Cardiopulmonary Sleep Spectrograms Open a Novel Window Into Sleep Biology-Implications for Health and Disease

The interactions of heart rate variability and respiratory rate and tidal volume fluctuations provide key information about normal and abnormal sleep. A set of metrics can be computed by analysis of coupling and coherence of these signals, cardiopulmonary coupling (CPC). There are several forms of CPC, which may provide information about normal sleep physiology, and pathological sleep states ranging from insomnia to sleep apnea and hypertension. As CPC may be computed from reduced or limited signals such as the electrocardiogram or photoplethysmogram (PPG) vs. full polysomnography, wide application including in wearable and non-contact devices is possible. When computed from PPG, which may be acquired from oximetry alone, an automated apnea hypopnea index derived from CPC-oximetry can be calculated. Sleep profiling using CPC demonstrates the impact of stable and unstable sleep on insomnia (exaggerated variability), hypertension (unstable sleep as risk factor), improved glucose handling (associated with stable sleep), drug effects (benzodiazepines increase sleep stability), sleep apnea phenotypes (obstructive vs. central sleep apnea), sleep fragmentations due to psychiatric disorders (increased unstable sleep in depression).

Understanding cell culture dynamics: a tool for defining protocol parameters for improved processes and efficient manufacturing using human embryonic stem cells

Standardization is crucial when culturing cells including human embryonic stem cells (hESCs) which are valuable for therapy development and disease modeling. Inherent issues regarding reproducibility of protocols are problematic as they hinder translation to good manufacturing practice (GMP), thus reducing clinical efficacy and uptake. Pluripotent cultures require standardization to ensure that input material is consistent prior to differentiation, as inconsistency of input cells creates end-product variation. To improve protocols, developers first must understand the cells they are working with and their related culture dynamics. This innovative work highlights key conditions required for optimized and cost-effective bioprocesses compared to generic protocols typically implemented. This entailed investigating conditions affecting growth, metabolism, and phenotype dynamics to ensure cell quality is appropriate for use. Results revealed critical process parameters (CPPs) including feeding regime and seeding density impact critical quality attributes (CQAs) including specific metabolic rate (SMR) and specific growth rate (SGR). This implied that process understanding, and control is essential to maintain key cell characteristics, reduce process variation and retain CQAs. Examination of cell dynamics and CPPs permitted the formation of a defined protocol for culturing H9 hESCs. The authors recommend that H9 seeding densities of 20,000 cells/cm2, four-day cultures or three-day cultures following a recovery passage from cryopreservation and 100% medium exchange after 48 hours are optimal. These parameters gave ~SGR of 0.018 hour-1 ± 1.5x10-3 over three days and cell viabilities ≥95%±0.4, while producing cells which highly expressed pluripotent and proliferation markers, Oct3/4 (>99% positive) and Ki-67 (>99% positive).

Raspberry Pi nest cameras: An affordable tool for remote behavioral and conservation monitoring of bird nests

Bespoke (custom-built) Raspberry Pi cameras are increasingly popular research tools in the fields of behavioral ecology and conservation, because of their comparative flexibility in programmable settings, ability to be paired with other sensors, and because they are typically cheaper than commercially built models.Here, we describe a novel, Raspberry Pi-based camera system that is fully portable and yet weatherproof-especially to humidity and salt spray. The camera was paired with a passive infrared sensor, to create a movement-triggered camera capable of recording videos over a 24-hr period. We describe an example deployment involving "retro-fitting" these cameras into artificial nest boxes on Praia Islet, Azores archipelago, Portugal, to monitor the behaviors and interspecific interactions of two sympatric species of storm-petrel (Monteiro's storm-petrel Hydrobates monteiroi and Madeiran storm-petrel Hydrobates castro) during their respective breeding seasons.Of the 138 deployments, 70% of all deployments were deemed to be "Successful" (Successful was defined as continuous footage being recorded for more than one hour without an interruption), which equated to 87% of the individual 30-s videos. The bespoke cameras proved to be easily portable between 54 different nests and reasonably weatherproof (~14% of deployments classed as "Partial" or "Failure" deployments were specifically due to the weather/humidity), and we make further trouble-shooting suggestions to mitigate additional weather-related failures.Here, we have shown that this system is fully portable and capable of coping with salt spray and humidity, and consequently, the camera-build methods and scripts could be applied easily to many different species that also utilize cavities, burrows, and artificial nests, and can potentially be adapted for other wildlife monitoring situations to provide novel insights into species-specific daily cycles of behaviors and interspecies interactions.

