Risk Of OSA Research Articles

Prevalence of metabolic syndrome in adult patients with obstructive sleep apnea syndrome

To assess metabolic syndrome prevalence in adult patients with OSAS. We administered a standardized clinical questionnaire and four sleep questionnaires (Berlin, Epworth Sleepiness Scale, STOP, and STOP-Bang), and measured anthropometric variables. We also measured serum glucose and lipids, and blood pressure following an overnight fast. Metabolic syndrome was diagnosed according to National Cholesterol Education Program criteria. Patients underwent an overnight ambulatory respiratory polygraphy to confirm the diagnosis of OSAS. The predictive variables were subjected to univariate and multivariate analysis in a logistic regression model. Of 1,030 screened patients, 68% were male, 92% had comorbidities and 58% had moderate-severe OSAS. Subjects with OSAS were more obese, had higher cervical and waist circumference, blood pressure and fasting serum glucose, had lower HDL cholesterol, and an increased incidence of metabolic syndrome (55.4% vs. 44.8%, p<0.013). Age, male sex, hypertension, body mass index, cervical, waist and hip circumferences, intense snoring, witnessed apnea, nocturia, and components of metabolic syndrome were associated with the risk of OSAS and its severity. Fasting blood glucose, blood pressure, and waist circumference were associated with the risk of moderate or severe OSAS, which was not significant for the alteration of blood lipids. Patients with OSAS have a high prevalence of metabolic syndrome. OSAS was associated with an increase in the cardiovascular risk factors that comprise the metabolic syndrome.

Lung Structure and Risk of Sleep Apnea in SPIROMICS.

The SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) is a prospective cohort study that enrolled 2981 participants with the goal of identifying new chronic obstructive pulmonary disease (COPD) subgroups and intermediate markers of disease progression. Individuals with COPD and obstructive sleep apnea (OSA) experience impaired quality of life and more frequent exacerbations. COPD severity also associates with computed tomography scan-based emphysema and alterations in airway dimensions. The objective was to determine whether the combination of lung function and structure influences the risk of OSA among current and former smokers. Using 2 OSA risk scores, the Berlin Sleep Questionnaire (BSQ), and the DOISNORE50 (Diseases, Observed apnea, Insomnia, Snoring, Neck circumference > 18 inches, Obesity with body mass index [BMI] > 32, R = are you male, Excessive daytime sleepiness, 50 = age ≥ 50) (DIS), 1767 current and former smokers were evaluated for an association of lung structure and function with OSA risk. The study cohort's mean age was 63 years, BMI was 28 kg/m2, and forced expiratory volume in 1 second (FEV1) was 74.8% predicted. The majority were male (55%), White (77%), former smokers (59%), and had COPD (63%). A high-risk OSA score was reported in 36% and 61% using DIS and BSQ respectively. There was a 9% increased odds of a high-risk DIS score (odds ratio [OR]=1.09, 95% confidence interval [CI]:1.03-1.14) and nominally increased odds of a high-risk BSQ score for every 10% decrease in FEV1 %predicted (OR=1.04, 95%CI: 0.998-1.09). Lung function-OSA risk associations persisted after additionally adjusting for lung structure measurements (%emphysema, %air trapping, parametric response mapping for functional small airways disease, , mean segmental wall area, tracheal %wall area, dysanapsis) for DIS (OR=1.12, 95%CI:1.03-1.22) and BSQ (OR=1.09, 95%CI:1.01-1.18). Lower lung function independently associates with having high risk for OSA in current and former smokers. Lung structural elements, especially dysanapsis, functional small airways disease, and tracheal %wall area strengthened the effects on OSA risk.

The causal relationship between obesity, obstructive sleep apnea and atrial fibrillation: a study based on mediated Mendelian randomization.

Atrial fibrillation (AF) is a common cardiac arrhythmia that is associated with obesity and obstructive sleep apnea syndrome (OSA). Obesity and OSA may increase the risk of AF by affecting cardiovascular health. The study used the Mendelian randomization (MR) approach, combined with two-sample and multivariable analyses, to assess the relationships between obesity, OSA, and AF. The study utilized GWAS data and applied various statistical methods for the analysis. The study found that obesity increased the risk of OSA, which in turn significantly increased the risk of AF. Through mediating MR analysis, it was found that OSA played a certain role in the causal relationship between obesity and AF, with about 6.4% of the risk of AF being mediated by OSA. This study highlights the relationships among obesity, OSA, and AF, providing useful guidance for future clinical researches.

