bluuebunny/crossref_metadata_2025_split huggingface dataset:
0580 Habitual Sleep Pattern, Anxiety and Depression are Predictive of Excessive Daytime Sleepiness in a Large-Scale Clinical Samples of Obstructive Sleep Apnea
Authors: Chang S , Huang W , Liu Y , Lee P 
Published: May 2020

Abstract

Introduction
Excessive daytime sleepiness (EDS) is a common symptom that patients with obstructive sleep apnea (OSA) seek medical attention for. Prevalence ranged from 20% to 60%. Previous studies reported factors associated with EDS included age, body mass index (BMI), depression, and OSA severity. In most studies, the sample size was small, participants having specific co-morbidities, and the definitions of EDS was heterogeneous. Moreover, the association between anxiety, depression, habitual sleep pattern, and EDS has not been widely studied. Therefore, the present study aims to investigate the prevalence of EDS and associated factors, especially anxiety, depression, and habitual sleep pattern, in a large-scale clinical sample.

Methods
Data was prospectively collected from 8,081 adult patients who underwent initial overnight polysomnography (PSG) for the first time were referred from 2009 to 2016. Patients with total recording time less than 240 minutes and missing data were excluded. Data collected include demographics, anthropometrics, co-morbidities, and self-reported habitual sleep patterns. Subjective sleepiness was assessed by the Epworth Sleepiness Scale (ESS) with EDS defined as ESS ≥10. Anxiety and depression were assessed by the Hospital Anxiety and Depression Scale (HADS). The stepwise forward Logistic regression was used to identified predictors for EDS.

Results
In 5,780 (82.6%) patients with OSA (apnea-hypopnea index, AHI≥5/h), mean age was 63.9±0.2 yr, BMI was 27.7±0.1, and ESS was 10.4±0.1 and 80.5% were male. Prevalence of EDS in all OSA patients was 55.1% where the patients with severe OSA had higher prevalence (59.8%) than that in mild (49.5%) and moderate OSA (51.8%). Anxiety (OR: 2.036, 95% CI:1.153-1.502), depression (OR: 1.159, 95% CI:1.01-1.33), and short sleep (&lt;6hr/night) (OR:1.316, 95% CI:1.32,1.70) were top three risk factors for EDS. Other risk factors for EDS included AHI, arousal index, % total sleep time with SpO2&lt;90%, %REM, smoking while hypnotic use and long sleep (≥ 8hr/night) were associated with lower risk.

Conclusion
Anxiety, depression, short sleep are predictive and OSA severity are predictive of EDS while long sleep was associated with lower risk.

Support
National Taiwan University (NTU-EPR-104R8951-1; 105R8951-1; 106R880301), Center of electronics technology integration (NTU-107L900502, 108L900502) by the Ministry of Education in Taiwan and MediaTek Inc (201802034RIND).
0608 Concordance Between Current AASM And CMS Scoring Criteria for Obstructive Sleep Apnea in Hospitalized Persons with TBI: A NIDILRR and VA Model System Study
Authors: Richardson R , Dahdah M , Almeida E , Ricketti P , Silva M , Calero K , Magalang U , Scwhartz D 
Published: May 2020

Abstract

Introduction
The objective of this study was to compare OSA, demographic, and TBI characteristics across the American Academy of Sleep Medicine (AASM) and Centers for Medicare and Medicare (CMS) scoring rules in moderate to severe TBI undergoing inpatient neurorehabilitation.

Methods
This is a secondary analysis from a prospective clinical trial of sleep apnea at six TBI Model System study sites (n=248). Scoring was completed by a centralized center using both the AASM and CMS criteria for OSA. Hospitalization and injury characteristics were abstracted from the medical record and demographics obtained by interview by trained research assistants using TBI Model System standard procedures.

