Effectiveness and optimization of low-sodium oxybate in participants with narcolepsy switching from a high-sodium oxybate: data from the SEGUE study.

STUDY OBJECTIVES: Low-sodium oxybate (LXB; calcium, magnesium, potassium, and sodium oxybates; Xywav) contains the same active moiety as high-sodium oxybates (sodium oxybate [SXB; Xyrem] and fixed-dose sodium oxybate [Lumryz]), with 92% less sodium, and is approved in the US for treatment of cataplexy or excessive daytime sleepiness in patients 7 years of age and older with narcolepsy, and idiopathic hypersomnia in adults. Patients with narcolepsy have increased cardiovascular risk relative to people without narcolepsy. LXB's lower sodium content is recognized by the US FDA in the narcolepsy population as clinically meaningful in reducing cardiovascular morbidity compared with high-sodium oxybates. The Substitution of Equal Grams of Uninterrupted Xyrem to Xywav (SEGUE) study (NCT04794491) examined the transition experience of patients with narcolepsy switching from SXB to LXB. METHODS: Eligible participants were aged 18 to 80 years with narcolepsy type 1 or 2 on a stable SXB dose/regimen. After 2 weeks, participants transitioned gram-per-gram to LXB for 6 weeks, with opportunity for subsequent titration. Assessments included the Epworth Sleepiness Scale (ESS), Patient Global Impression of Change (PGIc), ease of switching medication scale (EOSMS), and forced preference questionnaire (FPQ). RESULTS: The study enrolled 62 participants at baseline; 60 transitioned to LXB and 54 completed the study. At baseline and end of the LXB intervention/early discontinuation, respectively, mean total doses were 8.0 and 8.0 g/night; mean ESS scores were 9.4 and 8.8. Most participants reported improvement (45%) or no change (48%) in narcolepsy symptoms on the PGIc, reported the transition to LXB was "easy" (easy, extremely easy, not difficult at all; 93%) on the EOSMS, and preferred LXB compared with SXB (79%) on the FPQ, most commonly due to the lower sodium content. CONCLUSIONS: Most participants switched from SXB to LXB with minimal modifications of dose/regimen and reported the transition process was easy. Effectiveness of oxybate treatment was maintained on LXB, and most participants preferred LXB to SXB. No new safety or tolerability issues were identified. CLINICALTRIALREGISTRATION: Registry: ClinicalTrials.gov; Name: An Interventional Safety Switch Study (Segue Study) of XYWAV in Narcolepsy; URL: https://classic.clinicaltrials.gov/ct2/show/NCT04794491; Identifier: NCT04794491.

Fatigued but not sleepy? An empirical investigation of the differentiation between fatigue and sleepiness in sleep disorder patients in a cross-sectional study.

OBJECTIVE: Sleepiness and fatigue are common complaints among individuals with sleep disorders. The two concepts are often used interchangeably, causing difficulty with differential diagnosis and treatment decisions. The current study investigated sleep disorder patients to determine which factors best differentiated sleepiness from fatigue. METHODS: The study used a subset of participants from a multi-site study (n = 606), using a cross-sectional study design. We selected 60 variables associated with either sleepiness or fatigue, including demographic, mental health, and lifestyle factors, medical history, sleep questionnaires, rest-activity rhythms (actigraphy), polysomnographic (PSG) variables, and sleep diaries. Fatigue was measured with the Fatigue Severity Scale and sleepiness was measured with the Epworth Sleepiness Scale. A Random Forest machine learning approach was utilized for analysis. RESULTS: Participants' average age was 47.5 years (SD 14.0), 54.6% female, and the most common sleep disorder diagnosis was obstructive sleep apnea (67.4%). Sleepiness and fatigue were moderately correlated (r = 0.334). The model for fatigue (explained variance 49.5%) indicated depression was the strongest predictor (relative explained variance 42.7%), followed by insomnia severity (12.3%). The model for sleepiness (explained variance 17.9%), indicated insomnia symptoms was the strongest predictor (relative explained variance 17.6%). A post hoc receiver operating characteristic analysis indicated depression could be used to discriminate fatigue (AUC = 0.856) but not sleepiness (AUC = 0.643). CONCLUSIONS: The moderate correlation between fatigue and sleepiness supports previous literature that the two concepts are overlapping yet distinct. Importantly, depression played a more prominent role in characterizing fatigue than sleepiness, suggesting depression could be used to differentiate the two concepts.