Sex-based differences in obstructive sleep apnea and atrial fibrillation: Implication of atrial fibrillation burden

BackgroundObstructive sleep apnea (OSA) is a risk factor for atrial fibrillation (AF); however, it is unclear whether AF increases the risk of OSA. Furthermore, sex differences among patients with both AF and OSA remain unclear. We aimed to determine the association between an increased AF burden and OSA and investigate the differences in clinical characteristics between women and men with AF and OSA. MethodsThis was a descriptive, cross-sectional analysis from a prospective cohort study. Patients with non-valvular AF were recruited from the cardiac electrophysiology clinic of a tertiary center; they underwent a home sleep apnea test and 14-day ambulatory electrocardiography. Moderate-to-severe OSA was defined as an apnea-hypopnea index of ≥15. ResultsOf 320 patients with AF, 53.4% had moderate-to-severe OSA, and the mean body mass index (BMI) was 25.6 kg/m2. Less women (38.2%) had moderate-to-severe OSA than men (59.3%) (p < 0.001). In the multivariate analysis, age, being a man, and BMI were significantly associated with moderate-to-severe OSA. AF burden was associated with moderate-to-severe OSA only in men (odds ratio: 1.008; 95% confidence interval: 1.001–1.014). Women and men with OSA had similar BMI (p = 0.526) and OSA severity (p = 0.754), but women were older than men (70.1 ± 1.3 vs. 63.1 ± 0.9 years, p < 0.001). Women with moderate-to-severe OSA had a lower AF burden than men did (27.6 ± 7.1 vs. 49.5 ± 3.9%, p = 0.009). ConclusionsAF burden is a sex-specific risk factor for OSA and is limited to men. In contrast, women with both AF and OSA have a lower AF burden than men, despite being older and having similar OSA severity and body habitus. Thus, AF may develop later in women with OSA than in men.

Association between air pollutant exposure, body water distribution and sleep disorder indices in individuals with low-arousal-threshold obstructive sleep apnoea

BackgroundAir pollution may alter body water distribution, it may also be linked to low-arousal-threshold obstructive sleep apnoea (low-ArTH OSA). Here, we explored the mediation effects of air pollution on body...

Association between the Obstructive Sleep Apnea and Cephalometric Parameters in Teenagers.

OSA is a common problem in children and adolescents. Angle class II malocclusion, a tendency toward the vertical type of growth, causes a decrease in the volume of the oral air space, increasing the risk of OSAS. The aim of this study was to evaluate the relationship between cephalometric and OSA parameters, to develop collaborative approaches between orthodontists and somnologists in the treatment of adolescents with OSA. We analyzed data from 41 adolescents with OSA. Their mean age was 15.8 ± 1.08 years. Orthodontic and polysomnographic examinations of patients were conducted. Statistical analysis was performed in SPSS 19.0.0. Most often in patients with distal occlusion, a violation of the harmony in the development of the dental system was observed. The sagittal incisive fissure, characteristic of a distal occlusion, was absent due to the palatal inclination of the upper incisors in 25 (60.98%) patients. The SNB was 79.4 ± 3.1°, indicating a distal position of the mandible relative to the anterior cranial base. The SNA exceeded the normal value, which is one of the prerequisites for mandibular retrognathia. The ANB angle was 4.3 ± 1.9°. Tonsillar hypertrophy affected 6 patients, 21 had adenoid hypertrophy, and 3 had both of them. Movements of the masticatory muscles during sleep were recorded in 22.0% of patients. To improve the quality of diagnosis and treatment of OSA, a multidisciplinary approach is needed that will correct the processes of child growth and development.

Diagnostic Value of Neutrophil to Lymphocyte Ratio for Assessing Obstructive Sleep Apnea Risk in Surgical Patients

PurposeObstructive sleep apnea (OSA) is an important risk factor leading to perioperative complications in surgical patients. Neutrophil-to-lymphocyte ratio (NLR) is an important biomarker of increasing interest in recent years, and is used in the determination of systemic inflammatory response. DesignThe aim of this study was to evaluate the risk of OSA and the relationship between OSA risk and NLR in surgical patients. MethodsThe study was conducted in a tertiary care hospital between November 2021 and May 2022. The cross-sectional study included 604 patients who underwent surgery. OSA risk was evaluated with the STOP-Bang questionnaire in the preoperative evaluation in all patients. NLR was calculated as the ratio of neutrophil count to lymphocyte count. FindingsAccording to the STOP-Bang questionnaire, 62.3% of the patients had a high risk of OSA in the preoperative period. Patients who were male, elderly, obese, had hypertension, diabetes, chronic lung disease, and heart disease and polypharmacy were at greater risk of OSA. Patients at high risk of OSA had significantly higher NLR than patients at low risk of OSA. (2.65 vs 2.92, P.ß=.ß.024). NLR of 2.40 or higher predicted OSA risk with 58.8% sensitivity and 51.0% specificity (AUC.ß=.ß0.561) ConclusionsMost patients who were to undergo surgery had a high risk of OSA. NLR was higher in patients at high risk of OSA. Although the diagnostic efficacy is not high, NLR can be used to detect high OSA risk because it is a low-cost and easy to obtain biomarker.

