bluuebunny/crossref_metadata_2025_split huggingface dataset:
0566 Utilizing a Triage Tool Questionnaire to Identify PAP-Related Issues in Patients Newly-Initiated on Therapy for OSA
Authors: Saconi Bruno , Watach Alexa , Klimper Matthew , Arguelles Jessica , Hwang Dennis , Keenan Brendan , Plourde Andrew , Tran Jennifer , Sawyer Amy 
Published: April 2024

Abstract

Introduction
Developing strategies to enhance Positive Airway Pressure (PAP) adherence is crucial for improving outcomes in patients with obstructive sleep apnea (OSA). We introduce a novel Triage Tool (TT) questionnaire designed to identify specific usage challenges to facilitate targeted interventions.

Methods
Moderate-severe OSA (AHI≥15) patients newly-initiated on PAP therapy (AutoCPAP, ResMed) were enrolled (Kaiser Permanente, Fontana, CA). A digital platform (Somnoware, Inc.) emailed patients a link to the electronic TT questionnaire at 5, 10, and 30 days post-treatment initiation. The 31-item TT is comprised of 6 domains: Adverse Effects, Pressure, Mask/Device, Disturbed Sleep, Psycho-social, and Unintentional. A Likert scale (1 – 4) was used where ‘1 = not at all’ and ‘4 = a lot’ in response to “how much does this issue bother you?” We characterized the frequency of issues in the overall group and between adherent (Adh) and non-adherent (NA) subgroups (adherent: ≥70% usage, ≥4 hours over 30 days), using descriptive statistics.

Results
Of 150 enrolled patients (age 48±14; male 58%; AHI 41.1±21.1), 73 were Adh and 77 were NA. Overall TT response rate was 57% (63, 60, 50%, respectively, at day 5, 10, 30) and higher for Adh than NA (70.3% ± 5.0 vs 45.9% ± 6.7) Average number of patient endorsed issues (i.e., responses scored 3 or 4) was higher for NA than Adh and decreased over time – day 5: 4.1 ± 4.2 vs 3.4 ± 4.1; day 10: 3.9 ± 5.4 vs 2.8 ± 3.6; day 30: 2.5 ± 5.4 vs 2.2 ± 3.6. Commonly endorsed issues were: dry throat/mouth (21%), waking too early (20%), mask discomfort (19%), nasal congestion (18%), and difficulty initiating sleep (16%). NA patients additionally endorsed difficulty falling (23%) and staying (19%) asleep, waking with mask off (19%) and embarrassment (23%) or concern about appearance (23%). Adh patients more frequently concerned about traveling with PAP (20%).

Conclusion
The TT questionnaire identified “mask/device” discomfort and “adverse effects” as commonly endorsed problems among newly-treated OSA patients. NA patients also reported “disturbed sleep” and “psychosocial” barriers. Identifying specific treatment-related problems experienced by individuals may guide targeted interventions. Further psychometric evaluation is underway to refine the TT questionnaire.

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0567 Utilizing Machine Learning Based on Multi-Modal Data to Predict PAP Adherence in Patients with OSA
Authors: Hwang Dennis , Rusk Sam , Fernandez Chris , Nygate Yoav , Vanasse Tom , Wodnicki Jan , Sekhon Anupamjeet , Shi jiaxiao , Yan Rui 
Published: April 2024

Abstract

Introduction
Predicting future Positive Airway Pressure (PAP) adherence may support treatment decisions and timing of interventions in patients with obstructive sleep apnea (OSA). We developed machine learning (ML) prediction algorithms based on daily PAP metrics and diagnostic sleep study data to predict adherence at 3-months and 1-year.

Methods
ML models (eXtreme Gradient Boost) were trained on a dataset of 37,076 patients (Kaiser Permanente, Southern California) that comprised of daily PAP data (“usage” [minutes/night] and “leak”) and diagnostic sleep study data (Polysomnography and Home Sleep Apnea Tests). Models were trained to predict PAP adherence (≥70% days, ≥4 hours) at 3-months (i.e., 61-90 days) and 1-year (i.e., 330-360 days) after PAP initiation. Developed algorithms were based on: (a) Usage; (b) Leak; (c) Diagnostic sleep study data (i.e., AHI, oximetry metrics, sleep-wake metrics); (d) combination of those data types. For the models utilizing daily PAP data, different input days were applied (i.e., 7, 30, 90, etc.) to the training.

