authors: Vyata Vishruth , Deshpande Pushkar , So Jennifer , Glick Danielle , Verceles Avelino , Fang Beverly , Rolla Krishna Jayanth , Johnston Christine , Diaz-Abad Montserrat , Wickwire Emerson 
Published: April 2024

Abstract

Introduction
A substantial proportion of medical care is delivered through hospital networks and health systems. Yet relatively little is known about how sleep disorders are managed from a health systems perspective. Such insight is vital to improve population sleep health. The purpose of this study was to characterize sleep disorder practice patterns within a statewide health system.

Methods
The University of Maryland Medical System (UMMS) is comprised of 13 largely autonomous hospitals that function in a decentralized manner. Four UMMS hospitals feature sleep centers. In this study, patients diagnosed with sleep disorders (January 1 – December 5, 2023) were identified using the UMMS electronic health record (EPIC). Demographic information was obtained from the EHR. Sleep disorders were identified based on ICD-10 diagnostic codes assigned within the EHR. Descriptive statistics were used to characterize sleep disorder diagnoses at the system and hospital levels.

Results
Of UMMS patients seen during the study period, 5.8% of individuals (up to N=65,095) were diagnosed with sleep disorders. The two most common sleep disorders were obstructive sleep apnea (OSA; n=36,130 patients) and insomnia (n=20,280). Others included restless legs syndrome (n=3744), hypersomnia (n=1959), parasomnias (n=816), circadian rhythm disorders (n=532), narcolepsy (n=397), central sleep apnea (n=342), and periodic limb movement disorder (n=175). The highest numbers of sleep disorder diagnoses occurred at hospitals with sleep centers. Multiple points of care had zero diagnoses for common sleep disorders. In terms of sociodemographic characteristics, the ratio of OSA vs insomnia differed between Black and White adults.

Conclusion
Sleep disorders are commonly diagnosed in a statewide health system, with substantial variation between hospitals and points of care. Potential disparities were observed in the ratio of OSA vs insomnia diagnoses between Black vs White adults, suggesting possible underdiagnosis of insomnia among Black adults and an important topic for future research. Health systems leaders should consider system and hospital-level approaches including increasing provider awareness and leveraging telehealth and technology to improve outcomes for patients, providers, and health systems.

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University of Maryland, Baltimore
0507 A Novel Machine Learning Model to Predict Obstructive Sleep Apnea Using Craniofacial Photography with Questionnaire
Authors: Kim Yunsoo , Park June-Young , Jang Yeji , Kim Min Hye , Ryu Wi-Sun , Kim Jee Hyun , Shin Hye-Rim , Kim Tae-Joon 
Published: April 2024

Abstract

Introduction
Obstructive sleep apnea (OSA) is a complex and heterogeneous sleep-related breathing disorder, associated with systemic consequences such as hypertension, stroke, and cardiovascular diseases. Although initial screening tools such as STOP-BANG or the Berlin questionnaires have been developed, it is still challenging to capture the wide spectrum of the condition alone. Besides the questionnaires including clinical presentations, craniofacial abnormalities are also recognized as an important risk factor for detecting OSA. Herein we aim to develop an efficient approach to predict the risk of having moderate to severe OSA using machine learning techniques by incorporating anatomical information from 2D photographs.

Methods
This retrospective analysis included 348 patients, who completed answering the STOP-BANG questionnaires and took facial images at Dankook University Medical Center in South Korea between 2012 and 2022. A 1:1 Random under-sampling (RUS) method was applied to solve the imbalance problem between moderate to severe OSA cases (Apnea-Hypopnea Index ≥15 events/hour) and control. Balanced data were randomly divided into two data sets (training and validation: 80%; testing: 20%). We performed leave-one-out cross-validation (LOOCV) to seek the optimal parameters to improve the model performance and generalization using four machine learning models (logistic regression, random forest, support vector machine, XGBoost) in the training set. Thereafter, we adopted the model with the highest area under the receiver operating characteristic (AUROC) in the testing set. Finally, we evaluated the importance of each input feature in assessing OSA risk by calculating the Shapley additive explanations (SHAP) values.

Results
The logistic regression model achieved the best AUROC of 94.1% for predicting moderate to severe risk OSA. The value of craniofacial images built from deep learning algorithms was found to be a predominant contribution in the risk screening models of OSA with the aforementioned levels of severity.