Dosing and transition characteristics in people with narcolepsy transitioning from sodium oxybate to low-sodium oxybate: Data from the real-world TENOR study.

OBJECTIVE: The Transition Experience of persons with Narcolepsy taking Oxybate in the Real-world (TENOR) study assessed the real-world experience of people with narcolepsy switching from sodium oxybate (SXB) to low-sodium oxybate (LXB; 92 % less sodium than SXB). METHODS: TENOR is a patient-centric, prospective, observational, virtual-format study. Eligible participants included US adults with narcolepsy transitioning from SXB to LXB (±7 days from LXB initiation). Longitudinal data were collected from baseline (taking SXB) through 21 weeks post-transition. RESULTS: TENOR included 85 participants with narcolepsy (type 1, n = 45; type 2, n = 40). Mean (SD) age was 40.3 (13.0) years; the majority (73 %) were female and White (87 %). At study completion, wake-promoting agents were the most common concomitant medications (47 %). Mean (SD) SXB treatment duration was 57.8 (52.1) months; 96 % took SXB twice nightly. After transitioning, 97 % continued on twice-nightly regimens. Mean (SD) dose of both total nightly SXB (n = 85) and baseline LXB (n = 84) was 7.7 (1.5) g; SXB-LXB dose conversions at baseline were gram-for-gram in 87 % of participants. The mean final total nightly dose of LXB was 7.9 g. The most common participant-reported reasons for transitioning included lower sodium content for improved long-term health (93 %), physician recommendation (47 %), to avoid cardiovascular issues (39 %), to avoid side effects (31 %), and to improve control of narcolepsy symptoms (18 %). CONCLUSION: Most participants transitioned from SXB to LXB using a gram-for-gram strategy. The most commonly cited reason for transition was long-term health benefits due to lower sodium.

Proteomic insights into the pathophysiology of periodic limb movements and restless legs syndrome.

OBJECTIVES: We used a high-throughput assay of 5000 plasma proteins to identify biomarkers associated with periodic limb movements (PLM) and restless legs syndrome (RLS) in adults. METHODS: Participants (n = 1410) of the Stanford Technology Analytics and Genomics in Sleep (STAGES) study had blood collected, completed a sleep questionnaire, and underwent overnight polysomnography with the scoring of PLMs. An aptamer-based array (SomaScan) was used to quantify 5000 proteins in plasma. A second cohort (n = 697) that had serum assayed using a previous iteration of SomaScan (1300 proteins) was used for replication and in a combined analysis (n = 2107). A 5% false discovery rate was used to assess significance. RESULTS: Multivariate analyses in STAGES identified 68 proteins associated with the PLM index after correction for multiple testing (ie, base model). Most significantly decreased proteins were iron-related and included Hepcidin (LEAP-1), Ferritin, and Ferritin light chain. Most significantly increased proteins included RANTES, Cathepsin A, and SULT 1A3. Of 68 proteins significant in the base model, 17 were present in the 1300 panel, and 15 of 17 were replicated. The most significant proteins in the combined model were Hepcidin (LEAP-1), Cathepsin A, Ferritin, and RANTES. Exploration of proteins in RLS versus non-RLS identified Cathepsin Z, Heme oxygenase 2 (HO-2), Interleukin-17A (upregulated in the combined cohort), and Megalin (upregulated in STAGES only) although results were less significant than for proteins associated with PLM index. CONCLUSIONS: These results confirm the association of PLM with low iron status and suggest the involvement of catabolic enzymes in PLM/RLS.

Effectiveness and tolerability in people with narcolepsy transitioning from sodium oxybate to low-sodium oxybate: Data from the real-world TENOR study.