Temporal patterns of wildlife roadkill in the UK

Wildlife-vehicle collisions are one of the main causes of mortality for wild mammals and birds in the UK. Here, using a dataset of 54,000+ records collated by a citizen science roadkill recording scheme between 2014-2019, we analyse and present temporal patterns of wildlife roadkill of the 19 most commonly reported taxa in the UK (84% of all reported roadkill). Most taxa (13 out of 19) showed significant and consistent seasonal variations in road mortality and fitted one of two seasonal patterns; bimodal or unimodal: only three species (red fox Vulpes vulpes, European polecat Mustela putorius and Reeves' muntjac deer Muntiacus reevesi) showed no significant seasonality. Species that increase movement in spring and autumn potentially have bimodal patterns in roadkill due to the increase in mate-searching and juvenile dispersal during these respective time periods (e.g. European badger Meles meles). Unimodal patterns likely represent increased mortality due to a single short pulse in activity associated with breeding (e.g. birds) or foraging (e.g. grey squirrels Sciurus carolinensis in autumn). Importantly, these patterns also indicate periods of increased risk for drivers, potentially posing a greater threat to human welfare. In addition to behaviour-driven annual patterns, abiotic factors (temperature and rainfall) explained some variance in roadkill. Notably, high rainfall was associated with decreased observations of two bird taxa (gulls and Eurasian magpies Pica pica) and European rabbit Oryctolagus cuniculus. By quantifying seasonal patterns in roadkill, we highlight a significant anthropogenic impact on wild species, which is important in relation to conservation, animal welfare, and human safety.

Deep Learning-Based Assessment of Brain Connectivity Related to Obstructive Sleep Apnea and Daytime Sleepiness

PURPOSE

Obstructive sleep apnea (OSA) is associated with altered pairwise connections between brain regions, which might explain cognitive impairment and daytime sleepiness. By adopting a deep learning method, we investigated brain connectivity related to the severity of OSA and daytime sleepiness.

PATIENTS AND METHODS

A cross-sectional design applied a deep learning model on structural brain networks obtained from 553 subjects (age, 59.2 ± 7.4 years; men, 35.6%). The model performance was evaluated with the Pearson's correlation coefficient (R) and probability of absolute error less than standard deviation (PAE

RESULTS

We achieved a meaningful R (up to 0.74) and PAE

CONCLUSION

A deep learning method can assess the association of brain network characteristics with OSA severity and daytime sleepiness and specify the relevant brain connectivity.

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Key Words

• convolutional neural network
• daytime sleepiness
• diffusion tensor imaging
• obstructive sleep apnea
• structural brain network

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MESH Headings Collapse

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Sleep structure and electroencephalographic spectral power of middle-aged or older adults: Normative values by age and sex in the Korean population

The fine structure of sleep electrocortical activity reflects health and disease. The current study provides normative data for sleep structure and electroencephalography (EEG) spectral power measures derived from overnight polysomnography (PSG) and examines the effect of age and sex among Korean middle-aged and older adults with or without obstructive sleep apnea (OSA). We analysed home PSG data from 1,153 adult participants of an ongoing population-based cohort study, the Korean Genome and Epidemiology Study. Sleep stages were visually scored and spectral power was measured on a single-channel EEG (C4-A1). We computed spectral power for five frequency ranges. The EEG power was reported in relative (%) and log-transformed absolute values (µV² ). With ageing, the proportion of N1 sleep increased, whereas N3 decreased, which is more noticeable in men than in women. The amount of N3 was relatively low in this cohort. With ageing, relative delta power decreased and alpha and sigma power increased for the whole sleep period, which was more pronounced during REM sleep in non-OSA. For men compared with women, relative theta power was lower during REM and sigma and beta were higher during N1 sleep. The differences of relative powers by age and sex in OSA were comparable to those in non-OSA. In a community-based Korean population, we present normative data of sleep structure and spectral power for middle-aged or older adults of a non-Caucasian ethnicity. The values varied with age and sex and were not influenced by sleep apnea.

A longitudinal observational population-based study of brain volume associated with changes in sleep timing from middle to late-life

STUDY OBJECTIVES

Sleep behaviors are related to brain structure and function, but the impact of long-term changes in sleep timing on brain health has not been clearly addressed. The purpose of this study was to examine the association of longitudinal changes in sleep timing from middle to late-life with gray matter volume (GMV), an important marker of brain aging.

METHODS

We enrolled 1798 adults (aged 49-82 years, men 54.6%) who underwent magnetic resonance imaging (MRI) between 2011 and 2014. Midsleep time (MST) on free days corrected for sleep debt on workdays was adopted as a marker of sleep timing. Data on MST were available at the time of MRI assessment and at examinations that were given 9 years earlier (2003-2004). Longitudinal changes in MST over the 9-year period were derived and categorized into quartiles. Subjects in quartile 1 were defined as "advancers" (MST advanced ≥ 1 h) while those in quartile 4 were defined as "delayers" (MST delayed ≥ 0.2 h). Quartiles 2-3 defined a reference group (MST change was considered modest). The relationship of GMV with MST changes over 9 years was investigated.