Analysis of the relationship between sleep-related disorder and systemic immune-inflammation index in the US population

BackgroundThe association between sleep-related disorders and inflammation has been demonstrated in previous studies. The systemic immune-inflammation index (SII) is a novel inflammatory index based on leukocytes, but its relationship with sleep-related disorder is unclear. We aimed to investigate the relationship between sleep-related disorder and SII in a nationally representative nonhospitalized sample.MethodsData were obtained from the 2005–2008 National Health and Nutrition Examination Survey (NHANES). Exposure variables included self-reported sleep-related disorders, such as sleep duration, sleep problems, high risk of OSA, and daytime sleepiness. SII and other traditional markers of inflammation were considered as outcome variables, including platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR). Multiple linear regression models were employed to examine the correlation between sleep-related disorders and inflammatory markers. Subgroup interactions were analyzed using likelihood ratio tests, and nonlinear relationships were explored by fitting restricted cubic splines.ResultsA total of 8,505 participants were enrolled in this study. Overall, sleep-related disorders were found to have a stronger association with SII compared to the PLR and NLR. The results of multiple linear regression analysis revealed that participants who experienced sleep problems (β: 21.421; 95% CI 1.484, 41.358), had symptoms of OSA (β: 23.088; 95% CI 0.441, 45.735), and reported daytime sleepiness (β: 30.320; 95% CI 5.851, 54.789) exhibited a positive association with higher SII. For the analysis of other inflammatory markers, we only found that daytime sleepiness was associated with increased NLR levels (β: 0.081; 95% CI 0.002, 0.159).ConclusionSleep problems, symptoms of OSA, and daytime sleepiness were found to have a positive association with the SII in US adults. However, further prospective studies are necessary to establish whether there is a causal relationship between these factors.

Application and interpretation of machine learning models in predicting the risk of severe obstructive sleep apnea in adults

BackgroundObstructive sleep apnea (OSA) is a globally prevalent disease with a complex diagnostic method. Severe OSA is associated with multi-system dysfunction. We aimed to develop an interpretable machine learning (ML) model for predicting the risk of severe OSA and analyzing the risk factors based on clinical characteristics and questionnaires.MethodsThis was a retrospective study comprising 1656 subjects who presented and underwent polysomnography (PSG) between 2018 and 2021. A total of 23 variables were included, and after univariate analysis, 15 variables were selected for further preprocessing. Six types of classification models were used to evaluate the ability to predict severe OSA, namely logistic regression (LR), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), bootstrapped aggregating (Bagging), and multilayer perceptron (MLP). All models used the area under the receiver operating characteristic curve (AUC) was calculated as the performance metric. We also drew SHapley Additive exPlanations (SHAP) plots to interpret predictive results and to analyze the relative importance of risk factors. An online calculator was developed to estimate the risk of severe OSA in individuals.ResultsAmong the enrolled subjects, 61.47% (1018/1656) were diagnosed with severe OSA. Multivariate LR analysis showed that 10 of 23 variables were independent risk factors for severe OSA. The GBM model showed the best performance (AUC = 0.857, accuracy = 0.766, sensitivity = 0.798, specificity = 0.734). An online calculator was developed to estimate the risk of severe OSA based on the GBM model. Finally, waist circumference, neck circumference, the Epworth Sleepiness Scale, age, and the Berlin questionnaire were revealed by the SHAP plot as the top five critical variables contributing to the diagnosis of severe OSA. Additionally, two typical cases were analyzed to interpret the contribution of each variable to the outcome prediction in a single patient.ConclusionsWe established six risk prediction models for severe OSA using ML algorithms. Among them, the GBM model performed best. The model facilitates individualized assessment and further clinical strategies for patients with suspected severe OSA. This will help to identify patients with severe OSA as early as possible and ensure their timely treatment.Trial registrationRetrospectively registered.

SAT372 Obstructive Sleep Apnea (OSA) Risk Among Patients With Polycystic Ovary Syndrome (PCOS)

