Polysomnographic Measures Research Articles

Blood-based lipidomic signature of severe obstructive sleep apnoea in Alzheimer’s disease

BackgroundObstructive sleep apnoea (OSA) is the most frequent form of sleep-disordered breathing in patients with Alzheimer’s disease (AD). Available evidence demonstrates that both conditions are independently associated with alterations in lipid metabolism. However, it is unknown whether the expression of lipids is different between AD patients with and without severe OSA. In this context, we examined the plasma lipidome of patients with suspected OSA, aiming to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease.MethodsThe study included 103 consecutive patients from the memory unit of our institution with a diagnosis of AD. The individuals were subjected to overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥30/h), and blood was collected the following morning. Untargeted plasma lipidomic profiling was performed using liquid chromatography coupled with mass spectrometry.ResultsWe identified a subset of 44 lipids (mainly phospholipids and glycerolipids) that were expressed differently between patients with AD and severe and nonsevere OSA. Among the lipids in this profile, 30 were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses revealed a 4-lipid signature (phosphatidylcholine PC(35:4), cis-8,11,14,17-eicosatetraenoic acid and two oxidized triglycerides (OxTG(58:5) and OxTG(62:12)) that provided an accuracy (95% CI) of 0.78 (0.69–0.86) in the detection of OSA. These same lipids improved the predictive power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50–0.74) to 0.80 (0.70–0.90).ConclusionOur results show a plasma lipidomic fingerprint that allows the identification of patients with AD and severe OSA, allowing the personalized management of these individuals. The findings suggest that oxidative stress and inflammation are potential prominent mechanisms underlying the association between OSA and AD.

Cluster Analysis of Home Polygraphic Recordings in Symptomatic Habitually-Snoring Children: A Precision Medicine Perspective.

(1) Background: Sleep-disordered breathing (SDB) is a frequent problem in children. Cluster analyses offer the possibility of identifying homogeneous groups within a large clinical database. The application of cluster analysis to anthropometric and polysomnographic measures in snoring children would enable the detection of distinctive clinically-relevant phenotypes; (2) Methods: We retrospectively collected the results of nocturnal home-based cardiorespiratory polygraphic recordings and anthropometric measurements in 326 habitually-snoring otherwise healthy children. K-medoids clustering was applied to standardized respiratory and anthropometric measures, followed by Silhouette-based statistics. Respiratory Disturbance Index (RDI) and oxygen desaturation index (≤3%) were included in determining the optimal number of clusters; (3) Results: Mean age of subjects was 8.1 ± 4.1 years, and 57% were males. Cluster analyses uncovered an optimal number of three clusters. Cluster 1 comprised 59.5% of the cohort (mean age 8.69 ± 4.14 years) with a mean RDI of 3.71 ± 3.23 events/hour of estimated sleep (e/ehSleep). Cluster 2 included 28.5% of the children (mean age 6.92 ± 3.43 years) with an RDI of 6.38 ± 3.92 e/ehSleep. Cluster 3 included 12% of the cohort (mean age 7.58 ± 4.73 years) with a mean RDI of 25.5 ± 19.4 e/ehSleep. Weight z-score was significantly lower in cluster 3 [−0.14 ± 1.65] than in cluster 2 [0.86 ± 1.78; p = 0.015] and cluster 1 [1.04 ± 1.78; p = 0.002]. Similar findings emerged for BMI z scores. However, the height z-score was not significantly different among the 3 clusters; (4) Conclusions: Cluster analysis of children who are symptomatic habitual snorers and are referred for clinical polygraphic evaluation identified three major clusters that differed in age, RDI, and anthropometric measures. An increased number of children in the cluster with the highest RDI had reduced body weight. We propose that the implementation of these approaches to a multicenter-derived database of home-based polygraphic recordings may enable the delineation of objective unbiased severity categories of pediatric SDB. Our findings could be useful for clinical implementation, formulation of therapeutic decision guidelines, clinical management, prevision of complications, and long-term follow-up.