RESULTS

Nine-year change in MST were significantly associated with GMV. Compared to the reference group, advancers had smaller GMVs in the frontal and temporal regions. A delay in MST was also associated with smaller cerebellar GMV.

CONCLUSIONS

In middle-to-late adulthood, the direction of change in MST is associated with GMV. While advancers and delayers in MST tend to present lower GMV, associations appear to differ across brain regions.

Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during continuous positive airway pressure

Study Objectives

Sleep-disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. High loop gain (HLG) is a driving mechanism of central sleep apnea or periodic breathing. This study presents a computational approach that identifies “expressed/manifest” HLG via a cyclical self-similarity feature in effort-based respiration signals.

Methods

Working under the assumption that HLG increases the risk of residual central respiratory events during continuous positive airway pressure (CPAP), the full night similarity, computed during diagnostic non-CPAP polysomnography (PSG), was used to predict residual central events during CPAP (REC), which we defined as central apnea index (CAI) higher than 10. Central apnea labels are obtained both from manual scoring by sleep technologists and from an automated algorithm developed for this study. The Massachusetts General Hospital sleep database was used, including 2466 PSG pairs of diagnostic and CPAP titration PSG recordings.

Results

Diagnostic CAI based on technologist labels predicted REC with an area under the curve (AUC) of 0.82 ± 0.03. Based on automatically generated labels, the combination of full night similarity and automatically generated CAI resulted in an AUC of 0.85 ± 0.02. A subanalysis was performed on a population with technologist-labeled diagnostic CAI higher than 5. Full night similarity predicted REC with an AUC of 0.57 ± 0.07 for manual and 0.65 ± 0.06 for automated labels.

Conclusions

The proposed self-similarity feature, as a surrogate estimate of expressed respiratory HLG and computed from easily accessible effort signals, can detect periodic breathing regardless of admixed obstructive features such as flow limitation and can aid the prediction of REC.

Sleep staging from electrocardiography and respiration with deep learning

STUDY OBJECTIVES

Sleep is reflected not only in the electroencephalogram but also in heart rhythms and breathing patterns. We hypothesized that it is possible to accurately stage sleep based on the electrocardiogram (ECG) and respiratory signals.

METHODS

Using a dataset including 8682 polysomnograms, we develop deep neural networks to stage sleep from ECG and respiratory signals. Five deep neural networks consisting of convolutional networks and long- and short-term memory networks are trained to stage sleep using heart and breathing, including the timing of R peaks from ECG, abdominal and chest respiratory effort, and the combinations of these signals.

RESULTS

ECG in combination with the abdominal respiratory effort achieved the best performance for staging all five sleep stages with a Cohen's kappa of 0.585 (95% confidence interval ±0.017); and 0.760 (±0.019) for discriminating awake vs. rapid eye movement vs. nonrapid eye movement sleep. Performance is better for younger ages, whereas it is robust for body mass index, apnea severity, and commonly used outpatient medications.

CONCLUSIONS

Our results validate that ECG and respiratory effort provide substantial information about sleep stages in a large heterogeneous population. This opens new possibilities in sleep research and applications where electroencephalography is not readily available or may be infeasible.

HIV Increases Sleep-based Brain Age Despite Antiretroviral Therapy

STUDY OBJECTIVES

Age-related comorbidities and immune activation raise concern for advanced brain aging in people living with HIV (PLWH). The brain age index (BAI) is a machine learning model that quantifies deviations in brain activity during sleep relative to healthy individuals of the same age. High BAI was previously found to be associated with neurological, psychiatric, cardiometabolic diseases, and reduced life expectancy among people without HIV. Here, we estimated the effect of HIV infection on BAI by comparing PLWH and HIV-controls.

METHODS

Clinical data and sleep EEGs from 43 PLWH on antiretroviral therapy (HIV+) and 3,155 controls (HIV-) were collected from Massachusetts General Hospital. The effect of HIV infection on BAI, and on individual EEG features, was estimated using causal inference.

RESULTS

The average effect of HIV on BAI was estimated to be +3.35 years (p < 0.01, 95% CI = [0.67, 5.92]) using doubly robust estimation. Compared to HIV- controls, HIV+ participants exhibited a reduction in delta band power during deep sleep and rapid eye movement sleep.

CONCLUSION

We provide causal evidence that HIV contributes to advanced brain aging reflected in sleep EEG. A better understanding is greatly needed of potential therapeutic targets to mitigate the effect of HIV on brain health, potentially including sleep disorders and cardiovascular disease.

