bluuebunny/crossref_metadata_2025_split huggingface dataset:
0702 Real World Characteristics of Central Sleep Apnea: Experience at One Academic Medical Center
Authors: An Liudan , Genuardi Michael , Fudim Marat , Lund Lars , Mehra Reena , McKane Scott , Meyer Timothy , DeSensi Rebecca , Patel Sanjay 
Published: May 2022

Abstract

Introduction
Despite growing recognition of sleep disordered breathing, the prevalence and clinical characteristics of central sleep apnea (CSA) in real-world sleep referral populations remain poorly understood. We used historical data from the University of Pittsburgh Medical Center (UPMC) to assess the differences in patients with CSA compared to obstructive sleep apnea (OSA).

Methods
We retrospectively reviewed the medical records of 29,803 patients who underwent in-lab diagnostic polysomnography at six UPMC sleep labs between 2004 and 2018. Baseline clinical characteristics and polysomnography results including apnea hypopnea index (AHI), central apnea index (CAI), and obstructive apnea index (OAI) were extracted from the electronic health record. Among those with AHI≥5, patients were categorized as CSA if CAI≥5 and CAI&gt;OAI or OSA if OAI≥5 and OAI&gt;CAI.

Results
CSA and OSA were identified in 2% (583/29,803) and 34% (10,090/29,803) of patients, respectively, while 32% had AHI≥5 but didn’t meet either CSA or OSA criteria (CAI and OAI&lt;5 or CAI=OAI) and the remaining 32% had AHI&lt;5. Median AHI was 41 events/hr for CSA vs. 36 events/hr for OSA (p&lt;0.01). The median percentage of apneas being central was 78% for CSA vs. 0% for OSA (p&lt;0.01). Compared to patients with OSA, those with CSA were more likely to be male (78% vs. 66%), older (58 vs. 54 yrs), have lower body mass index (32 vs. 35 kg/m2), have heart failure (23% vs. 13%), atrial fibrillation (19% vs. 8%), stroke (5% vs. 2%), myocardial infarction (7% vs. 2%), diabetes (27% vs. 22%) and have received a prescription for methadone (1.5% vs. 0.3%) [all p&lt;0.01]. In multivariable logistic regression, all factors except stroke remained independently associated with CSA. The strongest predictors of CSA (compared to OSA) were methadone prescription (adjusted odds ratio=4.9, 95% CI [2.3-10.6]) and myocardial infarction (1.9, [1.3-2.8]). In contrast, the prevalence of CSA and OSA were similar across races.

Conclusion
CSA was identified in 2% of patients undergoing polysomnography in everyday clinical practice and independently associated with a variety of clinical characteristics. Recognition of characteristics associated with CSA can lead to more targeted screening and treatment in a broader population beyond just heart failure patients.

Support (If Any)
ZOLL Respicardia, Inc.
0710 Validation of the Predictive Utility of the Multivariable Apnea Index for Obstructive Sleep Apnea in Women
Authors: Orbell Staci , Chasens Eileen , Scott Paul , Luyster Faith , Morris Jonna 
Published: May 2022

Abstract

Introduction
The Multivariable Apnea Prediction (MAP) index is a commonly used screening tool for obstructive sleep apnea (OSA). Previous analyses have demonstrated higher sensitivity of the MAP in predicting OSA in men versus women and in post-menopausal versus pre-menopausal women with type 2 diabetes (T2DM) and an apnea-hypopnea index (AHI) ≥10. The purpose of this secondary analysis was to validate previous findings by comparing women with and without T2DM across all categories of OSA severity including mild (AHI ≥5).

Methods
The sample (N=386) was comprised of participants from the Diabetes Sleep Treatment Trial who were recruited because of risk for OSA with T2DM (n=279), and the EMPOWER study which examined triggers for lapses or relapse after intentional weight loss in overweight but otherwise healthy participants (n=115). AHI was assessed by in-home sleep study, ApneaLink Plus®. Descriptive statistics and binomial logistic regression and receiver operating characteristic analyses were conducted to evaluate classification of OSA diagnosis, defined as AHI ≥5 or ≥10, by MAP between sexes and by menopause status.

