bluuebunny/crossref_metadata_2025_split huggingface dataset:
0531 Excessive mask leak and its association with poor PAP compliance in women. A secondary analysis of the AWARE study
Authors: Lamboy-Hernández Ilean , Scott Paul , Patel Sanjay , Morris Jonna 
Published: May 2023

Abstract

Introduction
Studied have shown that continuous positive airway pressure(CPAP) adherence is lower in women. However, understanding of the specific challenges faced by woman when starting therapy remains poor. Specifically, is there any relationship between leak and women’s characteristics that could influence adherence?

Methods
The AWARE-study is a longitudinal pilot-study with the objective to identify in women modifiable barriers to initiating/adhering to treatment over 3-months. Adherence was considered when using CPAP for a minimum 4-hours 70% of the nights. But, is there any association between leak, mask type and other patient’s characteristics that could influence adherence in women? This is a secondary analysis looking at leak as a consequence of poor adherence in women within the AWARE-study. We gathered data directly from the PAP-data-base and evaluated adherence within the first 3-months after starting therapy and usage at-present-time. We investigated leakage (&gt;25 L/min) and gathered information about severity of OSA, age, BMI, and race. Our aims: to evaluate for leak as a cause of poor adherence and to identify characteristics that could potentiate leak in women.

Results
Data from 49 women from the AWARE-study between the ages of 28-85, with a recent diagnosis of OSA who started CPAP was analyzed. Adherence, leakage, age, OSA severity, and mask type was gathered. Chi-squared test of independence suggests a relationship between leakage and present adherence, Chi2(1)=11.34, p=0.001. Of those women experiencing high leakage, 83% were non-adherent to therapy. Logistic regression was run to compute an odds ratio with 95% CI. Those experiencing high leakage have about 92% times lower odds to still be compliant than those not experiencing high leakage [OR=0.08, 95% CI: 0.007, 0.478]. Overall, mask type relates to adherence, 72% of nasal mask wearers were still being adherent versus 38% when using facial masks. The prediction of adherence from leakage does not significantly differ across mask type. Age was found to be related to adherence; 57% of women under 50-years were not adherent to CPAP versus 26% in women over 50-years.

Conclusion
This information could guide us in suggesting strategies for better mask choosing and possibly to implement more specific strategies that can increase adherence in women.

Support (if any)
0533 Healthcare Utilization by Patients with Obstructive Sleep Apnea and Excessive Daytime Sleepiness After Airway Therapy in the UK
Authors: Abeynayake Iresha , O'Donohoe Peadar , Floam Samantha , Romero-Cruz Pamela , Andiappan Mano , McCormack Mark , Parks Gregory 
Published: May 2023

Abstract

Introduction
Obstructive Sleep Apnea (OSA) is a chronic condition characterized by repetitive episodes of upper airway collapse during sleep. Despite standard treatment with continuous positive airway pressure (CPAP), some patients continue to experience residual excessive daytime sleepiness (rEDS). Pharmacotherapy use for rEDS is low in Europe and some wake-promoting agents are no longer allowed as treatments by the European Medicines Agency. The objective of this study was to characterize the patient demographics, comorbidities, medications, and healthcare resource utilization (HCRU) in a population of OSA patients with and without rEDS after CPAP initiation.

Methods
The retrospective observational cohort study used the Clinical Practice Research Datalink (CPRD) AURUM, a primary care database, linked at the patient level to the Hospital Episode Statistics (HES) database, which covers secondary care for all of England. The population included 10,746 adult OSA patients with a first record of CPAP treatment during the eligibility period (Jan 1, 2009-Mar 21, 2018). rEDS patients were identified 6 months after initiating CPAP treatment.

Results
Among all eligible OSA patients in the AURUM database, 596 (5.6%) had rEDS; 80.5% of rEDS patients were identified using recorded diagnosis code of daytime fatigue, and 21.7% using ESS score ≥11 (13 patients had both measures). A greater percentage of patients had a history of psychiatric (21.5%; p&lt; 0.0001), gastrointestinal (7.7%; p&lt; 0.0001), and neurodegenerative (13.6%; p=0.003) disorders in the rEDS group, compared with the non-rEDS group, while the prevalence of obesity, cardiovascular, and sleep disorders did not significantly differ between groups. Across all patients, rates of prescription for stimulants or modafinil were low during the 12 months prior to CPAP initiation. Patients with rEDS had significantly higher HCRU compared to non-rEDS patients in the first and second years after CPAP initiation.