Current trends in flow cytometry automated data analysis software

Automated flow cytometry (FC) data analysis tools for cell population identification and characterization are increasingly being used in academic, biotechnology, pharmaceutical, and clinical laboratories. The development of these computational methods is designed to overcome reproducibility and process bottleneck issues in manual gating, however, the take-up of these tools remains (anecdotally) low. Here, we performed a comprehensive literature survey of state-of-the-art computational tools typically published by research, clinical, and biomanufacturing laboratories for automated FC data analysis and identified popular tools based on literature citation counts. Dimensionality reduction methods ranked highly, such as generic t-distributed stochastic neighbor embedding (t-SNE) and its initial Matlab-based implementation for cytometry data viSNE. Software with graphical user interfaces also ranked highly, including PhenoGraph, SPADE1, FlowSOM, and Citrus, with unsupervised learning methods outnumbering supervised learning methods, and algorithm type popularity spread across K-Means, hierarchical, density-based, model-based, and other classes of clustering algorithms. Additionally, to illustrate the actual use typically within clinical spaces alongside frequent citations, a survey issued by UK NEQAS Leucocyte Immunophenotyping to identify software usage trends among clinical laboratories was completed. The survey revealed 53% of laboratories have not yet taken up automated cell population identification methods, though among those that have, Infinicyt software is the most frequently identified. Survey respondents considered data output quality to be the most important factor when using automated FC data analysis software, followed by software speed and level of technical support. This review found differences in software usage between biomedical institutions, with tools for discovery, data exploration, and visualization more popular in academia, whereas automated tools for specialized targeted analysis that apply supervised learning methods were more used in clinical settings.

Impact of Catheter Ablation on Sleep Quality and Relationship Between Sleep Stability and Recurrence of Paroxysmal Atrial Fibrillation After Successful Ablation: 24-Hour Holter-Based Cardiopulmonary Coupling Analysis

Background

Sleep fragmentation and sleep apnea are common in patients with atrial fibrillation (AF). We investigated the impact of radio‐frequency catheter ablation (RFCA) on sleep quality in patients with paroxysmal AF and the effect of a change in sleep quality on recurrence of AF.

Methods and Results

Of 445 patients who underwent RFCA for paroxysmal AF between October 2007 and January 2017, we analyzed 225 patients who had a 24‐hour Holter test within 6 months before RFCA. Sleep quality was assessed by cardiopulmonary coupling analysis using 24‐hour Holter data. We compared cardiopulmonary coupling parameters (high‐frequency coupling, low‐frequency coupling, very‐low‐frequency coupling) before and after RFCA. Six months after RFCA, the high‐frequency coupling (marker of stable sleep) and very‐low‐frequency coupling (rapid eye movement/wake marker) was significantly increased (29.84%–36.15%; P<0.001; and 26.20%–28.76%; P=0.002, respectively) while low‐frequency coupling (unstable sleep marker) was decreased (41.25%–32.13%; P<0.001). We divided patients into 3 tertiles according to sleep quality before RFCA, and the risk of AF recurrence in each group was compared. The second tertile was used as a reference; patients with unstable sleep (Tertile 3) had a significantly lower risk of AF recurrence (hazard ratio [HR], 0.32; 95% CI, 0.12–0.83 for high‐frequency coupling; and HR, 0.22; 95% CI, 0.09–0.58 for low‐frequency coupling).

Conclusions

Sleep quality improved after RFCA in patients with paroxysmal AF. The recurrence rate was significantly lower in patients who had unstable sleep before RFCA. These results suggest that RFCA can influence sleep quality, and sleep quality assessment before RFCA may provide a risk marker for recurrence after RFCA in patients with paroxysmal AF.

Association of Sleep Electroencephalography-Based Brain Age Index With Dementia

IMPORTANCE

Dementia is an increasing cause of disability and loss of independence in the elderly population yet remains largely underdiagnosed. A biomarker for dementia that can identify individuals with or at risk for developing dementia may help close this diagnostic gap.

OBJECTIVE

To investigate the association between a sleep electroencephalography-based brain age index (BAI), the difference between chronological age and brain age estimated using the sleep electroencephalogram, and dementia.

DESIGN, SETTING, AND PARTICIPANTS

In this retrospective cross-sectional study of 9834 polysomnograms, BAI was computed among individuals with previously determined dementia, mild cognitive impairment (MCI), or cognitive symptoms but no diagnosis of MCI or dementia, and among healthy individuals without dementia from August 22, 2008, to June 4, 2018. Data were analyzed from November 15, 2018, to June 24, 2020.

EXPOSURE

Dementia, MCI, and dementia-related symptoms, such as cognitive change and memory impairment.

MAIN OUTCOMES AND MEASURES

The outcome measures were the trend in BAI when moving from groups ranging from healthy, to symptomatic, to MCI, to dementia and pairwise comparisons of BAI among these groups.