OBJECTIVES: The Transition Experience of persons with Narcolepsy taking Oxybate in the Real-world (TENOR) study was conducted to provide real-world insight into the experience of people with narcolepsy switching from sodium oxybate (SXB) to low-sodium oxybate (LXB; 92% less sodium than SXB). METHODS: TENOR is a patient-centric, prospective, observational, virtual-format study. Participants were adults with narcolepsy (type 1 or 2) who were transitioning from SXB to LXB treatment (±7 days from LXB initiation). Effectiveness and tolerability data were collected online from baseline (taking SXB) through 21 weeks (taking LXB) via daily and weekly diaries and questionnaires, including the Epworth Sleepiness Scale (ESS), the Functional Outcomes of Sleep Questionnaire, short version (FOSQ-10), and the British Columbia Cognitive Complaints Inventory (BC-CCI). RESULTS: TENOR participants (N = 85) were 73% female with a mean (SD) age of 40.3 (13.0) years. Mean (SD) ESS scores decreased numerically throughout the transition from SXB to LXB (baseline: 9.9 [5.2]; week 21: 7.5 [4.7]), with 59.5% and 75.0% of participants having scores in the normal range (≤10) at baseline and week 21, respectively. Mean (SD) FOSQ-10 scores (baseline: 14.4 [3.4]; week 21: 15.2 [3.2]) and BC-CCI scores (baseline: 6.1 [4.4]; week 21: 5.0 [4.3]) also remained stable. The most common symptoms related to tolerability reported by participants at baseline were sleep inertia, hyperhidrosis, and dizziness (45.2%, 40.5%, and 27.4%, respectively), which decreased in prevalence by week 21 (33.8%, 13.2%, and 8.8%, respectively). CONCLUSIONS: Findings from TENOR confirm maintenance of effectiveness and tolerability when transitioning from SXB to LXB treatment.

Health-related impact of illness associated with excessive daytime sleepiness in patients with obstructive sleep apnea.

OBJECTIVES: This real-world study aimed to characterize the impact of illness of excessive daytime sleepiness (EDS) in patients with obstructive sleep apnea (OSA) who are adherent to continuous positive airway pressure (CPAP). METHODS: This cross-sectional study surveyed participants in Evidation Health's Achievement app (November 2020-January 2021), a mobile consumer platform that encourages users to develop healthy habits and provides incentives to participate in research. Participants were US-resident adults who self-reported a physician diagnosis of OSA and adherence to CPAP (≥4 hours/night, ≥5 nights/week) for≥6 months. The survey included the Functional Outcomes of Sleep Questionnaire-Short Version (FOSQ-10), Epworth Sleepiness Scale (ESS), and questions regarding comorbidities, CPAP use, caffeine consumption, and physical activity. EDS was defined as ESS score >10. There were more female than male participants; therefore, data were reported separately for females/males. RESULTS: In total, 476 participants (female, n = 283 [59%]; mean [SD] age, 49.7 [10.8] years; obese, 74.4%) completed the survey; 209 had EDS (mean [SD] ESS, 13.8 [2.5]) and 267 did not (mean [SD] ESS, 6.3 [2.5]). Self-reported duration of CPAP use was consistent between the EDS/no EDS cohorts, with most participants using CPAP for 7 to 9 hours/night, 7 nights/week. Participants with EDS commonly reported anxiety ([EDS/no EDS] males: 31.5%/20.0%; females: 53.7%/39.5%), depression (males: 35.6%/24.2%; females: 55.9%/44.9%), and insomnia (males: 19.2%/6.7%; females: 25.7%/12.9%) and showed impairment on the FOSQ-10 ([EDS/no EDS] males: 80.8%/35.0%; females: 91.9%/53.1%). Participants with EDS reported that sleepiness 'very often' prevented physical activity and influenced dietary choices. CONCLUSION: EDS influences choices related to physical activity, caffeine consumption, and diet in patients who are adherent with CPAP. More research is needed to understand the association between EDS and choices of CPAP-adherent patients. Future research should explore the health-related consequences of residual EDS associated with OSA and whether they can be mitigated by improving EDS.

Approximately 1 billion people worldwide have a sleep disorder called obstructive sleep apnea (OSA). People with OSA experience a blockage in their upper airway during sleep, which can lead to snoring, gasping for air, difficulty breathing, and disturbed sleep. As a result, 50%­80% of people with OSA experience excessive daytime sleepiness (EDS) ­ the irresistible need to sleep during the daytime. Many people (9%­22%) who are treated for OSA using continuous positive airway pressure (CPAP) still experience EDS. Previous studies have described the negative impact EDS has on people, such as decreased work productivity and increased risk of motor vehicle accidents. However, it is unclear if EDS impacts health, behavioral choices, and lifestyle in the real world. This study surveyed people with OSA and collected their Fitbit data using Evidation's Achievement app. People with OSA and EDS reported having anxiety, depression, insomnia, and other health problems more often than people with OSA without EDS. Also, people with OSA and EDS reported having more impairments in daytime functioning than people with OSA without EDS. Furthermore, people with OSA and EDS reported that sleepiness 'very often' prevented them from engaging in physical activity. Women with OSA and EDS said that sleepiness 'very often' influenced their food choices. People with OSA and EDS also used caffeine and 'sometimes' used physical activity to stay awake during the daytime. Findings from this study show people with OSA alter their lifestyle and behavioral choices because of EDS.