Conclusion
Despite low rates of rEDS identified in this study, the clinical needs of patients with rEDS are significant, as evidenced by the volume of HCRU, low use of pharmacotherapy, and high comorbidity rates, highlighting the need to improve patient care in rEDS.

Support (if any)
Axsome Therapeutics and Jazz Pharmaceuticals
0534 How objective sleep quality with Odds Ratio Product differs by diagnosis of COMISA, OSA, and insomnia
Authors: Tomson Heather , Bender Amy , Lambing Kari , Guadagni Veronica 
Published: May 2023

Abstract

Introduction
Recent research has highlighted differences in sleep quality for comorbid insomnia and obstructive sleep apnea (COMISA). We investigated how COMISA affects objective sleep quality measured with odds ratio product (ORP) compared to individuals without insomnia or moderate to severe OSA.

Methods
410 participants (age 46.4±12.3; 174 females) recorded their sleep with in-home PSG using the Cerebra Sleep System and completed questionnaires. Sleep quality was measured using ORP derived from micro-analyzing frontal EEG channels. On the questionnaires, participants reported whether they experienced insomnia symptoms at least three times a week. Participants were classified as having no diagnosis if their RDI on the home PSG was &lt; 15 and no insomnia symptoms. They were classified as insomnia only if they reported at least one insomnia symptom with an RDI &lt; 15. They were classified as OSA only if they had an RDI ≥15 and reported no insomnia symptoms. Finally, they were classified as COMISA if they had an RDI ≥15 and reported at least one insomnia symptom. All analyses controlled for age and were corrected for multiple comparisons.

Results
113(27.6%) patients were classified as having no diagnosis, 109(26.6%) as insomnia only, 83(20.2%) as OSA only, and 105(25.6%) as COMISA. There was a significant effect of diagnosis on ORPNREM (F3,405= 6.042, p&lt;.001) and ORPTRT (F3,405= 3.799, p= 0.010). Participants with no diagnosis had lower ORPNREM than patients with OSA only (p= 0.039) and patients with COMISA (p&lt;.001) and had lower ORPTRT than COMISA (p= 0.009). OSA severity based on the AHI was the only significant predictor of ORPNREM (p &lt;.001, β= 0.321). Both AHI (p &lt;.001, β=0.176) and number of insomnia symptoms (p=0.002, β=0.141) were significant predictors of ORPTRT.

Conclusion
Participants with no diagnosis had the lowest ORP indicative of better sleep quality than participants with evidence of sleep disorders. Having COMISA may have greater impacts on sleep quality than insomnia symptoms alone. OSA severity was the only predictor of poor sleep quality when looking at ORPNREM. Yet both OSA severity and insomnia symptoms were associated with higher ORPTRT indicating that individuals with COMISA may show alterations of sleep quality in different states throughout the night.

Support (if any)
0536 Impact of Positive Airway Pressure Therapy on Clinical Outcomes in Older Veterans with Comorbid COPD and OSA: An Update
Authors: Greig Danny , Rastogi Ruchi , Bansal Jaskiran , Mishra Poonam , Ahmed Abdullahi , Zhao Lili , Mcconnell Andrew , Kushida Clete , Axelrod Bradley , Shamim-Uzzaman Q Afifa , Chowdhuri Susmita 
Published: May 2023

Abstract

Introduction
Cognitive impairment in older Veterans is an independent predictor of subsequent mortality and disability. Pilot data indicate that patients with OSA-COPD Overlap Syndrome (OVS) may have reduced sleep quality, cognitive function and quality of life (QoL). However, there are no prior systematic studies evaluating treatment paradigms in patients with OVS. Our ongoing clinical trial is investigating whether positive airway pressure (PAP) therapy alleviates sleep disturbances, sleepiness, and improves cognitive function and QoL in older adults with OVS.