Results
Participants were middle aged (mean 54.09 years + 10.63), obese (mean BMI of 34.79 + 6.52 kg/m2), primarily female (67%), and white (64%). Compared to men, women were younger (52.99 years + 10.15 vs. 56.26 years + 11.25, p=0.004) and had a lower AHI (9.10 + 18.94 vs. 17.25 + 18.94, p&lt;0.001). No significant differences, except for age, were noted between pre- and post-menopausal women. Sensitivity of MAP on OSA diagnosis was higher for men than women (AHI ≥5: 94.7% vs. 76%; AHI ≥10: 84.2% vs 29.6%). Sensitivity of MAP on OSA diagnosis was lower for pre-menopausal than post-menopausal women using AHI ≥5 (74.0% vs. 98.8%) and AHI ≥10 (19.0% vs. 32.1%).

Conclusion
This validation study corroborates previous findings that the MAP index was better at identifying OSA in men than women, and in post- versus pre-menopausal women using AHI values across all categories of OSA severity. Improved screening methods are needed to detect women at high risk for OSA.

Support (If Any)
This study was funded by the National Institutes of Health (R01-DK090628, R01-HL107370).
0722 Evaluation of Healthcare Insurance Claims Record based Artificial Intelligence Screening Tools for Undiagnosed Sleep Apnea
Authors: Rusk Sam , Turkington Fred , Fernandez Chris , Nygate Yoav , Glattard Nick , Abrahamian Melania , Vanasse Tom , Richardson Dana , Bartholow Tim , Watson Nathaniel 
Published: May 2022

Abstract

Introduction
Healthcare insurance claims data contain an unrecognized wealth of structured data that can be leveraged to investigate epidemiologic and economic relationships in health and disease. We studied the feasibility for machine learning algorithms to improve upon screening for obstructive and central sleep apnea (SA) at the population health level using existing health insurance claims data.

Methods
A logistic regression model was trained to predict the presence or absence of SA from an aggregated healthcare insurance claims dataset. The dataset was composed of medical and pharmacy claims between the years 2016 and 2020 from the Wisconsin All-Payor claims database which included coverage of &gt;4,000,000 patients, &gt;10,000 ICD codes, and &gt;$50 billion in medical spending. A total of 1,870,000 patients and 39,712 unique federal drug identification codes were included within 91.5 million pharmacy claims in the dataset. Input features were constructed by counting the total number of claims for each unique drug in each subject resulting in a patient-level feature vector of 39,712 drug frequencies. The positive SA population was defined by individuals who had both at least one medical claim for sleep apnea diagnosis (ICD codes G4733/G4731) and an appropriate sleep test (CPT codes 9580*/9581*). The logistic regression model was evaluated using randomized 10-fold cross-validation and performance reported using ROC-AUC statistics and top-10 feature importance analysis.

Results
The logistic regression model detecting SA based solely on observed medication frequencies produced a ROC-AUC of 0.77. In a feature importance analysis, three of the Top-10 most discriminative features were medications for the treatment of diabetes, hypertension, and hyperlipidemia. We hypothesize this drug-frequency based model functions by exploiting the strong correlation of SA with specific clusters of known co-morbid conditions and corresponding medication regimens.

Conclusion
We demonstrate health insurance claims records contain predictive information that can aid in more systematic screening of undiagnosed conditions like SA. Furthermore, in a statistical analysis of feature importance, we observed medications indicative of comorbidities with known association to SA. These findings are useful to clinicians and payers in identifying undiagnosed SA populations, including those responsible for value-based payment models.

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0728 Physical and Mental Health among Blacks with OSA and Insomnia: a Stakeholder-engaged community study
Authors: Rogers April , Seixas Azizi , Jin Peng , Casimir Georges , Nunes Joao , Jean-Louis Girardin 
Published: May 2022

Abstract

Introduction
Health consequences of co-occurring obstructive sleep apnea (OSA) and insomnia have been well documented. However, little is known about the mental and physical consequences of co-occurring OSA and insomnia among Blacks. We aimed to investigate the rate of OSA risk and insomnia symptoms and potential associations with physical and mental health in a community sample of Blacks.

Methods
Data were collected from an NIH-funded study ‘Peer-Enhanced Education to Reduce Sleep Ethnic Disparities, designed to navigate blacks at risk of OSA to receive timely diagnosis and treatment using peer-delivered linguistically and culturally tailored sleep health education. Blacks (n=878) were screened for OSA using the Apnea Risk Evaluation System Questionnaire; a score ≥6 denoted high OSA risk. The Sleep Disorders Questionnaire was used to assess insomnia based on three common insomnia symptoms: trouble falling asleep, difficulty staying asleep, and early morning awakening. Physical Health Composite Score (SF-12PCS) and Mental Health Composite Scores (SF-12MCS) were generated based on how the person answered the SF-12 questions. Scores range from 0 to 100, where 0 indicates the lowest level of health and 100, the highest. Logistic regression models were used to assess associations of physical and mental health among Blacks at risk for OSA, reporting insomnia symptoms, and co-occurring OSA risk and insomnia symptoms. All models adjusted for differences in age, sex, and BMI.#8232;