Accurate respiratory rate determination using a novel insertable cardiac monitor algorithm: implications for diagnostic and monitoring potentials beyond heart rhythm disorders

Abstract Background Respiratory rate (RR) is a critical vital sign that is highly relevant in patients with cardiopulmonary disorders. The implantable cardiac monitor (ICM) provides useful data pertaining to heart rhythm, but little is known up to this point regarding its potential diagnostic value in the direct measurement of respiratory parameters. The addition of respiration information could improve understanding of overall health status of heart rhythm patients with ICM. Objective The primary objective of this study was to evaluate the accuracy of the RR detected by an existing implanted ICM as compared to gold-standard polysomnography (PSG) measurement of respiration. Methods This prospective single center study enrolled 25 patients (17 male, 62.7±12.2 yesrs) with an implanted ICM and suspected sleep-disordered breathing. The ICM was custom configured with research software to collect respiration data (Fig. 1). Simultaneous, time-synchronized PSG and ICM data were evaluated in two-minute epochs episodically during the night. The offline novel prototype RR algorithm was evaluated on episodes collected by the ICM and compared against expert manual adjudicated RR from PSG by two separate investigators. The interobserver agreement was assessed using intraclass correlation coefficient (ICC). The performance of the novel algorithm was assessed using Bland-Altman analysis with 95% limits of agreement (LOA). Results A total of 495 epochs were graded by two independent observers, with good ICC of 0.83 (95% C.I. 0.79–0.86). Epochs free of severe sleep disordered breathing/apnea (n=363) were included in this analysis with 106 of these containing periods of hypopnea. The development and validation datasets were comprised of 235 and 128 epochs, respectively. In the development data, the mean RR was 14.99±3 breaths per minute, and the mean RR was 13.44±2 breaths per minute in the test data. Using Bland-Altman analysis, the bias for the novel prototype algorithm was only −0.13 and +0.32 breaths per minute with 95% LOA of −2.24 to +1.98 and −2.56 to +3.19 breaths per minute (Fig. 2), in the in the development and test dataset respectively. Conclusion The novel prototype algorithm applied to the ICM data provided accurate determination of respiratory rate as compared to gold-standard PSG data. The capability to determine respiratory rate accurately from an existing ICM platform demonstrates the potential to extend the diagnostic power of ICMs beyond heart rhythm abnormalities to address a broad range of comorbidities including breathing disorders and heart failure. Funding Acknowledgement Type of funding sources: None.

Applications of wireless sensor systems to sleep stage estimation for home sleep monitoring

In recent years, research on sleep monitoring and analysis has attracted many scholars. Among them, the polysomnography (PSG) is performed more accurately. However, PSG is not suitable to be used at home due to its complicated operation and expensive cost. On the other hand, although the Pittsburgh sleep quality index (PSQI) is a standardized form for sleep quality assessment, the subjective and backward evaluation may lead to intuitive results. Therefore, this paper is intended to develop a sleep stage estimation system for home health care services. In the proposed platform, the sleep conditions, including the heart rate (HR) and body movement, are collected by an HR monitor and a force sensor array, respectively. Also, the fuzzy inference system is applied to the sleep depth evaluation, and then, the finite state machine is utilised to estimate the sleep stage. Experimental results show that the developed platform not only reduces the burden of PSG measurements, but also provides more convincible and reasonable results, presenting as an assistive tool of the conventional PSQI tests.

Clonazepam for the management of sleep disorders.

The objectives of this review and meta-analysis of polysomnographic data are those to focus on the clinical use of clonazepam for the management of sleep disorders by re-analyzing clinical trials and randomized clinical trials which have been published in peer-reviewed journals. A review of the literature including clinical trials and randomized controlled trials was performed in PubMed®, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement protocol. A random effects model meta-analysis was then carried out for the four more frequently reported polysomnographic measures: total sleep time, sleep latency, sleep efficiency, and periodic leg movement during sleep (PLMS) index. A total of 33 articles were retrieved and screened in full text, of which 18 met the criteria for review; among the latter, nine met the criteria for meta-analysis. The studies included in the review involved patients with insomnia, REM sleep behavior disorder, sleep bruxism, and restless leg syndrome or PLMS which reported, most often, an increase in total sleep time with clonazepam. A clear sleep-promoting effect of clonazepam was found also by meta-analysis. Our results indicate that the pharmacological treatment of sleep disorders with clonazepam must always be personalized according to the type of patient, the risk of addiction and the concomitant presence of respiratory disorders are key factors to take into account. However, in light of the clinical evidence of the few studies in the literature on the different types of disorders, more studies on the use of clonazepam (also in association with first choice treatments) are definitely needed.

Validation of mandibular movements' analysis to measure sleep in adults with sleep complaints by comparison with actigraphy and polysomnography.

