bluuebunny/crossref_metadata_2025 huggingface dataset:
0935 An Investigation of ICU Ambient Noise Levels as a Potential Source for Poor Sleep Outcomes in a Community Hospital Setting
Authors: Iriana Sidney , Nicola Catalin , Nat Amritpal
Published: May 2023

Introduction

Patients in the intensive care unit (ICU) are subject to multiple necessary diagnostic and therapeutic interventions throughout the course of their treatment that contribute to sleep deprivation. These measures increase ambient noise, impacting patient morbidity and mortality by exacerbating confusion, ICU-related delirium, recovery time, and long term sequelae associated with Post-Intensive Care Syndrome. The World Health Organization suggests critically-ill patients not exceed exposure to sound levels higher than 35-40 decibels (dB). In this study, we measured ICU sound levels in a community hospital setting to support intervention with conservative bundle measures or behavior modification with a visual noise monitoring device.

Methods

This study took place over two months (October-November, 2021) in the critical care unit of St Agnes Medical Center in Fresno, CA. Ambient noise was monitored using a sound decibel meter (Gain Express Holdings, SLM-25) connected to recording software that measured the decibel levels at 1-minute intervals for 24 hours in three areas: two central stations (Station A and B) and one occupied patient room, equidistant to both central stations. The monitor data was exported to Microsoft Excel (2020 version; Microsoft Corp, Redmond, WA, USA) for analysis. Data from each sample was expressed as M±SE (95% confidence interval).

Results

Both central stations had average levels of 44.1dB± 4.7 and 48.0dB± 4.3, with a frequency range of 40-50 dB greater than 50% of the time. Station A had a frequency range of 50-60 dB approximately 11% of the time and Station B at 30% of the time. The occupied patient room had average levels of 48.0dB± 5.4, with frequency of 40-50 dB greater than 50%, and levels 50-60 dB greater than 30% of the time.

Conclusion

ICU’s with higher than recommended ambient sound levels may benefit from appropriate intervention such as visual noise monitoring devices or order-sets with protocols on equipment/staff phone volume, earplugs for patients, and limiting staff conversation to distances away from the bedside.

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0937 Developing a Protocol for Abbreviated Daytime Sleep Studies for Positive Airway Pressure Acclimation
Authors: Palmquist Aaron , El-Ali Mazen
Published: May 2023

Introduction

During the COVID pandemic, there was a decrease in the number of in lab positive airway pressure titration studies as well as in person DME company guided mask fittings due to COVID related restrictions. We wanted to assess the utility of daytime abbreviated sleep studies for PAP acclimation and mask fitting on patient compliance to therapy.

Methods

We assessed patients that were seen consecutively in our sleep lab for abbreviated sleep studies for positive airway pressure acclimation and mask fittings. Compliance rates 30 days prior to encounters were compared to compliance rates over the 30 days after the PAP acclimation and mask fitting took place.

Results

We found that the majority of patients that did undergo an encounter had improvement in their compliance rates. Despite this, we recognized that there was a lack of uniformity in the patient encounter as well as documentation as there was no formal protocol in place for physicians and sleep technicians to follow during these encounters. We sought to developed a new protocol that would allow for more uniform encounters and optimized patient care as well as clear and concise documentation of the encounter.

Conclusion

It is reassuring to see that daytime abbreviated PAP acclimation and mask fitting sessions do seem to improve compliance to therapy, but we recognize that the development of a new protocol is important to determine the clinical significance of this finding. This new protocol will allow us to improve the quality of care delivered to patients during in laboratory daytime abbreviated PAP acclimation and mask fitting sessions. With a new protocol in place we can reduce variables during the encounter and it will hopefully serve as a better platform to analyze how these sessions impact overall patient compliance to PAP therapy.

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0938 Energy Drink Consumption and Motivation related to Sleep and Sleepiness Among College Students: Possible Clinical Implications
Authors: Mastin David , Sanders Madison , Mathis Ashley , Sadiq Adielle , Shuler Molly , Moore Bruce , Peszka Jennifer
Published: May 2023

Introduction

We examined prevalence and motives of energy drink consumption (EDC) and the relationship between EDC and sleep in college students. A literature review revealed most common motives for EDC in the general population include promoting wakefulness, increasing energy, and enhancing alcohol’s effects. Excessive daytime sleepiness has been found the day after EDC and EDC increases sleep latency (persisting up to eight hours). We pursued these questions as well as clinical implications in a college population.