Abstract Disclosure: J.P. Christ: None. K. Shinkai: None. J. Corley: None. L. Pasch: None. M.I. Cedars: None. H. Huddleston: None. Background: Risk of OSA is increased up to seven-fold among patients with PCOS independent of body mass index (BMI). The cause of this increased risk is poorly understood. Likely a bi-directional relationship exists whereby OSA may worsen insulin resistance and hyperandrogenism which in turn may alter airway physiology. Improved understanding of the link between OSA risk and reproductive and metabolic features of PCOS could reveal new strategies to improve a variety of health outcomes for this population. Objective: To assess associations between OSA risk and reproductive and metabolic features among patients with PCOS. Methods: A cross-sectional analysis of patients that underwent a standardized evaluation for PCOS at a single tertiary center from 2017 to 2022 was completed. Patients were eligible for inclusion if they were aged 18-44, met modified Rotterdam criteria for PCOS and had completed a Berlin Questionnaire (BQ) for OSA risk assessment. The BQ contains 10 questions in 3 categories and a high-risk response was recorded if 2 out of 3 categories were positive. All patients underwent standardized anthropometric, ultrasound, endocrine, and metabolic phenotyping. PCOS features were compared between those with and without a high risk BQ. Results: Of the 572 patients screened, 309 patients with PCOS met inclusion criteria. Of these, 104 (33.7%) patients had a high risk BQ. Compared to those without a high risk BQ, those with high-risk BQ had significantly higher waist to hip ratio (WHR) (mean ± standard deviation, 0.9±0.1 vs 0.8±0.1), LDL (113±31.1 vs 103.3±26.5 mg/dL), triglycerides (132±75 vs 89±55 mg/dL), fasting insulin (22±21.2 vs 13.9±16.9 mIU/mL), 2-hour insulin (125±141.2 vs 68.4±108.9 mIU/mL), fasting glucose (100±39 vs 88±20 mg/dL), 2-hour glucose (125.7±56.4 vs 101.7±40 mg/dL), hemoglobin A1c (5.7±1.1 vs 5.2±0.6%), C-reactive protein (6.2±5.7 vs 2.8±3.8 mg/L), ALT (37±50 vs 27±27 U/L), free testosterone (6.5±3.9 vs 5.1±3.5 pg/mL), and lower HDL (49.7±12.4 vs 61.1±16.5 mg/dL) and sex hormone binding globulin (SHBG) (32.3±20.2 vs 53.7±37 nmol/L); p&amp;lt;0.05 for all comparisons. In multivariable regression, controlling for WHR and age, C-reactive protein (β=0.095, p=0.005), SHBG (β=-0.014, p=0.037), HDL (β=-0.025, p=0.032) and Hemoglobin A1c (β=0.421, p=0.073) were found to independently predict presence of high risk BQ. Conclusions: High risk for OSA is a frequent finding among patients with PCOS. Risk for sleep apnea appears to be associated with markers of dysglycemia, dyslipidemia, inflammation, and hyperandrogenism independent of adiposity. Future research is needed to determine if treatment of OSA has metabolic and/or reproductive benefits. Presentation Date: Saturday, June 17, 2023

Stop-bang questionnaire for screening obstructive sleep apnea syndrome among hypertensive patients in Kenya

IntroductionObstructive sleep apnea (OSA) is a type of breathing problem during sleep caused by the blockage of the upper airway, which can cause cessation of airflow. There is limited research on the prevalence of OSA in hypertensive patients in sub-Saharan Africa (SSA). The study aimed to describe the prevalence and clinical characteristics of OSA among hypertensive patients at a tertiary hospital in Nairobi, Kenya.MethodsThis cross-sectional study was conducted at the Aga Khan University Hospital in Nairobi, Kenya. Two hundred and fifty-one hypertensive patients were screened for OSA risk using the STOP-Bang questionnaire (SBQ). Patients with a SBQ score of ≥ 4 were categorized as high risk for OSA. Descriptive statistics were employed to describe both categorical and continuous variables and binary logistic regression to assess factors associated with the high risk of OSA.ResultsThe study reported that 78.5% of the participants had high-risk OSA. The median age and body mass index (BMI) were 57.0 years (IQR: 50.0–64.0) and 28.3 kg/m2, respectively. Age, neck circumference, gender, and BMI were significantly higher in the high-risk OSA group as compared to the low-risk group.ConclusionThe study highlights the importance of screening hypertensive patients for OSA using the SBQ in clinical settings, particularly in low-and middle-income countries (LMICs). Healthcare providers can use patient characteristics such as age, gender, neck circumference, and BMI to identify those at greater risk of developing OSA. Further research could focus on developing effective OSA prevention and treatment interventions in hypertensive patients.