ObjectiveIn adults with sleep complaints, we assessed the software of automatic analysis of mandibular movements to identify sleep and wake states by confrontation with the polysomnography (PSG) and the actigraphy (ACTG).Material and MethodsSimultaneous and synchronized in-lab PSG, ACTG, and JAWAC were carried out in 100 patients with a sleep complaint. Epoch by epoch analysis was realized to assess the ability to sleep-wake distinction. Sleep parameters as measured by the three devices were compared. These included three regularly reported parameters: total sleep time (TST), sleep onset latency (SOL), and wake after sleep onset (WASO). Also, two supplementary parameters, wake during sleep period (WDSP) and latency to arising (LTA) were added to measure separately the quiet wakefulness states.ResultsThe epoch by epoch analysis showed that the JAWAC, as compared to ACTG, classified sleep and wake states with greater specificity, while the overall accuracy and sensitivity of the two devices were comparable. The sleep parameters analysis showed that for the JAWAC estimates, the differences in TST, SOL, and LTA values were not statistically significant. However, WDSP and subsequently WASO were slightly underestimated. In contrast, the dissimilarities between ACTG estimates and PSG measurements of all the above sleep parameters were statistically significant; TST was overestimated whilst SOL, LTA, WDSP, and WASO were underestimated.ConclusionThis study indicated that, besides its ability to reliably estimate TST, the JAWAC based on mandibular movements’ analysis was able, in adults with sleep complaints, to overcome the important problem of the recognition of the state of quiet wakefulness.

Association of sleep abnormalities in older adults with risk of developing Parkinson's disease.

Parkinson's disease (PD) is associated with abnormalities of sleep macro- and microstructure as measured using polysomnography (PSG). Whether these abnormalities precede the development of PD is unknown. This study investigated the association between PSG measured sleep abnormalities in older adults and the risk of incident PD. A total of 2,770 men from the ancillary sleep study of the Osteoporotic Fractures in Men Study (MrOS), a population-based cohort from the United States, who were free from PD baseline and underwent overnight PSG, were included in this longitudinal analysis. Incident PD was based on a clinical diagnosis from a medical professional. Multivariable logistic regression was used to estimate odds ratios (OR) for incident PD by quartiles of PSG measures, with adjustment for sociodemographic characteristics, medical comorbidities, and lifestyle factors. During a median follow-up of 9.8 years, 70 (2.5%) cases of incident PD were identified. Longer total sleep time, lower rapid eye movement sleep (REM) percentage, a lower α/θ ratio during non-REM sleep and higher minimum oxygen saturations during REM sleep, were each associated with an increased risk of developing PD. Conversely, a higher awakening index was associated with a decreased risk of developing PD. The OR for the highest risk quartiles compared to the lowest risk quartiles, ranged from 2.1 to 3.7 (p's < .05). The associations remained significant when cases occurring within the first two years of follow-up were excluded from the analyses. Macro- and micro-structural sleep abnormalities precede the development of PD by several years and can identify individuals at high risk of developing PD in the future.

Childhood trauma and gender: Synergistic and additive effects on sleep in healthy young adults

ObjectivesTo examine whether gender moderates the effects of childhood trauma on subjective and objective sleep measures. DesignSecondary data analysis, exploratory SettingsSleep research lab ParticipantsA total of 213 men and 278 women aged 18-30 completed subjective measures. A subsample of 172 participants without any psychiatric, medical, or sleep disorders completed objective polysomnography for 1 night at baseline, before sleep manipulation. MeasurementsSubjective measures: Childhood Trauma Questionnaire (CTQ), Pittsburgh Sleep Quality Index, Insomnia Severity Index, and Epworth Sleepiness Scale. Objective measures: Standard polysomnography measures. Multiple regressions determined whether gender moderated CTQ score on any objective or subjective sleep measures. If gender was not a moderator, we examined additive effects of gender and CTQ score. Models were adjusted for race and age. ResultsGender and CTQ score interactions were non-significant for both subjective (p > .675) and objective (p > .110) sleep. Women demonstrated better subjective sleep quality (Pittsburgh Sleep Quality Index, B = -0.264, p = .041) and more delta sleep than men (B = 3.032, p =.005). Greater CTQ score was associated with increased sleepiness (Epworth Sleepiness Scale, B = 0.029, p = .042), increased insomnia severity (Insomnia Severity Index, B = 0.027, p = .005), and lower REM density (B = -0.132, p = .045). ConclusionOur finding of greater delta sleep and better subjective overall sleep quality in women suggests that, among people without comorbidities, women may experience better sleep. Childhood trauma is associated with objective and subjective sleep measures, but this association is non-specific to gender. Clear links between childhood trauma and sleep are detectable in a sample of healthy sleepers with no comorbidities.

Drowsiness detection from polysomnographic data using multivariate selfsimilarity and eigen-wavelet analysis.