Methods

Recruited from introductory psychology courses, 162 students (age: M=22.06 years, SD=5.87) met course requirements or obtained extra credit for participation. Participants completed demographic information, the Epworth Sleepiness Scale (ESS), the Pittsburgh Sleep Quality Index (PSQI), questions regarding associated features of inadequate sleep, the Sleep Hygiene Index, and questions assessing weekly quantity and motivation for energy drink consumption.

Results

90.6% of participants consumed energy drinks (42% traditional consumer drinks such as RedBull, 77% tea/coffee, 66% soda). The most common motivations were taste (57%), completing projects (43%), staying alert (42%), preventing sleepiness (41%), and staying productive (37%). More EDC was significantly related to greater daytime dysfunction (PSQI-7) (r(156)=.158, p=.024), more maladaptive sleep hygiene (r(158)=.206, p=.005), poor sleep quality (PSQI-Global) r(155)=.154, p=.027), shorter sleep duration (r(155)=-.161, p=.022), and associated features of poor sleep (daytime sleepiness: r(158)=.280, p<.001, worry: r(158)=.139, p=.04, and reduced attention: r(158)=.174, p=.014). Logistic regression models showed for each one additional energy drink per day, increasing odds of sleepiness (OR=1.71, CI=1.21-2.40) poor sleep quality (OR=1.63, CI=1.04-2.55), and short sleep duration (OR=1.56, CI=1.14-2.13).

Conclusion

EDC, including coffee/tea, is widespread among college students and is most frequently motivated by liking the taste and promoting productivity/alertness. The active ingredient most frequently associated with energy drinks, caffeine, is viewed as relatively innocuous. Causality is unclear, however, these data suggest frequent EDC in college students is associated with sleep problems and may oppose motivations for use (e.g., one consumes ED to combat sleepiness and/or improve efficiency and instead finds attention and sleep impaired). Education and clinical guidance could help users understand associated risks and that changes in even one drink per day could lead to clinically important improvements.

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0940 Reductions in Use of Sleep Aids Following an App-Based Sleep Coaching Platform
Authors: Gorovoy Suzanne , Grandner Michael
Published: May 2023

Introduction

Use of sleep supplements and other sleep aids is increasing. Yet, many of these are not supported strategies for ameliorating sleep problems. Providing educational and behavioral strategies may reduce reliance on these substances.

Methods

Data were obtained from N=93 individuals who participated in the 12-week Sleep Reset program. The Sleep Reset program (Simple Habit, Inc.) includes ongoing text-based communication with coaches trained to support sleep behavior change, and a mobile app that includes a sleep diary, educational modules, mindfulness exercises, and progress tracking. Potential users are screened prior to entry and if they demonstrate a contraindicated medical or psychiatric problem, they were not admitted to the coaching program. If they demonstrate a likely sleep disorder (including insomnia disorder) they are referred for additional support. The coaching communications included information about basic sleep and circadian principles (e.g., sleep hygiene, behavioral scheduling, light exposure, relaxation) and techniques based on CBTI (e.g., stimulus control). Participants were asked if they used any “sleep aids” (which could include medications or melatonin/supplements) daily while in the program. Type of substance was not assessed. Data were binned by week, dichotomized as yes/no regarding any use in that week.

Results

Of the N=93 participants, N=46 (49%) indicated that they used “sleep aids” at least once in the first week. Among Sleep Reset participants who reported using sleep aids at least once in their first week in the program, use was reduced to N=13 (28.9%) by week 12. This difference was statistically significant (t(44)=10.4, p< 0.0005). Reductions from week 1 were already seen in week 2 (57.8%; t(44)=5.7, p< 0.0005). Another reduction was seen between weeks 3 and 4 (51.1% to 37.8%, t(44)=1.8, p=0.042), and a trend was seen between weeks 9 and 10 (35.6% to 26.7%, t(44)=1.7, p=0.052).

Conclusion

In an app-led sleep coaching program, those who used sleep aids in week 1 reduced use by 71.1% by the end of the 12-week period, with the largest reductions in the first week. Future controlled studies are needed to validate whether a sleep coaching program can reduce use of sleep aid such as supplements that may not be helpful.