Methods
The design is a prospective parallel group randomized controlled trial in Veterans 60 years and older, with moderate-to-severe OSA with concomitant COPD (OVS). 225 eligible participants will be randomized to two treatment groups (PAP and conservative care) in 2:1 ratio for a duration of 6 months. Participants on the conservative care arm are required to follow good sleep habits and sleep hygiene, and on the PAP arm, in addition, are required to be adherent to PAP treatment (CPAP or Bilevel PAP, as required). Sleep questionnaires are administered to evaluate sleepiness, sleep quality, and general and disease specific QoL. Cognitive function is evaluated using Trail Making Test Part A and B, Paced Auditory Serial Addition Test, Stroop Task, Digit Coding, Hopkins Verbal Learning Test-R, Weschler Abbreviated Scale Intelligence II, Weschler Memory Scale IV, and Psychomotor Vigilance Test, respectively. All tests are administered at baseline visit, 3 months, and 6 months.

Results
In year-2 of the study, we have screened 7878 Veterans, enrolled 137 participants, randomized 34 participants (31 males, 3 females; age: 70.7±6.6 years, BMI: 29.6±6.7 kg/m2, AHI: 47±22 events/hr, spirometry FEV1: 60.8±11.7% predicted, arterial blood gas (n=22) pCO2:41.2 ±3.6 mmHg, ESS: 1.9 ±2.4); 15 have completed the study per the protocol. Analysis of data will be completed at the end of the RCT.

Conclusion
Our research seeks to systematically study the effects of treating a novel target (OVS) to maximize daytime function and QoL, while also providing a framework for early treatment of mild cognitive impairment in vulnerable older Veterans.

Support (if any)
VHA RR&D Merit Award # 1I01RX003124-01
0537 Incident Hypertension Prediction in Obstructive Sleep Apnea using Machine Learning
Authors: Milani Omid Halimi , Nguyen Tu , Parekh Ankit , Cetin Ahmet Enis , Prasad Bharati 
Published: May 2023

Abstract

Introduction
Obstructive sleep apnea (OSA) is associated with hypertension due to intermittent hypoxia and sleep fragmentation. Due to the complex pathogenesis of hypertension, it is difficult to predict incident hypertension associated with OSA. A Machine Learning (ML) model to predict incident hypertension identified up to five years after the diagnosis of OSA by polysomnography developed.

Methods
Polysomnography provides time-series data on multiple physiological signals. We used the sleep heart health study (SHHS) cohort, where 4,797 participants had OSA. After excluding participants with pre-existing hypertension at baseline, the sample size was 2,652. 1,814 participants with follow-up data at 5 years were included (911/1,814, 50% with incident hypertension). In addition to clinical data (i.e. age and race), features extracted from polysomnography (heart rate variability, HRV calculated based on the electrocardiography R-R interval), electroencephalography delta power, statistical information (i.e., mean and standard deviation of signals), and heart rate periodicity functions fed to support vector machine (SVM) ML model to train and validate. The polysomnography features were calculated over the 30-second epochs identified based on respiratory events and EEG arousal and respiratory events annotation, and their corresponding parts in other signals based on sampling frequency. Technical artifacts in oxygen saturation and ECG were reconstructed with the interpolation method and removed from the signal respectively. The SVM is a robust ML method trained in an iterative fashion to find the global optimum. In comparison to the Deep Neural Network (DNN) approaches, SVMs results are interpretable. Each polysomnography signal and its corresponding features were trained on a separate SVM, followed by a fusion of the SVM results. The final results were fused by voting of individual SVM results.

Results
The SVM ML model thus far has achieved a test accuracy (area under the curve, AUC) of 66.06%, sensitivity 63.21%, and specificity 68.9%.

Conclusion
This proof-of-concept study suggests that supervised ML models, such as the SVM, may be useful in predicting incident hypertension associated with OSA. Further research is required regarding optimal input features to boost the accuracy, followed by external validation of the model in additional OSA cohorts.

Support (if any)
Research support 1R56HL157182, NIH/NHLBI
0541 Obstructive Sleep Apnea Following Vagus Nerve Stimulator Implantation: A Meta-Analysis
Authors: Saleem Matthew , Santhumayor Brandon , Hasan Eusha , Kolesnik Michael , Bernbaum Melissa 
Published: May 2023

Abstract

Introduction
Vagus nerve stimulation (VNS) treatment for patients with intractable epilepsy has been shown to effectively lower seizure frequency and improve quality of life. However, due to stimulation of the vagus nerve, alterations in both central regulation of breathing and laryngeal muscle stimulation can precipitate obstructive sleep apnea (OSA). While there have been case reports describing OSA following VNS implantation, there has yet to be a detailed evaluation of this complication in a large cohort of VNS patients. The objective of this meta-analysis was to determine OSA rates in patients following VNS implantation.