Prevalence of Snoring in Pregnancy and Its Maternal-Fetal Outcomes at Vajira Hospital

Background: Snoring is an important symptom that is associated with obstructive sleep apnea and increases the risk of adverse pregnancy outcomes. In Thailand, the prevalence of snoring during pregnancy is uncertain. Determining the prevalence and characteristics may reduce the prevalence of snoring and improve pregnancy outcomes. Objective: The primary outcome was to determine the prevalence of snoring in Thai pregnant women in the third trimester, including pregnancy and chronic onset. The secondary outcome was to investigate the associations between pregnancy outcome and habitual snorer or those identified as high risk by the Thai Berlin Questionnaire. Materials and Methods: Three hundred eighty-two singleton pregnant women aged at least 18 years and at least 33 weeks of gestational age were recruited from the antenatal care clinic at Vajira Hospital, Navamindradhiraj University, between November 2021 and September 2022 and filled out the Thai Berlin Questionnaire. The 382 pregnant women were identified the presence of snoring or high risk of OSA in the previous month. Medical records, including demographic information and pregnancy outcomes, were collected, and analyzed. Results: The prevalence of snoring was 31.4% in the third trimester of pregnancy of which 27% were pregnancy onset snoring and 4.4% were chronic onset snoring. Habitual snoring was significantly different from non-snoring in regard to the requirement for positive-pressure ventilation in newborns (aOR 6.67, 95% CI 1.2 to 35.54). The high risk group had significantly more pregnancy induced hypertension than the low risk group (aOR 5.96, 95% CI 2.15 to 16.5), gestational hypertension (aOR 13.6, 95% CI 2.1 to 86.8), preeclampsia (aOR 4.07, 95% CI 1.09 to 15.2), severe preeclampsia (aOR 4.9, 95% CI 1.15 to 20.93), preterm birth (aOR 6.21, 95% CI 1.58 to 24.42), and low birth weight of newborn (aOR 6.09, 95% CI 2.5 to 14.87). Conclusion: The prevalence of snoring among Thai pregnant women was comparable to previous Western studies. Screening pregnant women at risk of the symptom may provide an early chance to lower the prevalence of snoring and adverse pregnancy outcomes. Keywords: Snoring; Snoring in pregnancy; Pregnancy outcomes

Obstructive sleep apnea in type 2 diabetes mellitus patients

Abstract Objective The study aims to identify the prevalence and risk factors for OSA in a group of Egyptian patients with type 2 diabetes. Methods 125 type 2 diabetes mellitus patients visited Mansoura University Hospital (Diabetes Mellitus Outpatient Clinic (OPC) at Specialized Medical Hospital and the Sleep Disordered Breathing Unit of the Chest Department), all of them exposed to history taking, the patients underwent anthropometric measurements (weight, height, body mass index, neck circumference), a test of their tonsillar size, Malampati score, Friedman OSA score, Epworth sleepiness scale (ESS), Berlin questionnaire, STOP BANG questionnaire, full-night polysomnography, fasting, and postprandial blood sugar. Results The study included 125 T2DM Egyptian patients with a mean age of 54.63 ± 9.47 years. Males accounted for 35.2 percent of patients, while females accounted for 64.8%. According to the study of co-morbidity, hypertension constituted 77 (61.1%), ischemic heart disease 28 (22.4%), other cardiac diseases 11 (8.8%), bronchial asthma 6 (4.8%), liver diseases 6 (4.8%), hypothyroidism 3 (2.4%), and renal diseases 3 (2.4%). A total of seven patients (5.6%) had no OSA symptoms, 87 had borderline symptoms, and 31 had positive symptoms. There were 51 (40.8%) normal patients, 12 (9.6%) borderline patients, and 62 (49.6%) sleepy patients on the Epworth scale. According to the Stop-Bang questionnaire, 121 (96.8%) patients answered positively. It was determined that 122 patients (97.6%) were at high risk based on the Berlin questionnaire. There were 17 patients (13.6%) with OSA on polysomnography, of which six were moderate (35.3%) and 11 were severe (64.7%). Among moderate and severe OSA patients, glycosylated hemoglobin levels differed significantly. Multivariate logistic regression analysis for independent predictors of OSA, chronic renal disease patients is the most common associated risk factor (OR = 14.3, CI = 1.2–67) then hypertension (OR = 5.6,CI=1.2–25.5) and heart failure (OR = 4.4). Conclusions OSA affects 13.6% patients with type 2 diabetes patients who are hypertensive are at higher risk of OSA, chronic renal failure is considered another risk factor Furthers studies are needed on a big scale of Egyptian diabetic patients to detect the prevalence of OSA

0455 Association of high-risk obstructive sleep apnea with endothelial dysfunction in a large population-based sample in MiHeart Study