Results
OSA was prevalent using the AASM (66%) and CMS (41.5%) criteria with moderate to strong agreement (weighted kappa = 0.64 (95%CI = 0.58, 0.70). Significant differences were observed for participants meeting AASM and CMS criteria (Agreement Group; AG) compared to those meeting criteria for AASM but not CMS (Disagreement Group; DG). At AHI ≥ 5, the DG (n=61) had lower Emergency Department Glasgow Coma Scale Scores consistent with greater injury severity (median 5 vs. 13, p = 0.0050), younger age (median 38 vs 58, p&lt;0.0001), and lower BMI (median 24.8 vs 22.1, p = 0.0007) compared to the AG (n=103). At AHI ≥ 15, female gender and but no other differences were noted possibly due to the smaller sample size.

Conclusion
The underestimation of sleep apnea using CMS criteria is consistent with prior literature; however, this is the first study to report the impact of the criteria in persons with moderate to severe TBI during a critical stage of neural recovery. Management of comorbidities in TBI has become an increasing focus for optimizing TBI outcomes. Given the chronic morbidity after moderate to severe TBI, the impact of CMS policy for OSA diagnosis for persons with chronic disability and young age are considerable.

Support
PCORI (CER-1511-33005), GDHS (W91YTZ-13-C-0015; HT0014-19-C-0004)) for DVBIC, NIDILRR (NSDC Grant # 90DPTB00070, #90DP0084, 90DPTB0013-01-00, 90DPTB0008, 90DPT80004-02).
0613 The Effects of Diabetes on Obstructive Sleep Apnea Severity and Progression: A Propensity Score Analysis
Authors: Li Q , Keenan B T , Punjabi N M , Maislin G , Kuna S T 
Published: May 2020

Abstract

Introduction
Obstructive sleep apnea (OSA) is associated with increased glucose intolerance and insulin resistance, and commonly coexists with type 2 diabetes mellitus (T2DM). Research suggests an independent association between these two conditions. However, more research into the role of T2DM in the development of OSA, or vice versa, is needed.

Methods
Leveraging data from 139 participants with T2DM from the Sleep AHEAD cohort and 5,085 participants without T2DM from the Sleep Heart Health Study (SHHS), we conducted two complementary propensity score (PS) subclassification analyses to estimate the effect of T2DM on the oxygen desaturation index (ODI), both at baseline and over 4-5 years of follow-up. PS models included age, sex, race, body mass index, neck circumference, waist circumference, total cholesterol, HDL cholesterol, triglycerides, Epworth Sleepiness Scale, and comorbid hypertension or cardiovascular disease. Models evaluating ODI progression also included baseline ODI.

Results
The PS subclassification analysis identified 109 participants with T2DM and 480 without T2DM, balanced with respect to baseline covariates, for evaluation of the effect of T2DM on baseline ODI. On average, those with T2DM had a 9 events/hour greater ODI compared to those without (24.3 [20.8, 27.9] vs. 15.3 [13.6, 16.9] events/hour; p&lt;0.0001). Among patients with baseline ODI≥5, a second PS subclassification identified 99 with T2DM and 227 without for evaluating the effect of T2DM on ODI progression. No difference in change in ODI was observed between those with and without T2DM (mean [95% CI] difference -0.25 [-10.7, 10.2] events/hour; p=0.963).

Conclusion
Using two robust PS subclassification designs to minimize selection bias, we evaluated the effect of T2DM on baseline ODI and ODI progression in adults with OSA after 4-5 years. Those with T2DM had more severe baseline ODI, but there were no meaningful differences in ODI progression. Results further our understanding of the association between these coexisting conditions.

Support
NIH grant HL070301
0616 Validation of a Sleep Headband for Detecting Obstructive Sleep Apnea
Authors: Guillot A , Moutakanni T , Harris M , Arnal P J , Thorey V 
Published: May 2020

Abstract

Introduction
Polysomnography (PSG) is the gold-standard to diagnose obstructive sleep apnea (OSA). OSA severity diagnosis is defined by the apnea-hypopnea index (AHI) defined as the number of apnea and hypopnea events measured per hour of sleep. The Dreem2 headband (DH) is a self-administered, easy to use device that measure EEG, breathing frequency, heart rate and sound at-home. In our study, we assessed the performance of the DH to automatically detects OSA compared to 3 sleep’s experts scoring on PSG.