FINDINGS

A total of 5144 sleep studies were included in BAI examinations. Patients in these studies had a median (interquartile range) age of 54 (43-65) years, and 3026 (59%) were men. The patients included 88 with dementia, 44 with MCI, 1075 who were symptomatic, and 2336 without dementia. There was a monotonic increase in mean (SE) BAI from the nondementia group to the dementia group (nondementia: 0.20 [0.42]; symptomatic: 0.58 [0.41]; MCI: 1.65 [1.20]; dementia: 4.18 [1.02]; P < .001).

CONCLUSIONS AND RELEVANCE

These findings suggest that a sleep-state electroencephalography-based BAI shows promise as a biomarker associated with progressive brain processes that ultimately result in dementia.

Prevalence of Undiagnosed Sleep Apnea in Patients With Atrial Fibrillation and its Impact on Therapy

OBJECTIVES

This study sought to evaluate the proportion of patients with atrial fibrillation (AF) who also have undiagnosed sleep apnea and examine the impact of its diagnosis on adherence to sleep apnea therapies.

BACKGROUND

Sleep apnea is a modifiable risk factor for AF. However, the proportion of patients with AF who also have undiagnosed sleep apnea and the impact of its diagnosis on therapy have not been well studied.

METHODS

This prospective study included 188 consecutive patients with AF without a prior diagnosis of sleep apnea who were scheduled to undergo AF ablation. Participants underwent home sleep apnea testing, completed a sleep apnea screening questionnaire (STOP-BANG [Snoring; Tiredness, Fatigue, or Sleepiness During the Daytime; Observation of Apnea and/or Choking During Sleep; Hypertension; Body Mass Index >35 kg/m²; Age >50 Years; Neck Circumference >40 cm; and Male Sex]) and were followed for ≥2 years to evaluate the impact of diagnosis on therapy.

RESULTS

Home sleep apnea testing was positive in 155 of 188 patients (82.4%); among those 155, 127 (82%) had a predominant obstructive component and 28 (18%) had mixed sleep apnea with a 15.2 ± 7.4% central component. Sleep apnea severity was mild in 43.8%, moderate in 32.9%, and severe in 23.2%. The sensitivity and specificity of a STOP-BANG questionnaire were 81.2% and 42.4%, respectively. In a multivariate analysis, STOP-BANG was not predictive for sleep apnea (odds ratio: 0.54; 95% confidence interval: 0.17 to 1.76; p = 0.31). Therapy with continuous positive airway pressure ventilators was initiated in 73 of 85 patients (85.9%) with moderate or severe sleep apnea, and 68 of the 73 patients (93.1%) remained complaint after a mean follow-up period of 21 ± 6.2 months.

CONCLUSIONS

Sleep apnea is exceedingly prevalent in patients with AF who are referred for ablation, with a large proportion being undiagnosed due the limited predictive value of sleep apnea symptoms in this AF population. Screening for sleep apnea resulted in high rate of long-term continuous positive airway pressure adherence.

Altered structural brain network resulting from white matter injury in obstructive sleep apnea

STUDY OBJECTIVES

To assess, using fractional anisotropy (FA) analysis, alterations of brain network connectivity in adults with obstructive sleep apnea (OSA). Abnormal networks could mediate clinical functional deficits and reflect brain tissue injury.

METHODS

Structural brain networks were constructed using diffusion tensor imaging (DTI) from 165 healthy (age 57.99 ± 6.02 years, male 27.9%) and 135 OSA participants (age 59.01 ± 5.91 years, male 28.9%) and global network properties (strength, global efficiency, and local efficiency) and regional efficiency were compared between groups. We examined MRI biomarkers of brain tissue injury using FA analysis and its effect on the network properties.

RESULTS

Differences between groups of interest were noted in global network properties (p-value < 0.05, corrected), and regional efficiency (p-value < 0.05, corrected) in the left middle cingulate and paracingulate gyri, right posterior cingulate gyrus, and amygdala. In FA analysis, OSA participants showed lower FA values in white matter (WM) of the right transverse temporal, anterior cingulate and paracingulate gyri, and left postcentral, middle frontal and medial frontal gyri, and the putamen. After culling fiber tracts through WM which showed significant differences in FA, we observed no group difference in network properties.

CONCLUSIONS

Changes in WM integrity and structural connectivity are present in OSA participants. We found that the integrity of WM affected brain network properties. Brain network analysis may improve understanding of neurocognitive deficits in OSA, enable longitudinal tracking, and provides explanations for specific symptoms and recovery kinetics.