Because drowsiness is a major cause in vehicle accidents, its automated detection is critical. Scale-free temporal dynamics is known to be typical of physiological and body rhythms. The present work quantifies the benefits of applying a recent and original multivariate selfsimilarity analysis to several modalities of polysomnographic measurements (heart rate, blood pressure, electroencephalogram and respiration), from the MIT-BIH Polysomnographic Database, to better classify drowsiness-related sleep stages. Clinical relevance- This study shows that probing jointly temporal dynamics amongst polysomnographic measurements, with a proposed original multivariate multiscale approach, yields a gain of above 5% in the Area-under-Curve quanti-fying drowsiness-related sleep stage classification performance compared to univariate analysis.

Association between early stage N2 sleep spindle burst characteristics and vigilance groups: an observational study on patients from a tertiary sleep centre

Objective. Obstructive sleep apnoea (OSA) is associated with impaired vigilance. This paper examines the hypothesis that sleep spindle (Sp) characteristics during nocturnal sleep can be mapped to vigilance deficits measured by the psychomotor vigilance task (PVT) in patients with OSA. Approach. The PVT was performed prior to In-laboratory Polysomnography for 250 patients. PVT outcomes were clustered into three vigilance groups (VGs). Spindles were scored manually for a Training Cohort of 55 patients, (9491 Sps) across different blocks of NREM sleep (SBs) and validated in a Test Cohort (25 patients, 4867 Sps). We proposed a novel set of Sp features including a spindle burst index (SBI), which quantifies the burst characteristics of spindles and constructed models mapping them to VGs. We also explored the performance of conventional Sp features (such as Sp number and density) in our modelling approach. Main results. In the Training Cohort, we observed statistically significant differences in the SBI across VGs and SBs independent of OSA severity (1st stage N2 SBI; p = <0.001 across VGs). In the Test Cohort, a Model based on the proposed SBI predicted VG membership with 88% accuracy. A model based on conventional Sp features mapped to VGs with 80% accuracy, and a model using mixed burst and conventional features reached an accuracy of 88%. Significance. Spindle features measured during diagnostic In-laboratory polysomnography measurements can be mapped to PVT outcomes. The novel SBI proved useful for exploring the relationship between PVT outcomes and sleep. Further studies in larger populations are needed to verify these conclusions.

The impact of thyroidectomy on obstructive sleep apnea: a systematic review and meta-analysis.

Various thyroid pathologies are speculated to contribute to obstructive sleep apnea (OSA). The underlying mechanisms of the intricate relationship between OSA and thyroid structure and function, and whether thyroidectomy can alleviate OSA symptoms remain unclear. An assessment of the impact of thyroidectomy on OSA is warranted. A systematic review of four electronic databases (PubMed (Medline), Embase, the Cochrane library, and ClinicalTrials.gov) was performed up to February 2022. The primary outcomes were preoperative and postoperative Apnea/Hypopnea Index (AHI), Epworth Sleepiness Scale (ESS), Berlin questionnaire scores, and continuous positive airway pressure (CPAP) use. A meta-analysis of continuous measures and odd ratios was conducted. Small-scale studies underwent a qualitative meta-analysis. Six cohort studies on 221 OSA patients who underwent thyroidectomies were included. The results showed that thyroidectomy was associated with significant reduction in postoperative AHI (Mean difference [MD], -6.39, 95% CI, -12.46 to -0.32), however, no significant association was found with CPAP withdrawal (Odd ratio [OR], 0.38, 95% CI, 0.12-1.18). Neither the Berlin questionnaire score (OR, 0.19, 95% CI, 0.03-1.17) nor the ESS improved postoperatively (MD, -1.04, 95% CI, -6.37 to 4.29). This meta-analysis provides a quantitative estimate for the effect of the thyroidectomy on OSA and suggests that thyroidectomy is associated with limited clinical improvement of polysomnographic measures. Future large-scale, well-designed prospective studies are necessary to validate these findings and to refine accordingly the preoperative assessment of both medical conditions individually and in combination.