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0944 Telemedicine (TM) to provide outpatient care for sleep disorders in complex neurological patients in an academic Medical Center
Authors: Tallavajhula Sudha
Published: May 2023

Introduction

Since the widespread adoption of telemedicine (TM) as a reimbursable option for the delivery of healthcare, (particularly clinic visits), the field of sleep medicine has been a beneficiary. In complex neurological patients, it was hypothesized that physical and cognitive constraints would limit the use of TM. This analysis was undertaken to evaluate patient care strategies in an academic neurology department based in a large metropolitan city

Methods

2964 adult patients who opted for neurology clinic visits via video TM in the last 6 months were included from electronic medical record review at the University of Texas Health Sciences Center in Houston. Of these, 557 were seen in sleep medicine specialty. A successful visit was defined as a simultaneous connection of at least 2 parties for a minimum duration of time defined by institutional guidelines. Patients were analyzed in age subgroups (< 30, 31-50, 51-70 and >70 years of age) as well as race (Asian, Black, Hispanic, White and Others). Neurological diagnoses in these patients included stroke, epilepsy, movement disorders, cognitive disorders, neuromuscular conditions and less commonly multiple sclerosis

Results

Sleep medicine providers comprise of 2/53 (3.7%) of the department’s clinical providers, but accounted for 18.7% of TM visits. 97% (182/186) of new patients and 95% (354/371) of established patients had successful TM visits. Among general neurology patients, these numbers were 89% and 88% respectively. There was a statistically significant difference between successful visits in the sleep medicine and overall neurology patient groups (p value 0.0003 for new, 0.0001 for established patients). Among sleep medicine patients, percentage failures were 2.9, 3.3, 4.1 and 3.9 among the respective age groups. Percentage failures across the respective racial groups were 0, 6.1, 4.8, 4.2 and 1.9. Reasons cited for unsuccessful visits included camera, microphone and general hardware failures. Surprisingly network failure was not reported

Conclusion

The success of telemedicine clinic visits for the management of sleep disorders is not impacted by physical and cognitive impairment in patients with complex neurological conditions. Further analysis to include success of sleep diagnostics and treatment of sleep disorders (start-to-finish pathway), via telemedicine in this complex population is underway

Support (if any)

None
0948 End-to-End utility of the Cardiopulmonary Coupling Sleep Spectrogram in Sleep Medicine
Authors: Barber Cameron , Chopra Sahil , Holzer Rena , Campbell Kimberly , Heckman Eric , Ahn Anjali , Thomas Robert
Published: May 2023

Introduction

Technology has improved the diagnosis and therapeutic tracking of sleep disorders, but remains fragmented. For example, the laboratory polysomnogram and home sleep apnea test is disconnected from the data available from therapy devices. Remote patient monitoring has focused more on apnea metrics rather than sleep quality. There is some value to a device or system which can be used for diagnosis, risk stratification, and tracking of clinical outcomes across different sleep disorders.

Methods

A method which offers the potential of end-to-end utility in sleep medicine is the cardiopulmonary coupling (CPC) spectrogram. Originally an ECG-base device, the current form is that of a Ring oximeter (finger) with an integrated activity monitor. The oximeter data is processed via Bluetooth in a smartphone, and then transferred to a Cloud-based analysis (www.sleepimage.com). The CPC analysis integrates heart rate variability and ECG or photoplethysmography-derived respiration. Outputs include a Sleep Quality Index and percentage of stable sleep (high frequency coupling which covaries with delta power on the electroencephalogram and is associated with blood pressure dipping), unstable sleep (low frequency coupling), an apnea-hypopnea index, oxygen desaturation index, heart rate profile across the night (dipping or non-dipping heart rate), total sleep time and sleep efficiency. Data from two clinical systems were used: Empower Sleep (an Internet-based “digital sleep clinic”) and Sleep Continuum (a sleep tracking service offered by Neurocare, Inc, in the Boston area).

Results

Data from over 500 patients across a range of sleep disorders show end-to-end utility of the SleepImage system. These include diagnosis of sleep apnea including multi-night recording, sleep apnea phenotyping (high loop gain and sleep fragmentation), remote patient monitoring during CPAP or oral appliance use, supportive information for diagnosis of hypersomnia, tracking medication effects (sodium oxybate, sedative-hypnotics, acetazolamide), sleep-wake instability in mood disorders and Long-Covid, impaired sleep quality in chronic fatigue syndrome and restless legs syndrome, off-label therapies for central sleep apnea (oxygen, acetazolamide, buspirone), and sleep fragmentation in Long-Covid and parasomnia. Examples from each of these clinical use cases will be shown.

Conclusion

The CPC-based SleepImage Ring system can provide complete diagnostic, phenotyping, and tracking functions.