Methods
41 subjects (8 females, 42.6 ± 13.7 y.o.) having a suspicion of OSA performed a night at-home wearing both a PSG and the DH. Each PSG record was scored for apnea and hypopnea events by 3 independent trained sleep experts following AASM guidelines. The deep learning approach DOSED, was trained on the DH signals using the manual apnea scoring. 10-fold cross-validation was used to provide predictions for each of the 41 subjects with the DH.

Results
We observed an average AHI expert’s scoring of 13.6 ± 10.1 CI[10.5, 16.5] compared to 12.9 ± 10.3 CI[9.6, 15.8] for the DH. Both, the correlation between the 3 scorers (r= 0.88, p &lt; 0.001) and the DH and the scorers (r=0.79, p&lt; 0.001) were significant. The specificity and sensitivity to detect mild OSA (AHI ≤ 5) was 84.4 % and 96.4 % for the DH and 86.5 % and 86.0% for the scorers.

Conclusion
The results show that the DH using deep learning can detect OSA with an accuracy similar to the sleep experts. The use of DH paves the way for longitudinal monitoring of patients with a suspicion of OSA and its accessibility could lead to better screening of the general population.

Support
This Study has been supported by Dreem sas.
0660 The Association Between Sleep-Related Breathing Disorders and Free Flap Reconstruction Surgery in Patients With Oral and Oropharyngeal Cancers During 6-Month Follow-Up
Authors: Fu-Hsin L , Chan-Chi C , Yu-Cheng L , Wei-Shu L , Cheng-Yu L 
Published: May 2020

Abstract

Introduction
Little was known about the association between sleep-related breathing disorders (SRBDs) and oral and oropharynx cancers (OOCs). To clarify the impact of free flap reconstruction on SRBDs, we performed a pilot study to investigate the change of SRBDs severity in patients with OOC before and after flap reconstruction surgery.

Methods
This study recruited 15 patients who were newly diagnosed with OOCs and expected to receive free flap reconstruction surgery. For each participant, polysomnography tests were performed repeatedly at the time of pre-operative, post-operative 1-week, and post-operative 6-month periods.

Results
All the subjects were male. Median age was 56 years (range 37-68). Mean of body mass index (BMI) was 24.5 (SD 5.8). Pre-operative apnea-hypopnea index (AHI) was 21.1/hour (SD 20.1). During post-operative 1-week period, BMI was 24.1(SD 5.8) and AHI was 40.2/hour (SD 27.9). During post-operative 6-month period, BMI was 23.4 (SD 3.3) and AHI was 33.3/hour (SD 21.6). Comparison between pre-operative and post-operative 6-month periods, there was no significant difference in BMI, but AHI increased significantly (21.1/hour v.s. 33.3/hour, P = 0.01).

Conclusion
Our study showed that OOCs patients with free flap reconstruction surgery had significantly increased AHI level during post-operative 1-week period. The SRBDs severity became partial remission after 6 months. We recommend that the head and neck cancer team should pay attention to the SRBDs issues in OOCs patients with free flap reconstruction surgery.

Support
0681 Comparison Of Upper Airway Stimulation Outcomes Between Regions And Bmi Groups From The Adhere Registry
Authors: Walia H K , Mehra R , Kominsky A , Kent D , Pham H , Upender R , Manchanda S 
Published: May 2020

Abstract

Introduction
As factors influencing Upper Airway Stimulation (UAS) effectiveness in obstructive sleep apnea (OSA) patients are of interest, we compared changes in apnea hypopnea index (AHI) and Epworth Sleepiness Scale (ESS) based on region and baseline body mass index (BMI).