Results
The prevalence of OSA risk, insomnia symptoms, and co-occurring OSA risk and insomnia symptoms was 47.9%, 73.3%, and 40.2%, respectively. Logistic regression analyses showed lower physical score was positively associated with the odds of reporting insomnia symptoms (OR=1.03, p=0.007) and co-occurring OSA risk and insomnia symptoms (OR=1.02, p=0.001). Lower mental score was positively associated with the odds of OSA risk (OR=1.04, p=0.001), insomnia symptoms (OR=1.04, p=0.001), and co-occurring OSA risk and insomnia symptoms (OR=1.04, p=0.001). Individuals with OSA were less likely to report higher physical scores compared with those with co-occurring OSA risk and insomnia symptoms.

Conclusion
Results demonstrate that blacks with insomnia symptoms are more likely to endorse worse physical and mental health. Future research should investigate further the mechanism underlying co-occurring OSA and insomnia in this population using objective measurements.

Support (If Any)
Support: NIH R01MD007716
0742 Characteristics of the Low ArTH phenotype in patients with OSA
Authors: Aiyer Ishan , Taweesedt Pahnwat , Gill Yash , Choudhury Saiara , Sharma Munish , Surani Salim 
Published: May 2022

Abstract

Introduction
Obstructive sleep apnea (OSA) is a heterogenous disease with both anatomic and nonanatomic factors contributing to the pathophysiology. Recently low arousal threshold (ArTH) has been described in some patients with sleep apnea and there is early evidence emerging that it could be a clinical phenotype. The aim of this study was to characterize this phenotype in a large cohort of patients with sleep apnea confirmed by overnight polysomnography

Methods
The setting was a community sleep center. We performed a retrospective review of patient charts. We included patients who underwent full-night diagnostic PSG. OSA was defined as an apnea hypopnea index (AHI) of &gt; 5. Epworth score, body mass index (BMI), neck circumference, and upper airway size using Modified Friedman (MF) were recorded. Low ArTH was calculated using AHI, fraction of hypopneas and O2 nadir.Abnormal airway narrowing was defined by MF &gt;2. Large neck was defined by neck circumference ≥ 17 inches in males or ≥ 16 in females. Obesity was defined by BMI&gt;30 kg/m2.

Results
652 patients were included - 421(65%) were male, and 230 (35%) female. 299 (46%) of patients had a low ArTH phenotype. Mean age was similar in both groups 54 +/- 14 vs 55 +/- 13 years. Male % was less pronounced in the low ArTH group (57% of patients with low ArTH male vs 71% of without low ArTH; p&lt;0.05). Patients with a low ArTH had lower percentage of abnormal airway narrowing (53.5 vs 62.6%, p&lt;0.001), large neck circumference ( 64.6 vs 78.8%, p&lt;0.001) and obesity (65.6 vs 77.9%, p&lt;0.001). Average BMI was lower in the low ArTH group (34.8 +/- 8 vs 36.9 +/- 8; p &lt; 0.005), and neck circumference was also lower in low ArTH group (NC 16.5 +/- 1.8 vs 17.4 +/- 1.8 respectively). Epworth sleepiness scale was lower in low ArTh group (10 +/- 8 vs 11 +/- 9; p 0.007)

Conclusion
We describe the phenotypic characteristics of low ArTH phenotype in a large cohort of patients with OSA. Patients with low ArTH have lower BMI, lower neck circumference, and lower Modified Friedman. Further research studies should focus on whether there are differences in therapeutic responses to this phenotype, and what clinical characteristics might help clinicians more effectively detect this phenotype.

Support (If Any)
NA
0744 A Comparison of Visual and Physiologic Assessments of Upper Airway Collapse during Drug-Induced Sleep Endoscopy (DISE)
Authors: Seay Everett , Dedhia Raj , Thuler Eric , Jafari Niusha , Keenan Brendan , Troske Kendra , Schwartz Alan 
Published: May 2022

Abstract

Introduction
The VOTE score, critical closing pressure (Pcrit), and therapeutic CPAP levels are assessments that quantify upper airway collapse by either subjective visual scoring or objective pressure-flow analysis. We hypothesized that there would be an association between collapse severity and physiologic metrics (VOTE versus Pcrit and PAP levels, respectively) acquired during drug-induced sleep endoscopy (DISE).