Results
Models based on daily usage alone demonstrated excellent predictive performance with relatively short input days (ROC-AUC 0.86 and 0.96 in predicting 3-month adherence utilizing 7 and 30 input days; 0.74, 0.82, 0.88 in predicting 1-year adherence utilizing 7, 30, and 90 input days). Models based on daily leak demonstrated more modest performance (0.69 and 0.83 predicting 3-month adherence with 7 and 30 input days; 0.60, 0.70, 0.80 predicting 1-year adherence with 7, 30, 90 input days.) Models based only on diagnostic sleep study data (without PAP data) demonstrated only small but similar 3-month and 1-year predictive accuracy (0.57 and 0.56, respectively). The addition of leak and sleep study data to usage did not significantly improve performance.

Conclusion
ML algorithms based on daily usage data early after therapy initiation can accurately predict future adherence to at least 1 year after therapy, enabling decision support after starting PAP. Algorithms using sleep study data could enable treatment decisions prior to prescribing PAP, but performance was modest. Whether the addition of electronic health record or direct ML processing of raw sleep study data could improve predictive accuracy requires further exploration.

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AASM Foundation 205-SR-19
0568 Promoting Shared Decision Making with a Novel Self-Monitoring Program for Veterans with Obstructive Sleep Apnea
Authors: Mak Selene , Ghadimi Sara , Der-Mcleod Erin , Moore Virginia , Naeem Saadia , Chohan Moeed , Zeidler Michelle , Ash Garrett , Fung Constance H 
Published: April 2024

Abstract

Introduction
Optimal shared decision making (SDM) occurs when patients are well-informed about their treatment options and, with clinician collaboration, can determine the best care for their well-being. Data pertaining to treatment success guide future decisions on care management, such as the decision to continue with current therapy versus transitioning to alternate therapies. Unfortunately, patients with obstructive sleep apnea (OSA) on non-positive airway pressure (non-PAP) treatments (e.g., dental devices) often lack night-to-night data supporting therapy effectiveness. We designed a self-monitoring program that provides night-to-night data for Veterans on non-PAP OSA treatment, with the goal of promoting SDM.

Methods
Patients with OSA prescribed non-PAP treatment from a VA sleep center were invited to participate in a quality improvement project for 1, 2, or 4 weeks, depending on project phase. A consumer-grade smartwatch was provided to each patient to collect pulse oximetry (SpO2) data while sleeping. Patients completed a weekly survey on their daytime sleepiness, mood, daily functioning, and use of non-PAP treatment. A report with their survey responses and SpO2 data was sent to patients weekly. A sleep clinician met with patients to discuss the report and OSA treatment. We assessed SDM with CollaboRATE-5 (3-items, score range 0-12, 0=no effort was made, 12=every effort was made). We conducted post-program semi-structured interviews with patients and analyzed interview data using content analysis to infer themes and/or meanings of SDM.

Results
Out of 11 veterans enrolled in the program (1 [9.1%] female, mean age 54, 7 [63.6%] non-white or multiracial), 9 (81.8%) have completed the program. Qualitative analysis revealed 3 themes related to SDM: 1) Information provision; 2) Patient preference elicitation; and 3) Patient preference integration. Four of 9 participants mentioned that they would reconsider PAP therapy at the conclusion of the program. A mean CollaboraRATE score of 7.1 (SD=3.0) indicates that respondents felt the program made some effort to address their concerns and integrated their preferences in OSA treatment.

Conclusion
Implementing a self-monitoring program as part of OSA treatment has promoted SDM with nearly half of patients expressing an interest to retry or consider PAP treatment.

Support (if any)
VA Office of Connected Care
0569 Breathing Easy Together: How Positive Airway Pressure Adherence Benefits Both Patients and Partners
Authors: Troxel Wendy , Baucom Brian , Shock Stevie , Baron Kelly 
Published: April 2024

Abstract

Introduction
Emerging research highlights the interdependence of sleep within couples and the impact of sleep and sleep disorders on couples’ relationship quality. The current study examines how adherence to positive airway pressure (PAP) as well as sleep duration and efficiency associates with both patient and partners’ relationship quality, among patients with obstructive sleep apnea (OSA) and their partners.

Methods
The sample included OSA patients initiating PAP treatment and their partners (N= 36 couples; mean age = 63.06, SD = 9.15). Mixed model analyses examined actor and partner effects of PAP adherence and actigraphy-assessed sleep duration and efficiency, on patient and partners’ self-reported relationship satisfaction and conflict.