Methods
Patients (15≥AHI≤65) of the ADHERE registry with AHI at one-year were grouped by region (Europe (EU) vs United States (US)), and BMI (≤32kg/m2 vs 32-35kg/m2). T-tests and equivalence testing (if the former non-significant) was performed using two-one-sided t-tests. Equivalence margin for AHI was set between -5 and 5 and -2 and 2 for ESS.

Results
By December 2019, 553 of 1600 patients completed 1-year follow-up. Average age was 60±11, 75% male, BMI 29±4 kg/m2, ESS=11±6. Median AHI decreased from 33 to 10, median ESS decreased from 11 to 6. Response defined by 50% AHI reduction and &lt;20 was 70%. Both regions had similar improvements in median AHI (EU: 33 to 10, US: 34 to 10, p &lt; 0.001 vs baseline), median ESS (EU: 12 to 7; US: 11 to 6, p&lt;0.001 vs baseline), and treatment response (EU: 71%, US: 68%). The mean AHI and ESS difference between regions met the equivalence margin. (AHI: mean difference: 0.34, CI:-1.78, 2.46, ESS: mean difference: 0.57, CI:-0.04, 1.19). Mean change in AHI at 1-year was equivalent in BMI groups (≤32 kg/m2 vs 32-35 kg/m2 respectively) median difference: -19.6 vs. -18.8; mean difference: -0.48, (CI:-3.95, 2.97) However, treatment response ratio was different; 73% vs. 60%, p=0.02, i.e. higher BMI patients were less likely to achieve AHI &lt; 20. ESS scores were equivalent; median: 6 vs. 7; mean difference: -0.33, CI: [-1.16, 0.47].

Conclusion
UAS influence on OSA severity defined by AHI and sleepiness was similar irrespective of region and BMI category, however, treatment response defined by 50% AHI reduction and &lt;20 was greater in those with lower BMI.

Support
The statistical support was provided by Inspire Medical System.
0687 Comparative Changes Of Patient Reported Outcomes In Positive Airway Pressure And Upper Airway Stimulation For Obstructive Sleep Apnea
Authors: Bhambra R , Pascoe M , Kominsky A , Mehra R , Aylor J , Wang L , Phillips K , Waters T , Walia H K 
Published: May 2020

Abstract

Introduction
Upper Airway Stimulation (UAS) is increasingly being used for obstructive sleep apnea (OSA) treatment, however, data comparing changes in patient reported outcomes (PROs) in response to positive airway pressure (PAP) versus UAS are limited. We hypothesize that there will be no difference in PROs between the two groups after treatment.

Methods
UAS and PAP groups were 1:3 matched on age, sex, Body Mass Index (BMI) and Apnea Hypopnea Index (AHI, category 15-30, &gt;30). Linear mixed models assessed the difference of change in Epworth Sleepiness Scale (ESS), Functional Outcomes of Sleep Questionnaire (FOSQ), Patient Health Questionnaire (PHQ9) and Insomnia Severity Index (ISI) measures on matched strata of UAS versus PAP groups with adjustment of baseline and matching factors. All analysis was performed in SAS software (version 9.4, Cary, NC).

Results
The analytic sample comprised 193 PAP patients and 69 UAS patients, with mean age=62.9+/-9.4 years, 27.5% female, mean BMI=29.1+/-3.2kg/m2, and median AHI 42.7, IQR: 31.5, 57.2. ESS in PAP (n=190) reduced by -2.63 (-3.38,-1.88) and in UAS (n=56) reduced by -2.22 (-3.34, -1.10), with a mean difference of 0.41 (-0.70, 1.52, p=.46). FOSQ in PAP (n=188) showed a change of 1.38 (0.99, 1.78) and in UAS (n=49) a change of 1.82 (1.17, 2.46), with a mean difference of 0.43 (-0.23, 1.09, p=.19). PHQ9 in PAP (n=185) showed a significant change of -2.24(-3.00, 1.47) and in UAS (n=45) a change of -3.75(-5.07,-2.42), with a mean difference of -1.51(-2.93,-0.088, p=.038). ISI in PAP (n=193) showed a significant change of -3.20(-4.39,-2.02) and in UAS (n=47) a change of -4.83(-6.77,-2.90), with a mean difference of -1.63(-3.62, 0.37, p=.11).