Methods
This prospective cohort study evaluated 100 consecutive patients with obstructive sleep apnea (OSA) who underwent DISE with application of nasal positive airway pressure between June 3rd, 2020 and June 11th, 2021. Patients were assigned a VOTE score of 0, 1, or 2 indicating no collapse, partial collapse, or complete collapse at the velum, oropharynx, tongue base, and epiglottis, respectively. We assessed two metrics of pharyngeal collapsibility with progressive increases in nasal pressure: (1) the pressure at which inspiratory airflow commences (critical pressure, Pcrit), and (2) the pressure at which inspiratory flow limitation is abolished (pharyngeal opening pressure, PhOP). Our analysis examined the association between the composite VOTE score [0-8 units] and collapsibility metrics.

Results
Ninety-one patients met inclusion criteria for VOTE scoring; of these, 87 were included for PhOP analysis and 79 for Pcrit analysis. The cohort was 76% male, mean (SD) age was 54.7 (14.1) years, body-mass index was 29.7 (4.9), and AHI was 30.3 (20.9). Composite VOTE score was positively associated with Pcrit (β = 0.88 ± 0.38 cm H2O per unit, standardized estimate = 0.26, p=0.023). We found no significant association between the composite VOTE score and PhOP (β = 0.57 ± 0.40 cm H2O per unit, standardized estimate = 0.15, p=0.162).

Conclusion
Our findings suggest that visual and physiological assessments of upper airway collapsibility provide both overlapping and complementary information in characterizing upper airway mechanics. Measures of pharyngeal collapsibility during DISE can be used to model the ultimate impact of therapeutic maneuvers on OSA. Future studies investigating the utility of each assessment both in isolation and in combination for predicting OSA therapy outcomes are indicated.

Support (If Any)
National Institutes of Health: 1R01HL144859
0762 Baseline characteristics: Solriamfetol’s effect on cognitive Health in Apnea participants during a Randomized Placebo-controlled study (SHARP)
Authors: Van Dongen Hans , Dronamraju Nalina , Macfadden Wayne , Leary Eileen 
Published: May 2022

Abstract

Introduction
Patients with excessive daytime sleepiness (EDS) associated with obstructive sleep apnea (OSA) may experience cognitive impairment. Solriamfetol (Sunosi®) is a dopamine/norepinephrine reuptake inhibitor approved in the US and EU to treat EDS associated with OSA. The objective of this study is to assess whether solriamfetol reduces cognitive impairment in patients with EDS associated with OSA.

Methods
This phase 4, randomized, double-blind, placebo-controlled, crossover trial (NCT04789174) is enrolling adults with OSA and associated EDS (Epworth Sleepiness Scale score &gt;10) and impaired cognitive function defined by an age-adjusted scaled score ≤8 on the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV) Coding subtest and a score ≥9 on the British Columbia–Cognitive Complaints Inventory (BC-CCI). Participants are randomized (1:1) to 2 weeks of placebo or solriamfetol (75 mg/day for 3 days, then 150 mg/day) during treatment period 1. After a 1-week washout, participants crossover to receive 2 weeks of the opposite treatment during treatment period 2. Assessments at baseline and after each treatment period include Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Coding administered 2, 4, 6, and 8 hours post-dose and the BC-CCI. The primary endpoint is change from baseline after each treatment period in the average of 2- and 4-hour post-dose RBANS Coding scores. A secondary endpoint is change from baseline after each treatment period in BC-CCI score. Target enrollment range is 116‒164 participants, pending interim analysis. Enrollment is ongoing; baseline characteristics to date are reported.

Results
As of October 20th, 2021, 33 participants have been randomized across 20 study sites in North America and Europe. In the intent-to-treat population to date (n=33), mean±SD age is 53.0±10.4, mean±SD BMI is 31.6±4.5, 64% are male, 70% are White (Black or African American, 24%; Asian, 6%), and most (91%) are not Hispanic or Latino. The mean±SD WAIS-IV Coding subtest age-correct scaled score is 6.7±1.3 at baseline, which is below previously observed scores in healthy individuals.

Conclusion
This ongoing study is the first to examine solriamfetol’s impact on cognitive impairment in participants with OSA. Participants enrolled to date reflect the typical demographics of patients with OSA and demonstrate substantial cognitive impairment.