Results
Greater patient PAP adherence (defined as &gt; 4 hours use per night on average over 3 months of recording) was associated with higher levels of relationship satisfaction (B = 4.26; SE = 1.40; p = 0.01) and lower levels of relationship conflict (B = -5.24; SE = 2.51; p = 0.04) for patients and partners. Higher patient sleep efficiency was associated with higher levels of patient and partner reported relationship satisfaction (B = 0.12; SE = .06; p = 0.04). Associations involving sleep duration were significantly different for patients and partners. For patients, greater own total sleep time was significantly associated with higher levels of patients’ relationship satisfaction (B = 0.92; SE = 0.35; p = 0.01) whereas greater partner total sleep time was significantly associated with lower levels of patients’ relationship satisfaction (B = -1.35; SE = 0.67; p = 0.045). After adjusting for patient adherence, the magnitude and direction of these associations were similar but the p-values increased slightly (p = 0.085 for sleep efficiency; p = 0.054, 0.14, 0.12, respectively for sleep duration).

Conclusion
Results highlight how sleep and sleep disorders are implicated in couples’ relationship quality. Among couples in which one member has sleep apnea, adherence to PAP treatment and better sleep efficiency is associated with higher relationship satisfaction. Recognizing the dyadic implications of sleep and sleep disorders, including the potential impact on relationship quality, may be a powerful motivator to encourage adherence in sleep disorders populations.

Support (if any)
R21AG067183 (Baron and Troxel)
0570 Impact of a Sleep Apnea Management Group Clinic on PAP Adherence and PROs: A Randomized Controlled Trial
Authors: Bhambra Raman , Khazaie Sepideh , Bena James , Morrison Shannon , Moul Douglas , Foldvary-Schaefer Nancy , Vanek Robon , Mehra Reena , Walia Harneet 
Published: April 2024

Abstract

Introduction
Positive airway pressure (PAP) is the mainstay treatment for obstructive sleep apnea (OSA), yet suboptimal adherence limits treatment effectiveness. We examined the impact of a sleep apnea management (SAM) clinic, an innovative, interactive group clinic which provides interpersonal support to patients and allows access to resources and education, on PAP adherence and patient reported outcomes (PROs) compared to usual care.

Methods
Participants with OSA and newly prescribed PAP therapy and sub-optimally adherent (CMS criteria) during the first two weeks, were randomized to SAM clinic(n=26) versus usual care(n=30) from April 2019 to November 2022 (NCT-03835702). The primary outcome was change in average daily PAP usage, whereas secondary outcomes were changes in Epworth Sleepiness Scale (ESS), Patient Health Questionnaire-9 (PHQ-9), and PROMIS scales from baseline to 1 and 3 months. Baseline adjusted mixed effect linear and logistic models estimated between and within groups differences.

Results
A total of 56 participants were enrolled with a mean age of 55 years, 57% female, 63% Caucasian, median AHI of 22.8 (9.3,39.6), and median baseline PAP usage of 172 minutes. After 3 months, the mean (95% CI) SAM clinic daily PAP use was 193(139, 247) minutes vs usual care at 148(110, 185) minutes with mean difference of 46(-8, 99) minutes per day (p=0.093). Within each group, a mean daily difference of 11(-36,57) minutes (p=0.65) in SAM clinic and -32(-75,12) (p=0.15) in the usual care was observed. No significant differences were observed in PROs between SAM and usual care. Within each group, ESS change was -0.7(-2.5,1.2) (p=0.48) in SAM clinic and -2.5(-4.2, -0.83) (p=.004) in usual care. Significant decrease was noted in PHQ-9 within both SAM clinic at-2.2(-3.9, -0.4) (p=0.019) and in usual care at -2.3(-4.0, -0.7) (p=0.006). Improvement in PROMIS sleep related impairment was noted within both groups: SAM clinic at -3.0(-6.2,0.1) (p=0.059) and usual care group at -3.5(-6.4, -0.60) (p=0.019). Similar changes in PAP adherence and PROS were seen at the 1-month follow-up.

Conclusion
SAM clinic may improve PAP adherence and some PROs better than usual care; however future studies are needed to confirm findings as this trial was underpowered due to premature termination resulting from the pandemic.

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0572 Impact of CPAP Therapy on HbA1c in Patients with Obstructive Sleep Apnea and Pre-Diabetes: A Preliminary Analysis
Authors: Maheshwari Narinder , Lenka Jyoti , Yang Zehan , Salmon Adrian , Wu Helen 
Published: April 2024

Abstract

Introduction
Patients with Obstructive Sleep Apnea (OSA) have higher levels of inflammatory cytokines, like tumor necrosis factor α (TNF-α) and interleukin-6 (IL-6). Similar higher systemic inflammatory cytokines have been linked to insulin resistance, thus emphasizing possible metabolic complications of OSA. Yet, the effect of positive airway pressure (PAP) therapy on glycemic control in those with concomitant OSA and pre-diabetes i unknown.