Support (if any)

The Institute for Personalized Sleep Health, BIDMC, Empower Sleep
0949 Real-time acoustic apnea event detector by training a deep learning model with home noise added data
Authors: Le Linh , Kim Daewoo , Cho Eunsung , Jang Hyeryung , Reyes Roben Delos , Kim Hyunggug , Lee Dongheon , Yoon In-Young , Hong Joonki , Kim Jeong-Whun
Published: May 2023

Introduction

For diagnosis and management of Obstructive Sleep Apnea (OSA), long-term multi-night monitoring is crucial. Convenient detection of OSA at home is required for this purpose. Using sound recorded by smartphone can provide a convenient way to detect OSA. In this study, we present a sound-based OSA detection deep learning model that can detect OSA in real-time even in a home environment where various noises exist. The model is trained with home noise simulated sound to be robust for detecting home noises.

Methods

Two types of data were used for training and testing. The first type was sleep breathing sound data collected at the hospital while patients underwent a PSG. It included 1,154 and 297 nights recorded by a PSG microphone and a smartphone, respectively. We split them into 150 nights of smartphone data for testing and the rest for training. The second type was home noise data, which included 22,500 noises that might occur in a residential environment. The proposed acoustic apnea event detector inputs Mel spectrograms of sleep breathing sounds and outputs OSA event classes for each epoch (APNEA, HYPOPNEA, or NO-EVENT). The home noises were used to make the model robust to a noisy home environment. The performance of the prediction model was assessed by epoch-by-epoch prediction accuracy and OSA severity classification based on the apnea-hypopnea index (AHI).

Results

Our model achieved 86 % epoch-by-epoch agreement (0.75 in macro F1) for 3-class event detection task. The model had an accuracy of 92% for NO-EVENT, 84% for APNEA, and 51% for HYPOPNEA. Most misclassifications were made for HYPOPNEA, with 15% and 34% of HYPOPNEA being wrongly predicted as APNEA and NO-EVENT, respectively. The sensitivity and specificity of OSA severity classification (AHI ≥ 15) were 0.85 and 0.84, respectively.

Conclusion

Our study presents a real-time epoch-by-epoch OSA detector that works in a variety of noisy home environments. Based on this, additional research is needed to verify the usefulness of various multi-night monitoring and real-time diagnostic technologies in the home environment.

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0950 Sound-based Sleep Staging at Home Using Smartphone via Deep Learning
Authors: Tran Hai , Hong Jung Kyung , Jang Hyeryung , Jung Jinhwan , Kim Jongmok , Hong Joonki , Lee Minji , Kim Jeong-Whun , Kushida Clete , Lee Dongheon , Kim Daewoo , Yoon In-Young
Published: May 2023

Introduction

Daily sleep tracking at home is growing in demand as more and more people are aware of the significance of sleep. The objective of this study is to propose a sound-based sleep staging model based on deep learning that works well in home environments with recorded audio data from general smartphones.

Methods

Three different audio datasets were used. A labeled hospital dataset (PSG and audio, N=812) and an unlabeled home dataset (audio only, N=829) were used for training. A limited number of labeled sound data from home (PSG and audio, N=45) were used for testing. Our proposed HomeSleepNet has three components: (1) supervised learning using the labeled hospital data that trains the model to make correct predictions in hospital environments; (2) unsupervised domain adaptation (UDA), which used both the labeled hospital data and unlabeled home data, and transferred the sleep staging power from hospital domain to home domain by adversarial training; (3) unsupervised data augmentation for consistency training (UDC), which augmented hospital data by adding home noise and trained the model to make consistent predictions on original and augmented data. After all training, HomeSleepNet is expected to make robust sleep staging despite the home noise presence.

Results

HomeSleepNet achieved 76.2% accuracy on the sleep staging task in home environments for the 3-stage classification case (Wake, NREM, REM). Specifically, it correctly predicted 63.4% of wake, 83.6% of NREM sleep, and 64.9% of REM sleep. The contributions of UDA and UDC were demonstrated by the following results. The accuracy of the model trained without both was 69.2%. Either addition of UDA or UDC training to the model improved the performance, with increased accuracy of 69.3% for UDA and 73.5% for UDC. As expected, using both UDA and UDC (i.e., HomeSleepNet) achieved the best performance, with a 7% increase in accuracy compared to the model trained without both components.

Conclusion

To the best of our knowledge, this is the first sound-based sleep staging study conducted in home environments. Moreover, the sounds were recorded by commercial smartphones and not through professional devices. Our proposed model introduced a reliable and convenient method for daily sleep tracking at home.