Polysomnography Following Traumatic Brain Injury: A Systematic Review and Meta-Analysis

IntroductionSleep disturbances are common following traumatic brain injury (TBI) worsening morbidity and other neuropsychiatric symptoms. Post-TBI alterations in sleep architecture require further study.Objectives(1) To evaluate polysomnographic measures of sleep architecture in participants with history of TBI compared to controls and as meta-analyses of pooled means. (2) To evaluate effects of timing and severity of TBI on polysomnographic outcomes.MethodsPRISMA compliant systematic review was conducted of MEDLINE, PsycINFO, EMBASE and Scopus. Inclusion criteria: 1) reporting polysomnography in the context of TBI and 2) operationalizing TBI using clear/formalized criteria. Data were pooled in random-effects meta-analyses with outcomes expressed as mean differences (MD).ResultsIn participants with TBI, sleep was comprised of 19.39% REM sleep, 8.13% N1, 51.18% N2, and 17.53% N3, as determined by meta-analyses of single means. Total sleep time was reduced in chronic (&gt;6 months) TBI compared to acute-intermediate TBI (&lt;6 months) (p=0.01). Compared to controls, participants with TBI differed with increased N1 sleep (MD=0.64%; 95%CI=0.02,1.25; p=0.04), reduced sleep efficiency (MD=-1.65%; 95%CI=-3.18,-0.12; p=0.03), and reduced sleep latency on the multiple sleep latency test (MD=-5.90mins; 95%CI=-10.09,-1.72; p&lt;0.01). On sub-group analyses, participants with mild TBI differed from controls with reduced total sleep time (MD=-29.22mins, 95%CI=-54.16,-4.27; p=0.02). Similarly, participants with acute-intermediate TBI exhibited increased sleep latency compared to controls (MD=8.96mins; 95%CI=4.07,13.85; p&lt;0.01) and differed significantly from participants with chronic TBI (X2(1,N=608)=6.54; p=0.01).ConclusionsSleep architecture is altered following TBI with potential implications regarding functional outcomes and recovery. These alterations appear to differ based on severity of injury and time since injury.DisclosureNo significant relationships.

0795 Association of Nasal and Sleep Apnea Clinical Measures

Abstract Introduction The association between nasal measures and polygsomnography measures is modest. However, nasal treatment can improve sleep quality in people without sleep apnea. The association of nasal and sleep apnea clinical measures in patients with sleep apnea is unknown. Our primary hypothesis is that the subjective nasal obstruction is associated with reduced sleep apnea-specific quality of life at baseline and with sleep apnea treatment after 6 months. Methods This prospective cohort study included patients with newly diagnosed sleep apnea who were prescribed CPAP. Data were collected before CPAP and 6 months later, including the validated Nasal Obstruction Symptom Evaluation (NOSE, range 0-100, higher worse) scale and validated Symptoms of Nocturnal Obstruction &amp; Related Events (SNORE-25, range 0-5, higher worse) quality of life instrument. Additional nasal measures, sleep apnea clinical measures, and covariates were collected. We tested the association between nasal and sleep apnea clinical measures with multivariate linear regression, adjusting for important confounding variables. Results The cohort (N=242) was middle-aged (47+/-12 years), included both sexes (65% men), and had severe sleep apnea (apnea-hypopnea index 33+/-24 events/hour). The baseline NOSE was strongly associated with SNORE-25, independent of demographics, comorbidity, and sleep apnea severity: beta 18, 95% CI 15-22, p&amp;lt;0.001, meaning for every unit of SNORE-25 increase there was an adjusted increase in NOSE score of 18. The 6-month changes in NOSE and SNORE-25 were strongly associated, independent of demographics, comorbidity, sleep apnea severity, and CPAP use: beta 17, 95%CI 13-22, p&amp;lt;0.001. Secondary nasal and sleep apnea clinical measures were associated, but nasal and polysomnography measures were not associated. Conclusion Nasal clinical measures are associated with sleep apnea clinical measures at baseline and with sleep apnea treatment, while the nasal measures are not associated with polysomnography measure. These data support the importance of the nasal airway on sleep apnea clinical outcomes. Support (If Any) R01 HL084139 (Weaver), T32 DC000018 (Stone), Seattle Veterans Affairs Medical Center