Abstract Introduction Obstructive Sleep Apnea (OSA) is associated with endothelial dysfunction and cardiovascular disease (CVD). There are limited data evaluating the association with endothelial dysfunction measured by reactive hyperemia index (RHI) in an asymptomatic population free of CVD. We hypothesized that there would be a significant association between high risk of OSA and endothelial dysfunction in the Miami Heart (MiHeart) study, a population-based cohort of relatively young individuals free of known cardiovascular disease (CVD). Methods Cross-sectional data from 2097 participants (mean age: 53 years, 50% female) enrolled in the MiHeart study and underwent flow-mediated dilation using the EndoPat 2000 system was analyzed for this study. OSA was determined by Berlin questionnaire (high vs. low risk); logistic regression was utilized to examine the association between high OSA risk (reference low-risk OSA) and RHI (cut off &amp;lt; 1.67 vs. ≥1.67) in unadjusted models, and after accounting for age, sex, race/ethnicity (model 2), and BMI, diabetes, hypertension, high cholesterol, and smoking (model 3). Results 704 (34%) participants were categorized as high OSA risk, according to the Berlin questionnaire. These participants were more likely to be male, Hispanic and had a higher CVD risk factor burden when compared to low OSA risk. In addition, those with high OSA risk had higher prevalence of endothelial dysfunction (17.5% vs. 13.9%) than the low OSA risk (p &amp;lt; 0.05) group. High risk of OSA was associated with a higher risk of endothelial dysfunction in the unadjusted model (OR=1.32, 95% CI 1.03, 1.68). When adjusted for age, sex, and race/ethnicity, this association was slightly attenuated (OR 1.26, 95% CI 0.97, 1.62). Upon adjusting for CVD risk factors (model 3), the association between high-risk OSA and endothelial dysfunction was further attenuated and was not statistically significant (OR=1.18, 95% CI 0.87, 1.59). There was a strong, independent association between presence of diabetes and endothelial dysfunction (OR= 2.01, 95% CI 1.35, 2.94). Conclusion Younger individuals with high risk for OSA have elevated odds of endothelial dysfunction, and this relationship is likely mediated by demographics and cardiometabolic risk factors such as diabetes. Support (if any) The Miami Heart Study is funded by Baptist Health South Florida.

0496 Factors Associated with the Report of Trouble Sleeping to Healthcare Providers in Adults at High Risk for Obstructive Sleep Apnea

Abstract Introduction Obstructive sleep apnea (OSA) is often underdiagnosed and untreated partially because only one-third of adults with symptoms of OSA talk to a healthcare provider (HCP) about their sleep. It is unclear how sociodemographic and clinical factors may influence communication with HCPs regarding sleep difficulties in adults at risk for OSA. This analysis examined associations between sociodemographics, comorbidities, and OSA-related symptoms and reporting trouble sleeping to an HCP in adults at high risk for OSA. Methods The sample comprised adults at high risk for OSA (STOP-Bang of &amp;gt;=5 or STOP &amp;gt;=2 + body mass index (BMI) &amp;gt;35 kg/m2 or male sex) from the 2015-2018 National Health and Nutrition Examination Survey (n=2009). Participants were asked, “Have you ever told a doctor or other health professional that you have trouble sleeping?” OSA-related symptoms included daytime sleepiness, fatigue, insomnia, nocturia, snoring, and snorting/gasping/breathing cessation during sleep. Weighted binomial logistic regression models were employed. Results Participants were middle aged (mean age = 53.21 years + 0.5), obese (mean BMI = 34.76 + 0.25 kg/m2), and primarily male (71.9%) and white (65.2%). Half of the sample (50.8%) never reported trouble sleeping to an HCP. Female sex, former smoking, and diabetes, obstructive lung disease, daytime sleepiness, insomnia, nocturia, and/or snorting/gasping/breathing cessation during sleep were associated with higher odds of reporting trouble sleeping to an HCP. Snoring was not a significant predictor. Mexican American and non-Hispanic Asian race, having less than a high school education, and male sex were associated with lower odds of reporting trouble sleeping to an HCP. Conclusion Not reporting trouble sleeping to an HCP among adults at high risk for OSA is common. Differences in sex, race, education, smoking status, comorbidities, and OSA-related symptoms exist between whose who have and have not reported trouble sleeping to an HCP. Insomnia and snorting/gasping/breathing cessation during sleep were the strongest symptom-related factors associated with reporting trouble sleeping to an HCP. It is important for HCPs to ask all adults about sleep problems, recognizing that men, racial minorities, and persons with lower educational attainment may be less likely to initiate a conversation about trouble sleeping. Support (if any) None