Nasomaxillary Expansion by Endoscopically-Assisted Surgical Expansion (EASE): An airway centric approach / Expansion nasomaxillaire chirurgicale assistée par endoscopie (EASE) : une approche centrée surles voies respiratoires

Introduction: The aim of this study was to analyze the skeletal, dental and airway changes with endoscopically assisted surgical expansion (EASE) to widen the nasomaxillary complex for the treatment of sleep apnea in adults. Methods: One hundred and five consecutive patients underwent EASE. Cone beam computed tomography (CBCT) was conducted preoperatively and within four weeks after the completion of the expansion process. Computational fluid dynamic (CFD) analysis was performed on 20 randomly selected patients to assess airway flow changes. Results: One hundred patients (67 males) with the mean age of 35.0±13.5 years (17-64 years) had completed pre- and post-expansion imaging. Ninety-six patients (96%) had successful expansion defined as separation of the midpalatal suture at least 1 mm from anterior nasal spine (ANS) to posterior nasal spine (PNS). The nasal cavity expansion was 3.12±1.11 mm at ANS, 3.64±1.06 mm at first molar and 2.39±1.15 mm at PNS. The zygoma expansion was 2.17±1.11 mm. The ratio of dental expansion to skeletal expansion was 1.23:1 (3.83 mm:3.12 mm) at canine and 1.31:1 (4.77 mm:3.64 mm) at first molar. CFD airway simulation showed a dynamic change following expansion throughout the airway. The mean negative pressure improved in the nasal airway (from -395.5±721.0 to -32.7±19.2 Pa), nasopharyngal airway (from -394.2±719.4 to -33.6±18.5 Pa), oropharyngeal airway (from -405.9±710.8 to -39.4±19.3 Pa) and hypopharyngeal airway (from -422.6±704.9 to -55.1±33.7 Pa). The mean airflow velocity within the nasal airway decreased from 18.8±15.9 to 7.6±2.0 m/s and the oropharyngeal airway decreased from 4.2±2.9 to 3.2±1.2 m/s. The velocity did not change significantly in the nasopharyngeal and hypopharyngeal regions. Conclusions: EASE results in expansion of the midpalatal suture from the ANS to PNS with a nearly pure skeletal movement of minimal dental effect. The expansion of the nasomaxillary complex resulted in the widening of the nasal sidewall throughout the nasal cavity. The improved air flow dynamics was demonstrated by CFD simulation.