0499 Sleep and Neurocognition in Adolescents with ADHD: A Polysomnographic Study

Abstract Introduction Sleep disturbances are common among adolescents with ADHD; however, few studies have characterized the nature of ADHD-related sleep problems using the gold-standard sleep measure, polysomnography (PSG), in adolescence. Additionally, although similar cognitive deficits are common across ADHD and sleep-disordered populations, the potential role of sleep in contributing to cognitive impairment in adolescent ADHD is unknown. This study investigates differences in PSG-measured sleep among adolescents with ADHD versus healthy controls without psychiatric disorders (HC) and associations with cognition. Methods Sixty-two adolescents aged 13-17 (31 ADHD, mean age=15.3, 50% female) completed a psychiatric evaluation and 3 nights of ambulatory PSG. Following the third night, participants completed the Cambridge Neuropsychological Test Automated Battery (CANTAB). Sleep variables were averaged over 3 nights. Linear regressions controlling for age and sex examined group differences in a range of traditional PSG and spectral EEG indices as well as relationships between PSG/spectral indices and cognition (two summary scores derived from CANTAB: response accuracy and response time) within the ADHD group. Results Adolescents with ADHD displayed reduced SWS% (F(3,51)=9.67, p=.003), increased N2% (F(3,51)=10.35, p=.002), increased relative sigma (F(3,47)=6.55, p=.01) and beta (F(3,47)=4.10, p&amp;lt;.05) power, and a trend toward reduced relative delta power (F(3,47)=2.95, p=.09) compared to HC. Within the ADHD group, greater REM% (r=.43), reduced N2% (r=-.55), greater relative delta power (r=.52), higher delta power peak (r=.56), steeper delta decline overnight (r=-.56), and reduced relative theta (r=-.53), beta (r=-.74), and gamma (r=-.67) power were associated with better response accuracy (p’s&amp;lt;.05). Greater relative delta (r=-.51), and reduced relative theta (r=.55) and beta (r=.63), power were associated with faster response times. Conclusion Although adolescents with ADHD did not differ from HC on traditional PSG measures (TST, WASO), they exhibited abnormalities in sleep stage distribution and non-REM EEG frequency spectral indices, including reduced SWS and low frequency power and increased stage 2 sleep and high frequency power overnight. Notably, similar parameters were associated with impaired cognition, suggesting sleep may contribute to cognitive deficits in ADHD. Future studies may clarify whether sleep plays a causal role in cognitive impairments in adolescent ADHD and if sleep treatments result in improved cognition in this population. Support (If Any) K23MH108704

0218 N2 and wakefulness drive subjective sleep satisfaction in adults

Abstract Introduction The measurable aspects of brain function derivable from polysomnography (PSG) that are correlated with sleep satisfaction are poorly understood. Previously, a weak association of PSG measures with subjectively rated sleep depth and restfulness was shown. Using recent developments in automated sleep scoring, which remove the within- and between-rater error associated with human scoring, we revisit whether whole night PSG measurements are associated with sleep satisfaction. Additionally, we investigate if PSG data collected closer to wake time explains the subjective sleep experience better than whole night PSG. Methods Random Forest machine learning was used to investigate the relationship between PSG data from the Sleep Heart Health Study (N=3,165, middle-aged and older adults) and self-reported sleep satisfaction (restfulness, depth). PSG were rescored using a novel automated algorithm that generates both a sleep stage for each 15-s epoch as well as a stage matching probability. Data were also parsed into 20 minute-fragments based on time relative to wake. Results Models explained 30% of subjective sleep depth and 27% of subjective sleep restfulness, with a similar top four predictors: minutes of N2 and wake after sleep onset (WASO), sleep efficiency, and age, capturing 28% (restfulness) and 26% (depth) of the relative model variance. With increasing subjective sleep quality, there was a progressive increase in N2 and decrease in WASO of similar magnitude, without systematic changes in N1, N3 or REM. In comparing those with the best and worst subjective experience of sleep, there is a range of approximately 30 minutes more N2, 30 minutes less WASO, an improvement of sleep efficiency of 7-8%, and an age span of 3-5 years. Random Forest models derived from PSG fragments closer to the offset of sleep did not provide better explanatory power compared to the whole-night data set. Conclusion Approximately one-third of the variance in two measures of self-reported sleep experience can be explained by whole-night PSG variables, notably an increase in N2 and decrease in wake that led to improved sleep efficiency. Interventions that specifically target these may be suitable for improving the self-reported sleep experience. Support (If Any)

0614 Polysomnographic Measures of Sleep Architectural Disruption and Incident Atrial Fibrillation and Stroke in a Large Clinical Cohort