1008 Brain Age Based on Sleep Encephalography is Elevated in HIV+ Adults on ART

Introduction

Sleep EEG is a promising tool to measure brain aging in vulnerable populations such as people with HIV, who are high risk of brain aging due to co-morbidities, increased inflammation, and antiretroviral neurotoxicity. Our lab previously developed a machine learning model that estimates age from sleep EEG (brain age, BA), which reliably predicts chronological age (CA) in healthy adults. The difference between BA and CA, the brain age index (BAI), independently predicts mortality, and is increased by cardiovascular co-morbidities. Here, we assessed BAI in HIV+ compared to matched HIV- adults.

Methods

Sleep EEGs from 43 treated HIV+ adults were gathered and matched to controls (HIV-, n=284) by age, gender, race, alcoholism, smoking and substance use history. We compared BAI between groups and used additional causal interference methods to ensure robustness. Individual EEG features that underlie BA prediction were also compared. We performed a sub-analysis of BAI between HIV+ with or without a history of AIDS.

Results

After matching, mean CA of HIV+ vs HIV- adults were 49 and 48 years, respectively (n.s.). The mean HIV+ BAI was 3.04 years higher than HIV- (4.4 vs 1.4 yr; p=0.048). We found consistent and significant results with alternative causal inference methods. Several EEG features predictive of BA were different in the HIV+ and HIV- cohorts. Most notably, non-REM stage 2 sleep (N2) delta power (1-4Hz) was decreased in HIV+ vs. HIV- adults, while theta (4-8Hz) and alpha (8-12Hz) power were increased. Those with AIDS (n=19, BAI=4.40) did not have significantly different BAI than HIV+ without AIDS (n=23, BAI=5.22). HIV+ subjects had higher rates of insomnia (56% vs 29%, p&lt;0.001), obstructive apnea (47% vs 30%, p=0.03), depression (49% vs 23%, p&lt;0.001), and bipolar disorder (19% vs 4%, p&lt;0.001).

Conclusion

HIV+ individuals on ART have excess sleep-EEG based brain age compared to matched controls. This excess brain age is partially due to reduction in delta power during N2, suggesting decreased sleep depth. These results suggest sleep EEG could be a valuable brain aging biomarker for the HIV population.

Support

This research is supported by the Harvard Center for AIDS Research HU CFAR NIH/NIAID 5P30AI060354-16.

0662 Hybrid Therapies to Improve Sleep Apnea Management

Introduction

A one-size fits all approach to sleep apnea management, as is promoted by insurance requirements, pervades the field of sleep medicine but does not address individual differences in disease phenotype or treatment tolerance or attempt to achieve meaningful targets for adherence or disease optimization. Continuous positive airway pressure (CPAP) is considered to be the gold standard treatment for sleep apnea, yet CPAP nonadherence rates remain high (estimates at &gt; 30%) while usage goals (at least 4 hours/night) and therapeutic success targets (machine detected AHI &lt; 5) allow for substantial residual disease to persist. Hybrid therapy, combining mandibular advancement device (MAD) and positive airway pressure (PAP), has demonstrated additive effects on lowering the AHI, ODI, and therapeutic PAP pressure in severe OSA patients with pressure intolerance. This analysis explores the impact of hybrid therapy on treatment adherence and optimization, and identifies patient and data characteristics suggestive of benefit from combined therapies.

Methods

In a retrospective analysis, we reviewed the demographic data, medical histories, home sleep test, diagnostic and therapeutic attended polysomnography results, and PAP device settings and data (including usage, leak, residual event index, and waveforms) pre-and post-hybrid approach, in patients treated with hybrid therapy in our multidisciplinary academic sleep disorders clinic from 2014-2019.

Results

Hybrid therapies utilized include simultaneous (MAD worn together with PAP), alternating (MAD and PAP separately over parts of or on alternating nights), and anchoring (MAD to maintain mouth closure and jaw stability to minimize leak). Preliminary analysis (N=30) shows that hybrid therapy compared to PAP alone improves PAP adherence, lowers residual AHI, minimizes periodic breathing, reduces aerophagia, and lowers therapeutic PAP pressure in these patients. Patient and data characteristics suggestive of benefit include high loop gain sleep apnea, complex apnea, mouth breathing, and position dominance.

Conclusion

Individualizing treatment by combining therapies can result in improved PAP tolerance, usage, and disease control.

Support

 

0758 Quantification of Late REM Periods in Patients With Prolonged Sleep Duration

Introduction

Evaluation of hypersomnia includes polysomnography followed by mean sleep latency testing (MSLT). As consistent with guidelines as applied in most centers, the overnight portion of the study will be terminated to begin sleep latency testing. For patients with prolonged sleep duration, this interruption could result in REM sleep on nap testing that reflects continuation of their biological night, rather than abnormalities in REM sleep pressure/regulation.