Conclusion
Similar improvements in PROs were observed in both UAS and PAP patient groups, however UAS appeared to confer greater benefit in depressive symptoms relative to PAP. Randomized clinical trials should be designed to confirm these findings.

Support
N/A
0688 Evaluation Of A Novel Nasal Airway Stent For Snoring And OSA Treatment By Prospective Japanese Patients
Authors: Wang W , Ding F , Satoh M , Kushida C 
Published: May 2020

Abstract

Introduction
This cross-sectional study evaluated a novel nasal airway stent (NAS) in the form of a single-use, disposable device (naśtent® classic, Seven Dreamers Laboratories, Inc., Tokyo, Japan), which represents a significant advancement in NAS technology for the treatment of OSA.

Methods
1353 individuals whom were interested in NAS treatment for their snoring and/or OSA were enrolled in this study conducted in different districts in Tokyo, Japan from 8/21/2015 to 3/7/2016. A total of 1335 participants with complete data were included in the final dataset. Collected data included demographic features, self-reported sleep and OSA characteristics, anatomic traits, Epworth Sleepiness Scale (ESS) scores, and NAS tolerance.

Results
The majority of the participants were middle-aged men (91.5% male, 45±10.8 years) with normal BMI (24.5±5.7). Self-reported sleep was 9-11 hours (0.1%), 7-9 hours (8.2%), 5-7 hours (66.7%), 3-5 hours (22%), 1-3 hours (1.2%), and unreported (1.9%). Their mean Epworth Sleepiness Scale score was 9±5.56, and their peak Mallampati and tonsillar grading scores were 2/4 and 3/5, respectively. Of the participants, 87.4% were aware of possible OSA either by snoring or by prior diagnosis of OSA, and their reasons for desiring use of NAS therapy presented in a similar ratio. Over 80% of the participants had never been treated for their diagnosis of OSA; for those with current or prior treatment for their OSA, 62.9% reported PAP as their primary therapy, followed by oral appliances (25.7%), surgery (0.5%), and other therapies (10.8%). On a scale of 1 to 5 where 5 indicated good tolerance to the NAS, the mean scores were 4±1.3 for easy of insertion and 4±1.2 for convenience of use.

Conclusion
This large, cross-sectional study indicated that the majority of individuals seeking a novel NAS treatment for their snoring and/or OSA in Tokyo, Japan were middle-aged men with 5-7 hours of self-reported sleep whom had some daytime sleepiness, displayed signs of mild anatomic upper airway narrowing, had not been treated for their OSA, and whom felt that the NAS was easy and convenient to use.

Support
Seven Dreamers Laboratories, Inc. and WSS ISRTP
0701 Positive Airway Pressure Therapy To Treat Sleep Disordered Breathing Impacts Number Of Hospitalizations In Patients With Heart Failure
Authors: Patel S I , Vasquez M , Huang F , Combs D , Parthasarathy S 
Published: May 2020

Abstract

Introduction
Some studies have shown a benefit while others have shown possible harm in patient outcomes when using positive airway pressure therapy (PAP) for treating sleep disordered breathing (SDB) in patients with heart failure (HF). The goal of this study was to evaluate the number of HF-related and all-cause related hospitalizations in patients with HF and SDB on various forms of PAP therapy versus those on no PAP therapy.

Methods
Administrative claims data from the Truven Health MarketScan Database from 1/1/2005- 10/31/2015 were analyzed. Those included were at least 21 years old, were continuously enrolled for 12 months before and 6 months after their index date (date of PAP prescription), had at least two distinct HF-related claims and were prescribed PAP therapy (n=1,324,414). To model the relationship between each device and hospitalization risk, and to account for the longitudinal and correlated nature of these binary outcome data, generalized estimating equations with binomial family, logit link, and unstructured correlation structure were used.