Methods
We performed a retrospective cohort study analyzing data from our tertiary care sleep center in adults with OSA and concomitant prediabetes who were initiated on CPAP therapy between April 2018 to April 2021. OSA was identified using ICD-9-CM (327.23) and ICD-10code (G47.39). Prediabetes was defined as hemoglobin A1c (HbA1c) between 5.7–6.4%. Demographic data were collected including age, gender, BMI, and number of comorbidities. The data was stratified among those on medications for pre-diabetes versus those that were not on any medications for it. Our outcome of interest was the change of mean A1c after CPAP initiation. Descriptive statistics were performed, while t-test was used to assess the changes of mean A1c values before and after CPAP treatment with a statistically significant level p&lt; 0.05

Results
A total of 71 patients were included in the current analysis. The average age was 61.53 years, and 65% were female, while 44% non-Hispanic whites, 28% non-Hispanic blacks, 21% Hispanics and 6% Asians. Among those with concomitant OSA-prediabetes on medications, the mean HbA1c before CPAP initiation was 6.03% which changed to 6.63% after CPAP initiation over a mean follow up duration of 485 days (p=0.04 from one-tail t-test). Among those with concomitant OSA-prediabetes not on medications, the mean A1c before CPAP initiation was 6% which marginally had changed to 6.42% after CPAP therapy over mean follow up duration of 447 days (p=0.05 from one-tail t-test), again remaining within pre-diabetes range.

Conclusion
Our results show that HbA1c remain stable within pre-diabetes range in patients with concomitant OSA and pre-diabetes using CPAP therapy. Some limitations could be retrospective nature of the study, small sample size, lack of CPAP compliance data. Larger prospective studies are suggested to further investigate the effect of CPAP on progression to diabetes among these patients.

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0574 An Intervention to Promote Positive Airway Pressure (PAP) Use: Qualitative Analysis of Barriers and Facilitators
Authors: Gomez Giselle , Carlson Gwendolyn , Alessi Cathy , Zeidler Michelle , Kelly Monica 
Published: April 2024

Abstract

Introduction
Health literacy of sleep apnea (SA) and access to behavioral strategies to promote positive airway pression (PAP) adherence remain challenges in clinical settings. Understanding what factors hinder or support PAP use is critical to increasing adherence and optimizing patient outcomes. We developed and implemented a brief PAP education and behavioral intervention program (1-hour 1:1 telehealth session prior to initiating PAP and 1-week follow-up call) in a VA sleep medicine clinic to increase SA knowledge and PAP use. To evaluate the program, we collected qualitative feedback from participants.

Methods
The PAP program was offered to Veterans newly diagnosed with SA. Among 43 veterans who participated in the program, 10 completed the Self-Efficacy Measure for Sleep Apnea (SEMSA) prior to program initiation and provided retrospective qualitative feedback within 6 months of initiating PAP. Three raters independently coded qualitative responses and reached consensus on domains and subcategories that emerged.

Results
Veterans (M=56 years) were categorized as “low” (n=5) or “high (n=5)” based on mean SEMSA perceived risk subscale score. Qualitative analysis revealed 3 domains (pre-program SA knowledge, pre-program PAP knowledge, and post-program SA/PAP knowledge) and categories of barriers or facilitators emerged. Four out of the 5 participants in both groups reported a perceived lack of knowledge of SA before the PAP program (unaware of SA-associated health risks). Despite this perception, the high group reported more pre-program basic knowledge about PAP vs. the low group, and knowing a family/friend with a neutral/positive PAP experience. Two participants in the low group expressed negative PAP-related expectations/cognitions vs. no participants in the high group. Participants in both groups reported having increased knowledge about SA/PAP post-PAP program; however, only participants in the low group recalled specific skills/strategies to facilitate PAP use.

Conclusion
Qualitative feedback revealed a general lack of knowledge about SA pre-PAP education program. A PAP education program may help those newly diagnosed with SA increase their health literacy and learn skills/strategies to facilitate PAP use, particularly for those who have a lower risk perception of SA. Future research should explore the impact of negative SA/PAP-related perceptions on PAP adherence.