Methods

We reviewed 42 consecutive extended (unrestricted) sleep studies for patients with a total sleep time greater than 600 minutes. For studies with sleep onset before midnight, we evaluated for REM period onset after 6AM, the number of REM periods after 6AM and 8AM, and the time of the final REM period onset.

Results

42 hypnograms were reviewed for patients undergoing evaluation of hypersomnia, median age 32 years (range 19-92) with a median total sleep time of 663 minutes (range 602-832), of these 28/42 (67%) had sleep onset before midnight (12 AM) and were included in the analysis. 27/28 (96%) of hypnograms reviewed had REM sleep after 6 AM, 24/28 (86%) had REM sleep after 8 AM, with the onset of the final REM period ranging from 4:46 AM-12:30 PM for patients with sleep onset time before midnight (12 AM).

Conclusion

These data suggest that termination of overnight polysomnography to complete mean sleep latency testing, as is standard in most sleep labs, may influence the presence of REM sleep on MSLT for patients with prolonged total sleep duration. These results may have implications for the interpretation of MSLT for patients with long sleep duration, and may explain why a given individual may test as type II narcolepsy or idiopathic hypersomnia unpredictably on repeat testing.

Support

Sleep Medicine Fellowship at BIDMC

0786 Non-24 Hour Sleep Wake Syndrome: A Cohort Analysis

Introduction

Although commonly described in the blind population, diagnosis in sighted individuals can be difficult due to perceived rarity and underlying co-morbid conditions. Our objective was to identify the characteristics of N24 rhythm individuals, and responses to varied treatments.

Methods

Patients were identified to have non-24-hour sleep wake syndrome (N24) via history, sleep diaries or digital logs, paired melatonin profiling as well as actigraphy through retrospective chart review at the Beth Israel Deaconess Medical Center, Sleep Disorders Clinic.

Results

37 patients were identified from 2007 to 2019 with N24 syndrome, BMI of 28, and 67% male. The mean age of onset was within the teenage years (16), and age at diagnosis of 35 years. Paired melatonin profiles (24-hour salivary melatonin, 3-hourly, separated by 7 days, in the subject’s own home) showed “movement”. Depression and anxiety were seen in 54% and 29% of the cohort respectively. 75% (28) of the patients had a treatment strategy involving light, and 54% (20) included melatonin. The combination of melatonin and light led to a clinical improvement in 41% of individuals under that regimen (17). Low dose lithium (8 subjects) enhanced melatonin/light responses. A strategy of combining the orexin antagonist suvorexant with melatonin or ramelteon (3 subjects) helped stabilize the circadian rhythm. Tasimelteon treatment has been initiated in 4 subjects.

Conclusion

These data suggest that while comorbid psychiatric conditions are prevalent, a significant proportion of the cohort did not have associated psychiatric disease. Patients reported onset of symptoms in the teenage years, however there was significant delay to diagnosis. Besides light/melatonin, orexin antagonism and low dose lithium may have benefits, but require more systematic assessments. Paired melatonin estimations could be considered as a definitive testing strategy.

Support

 

0704 Treatment-emergent Central Sleep Apnea Predicts Residual Respiratory Instability During Cpap Use At 6 Months

Introduction

The prevalence, severity, significance, and predictors of residual sleep apnea during use of continuous positive airway pressure (CPAP) remain uncertain. High loop gain is associated with or induces periodic breathing and central sleep apnea (CSA). Treatment-emergent CSA (TE-CSA) is often considered a transient phenomenon of no long-term clinical significance. Standard polysomnographic features were assessed as risk factors for high residual apnea during compliant CPAP use.

Methods

Patients with sleep apnea (mean AHI 53.6, SD:33/hour of sleep) who underwent split night studies were prospectively entered in a database. They were all treated with positive airway pressure at the Beth Israel Deaconess Medical Center (Boston) and tracked by the EncoreAnywhere system. Machine detected AHI (AHIm) was extracted for a week average at month 6. The manual scored AHI(AHIs) was calculated from the last waveform graph during every month. Logistic regression assessed predictors of elevated automated (5 or greater) or manual (10 or greater) residual events//hour of use.

Results

A total of 69 CPAP compliant (average of at least 4 hours) subjects were analyzed. Age: 59.5 (range 17-81), gender: 47/69 male. 44/69 had an elevated manual AHI, while 20/69 had an elevated autodetected AHI. The only predictors of high residual apnea were TE-CSA (5 or more central apneas and hypopneas/hour of sleep): Odds Ratio 3.6 (CI: 1.07-12-3), p: 0.39. and the treatment component arousal index: Odds Ratio 1.06 (CI: 1.01-1.11), p: 0.018. Machine estimated AHI, which under-detected events by a factor of 3 or more, was not associated with any measure.