Conclusion
The results of the study suggest that the proposed model improved the diagnosis of patients with moderate to severe OSA based on the combination of sleep-related questionnaires and 2D facial images by identifying the risk factors more efficiently.

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0509 Association Between Access to Sleep Care and Acute Care Utilization: A Preliminary Analysis
Authors: Deshpande Pushkar , Vyata Vishruth , Glick Danielle , Verceles Avelino , Fang Beverly , Rolla Krishna Jayanth , Johnston Christine , Diaz-Abad Montserrat , Wickwire Emerson , So Jennifer 
Published: April 2024

Abstract

Introduction
Obstructive Sleep Apnea (OSA) has been linked to increased cardiopulmonary morbidity and mortality, as well as acute care healthcare resource utilization (HCRU; emergency department [ED] visits and hospitalizations). The purpose of this study was to test the hypothesis that access to OSA care was associated with decreased acute care HCRU in the state of Maryland.

Methods
The University of Maryland Medical System (UMMS) is comprised of 12 autonomous hospitals that function in a decentralized manner. Patients (N=31,477) were identified within the UMMS electronic health record system based on ICD-10 code for OSA (G47.33). Access to care was defined based on the number of AASM-accredited sleep centers in the five main regions of Maryland. Acute care HCRU was defined based on rates of ED admissions and inpatient hospitalizations from January 1st, 2023 to December 5th 2023 in each of the 12 hospitals and main regions of Maryland.

Results
The final sample included 31,447 patients diagnosed with OSA. At the individual hospital level, the highest rate of ED admissions was observed within a suburban hospital (7.79%). The highest rate for inpatient hospitalizations was observed within an urban hospital (6.47%). At a regional level, the Central Maryland region (seven hospital sites) showed the highest average rate of ED admission (3.78%) and inpatient hospitalizations (2.98%). Notably the Central Maryland region also had the largest number of AASM-accredited sleep centers (n=14) compared to other Maryland regions, suggesting a positive association between access to OSA care and acute care HCRU. From a socioeconomic stand point, Central Maryland average median household income was only the third highest ($96,128).

Conclusion
Contrary to our hypothesis, access to OSA care was associated with increased acute care HCRU among individuals with OSA in a statewide health system. The most likely explanation for this finding is a higher number of OSA diagnoses around sleep centers which are regionally clustered and possible regional differences in patient population. Future research should seek to improve OSA management and reduce acute care HCRU.

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None
0510 ETCO2 Screening for Obesity Hypoventilation Syndrome: A Patient Safety and Quality Improvement Study
Authors: Cocozza Victoria , Clay Collin , Scheuller H Samuel , Brock Matthew , Tchopev Zahari 
Published: April 2024

Abstract

Introduction
Obesity hypoventilation syndrome (OHS) is a disorder of daytime hypercapnia which worsens during sleep. OHS may be underdiagnosed yet has an insidious progression to significant cardiopulmonary and neurologic morbidities and increased mortality. End-tidal carbon dioxide (ETCO2) monitoring is not routinely obtained in adult patients undergoing in-lab diagnostic polysomnography (PSG), possibly contributing to underdiagnosis. Patients with OHS may be missed without initial screening and consideration for this diagnosis. This quality improvement project sought to estimate the incidental rates of OHS in obese patients and describe their clinical characteristics.

Methods
Patients presented to our academic sleep center from September – November 2023 for clinically indicated diagnostic PSG. Those with a body-mass index (BMI) greater than 30 kg/m2 underwent ETCO2 monitoring during their PSG. Those with a documented history of opioid use, primary pulmonary or neurologic disease were excluded. Basic demographics and sleep screening questionnaires were obtained.

Results
Initial data revealed 43 eligible patients. 21% (n=9) of patients met the International Classification of Sleep Disorders (ICSD) Third Edition Text Revision diagnostic criteria for OHS. There was no statistical difference between the OHS group and the non-OHS group in the following categories: Male (77.8% v 76.5%), Age (33.8 v. 33.6), BMI (33.2 v. 33.8), AHI (23.6 v. 22.9), and ESS (12.8 v. 12.3). Of note, ISI scores were significantly different (15.9 v. 16.9, p=0.04).

Conclusion
Implementing an OHS screening protocol is a quick, feasible way to improve diagnosis of OHS. The incidental discovery of OHS was found to be clinically meaningful. Given the relatively low BMI, this may be an underestimation of OHS prevalence in obese patients. To the authors knowledge, no published improvement projects exist for improving diagnosis of OHS with routine PSG in an outpatient setting.

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