Support (If Any)
Jazz Pharmaceuticals
0770 The effect, compliance, and side effect of acetazolamide in obstructive sleep apnea patients with high loop gain: a retrospective study
Authors: Ni Yuenan , Thomas Robert 
Published: May 2022

Abstract

Introduction
Acetazolamide (AZT) has beneficial effects on central, high altitude sleep apnea, or residual apnea on CPAP, high loop gain obstructive sleep apnea (HLGSA is general). Data on intermediate and long-term real world effectiveness of AZT is lacking.

Methods
Patients with HLGSA (mostly HLG OSA) and using AZT were included. The auto-machine estimated (aREIFLOW) and manually scored respiratory events(mREIFLOW), compliance to PAP, and excessive sleepiness scale were compared prior to, and after 3 months of AZT.

Results
The total study sample size of Diamox users was 325 patients; 43 stopped AZT in one month. Automated and/or manual efficacy parameters were available in 109 for before-after comparison, but not available in the rest of them due lack of waveforms (manufacturer limitation) or not using PAP before AZT (i.e., started simultaneously). AZT reduced aREIFLOW (2.60 [1.70-5.35] vs. 5.10[2.90-10.25], p&lt;0.001). and the percentage of patients whose aREI-FLOW &gt;5 times/hour (50.5% vs. 27.5%, p&lt;0.001). AZT did not influence mean daily usage of PAP (372.53 [295.26-444.22] vs. 368.50 [273.00-438.87] minutes, p=0.275) or the percentage of the day using the machine &gt;4 hours (87.50[75.00-100.00] vs. 87.50 [62.50-100.00], p=0. 999). In the 75 patients with manually scored waveform data, AZT reduced the mREIFLOW (21.11[15.07-28.14] vs. 28.55[21.92-35.45], p&lt;0.001), and the percentage of patients whose mREIFLOW &gt;20 times/hour (78.7% % vs. 52.0%, p&lt;0.001 ). AZT decreased the Epworth sleepiness scale (5[4-8] vs. 6.5[4-12], p=0.009). Among 282 patients who used AZT long term, 60 reported side effects. The most common side effect was paresthesia (7.09%). .

Conclusion
Chronic use of AZT can reduce the REIFLOW in HLG sleep apnea (HLGSA, predominantly obstructive) treated by PAP. Adherence to AZT was good, and the most common side effect even at low doses was distal paresthesia.

Support (If Any)
This study was supported by American Academy of Sleep Medicine Foundation, category-I award to RJT
0771 Artificial Intelligence Based Mask Fit Algorithm Application in the Pittsburgh Veteran Population
Authors: Chan Megan , Soreca Isabella , Ali Mazen El , Chakravorty Sangeeta , Gulla Aaron , Shroyer Brian , Atwood Charles 
Published: May 2022

Abstract

Introduction
Positive airway pressure (PAP) therapy has been used for obstructive sleep apnea (OSA) since 1980 and remains the treatment of choice for moderate to severe OSA. Proper mask fitting for patient comfort is essential to continued success on PAP therapy, as early adherence rates are strong predictors of future use. Mask selection continues to be challenging given the significant heterogeneity in craniofacial phenotypes and the rapidly growing mask options. Artificial intelligence software has combined survey data and digital photography to algorithmically predict PAP masks for best fit. This study aimed to describe mask failure rates in the Pittsburgh Veteran population with OSA following mask selection utilizing this specialized software.

Methods
Retrospective chart review was performed on 124 patients who underwent mask fitting with AI software May through November 2021. The primary outcome was to determine the rate of mask success within 1-3 months of fitting as defined by absence of mask switching. Mask switch was identified when patients underwent re-evaluation for new mask selection either by the AI software or had evidence of new mask selection from supply orders.

Results
Of the 124 patients who underwent evaluation with AI mask fit software, 96% were male with an average AHI 35/hr, BMI 34 and average age of 58 years. Of the 65 patients who were new to PAP therapy, 14 patients required refitting, yielding an initial mask acceptance rate of 78%. Of the 59 patients established on PAP, 8 required subsequent mask switches, yielding a refit mask acceptance rate of 86%. Overall mask acceptance rate after first exposure to fitting software across both groups was 82%.

Conclusion
AI software appears to result in successful mask fitting in a high proportion of VA patients. Higher mask acceptance rate was noted in the refit group, suggesting a particular use-case for this software. Most importantly, this software allows for remote mask fitting. This is ideal given recent telehealth growth and can save time and visits, leading to expedited therapy and increased access.

Support (If Any)