Conclusion

Residual apnea is common after 6 months of compliant CPAP use, and the only predictors identified were TE-CSA and treatment component arousal index.

Support

This study is supported by American Academy of Sleep Medicine Foundation, Category-I award to RJT

Dietary intake of broccoli and the risk of cancer in the prostate, lung, colorectal, and ovarian cancer (PCLO) screening trial

e13560

Background: The cruciferous vegetable broccoli, are a good source of vitamins, minerals and fibre, as well as thiol phytochemicals (indole-3-carbinol), glucosinolates (isothiocyanates, its metabolite, sulforaphane), carotenoids (lutein and zeaxanthin) and flavonols (kaempferol). Laboratory and human biopsy studies have found that broccoli intake influenced epigenetic expression of genes via blockage of histone deacetylase which reduce inflammation and cancer growth. Clinically, a randomised control study reported dried broccoli extract (along with three other foods) influenced PSA progression in men with prostate cancer1. However, no preventative intervention studies in humans have been conducted and data from cohort studies are inconsistent for its influence on cancer incidence2,3. Methods: We analysed 49,104 people within the intervention arm of the 155,000 participant PLCO screening trial. Histological confirmed cases of any cancer were reported in 8,263 (16.83%) during the 11.5 year follow up. Broccoli consumption was assessed with a food frequency questionnaire (FFQ). Baseline characteristics were compared between broccoli consumption groups using Chi-square and Kruskal-Wallis tests. Cox regression models were used to assess the association between broccoli intake and cancer incidence. Results: Broccoli consumption was associated with reduced cancer incidence: HR 0.95 (CI 0.93-0.97, p < 0.001). This pattern persisted with adjustments for age, sex, race, education level and family history (HR 0.97, CI 0.96-0.99, p = 0.007) as well as smoking, BMI and alcohol consumption (HR 0.98, CI 0.96-0.99, p = 0.010). Conclusions: The study identified an association between increased broccoli consumption and reduced cancer risk. In practical terms, 15g of broccoli, or more, consumed per day (about a small cup) was associated with a 5% lower risk of cancer. Broccoli should continue to be included in healthy eating advice. This data supports the consideration of future prospective intervention studies investigating the role of broccoli as part of a cancer prevention programme. References 1. Thomas et al. The NCRN Pomi-T RCT. Prostate cancer & prostatic diseases (2014), 2,180. 2. Liu et al Cruciferous vegetables inversely linked with breast cancer: Breast (2013), 22;3,309. 3. Bosetti et al Cruciferous vegetables and cancer risk Ann Oncol (2012) 23(8);2198.

Dietary consumption of tea and the risk of prostate cancer in the prostate, lung, colorectal, and ovarian cancer screening trial

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Background: The popular beverage tea, brewed from infused leaves of camellia sinesis, contains non-phytoestrogenic polyphenols such as flavonoids, anthocyanidins, flavanols (epigallocatechin gallate); phenolic acids (ellagic acid) and stimulants (caffeine, theophylline). Laboratory studies report tea promotes antioxidant enzyme formation, slows cancer cell proliferation and unblocks apoptosis. Clinically, the Pomi-T randomised study reported tea extract (along with three other foods) reduced PSA progression in men with prostate cancer1. Evidence of prostate cancer prevention, however, from prospective cohort data is conflicting with one recent study even implying an increased risk2. Methods: We analysed 25,097 men within the intervention arm of the 155,000 participant PLCO screening trial. Histological confirmed cases of prostate cancer were reported in 3,088 men (12.3%) during the 11.5 year follow up. Tea consumption was assessed with a food frequency questionnaire (FFQ). Baseline characteristics were compared between groups using Chi-square and Kruskal-Wallis tests. Cox regression models were used to assess the association between tea intake and prostate cancer incidence. Results: Overall tea consumption was associated with a significantly lower risk of prostate cancer (p = 0.009). More precisely, the participants in the highest third of consumption group had a significantly lower risk compared to those in the lowest third (HR 1.16 (CI 1.05-1.29, p = 0.004). This pattern persisted with adjustments for age, sex, race and education level (p = 0.034), family history of cancer (p = 0.037). Those who never drank tea, however, had no statistical lower risk of prostate cancer compared to other groups (p = 0.501). Conclusions: Among tea drinkers, this data revealed a positive association between drinking tea and a reduced risk of prostate cancer. This data supports the consideration of future prospective intervention studies investigating the role of tea as part of a prostate cancer prevention programme. 1. Thomas et al. The NCRN Pomi-T RCT. Prostate cancer & prostatic diseases (2014), 2,180. 2. Reger et al. Dietary isoflavones and prostate cancer risk. Int J. Cancer (2017), 142; 4, 719.