0454 A Specific STOP-BANG Score Cutoff is Not Predictive of Severe Obstructive Sleep Apnea in Bariatric Patients

Abstract Introduction Obstructive sleep apnea (OSA) is a common sleep disorder with obesity being a significant risk factor. Undiagnosed OSA increases the risk of complications at the time of surgery and those with severe OSA at increased risk of post-operative MI, stroke, arrhythmias, and death as well as readmission and acuity of post-operative care. Because of this, our Bariatric program screens all patients pre-operatively with a STOP-BANG questionnaire. Those with severe OSA (AHI or REI &amp;gt; 29) require pre-treatment with PAP therapy until compliance is reached before the patient is eligible for surgery. This study examines those that screened at high risk for OSA with a STOP-BANG score &amp;gt; 2 to see if there was a specific cutoff that predicts those having severe OSA in order to better expedite sleep testing as recent supply chain issues have greatly impacted the timeliness of care for these patients. Methods During the months of January to June 2022, demographic, clinical and sleep data was collected on all new patients being evaluated by the Bariatric Sleep clinic for use in quality assessment. Bariatric patients with BMI &amp;lt; 50 and no significant cardiac or pulmonary disease were tested using HSAT, whereas those who met one or more of the above comorbidities underwent PSG. Results There were 143 bariatrics patients who screened as “high risk” for OSA with a STOP-BANG score &amp;gt; 2 during these 6 months and 112 (78%) of them completed sleep testing. There were 25 patients (22%) with severe OSA. The average STOP-BANG score for those with severe OSA was 4.3. Women averaged 4.0 (range 3-6), while men averaged higher at 4.8 (range 4-6) likely reflecting that male gender garners an extra point with the STOP-BANG. STOP-BANG scores increased with age: 20s x=3, 30s x=4.1, 40s x=4.4, 50s x=4.6, 60s x=6. Conclusion There was no specific cutoff for the STOP-BANG score that predicted severe OSA in our bariatric patients to help our program triage those most at surgical risk in order to place them in an expedited sleep testing and PAP therapy pathway. Overall, STOP-BANG scores were impacted by gender and age. Support (if any)

0504 STOP BANG FAN, A Novel Screening Tool of OSA in Sleep Clinic

Abstract Introduction We noticed that patients with OSA when admitted to hospital requested a fan even in winter. We explored the literature and did not find any reports about fan use in OSA. STOP-Bang questionnaire has been widely used in preoperative clinics [4-6], sleep clinics [7-8] to detect patients at high-risk of OSA. STOP Bang score 5 or more has high risk of OSA. We did a pilot study to explore if adding the use of FAN, especially in winter, would increase the sensitivity of STOP Bang questionnaire in the sleep clinic. Methods We screened 350 consecutive patients referred to our sleep clinic for suspected OSA in the period of March 2021 to April 2022, with STOP Bang FAN questionnaire. The questionnaire added if they use FAN during sleep in addition to the air condition and if they still use it in winter. Results 255 (73%) used FAN during sleep and 210 (60%) used the fan in winter. 247 patients had PSG, the others did not for variable reasons, including refusing COVID test before the study, insurance issues or no insurance. In the 247 patients who had the PSG the sensitivity of STOP Bang score 5 or more, STOP Bang score 5 or more + Sleeping with FAN and STOP Bang score 5 or more + sleeping with Fan in winter for OSA AHI 5 or more were 78%, 83% and 89%. The sensitivity of STOP Bang score 5 or more, STOP Bang score 5 or more + Sleeping with FAN and STOP Bang score 5 or more + sleeping with Fan in winter for moderate and severe OSA AHI 15 or more were 65%, 74% and 79%. The sensitivity of STOP Bang score 5 or more, STOP Bang score 5 or more + Sleeping with FAN and STOP Bang score 5 or more + sleeping with Fan in winter for severe OSA AHI 30 or more were 55%, 64% and 71%. Conclusion Adding the use of the FAN and especially FAN in winter during sleep to STOP Bang would increase the sensitivity of the questionnaire for suspected OSA in sleep clinic. Support (if any)

0034 Genetic Variants for Obstructive Sleep Apnea Identified after Modeling Interactions with Daytime Sleepiness

Abstract Introduction Obstructive sleep apnea (OSA) is a complex sleep disorder that presents with a range of symptoms, including excessive daytime sleepiness (EDS), postulated to represent a more severe subtype. Despite significant heritability and past GWASs, genetic mechanisms of the disorder remain unclear. Given that EDS often reflects chronic sleep insufficiency and a pro-inflammatory state, we reasoned it may interact with genetic variants to modify risk for OSA. We tested this hypothesis by investigating gene by sleepiness interaction analysis of OSA. Methods Whole-genome sequencing data of 11,619 individuals of diverse race and ethnic backgrounds from the NHLBI Trans-Omics for Precision Medicine program was used, with the outcome being Apnea-Hypopnea Index (AHI) and the exposure Epworth Sleepiness Scale (&amp;gt;10: EDS, &amp;lt;=10: non-EDS). GENESIS R package was used to perform 2-stage rank normalization, adjusting for age, sex, BMI, ancestral PCs, cohort, and genetic relatedness, and rescaling residuals to a unit variance, separately in each study/ancestry group. GEM software was used to perform gene-EDS interaction analyses, including 1 df tests of marginal SNP effect and interaction effect of SNPxEDS on AHI, respectively, and 2 df test of joint significance of both. Robust standard errors were used, with a significance threshold of p&amp;lt; 5x10-8. Results The 1 df test of marginal SNP effect identified one novel locus (rs35370454) that mapped to IFRD1, whose overexpression has been associated with sleep restriction, and hypomethylation with narcolepsy. The 1 df test of interaction effect identified two novel loci (rs13118183, rs281851) that mapped to genes MARCHF1 and CCDC3. The 2 df joint test did not reveal additional novel loci. CCDC3 has shown to repress inflammatory activity of TNF-alpha, a cytokine postulated to be involved in sleep regulation. MARCHF1 has shown to inhibit cellular insulin sensitivity as well as promote NF-KB, with degree of activation positively correlating with OSA severity. Conclusion By modeling the modification effect of EDS on OSA we identified 3 novel loci. This approach may be useful in understanding the genetic factors that vary across OSA subtypes. For next steps, we seek to conduct replication analysis using independent imputed samples. Support (if any) NHLBI, R01HL153814 (H.W.), R35HL135818 (S.R.).