Introduction: L'objectif de cette étude était d'analyser les modifications obtenues au niveau du squelette, des dents et des voies respiratoires lors d'une expansion nasomaxillaire chirurgicale assistée par endoscopie (EASE), visant à élargir le complexe nasomaxillaire pour le traitement de l'apnée du sommeil chez des adultes. Méthodes: Cent cinq patients consécutifs ont subi une EASE. Une tomographie à faisceau conique (CBCT) a été réalisée en préopératoire et dans les quatre semaines suivant la fin du processus d'expansion. Une analyse de la dynamique des fluides computationnelle (DFC) a été réalisée sur vingt patients sélectionnés au hasard pour évaluer les modifications du débit de leurs voies respiratoires. Résultats: Un bilan d'imagerie pré- et post-expansion a été réalisé chez cent patients (dont 67 hommes) d'un âge moyen de 35,0 ± 13,5 ans (17-64 ans). Quatre-vingt-seize patients (96 %) ont bénéficié d'une expansion réussie, définie comme une séparation de la suture médiopalatine d'au moins 1 mm, de l'épine nasale antérieure (ENA) à l'épine nasale postérieure (ENP). L'expansion de la cavité nasale était de 3,12 ± 1,11 mm au niveau de l'ENA, de 3,64 ± 1,06 mm au niveau de la première molaire et de 2,39 ± 1,15 mm au niveau de l'ENP. L'expansion zygomatique était de 2,17 ± 1,11 mm. Le rapport entre l'expansion dentaire et l'expansion squelettique était de 1,23 : 1 (3,83 mm : 3,12 mm) au niveau de la canine et de 1,31 : 1 (4,77 mm : 3,64 mm) au niveau de la première molaire. Après l'expansion, la simulation des voies respiratoires par DFC a montré un changement dynamique au niveau de l'ensemble des voies respiratoires. La pression négative moyenne s'est améliorée dans les voies nasales (de -395,5 ± 721,0 à -32,7 ± 19,2 Pa), les voies nasopharyngiennes (de -394,2 ± 719,4 à -33,6 ± 18,5 Pa), les voies aériennes oropharyngées (de -405,9 ± 710,8 à -39,4 ± 19,3 Pa) et les voies aériennes hypopharyngées (de -422,6 ± 704,9 à -55,1 ± 33,7 Pa). La vitesse moyenne du flux d'air dans les voies nasales a diminué de 18,8 ± 15,9 à 7,6 ± 2,0 m/s et de 4,2 ± 2,9 à 3,2 ± 1,2 m/s dans les voies oropharyngées. La vitesse n'a pas changé de manière significative dans les régions nasopharyngienne et hypopharyngienne. Conclusions: L'EASE entraîne une expansion de la suture médiopalatine, de l'ENA jusqu'à l'ENP avec un mouvement squelettique presque pur et un effet dentaire minimal. L'expansion du complexe nasomaxillaire a entraîné l'écartement des parois nasales latérales dans toute la cavité nasale. L'amélioration de la dynamique du flux d'air a été démontrée par une simulation DFC.

Proteomic Biomarkers of the Apnea Hypopnea Index and Obstructive Sleep Apnea: Insights into the Pathophysiology of Presence, Severity, and Treatment Response.

Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea−hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.

Age estimation from sleep studies using deep learning predicts life expectancy.

Sleep disturbances increase with age and are predictors of mortality. Here, we present deep neural networks that estimate age and mortality risk through polysomnograms (PSGs). Aging was modeled using 2500 PSGs and tested in 10,699 PSGs from men and women in seven different cohorts aged between 20 and 90. Ages were estimated with a mean absolute error of 5.8 ± 1.6 years, while basic sleep scoring measures had an error of 14.9 ± 6.29 years. After controlling for demographics, sleep, and health covariates, each 10-year increment in age estimate error (AEE) was associated with increased all-cause mortality rate of 29% (95% confidence interval: 20-39%). An increase from -10 to +10 years in AEE translates to an estimated decreased life expectancy of 8.7 years (95% confidence interval: 6.1-11.4 years). Greater AEE was mostly reflected in increased sleep fragmentation, suggesting this is an important biomarker of future health independent of sleep apnea.

Nasomaxillary Expansion by Endoscopically-Assisted Surgical Expansion (EASE): An airway centric approach

Introduction: The aim of this study was to analyze the skeletal, dental and airway changes with endoscopically assisted surgical expansion (EASE) to widen the nasomaxillary complex for the treatment of sleep apnea in adults. Methods: One hundred and five consecutive patients underwent EASE. Cone beam computed tomography (CBCT) was conducted preoperatively and within four weeks after the completion of the expansion process. Computational fluid dynamic (CFD) analysis was performed on 20 randomly selected patients to assess airway flow changes. Results: One hundred patients (67 males) with the mean age of 35.0±13.5 years (17-64 years) had completed pre- and post-expansion imaging. Ninety-six patients (96%) had successful expansion defined as separation of the midpalatal suture at least 1 mm from anterior nasal spine (ANS) to posterior nasal spine (PNS). The nasal cavity expansion was 3.12±1.11 mm at ANS, 3.64±1.06 mm at first molar and 2.39±1.15 mm at PNS. The zygoma expansion was 2.17±1.11 mm. The ratio of dental expansion to skeletal expansion was 1.23:1 (3.83 mm:3.12 mm) at canine and 1.31:1 (4.77 mm:3.64 mm) at first molar. CFD airway simulation showed a dynamic change following expansion throughout the airway. The mean negative pressure improved in the nasal airway (from -395.5±721.0 to -32.7±19.2 Pa), nasopharyngal airway (from -394.2±719.4 to -33.6±18.5 Pa), oropharyngeal airway (from -405.9±710.8 to -39.4±19.3 Pa) and hypopharyngeal airway (from -422.6±704.9 to -55.1±33.7 Pa). The mean airflow velocity within the nasal airway decreased from 18.8±15.9 to 7.6±2.0 m/s and the oropharyngeal airway decreased from 4.2±2.9 to 3.2±1.2 m/s. The velocity did not change significantly in the nasopharyngeal and hypopharyngeal regions. Conclusions: EASE results in expansion of the midpalatal suture from the ANS to PNS with a nearly pure skeletal movement of minimal dental effect. The expansion of the nasomaxillary complex resulted in the widening of the nasal sidewall throughout the nasal cavity. The improved air flow dynamics was demonstrated by CFD simulation.