Methods
English full-text articles were searched for on Pubmed, Scopus, and Embase databases. Articles had to follow patients before and after VNS implantation; report apnea-hypopnea index (AHI), respiratory disturbance index (RDI), or OSA rates following VNS implantation; be from a clinical trial, cohort, or case-control study. Two reviewers reviewed articles and a third settled disagreements. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies were used. Following Freeman-Tukey transformation, the generic inverse variance method with random effects model was used for meta-analysis.

Results
Ten studies, seven retrospective and three prospective, representing a cohort of 306 patients were included in this study. Pooled OSA rates following VNS implantation were 27.3%, 95% CI: 15.1 - 41.5%. Subgroup analysis found no difference in rates between studies of pediatric populations (22.1%, 95% CI: 8.2 - 40.5%) and adult populations (31.9%, 95% CI: 18.9 - 47.5%) following VNS implantation (P = 0.39). There was significant heterogeneity in pooled analysis (P &lt; 0.00001, I2 = 100%), but no inter-subgroup heterogeneity (I2 = 0%).

Conclusion
Obstructive sleep apnea is a common adverse effect following VNS treatment and patients should be monitored following implantation. There are no differences in OSA rates between pediatric and adult populations. Routine screening for OSA following VNS implantation may be a reasonable choice.

Support (if any)
No institutional or NIH funding was received for this project
0545 Optimizing Access to Oral Appliances for OSA: Decrease Cost and Increase Availability with 3D Printing
Authors: Russo Steven , Hardin Kimberly 
Published: May 2023

Abstract

Introduction
Mandibular advancement devices (MAD) for obstructive sleep apnea have traditionally been a prohibitive therapy for a large number of patients due to high out-of-pocket expense and access to dentistry. This study examined if an increasingly more accessible and user-friendly technology, 3D printing, may provide a cost-effective in-office workflow to increase access to MAD use.

Methods
Available pricing data was sourced via PubMed articles searching keywords “oral appliance”, “sleep apnea”, “mad” and “cost”. Additional price point data was compiled from publicly available information from the largest dental insurance provider in the United States, Delta Dental. Computer Aided Design (CAD) software Fusion360 was used to prototype a MAD and Stereolithography (SLA) printing using FormLab’s 3B+ printer was performed by a University-run 3D printing lab.

Results
Traditional cost per MAD ranges from 400USD – 2,450USD with a mean of 933USD (based on the only available 1997 pricing data). The total cost of the one-off MAD used in this study was 150USD (consumable cost of 2.66USD, labor cost of 147.34USD). This excluded the one-time 3D printer cost of 3,750USD. At 1 device printed per day over 1 year, total cost per printed device would be estimated at $22, which is 5% of the traditional cost of MAD. Total print time is estimated at 54 minutes, post processing time is estimated at 25 minutes, with a total MAD delivery to patient time of 1.3 hours.

Conclusion
Point-of-care 3D printed oral appliances are a feasible and inexpensive workflow to expand the use of MADs in the treatment of mild to moderate sleep apnea. Multiple barriers remain in integrating this workflow into patient care, including integration with dentistry.

Support (if any)
0548 Position-dependent obstructive sleep apnea and the cardiovascular risks
Authors: Chow Christine , Kang Hyojung , Logan Jeongok , Sohn Min-Woong , Bonner Heather , Lobo Jennifer , Kwon Younghoon 
Published: May 2023

Abstract

Introduction
Position dependent obstructive sleep apnea (PdOSA) is highly prevalent, but the implication of PdOSA in cardiovascular (CV) outcomes has not been studied. We hypothesized that PdOSA is associated with lower risk of future CV events than those without PdOSA.