0808 Comparison of Maxillary Transverse Dimension with Pediatric Obstructive Sleep Apnea Presence and Severity

Abstract Introduction Obstructive Sleep Apnea (OSA) in children and adolescents is commonly discussed amongst dental specialists. Physical attributes such as a high and narrow palate, dolichofacial appearance, and retrognathic mandible are reported to increase pediatric risk for OSA. Previous research states rapid maxillary expansion decreases AHI in children with OSA and may be an effective treatment option. Current literature does not report a consistent method of measuring a maxillary transverse deficiency nor does it report a numerical maxillary threshold deficiency that requires expansion in pediatric patients with OSA. Our aims are to compare two different orthodontic diagnostic methods for measuring the maxillary transverse dimension and to assess whether patients diagnosed with mild, moderate, or severe OSA have a numerical threshold for maxillary deficiency. Methods Participants were ages 7-17 years old (average 11.7 years) with no history of orthodontic treatment, craniofacial syndromes, craniosynostosis forms, or nasal abnormalities. Those with and without adenoids and tonsils were included. Participants presented to the Mayo Clinic Sleep Center for their polysomnogram. Their dentition was scanned, and a digital model was rendered. The maxillary transverse dimension was measured via two different methods: McNamara’s Analysis and Andrew’s Six Elements of Orofacial Harmony. Results There were 65 participants: 31 diagnosed with OSA (13 Mild, 4 Moderate, 5 Severe, and 9 Other) and 34 without (controls). Patients in the Other category were diagnosed based on clinical findings. No statistical difference was found between the maxillary transverse measurements of patients with versus without OSA or between the OSA categories. Patients with OSA were more likely to have permanent teeth (61.3% vs 32.4%, p=0.019), tonsils removed (54.8% vs 26.5%, p=0.020), and to have snored during the PSG (83.9% vs 55.9%, p=0.048). Conclusion Conclusions based on this pilot study should be interpreted carefully due to limited sample sizes. No statistically significant differences of the maxillary transverse dimension were found between those with and without OSA using either diagnostic method. No numerical maxillary deficiency threshold was found. Maxillary expansion should not be recommended based on OSA diagnosis alone. Referral to a dental specialist is recommended based on dental needs. Support (if any) Support was provided by Mayo Clinic CTSA grant UL1TR002377.

Network analysis of sleep bruxism in the EPISONO adult general population.

Sleep bruxism (SB) has been associated with biological and psychosocial factors. The assessment of SB includes self-report, clinical evaluation, and polysomnography. This study aimed to investigate the associations of self-reported SB with other sleep disorders and demographic, psychological, and lifestyle factors in the adult general population, and to investigate whether self-reported SB and polysomnographically (PSG) confirmed SB provide similar outcomes in terms of their associated factors. We recruited 915 adults from the general population in Sao Paulo, Brazil. All participants underwent a one-night PSG recording and answered questions about sex, age, BMI, insomnia, OSA risk, anxiety, depression, average caffeine consumption, smoking frequency, and alcohol consumption frequency. We investigated the link between SB and the other variables in univariate, multivariate, and network models, and we repeated each model once with self-reported SB and once with PSG-confirmed SB. Self-reported SB was only significantly associated with sex (p = 0.042), anxiety (p = 0.002), and depression (p = 0.03) in the univariate analysis, and was associated with insomnia in the univariate (p < 0.001) and multivariate (β = 1.054, 95%CI 1.018-1.092, p = 0.003) analyses. Network analysis showed that self-reported SB had a direct positive edge to insomnia, while PSG-confirmed SB was not significantly associated with any of the other variables. Thus, sleep bruxism was positively associated with insomnia only when self-reported, while PSG-confirmed SB was not associated with any of the included factors.