Prediction of Patient Demographics using 3D Craniofacial Scans and Multi-view CNNs.

3D data is becoming increasingly popular and accessible for computer vision tasks. A popular format for 3D data is the mesh format, which can depict a 3D surface accurately and cost-effectively by connecting points in the (x, y, z) plane, known as vertices, into triangles that can be combined to approximate geometrical surfaces. However, mesh objects are not suitable for standard deep learning techniques due to their non-euclidean structure. We present an algorithm which predicts the sex, age, and body mass index of a subject based on a 3D scan of their face and neck. This algorithm relies on an automatic pre-processing technique, which renders and captures the 3D scan from eight different angles around the x-axis in the form of 2D images and depth maps. Subsequently, the generated data is used to train three convolutional neural networks, each with a ResNet18 architecture, to learn a mapping between the set of 16 images per subject (eight 2D images and eight depth maps from different angles) and their demographics. For age and body mass index, we achieved a mean absolute error of 7.77 years and 4.04 kg/m2 on the respective test sets, while Pearson correlation coefficients of 0.76 and 0.80 were obtained, respectively. The prediction of sex yielded an accuracy of 93%. The developed framework serves as a proof of concept for prediction of more clinically relevant variables based on 3D craniofacial scans stored in mesh objects.

PSG Validation of minute-to-minute scoring for sleep and wake periods in a consumer wearable device.

BACKGROUND: Actigraphs are wrist-worn devices that record tri-axial accelerometry data used clinically and in research studies. The expense of research-grade actigraphs, however, limit their widespread adoption, especially in clinical settings. Tri-axial accelerometer-based consumer wearable devices have gained worldwide popularity and hold potential for a cost-effective alternative. The lack of independent validation of minute-to-minute accelerometer data with polysomnographic data or even research-grade actigraphs, as well as access to raw data has hindered the utility and acceptance of consumer-grade actigraphs. METHODS: Sleep clinic patients wore a consumer-grade wearable (Huami Arc) on their non-dominant wrist while undergoing an overnight polysomnography (PSG) study. The sample was split into two, 20 in a training group and 21 in a testing group. In addition to the Arc, the testing group also wore a research-grade actigraph (Philips Actiwatch Spectrum). Sleep was scored for each 60-s epoch on both devices using the Cole-Kripke algorithm. RESULTS: Based on analysis of our training group, Arc and PSG data were aligned best when a threshold of 10 units was used to examine the Arc data. Using this threshold value in our testing group, the Arc has an accuracy of 90.3%±4.3%, sleep sensitivity (or wake specificity) of 95.5%±3.5%, and sleep specificity (wake sensitivity) of 55.6%±22.7%. Compared to PSG, Actiwatch has an accuracy of 88.7%±4.5%, sleep sensitivity of 92.6%±5.2%, and sleep specificity of 60.5%±20.2%, comparable to that observed in the Arc. CONCLUSIONS: An optimized sleep/wake threshold value was identified for a consumer-grade wearable Arc trained by PSG data. By applying this sleep/wake threshold value for Arc generated accelerometer data, when compared to PSG, sleep and wake estimates were adequate and comparable to those generated by a clinical-grade actigraph. As with other actigraphs, sleep specificity plateaus due to limitations in distinguishing wake without movement from sleep. Further studies are needed to evaluate the Arc's ability to differentiate between sleep and wake using other sources of data available from the Arc, such as high resolution accelerometry and photoplethysmography.