Abstract Introduction Although epidemiologic studies have identified associations of architectural disruptions in sleep and atrial fibrillation (AF), inconsistencies in results limit understanding of longitudinal AF and stroke development in clinic-based cohorts. We hypothesize lower arousal index as a biomarker of prolonged respiratory events and objective measures of sleep disruption increase incident AF and stroke. Methods Cleveland Clinic patients (age&amp;gt;18) who underwent polysomnogram (PSG) or split studies 11/27/2004-12/30/2015 were examined. Arousal index, total sleep time (TST,hours), sleep efficiency (SE,%), and wake after sleep onset (WASO,hours) were assessed as predictors of incident AF. Cox proportional hazard models were fit with time from sleep study to AF diagnosis. Secondary analyses were conducted in the subset of patients with baseline AF, with time from sleep study to stroke. Covariates included age, sex, race, body mass index (BMI,kg/m2), cardiovascular risk factors (hypertension, diabetes mellitus, hyperlipidemia), heart failure, coronary artery disease, myocardial infarction, coronary artery bypass grafting, chronic obstructive pulmonary disease, tobacco use, and use of anti-arrhythmic drugs. Data were censored at date of last follow up or the 5-year mark. Results The sample comprised 43,634 patients: age 51.7±14.5, 51.9% male, 74.5% White, and 7.1%(n=3,090) with AF. Of those without baseline AF, 1,176(2.9%) developed 5-year incident AF. Incident AF increased by 9% (HR=1.09, 95%CI=1.04-1.13) for each hour of lost TST. For every 10 percentage point decreased SE, incident AF increased by 7% (HR=1.07, 95%CI=1.04-1.11). For every hour increased WASO, incident AF increased by 14% (HR=1.14, 95%CI=1.07-1.21). Arousal index conferred no statistically detectable change of incident AF. In secondary analyses, any association of arousal index and incident stroke was attenuated after accounting for confounding comorbidities (omnibus p=0.055). Conclusion Objective measures of disrupted sleep architecture predicted incident AF in this clinical cohort. However, arousal index was not associated with AF development, nor stroke development in secondary analyses. Further investigation is needed to elucidate the role of arousal in SDB, perhaps with hierarchal models to clarify the degree to which confounders attenuate or accentuate any relationship. Support (If Any) Cleveland Clinic Neurological Institute Center for Outcomes Research &amp; Education Pilot Grant

The association between sleep architecture, quality of life, and hypertension in patients withobstructive sleep apnea.

The aim of this study was to investigate the association between hypertension and overnight polysomnography measures of sleep duration, sleep architecture, and quality of life (QoL) in patients withobstructive sleep apnea (OSA). Participants were patientssuspected of havingOSA with orwithout hypertension. All patients underwent overnight polysomnography and completed the Epworth Sleepiness Scale (ESS), Self-Rating Anxiety Scale, Self-Rating Depression Scale, and 12-item Short-Form Health Survey. Of 128 patients (mean age 46.2 ± 12.5years), 53% had hypertension. The average total sleep duration was 344min (standard deviation 90) or 5.7h and sleep efficiency was < 70%. There was no significant difference between patients withOSA with/without hypertension in total sleep duration, sleep architecture, anxiety, depression, ESS scores, or QoL. In patients withOSA, nocturnal minimum oxygen saturation was significantly negatively correlated with bodily pain and physical component summary (PCS) scores; mean nocturnal saturation was negatively correlated with bodily pain and social function; anxiety showed a significant negative correlation with role emotional; and depression was significantly negatively correlated with physical function, role physical, general health, role emotional, PCS, and mental component summary (MCS) scores. In the group withOSA and hypertension, N3 duration was negatively correlated with social function, mental health, and MCS scores. Anxiety was significantly negatively correlated with physical function, role physical, vitality, mental health, role emotional, PCS, and MCS scores. Depression was significantly negatively correlated with physical function, role physical, vitality, mental health, role emotional, PCS, and MCS scores. In patients withmild, moderate, and severe OSA, QoLwas associated with depression. In mild OSA, PCS was correlated with ESS and anxiety. In moderate OSA, MCS was correlated with apnea-hypopnea index scores. In severe OSA, MCS and PCS were correlated with anxiety. There were no significant associations between the presence of hypertension and total sleep duration, sleep architecture, or QoL in patients withOSA. However, hypertension may affect the influencing factors of QoL in patients withOSA. Further cohort studies are needed to confirm these findings.

A novel EEG marker predicts perceived sleepiness and poor sleep quality.