Results
There were a total of 12,538 patients on Bilevel-PAP, 2,700 patients on bilevel-PAP with backup rate, and 57,405 patients on CPAP, and 73,353 patients with HF and comorbid sleep apnea who were not on any treatment. The reduction in HF-related hospitalization for patients with HF and comorbid SDB treated with bilevel-PAP therapy (0.28; 95% CI 0.26, 0.31) was greater than that in patients receiving CPAP (OR 0.46 95% CI 0.43, 0.49), bilevel PAP with back-up rate (0.39; 95% CI 0.32, 0.49), or no PAP treatment (OR 0.54; 95%CI 0.50, 0.57)(P&lt;0.01). Similar trend was observed for all-cause related hospitalizations. All results were adjusted for propensity score and other relevant confounders.

Conclusion
In claims-based analysis of patients with HF and comorbid SDB, bilevel PAP treatment was associated with reduced hospitalizations when compared to CPAP therapy or no PAP treatment.

Support
Phillips Respironics
0712 CPAP Compliance: Roles Of Depressive Symptoms, Polysomnographic And Self-report Sleep Measures
Authors: Dubrovsky B , Inamac A , Gikashvili L , Weingarten J , Cunningham J 
Published: May 2020

Abstract

Introduction
OSA poses major health risks; however, CPAP compliance is often suboptimal. Comorbid insomnia and depression contributed to poor CPAP compliance in different studies. Presently, PSG variables, self-report measures of insomnia, sleep quality and depression were tested simultaneously as predictors of compliance in new CPAP users who at 180 days of therapy had any non-zero use of CPAP.

Methods
PSG-diagnosed 47 patients (18-79 y.o., 24 women) were titrated in the lab and initiated on CPAP. Compliance was assessed during days 1-30 and 151-180. For each period, percentage of days with &gt;4hrs of CPAP use (%&gt;4h-days30, %&gt;4h-days180) and the average hours-per-day use (Tav30, Tav180) were measured. After regressing each compliance variable on age, sex and BMI, one at a time were tested: PSG variables from the diagnostic and titration studies, subjective reactions to CPAP after titration (sleep better vs. same/worse than usual; will vs. won’t use CPAP at home), pre-treatment ISI, PSQI, ESS, and Center for Epidemiologic Studies Depression Scale-Revised (CESDR).

Results
AHI ranged 6/hr-101/hr (M=24.2±19.5); %&gt;4h-days30, 0-100% (M=68%±32%); Tav30, 0.0-9.8 hours (M=5.2±2.5); %&gt;4h-days180, 0-100% (M=64%±34%); Tav180, 0.2-10.5 hours (M=4.7±2.8). PSG variables from both diagnostic and titration studies, reactions to CPAP, ESS and CESDR were not significant predictors of compliance (all p&gt;0.1). ISI was marginally inversely related to %&gt;4h-days30 (p=0.087) and Tav30 (p=0.075). Higher pre-treatment PSQI was related to lower %&gt;4h-days30 (p=0.003, R2=19%) and Tav30 (p=0.011, R2=15%). Entered alone, PSQI was related to %&gt;4h-days180 (p=0.042) and Tav180 (p=0.043); however, when the 1-30-day compliance was accounted for, PSQI no longer related to the 151-180-day compliance. The 1-30-day compliance strongly predicted respective 151-180-day measures (%&gt;4h-days, p&lt;0.001, R2=55%; Tav, p&lt;0.001, R2=68%).

Conclusion
In this limited sample of naive CPAP users, higher pre-treatment sleep disturbance reported on PSQI was a useful predictor of lower 1-30-day CPAP compliance. Neither depressive symptoms nor PSG variables from diagnostic and titration studies predicted compliance. As the initial 30-day compliance is the best predictor of later CPAP use, early interventions are crucial.

Support
none