Association of Rapid Eye Movement Sleep With Mortality in Middle-aged and Older Adults.

Importance: Rapid eye movement (REM) sleep has been linked with health outcomes, but little is known about the relationship between REM sleep and mortality. Objective: To investigate whether REM sleep is associated with greater risk of mortality in 2 independent cohorts and to explore whether another sleep stage could be driving the findings. Design, Setting, and Participants: This multicenter population-based cross-sectional study used data from the Outcomes of Sleep Disorders in Older Men (MrOS) Sleep Study and Wisconsin Sleep Cohort (WSC). MrOS participants were recruited from December 2003 to March 2005, and WSC began in 1988. MrOS and WSC participants who had REM sleep and mortality data were included. Analysis began May 2018 and ended December 2019. Main Outcomes and Measures: All-cause and cause-specific mortality confirmed with death certificates. Results: The MrOS cohort included 2675 individuals (2675 men [100%]; mean [SD] age, 76.3 [5.5] years) and was followed up for a median (interquartile range) of 12.1 (7.8-13.2) years. The WSC cohort included 1386 individuals (753 men [54.3%]; mean [SD] age, 51.5 [8.5] years) and was followed up for a median (interquartile range) of 20.8 (17.9-22.4) years. MrOS participants had a 13% higher mortality rate for every 5% reduction in REM sleep (percentage REM sleep SD = 6.6%) after adjusting for multiple demographic, sleep, and health covariates (age-adjusted hazard ratio, 1.12; fully adjusted hazard ratio, 1.13; 95% CI, 1.08-1.19). Results were similar for cardiovascular and other causes of death. Possible threshold effects were seen on the Kaplan-Meier curves, particularly for cancer; individuals with less than 15% REM sleep had a higher mortality rate compared with individuals with 15% or more for each mortality outcome with odds ratios ranging from 1.20 to 1.35. Findings were replicated in the WSC cohort despite younger age, inclusion of women, and longer follow-up (hazard ratio, 1.17; 95% CI, 1.03-1.34). A random forest model identified REM sleep as the most important sleep stage associated with survival. Conclusions and Relevance: Decreased percentage REM sleep was associated with greater risk of all-cause, cardiovascular, and other noncancer-related mortality in 2 independent cohorts.

Proteomic biomarkers of sleep apnea.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is characterized by recurrent partial to complete upper airway obstructions during sleep, leading to repetitive arousals and oxygen desaturations. Although many OSA biomarkers have been reported individually, only a small subset have been validated through both cross-sectional and intervention studies. We sought to profile serum protein biomarkers in OSA in unbiased high throughput assay. METHODS: A highly multiplexed aptamer array (SomaScan) was used to profile 1300 proteins in serum samples from 713 individuals in the Stanford Sleep Cohort, a patient-based registry. Outcome measures derived from overnight polysomnography included Obstructive Apnea Hypopnea Index (OAHI), Central Apnea Index (CAI), 2% Oxygen Desaturation index, mean and minimum oxygen saturation indices during sleep. Additionally, a separate intervention-based cohort of 16 individuals was used to assess proteomic profiles pre- and post-intervention with positive airway pressure. RESULTS: OAHI was associated with 65 proteins, predominantly pathways of complement, coagulation, cytokine signaling, and hemostasis which were upregulated. CAI was associated with two proteins including Roundabout homolog 3 (ROBO3), a protein involved in bilateral synchronization of the pre-Bötzinger complex and cystatin F. Analysis of pre- and post intervention samples revealed IGFBP-3 protein to be increased while LEAP1 (Hepicidin) to be decreased with intervention. An OAHI machine learning classifier (OAHI >=15 vs OAHI<15) trained on SomaScan protein measures alone performed robustly, achieving 76% accuracy in a validation dataset. CONCLUSIONS: Multiplex protein assays offer diagnostic potential and provide new insights into the biological basis of sleep disordered breathing.

Design of a deep learning model for automatic scoring of periodic and non-periodic leg movements during sleep validated against multiple human experts.