To determine if a novel EEG-derived continuous index of sleep depth/alertness, the odds ratio product (ORP), predicts self-reported daytime sleepiness and poor sleep quality in two large population-based cohorts. ORP values which range from 0 (deep sleep) to 2.5 (fully alert) were calculated in 3s intervals during awake periods (ORPwake) and NREM sleep (ORPNREM) determined from home sleep studies in the HypnoLaus (N = 2162: 1106 females, 1056 males) and men androgen inflammation lifestyle environment and stress (MAILES) cohorts (N = 754 males). Logistic regression was used to examine associations between ORPwake, ORPNREM, and traditional polysomnography measures (as comparators) with excessive sleepiness (Epworth sleepiness scale >10) and poor sleep quality (Pittsburgh sleep quality index >5) and insomnia symptoms. High ORPwake was associated with a ~30% increase in poor sleep quality in both HypnoLaus (odds ratio, OR, and 95% CI) 1.28 (1.09, 1.51), and MAILES 1.36 (1.10, 1.68). High ORPwake was also associated with a ~28% decrease in excessive daytime sleepiness in the MAILES dataset. ORPNREM was associated with a ~30% increase in poor sleep quality in HypnoLaus but not in MAILES. No consistent associations across cohorts were detected using traditional polysomnography markers. ORP, a novel EEG-derived metric, measured during wake periods predicts poor sleep quality in two independent cohorts. Consistent with insomnia symptomatology of poor perceived sleep in the absence of excessive daytime sleepiness, ORPwake may provide valuable objective mechanistic insight into physiological hyperarousal.

Clinical polysomnographic methods for estimating pharyngeal collapsibility in obstructive sleep apnea.

Obstructive sleep apnea has major health consequences but is challenging to treat. For many therapies, efficacy is determined by the severity of underlying pharyngeal collapsibility, yet there is no accepted clinical means to measure it. Here, we provide insight into which polysomnographic surrogate measures of collapsibility are valid, applicable across the population, and predictive of therapeutic outcomes. Seven promising polysomnography-derived surrogate collapsibility candidates were evaluated: Vpassive (flow at eupneic ventilatory drive), Vmin (ventilation at nadir drive), event depth (depth of the average respiratory event), oxygen desaturation slope and mean oxygen desaturation (events-related averages), Fhypopneas (fraction of events scored as hypopneas), and apnea index. Evaluation included (1) validation by comparison to physiological gold-standard collapsibility values (critical closing pressure, Pcrit), (2) capacity to detect increased collapsibility with older age, male sex, and obesity in a large community-based cohort (Multi-Ethnic Study of Atherosclerosis, MESA), and (3) prediction of treatment efficacy (oral appliances and pharmacological pharyngeal muscle stimulation using atomoxetine-plus-oxybutynin). Pcrit was significantly correlated with Vmin (r = -0.54), event depth (r = 0.49), Vpassive (r = -0.38), Fhypopneas (r = -0.46), and apnea index (r = -0.46; all p < .01) but not others. All measures detected greater collapsibility with male sex, age, and obesity, except Fhypopneas and apnea index which were not associated with obesity. Fhypopneas and apnea index were associated with oral appliance and atomoxetine-plus-oxybutynin efficacy (both p < .05). Among several candidates, event depth, Fhypopneas, and apnea index were identified as preferred pharyngeal collapsibility surrogates for use in the clinical arena.

The relationship between the HDRS insomnia items and polysomnographic (PSG) measures in individuals with treatment-resistant depression

The Hamilton Depression Rating Scale (HDRS), which includes several insomnia-related items, is potentially valuable in evaluating both depressive and sleep symptoms. However, the HDRS insomnia items have not been fully assessed by objective measures. This study compared the three HDRS insomnia items (Early, Middle, and Late) with the corresponding objective polysomnography (PSG) measures of Sleep Latency (SL), middle wakefulness, and late wakefulness. The study used HDRS and PSG data from 130 baseline nights, drawn from 80 participants enrolled in clinical trials for treatment-resistant depression (TRD). Mixed models evaluated the relationship between the HDRS and PSG, and primary analyses examined the Early, Middle, and Late Insomnia HDRS items and the PSG variables SL and Waking After Sleep Onset (WASO). To approximate the Middle and Late HDRS Insomnia items more closely, WASO was divided into WASO before 4:00 a.m. (waking between Sleep Onset and 0400 h) and WASO after 4:00 a.m. (waking between 0400 h and 0700 h). Secondary analyses included summed HDRS Global Insomnia score. HDRS Early and Late Insomnia items predicted objective PSG measures of early and late wakefulness. For Early Insomnia, each additional point in severity was associated with 61% [95%CI: 35%, 93%] longer SL. For Late Insomnia, each additional point was associated with a 35% [95% CI: 13%, 63%] increase in WASO after 4:00 a.m. Middle Insomnia was marginally related to WASO before 4:00 a.m. HDRS Early and Late Insomnia items may thus provide an index of wakefulness in TRD and help monitor treatment response when objective measures such as PSG are not feasible. Clinical trials identifierwww.clinicaltrials.gov (NCT01204918, NCT00054704, NCT00088699).