Support (if any)
AASM Foundation#211-FP-19, VAGLAHS GRECC/CSHIIP, VA-HSR&D-CDA-20-227
0575 Parallel Comparison of Apnea Hypopnea Index with WatchPAT and CPAP Compliance Download
Authors: Akpa Bimaje , Liendo Alicia , Wang QI , iber Conrad , Pusalavidyasagar Snigdha 
Published: April 2024

Abstract

Introduction
Some OSA patients have sleep associated hypoxemia, defined as time spent with oxygen (O2) saturation ◻88% for &gt; 5 minutes (T88). Positive airway pressure (PAP) is the gold standard treatment for OSA. Apnea-Hypopnea index (AHI) estimation from PAP download (DL) is used by clinicians to determine the treatment efficacy. Overnight oximetry with PAP therapy is usually used to check for resolution of hypoxemia. During the COVID-19 pandemic, we used WPAT to check for resolution of hypoxemia in OSA patients who were prescribed PAP therapy. However, this practice change allowed us to compare the AHI measured simultaneously by WPAT and PAP DL

Methods
A retrospective study of 42 patients from August - November 2021 seen at University of Minnesota Sleep Clinic. All patients had a previous diagnosis of OSA and sleep associated hypoxemia confirmed by either Noxturnal [Nox MEDICAL] HSAT or PSG. All patients were being treated with either CPAP or bilevel PAP. Single night of HSAT was obtained with WPAT 100 (Itamar Medical) while simultaneously using PAP at their usual prescribed settings. PAP data included usage time, adherence, 30-day and same night AHI. WPAT data included total AHI, rapid eye movement related AHI, and T88

Results
Of the 42 patients, 60% were males with mean age 58.8 ± 14.6 years, body mass index (BMI) 38.9 ± 9.6 kg/m2 and Epworth sleepiness scale 10.7 ± 5.1. We identified an elevated AHI (≥ 5) with WPAT in more than half of the patients though hypoxemia resolved, ESS improved and OSA was optimally controlled with AHI&lt; 5 per PAP DL. There was a significant difference between the AHI on WPAT and same day PAP DL (AHI; 7.9 ± 12.2; p =0.0006). There was moderate correlation with BMI (r=0.51; p= 0.0017) and poor correlation with central AHI on WPAT (r = 0.29; p= 0.10)

Conclusion
There was discrepancy between AHIs with results from WPAT and PAP DL measured during the same night. Higher residual WPAT AHI could have significant implications with regards to validity of the algorithm used in these devices. This can potentially lower the threshold for performing titration PSGs to ensure optimal treatment of OSA

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0576 Patient Perception of Sleep Medicine During Hospitalization and Treatment of Diagnosed Sleep Apnea
Authors: Rojas Edward , Srinivasan Priyanka , Olgers Kassandra , Knollinger Scott , Stansbury Robert , Sharma Sunil 
Published: April 2024

Abstract

Introduction
Screening for sleep apnea among hospitalized patients has been shown to help practitioners identify sleep apnea and improve patients’ outcome. Patient perception of this intervention from the sleep medicine team has never been examined in a hospital setting. In this study, we examined the attitudes patients held about their diagnosis of sleep apnea and the team working with them.

Methods
Between June 2023 and November 2023, 152 consecutive patients, screened for sleep apnea, went through a sleep study. A carefully designed questionnaire was adapted from the validated Obstructive Sleep Apnea Knowledge and Attitudes (OSAKA) questionnaire. The survey was intended to understand patients’ beliefs on the importance of sleep apnea and their perception of the sleep medicine service. One question was designed to determine the patients’ confidence with using the CPAP therapy. The responses were then analyzed.

Results
Of the 152 patients interviewed, the mean age was 60 years (15) and 59% were female. The average BMI for these patients was 39.2 (20.5). 76% (n=115) mentioned they were aware of sleep apnea before the sleep medicine team’s assessment. On a 5-point scale, 87% of patients ranked at least “3” (important) for the importance of knowing whether they had sleep apnea. Of the subset of patients (n=26) who were prescribed CPAP therapy in the hospital, 63% indicated they at least “agreed” (3 on 5-point scale) with confidence on their ability to use a CPAP device at home.

Conclusion
Our analyses signify most hospitalized patients who underwent sleep apnea screening and evaluation perceived sleep apnea is an important condition and exhibit a constructive attitude towards the sleep medicine team and CPAP therapy. Moreover, a significant number were aware of the condition among their immediate family and community. With patient education and guidance provided by the sleep medicine team, the patients developed a constructive understanding of their diagnosis and how to manage OSA using CPAP therapy. Thus, this study suggests that hospitalized patient’s knowledge of OSA is high, and patients are receptive to pro-active work up.

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