OBJECTIVE: Currently, manual scoring is the gold standard of leg movement scoring (LMs) and periodic LMs (PLMS) in overnight polysomnography (PSG) studies, which is subject to inter-scorer variability. The objective of this study is to design and validate an end-to-end deep learning system for the automatic scoring of LMs and PLMS in sleep. METHODS: The deep learning system was developed, validated and tested, with respect to manual annotations by expert technicians on 800 overnight PSGs using a leg electromyography channel. The study includes data from three cohorts, namely, the Wisconsin Sleep Cohort (WSC), Stanford Sleep Cohort (SSC) and MrOS Sleep Study. The performance of the system was further compared against individual expert technicians and existing PLM detectors. RESULTS: The system achieved an F1 score of 0.83, 0.71, and 0.77 for the WSC, SSC, and an ancillary study (Osteoporotic Fractures in Men Study, MrOS) cohorts, respectively. In a total of 60 PSGs from the WSC and the SSC scored by nine expert technicians, the system performed better than two and comparable to seven of the individual scorers with respect to a majority-voting consensus of the remaining scorers. In 60 PSGs from the WSC scored accurately for PLMS, the system outperformed four previous PLM detectors, which were all evaluated on the same data, with an F1 score of 0.85. CONCLUSIONS: The proposed system performs better or comparable to individual expert technicians while outperforming previous automatic detectors. Thereby, the study validates fully automatic methods for scoring LMs in sleep.

Factors associated with fatigue in patients with insomnia.

Although fatigue is common in insomnia, the clinical associates of fatigue in patients with insomnia are largely unknown. We aimed to investigate the clinical associates of fatigue in patients with insomnia. Patients visiting the Stanford Sleep Medicine Center completed the Insomnia Severity Index (ISI), Insomnia Symptom Questionnaire (ISQ), the Fatigue Severity Scale (FSS), the Epworth Sleepiness Scale (ESS), and the Patient Health Questionnaire (PHQ-9). Among 6367 patients, 2024 were diagnosed with insomnia (age 43.06 ±â€¯15.19 years; 1110 women and 914 men) according to the ISI and the ISQ. Insomnia patients with severe fatigue (n = 1306) showed higher insomnia symptoms, daytime sleepiness, depression and longer habitual sleep duration than those without severe fatigue (n = 718). Higher insomnia symptoms, daytime sleepiness and depressive symptoms, and longer habitual sleep duration, independently predicted higher fatigue scores. Among insomnia patients with daytime sleepiness (ESS≥10), only habitual sleep duration and depression predicted fatigue scores. The interaction between insomnia severity and daytime sleepiness significantly predicted the severity of fatigue. Depression was a significant mediator between insomnia and fatigue. For 598 insomnia patients undergoing overnight polysomnography (PSG), no significant correlations were found between fatigue and any PSG parameters. The current study suggests that managing insomnia or depression may reduce the fatigue of insomnia patients, whereas arbitrary efforts to prolong sleep duration may worsen their fatigue.

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

OBJECTIVE: Obstructive sleep-disordered breathing (SDB) events, unlike central events, are associated with increased respiratory effort. Esophageal pressure (P es) monitoring is the gold standard for measuring respiratory effort, but it is typically poorly tolerated because of its invasive nature. The objective was to investigate whether machine learning can be applied to routinely collected non-invasive, polysomnography (PSG) measures to accurately model peak negative P es. APPROACH: One thousand one hundred and nineteen patients from the Stanford Sleep Clinic with PSGs containing P es served as the sample. The selected non-invasive PSG signals included nasal pressure, oral airflow, thoracoabdominal effort, and snoring. A long short-term memory neural network was implemented to achieve a context-based mapping between the non-invasive features and the P es values. A hold-out dataset served as a prospective validation of the algorithm without needing to undertake a costly new study with the impractically invasive P es. MAIN RESULTS: The median difference between the measured and predicted P es was 0.61 cmH2O with an interquartile range (IQR) of 2.99 cmH2O and 5th and 95th percentiles of -5.85 cmH2O and 5.47 cmH2O, respectively. The model performed well when compared to actual esophageal pressure signal (ρ median = 0.581, p  = 0.01; IQR = 0.298; ρ 5% = 0.106; ρ 95% = 0.843). SIGNIFICANCE: A significant difference in predicted P es was shown between normal breathing and all obstructive SDB events; whereas, central apneas did not significantly differ from normal breathing. The developed system may be used as a tool for quantifying respiratory effort from the existing clinical practice of PSG without the need for P es, improving characterization of SDB events as obstructive or not.