Methods
We included patients who underwent diagnostic polysomnography (PSG) at a single academic center. The study included patients with ≥2 hours of total sleep time, 30 minutes in both supine and non-supine sleep, and OSA (apnea hypopnea index [AHI]≥5/hr). We defined PdOSA as either POSA (overall AHI≥5/hr accompanied by supine AHI (sAHI) at least twice as high as non-supine AHI (ns-AHI)), or ePOSA (POSA criteria + ns-AHI &lt; 5/hr (i.e., normalized)). Blood pressure (BP) was derived by averaging multiple measures of clinic BP within 1 year of PSG. All patients were followed up to 11 years to identify incident CV events (including acute coronary syndrome, stroke, and new heart failure). We examined the association of PdOSA with CV events with a logistic regression, adjusting for age, sex, race, BMI, systolic BP, and OSA severity (mild [AHI 5-15] vs. moderate to severe [≥15]).

Results
A total of 1750 patients (mean age: 54 years, female 60%) were included. POSA and ePOSA were present in 47% and 23% of the cohort. Patients with either POSA or ePOSA were less obese and had less severe OSA compared with those without POSA and ePOSA. Patients with ePOSA had lower BP (systolic BP 128.8 vs 131.2 mmHg, p=0.003) than those without ePOSA. Over a median 8.3 years of follow-up, a total of 340 CV events occurred. In multivariable analysis, both POSA and ePOSA were associated with lower odds of future CV events (OR 0.8, 95% CI [0.64-0.99], p=0.044; OR 0.69 [0.52-0.89], p=0.0061, respectively). Analysis stratified by OSA severity showed that the ePOSA association was present only in those with mild OSA (OR 0.67 [0.48-0.94], p=0.021).

Conclusion
Among patients with OSA, PdOSA is associated with more favorable CV outcomes than those without PdOSA. The benefit appears to be limited to those with mild OSA. Future studies should compare the CV risks between PdOSA patients and those without OSA.

Support (if any)
0552 Predictive Characteristics of Run-In Period Adherence in a Randomized Controlled Trial
Authors: Obeid Carla , Puri Reena , Aylor Joan , Wang Lu , Mehra Reena 
Published: May 2023

Abstract

Introduction
The run-in period has been used in randomized controlled trials in obstructive sleep apnea (OSA) to assess continuous positive airway pressure (CPAP) adherence. We hypothesize that there are differences in participant characteristics and PAP adherence between those excluded after the run-in period and those included in the final analytic sample of the Sleep Apnea Stress Study (SASS, NCT00607893), a trial designed to examine effect of PAP treatment on intermediate cardiovascular outcomes.

Methods
The SASS trial was designed to include a 2-week run-in period with a 1-month wash-out period. Patients with CPAP adherence &gt;4 hours of CPAP use for 70% of run-in period nights were randomized. Demographic factors were compared among groups using analysis of variance (ANOVA) or Kruskal-Wallis test in continuous variables, Pearson’s chi-square test or Fisher’s exact test was used for categorical variables. Bonferroni correction was applied for pairwise comparisons. SAS version 9.4 (The SAS Institute Cary, NC) was used to perform all analyses.

Results
Fifty-nine participants(30.8%) who did not meet PAP adherence threshold were excluded after run-in period and compared to Sham and CPAP treatment group(n=74 in each group). Results are presented as excluded vs sham treatment vs CPAP treatment. Participants excluded after the run-in period were more likely to be female than those who proceeded to randomization: 66% vs. 47% vs. 45%,p=0.031 and of Black race:73% vs. 42% vs. 47%, p=0.002. Participants excluded after the run-in period and those non-adherent to treatment in sham and CPAP were younger than adherent participants: excluded: 48.9±12.0, sham non-adherent 49.7±12.3, CPAP non-adherent 47.7 ± 13.2, sham adherent 58.3±9.3, CPAP non-adherent 54.3 ± 9.4, p=0.014. In the run-in period, participants who were excluded had the median of number of days using the device 12 (IQR 7-15), mean of average daily use 2.8±2.1 hours and median percent of days with 4+ hours use 18.2% (IQR 0-57.1%).

Conclusion
We identify that age and race are predictors of run-in period non-adherence to PAP therapy underscoring the need to develop pre-randomization PAP adherence optimization strategies specific to these subgroups to ensure representation in the trial.

Support (if any)
This work was supported by NIH HL079114-02.