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0951 Inter-Scorer Reliability between Somno-Art Software and 5 Sleep Centers
Authors: Viola Antoine , Thiesse Laurie , Staner Luc , Fuchs Gil , Roth Thomas , Schaffhauser Jean Yves , Saoud Jay , Luthringer Remy
Published: May 2023

Introduction

A number of studies have evaluated epoch-by-epoch agreement between 2 technologists in scoring individual sleep stage. Scoring for the specific sleep stages average agreement ranged from 20% to 90% in different studies. The goal of this study is to evaluate the validity of the Somno-Art analyses against a pool of scorers including validated automated system for scoring polysomnograms.

Methods

Sixty polysomnography recording nights, representative of clinical practice (participants who are healthy or suffering from obstructive sleep apnea [OSA], or insomnia or major depressive disorder [MDD]), were scored by 5 different sleep scoring centers and by the Somno-Art Software (total of 6 scorers). Intra-class correlation coefficient (ICC) and Wilcoxon Signed-Rank Test were calculated between each scorer and the average value of the 6 scorers. In addition, epoch-by-epoch agreements between scorers were analyzed.

Results

Somno-Art Software estimation of sleep efficiency, wake, N1+N2, N3 and REM sleep belonged to the interscorer range for the full dataset and the participant groups, except N3 sleep in OSA patients. Somno-Art Software tended to overestimate sleep latency with a significant difference to the average scoring for insomniacs (4.7±1.6 min). On the full dataset, Somno-Art Software had good or excellent ICC scores for all sleep parameters except N3 sleep (moderate score). 4-stages epoch-by-epoch agreement ranged between 78.5-88.7% for the visual scorers and 69.9-71.2% for Somno-Art Software. For the healthy participants, visual scorers agreed between 68.9 and 86.9%, while Somno-Art Software overlapped this range with an interscorer agreement between 62.0 and 71.4%.

Conclusion

Somno-Art solution provides results that are comparable to manual and automatic scoring for commonly used metrics in sleep medicine. It shows a robust interscorer reliability in the range of the 5 polysomnography scorers

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0954 CORRELATION OF PULSE RATE VARIABILITY (PRV) AND HEART RATE VARIABILITY (HRV) METRICS DURING SLEEP IN SUBJECTS SUSPECTED OF OSA
Authors: Tsai Chih-Wei , Gu Wenbo , Yeh Eric , Chen Pai-Lien , Leung Lydia , Cheung Cynthia , Wu I-Chen , Wu Jia-Rong , Strohl Kingman , Chiang Ambrose
Published: May 2023

Introduction

Whether photoplethysmography (PPG)-derived pulse rate variability (PRV) metrics can be surrogates for ECG-derived heart rate variability (HRV) is a decade-long debate. Very few studies have assessed the performance of PRV metrics in wearables. We aimed to evaluate the performance of time- and frequency-domain PRV metrics derived from the Belun Ring (BR) in subjects suspected of sleep apnea.

Methods

Using Pearson’s correlation coefficient (PCC), we retrospectively analyzed the relationship between concurrent BR-PRV and PSG ECG-HRV metrics (standard deviation of NN intervals [SDNN], root mean square of successive RR interval differences [RMSSD], percentage of successive RR intervals that differ by more than 50 ms [PNN50], HF [high frequency] power, LF [low frequency] power, VLF [very low frequency] power, and LF/HF ratio) in 73 subjects suspected of OSA. Subgroup analyses were performed based on demographic information, OSA, co-morbidities, and HR-affecting medication status.

Results

Age (SD) 50.1 (13.4); female 68%; black 52%; BMI (SD) 36.1 (9.7); 56% OSA; mean AHI (SD) 14.7 (17.3). Nine (12%) subjects had significant arrhythmias (defined as having any arrhythmias in ≥25% of all 12-second segments.) Key findings: There was a unitary linear relationship between BR PPG-pulse rate and ECG-heart rate in the overall group. In those without significant arrhythmias (N=64), PRV-SDNN, PNN50, HF, LF, and VLF had excellent correlations (PCC ≥0.90) with corresponding HRV metrics in all subgroups. PRV-RMSSD and PRV-LF/HF also had a strong correlation (PCC ≥0.80) with ECG HRV-RMSSD and HRV-LF/HF in all subgroups except for LF/HF in the diabetes group. In those with significant arrhythmias (N=9), PRV performed less well, with most metrics having PCC < 0.90 or wide CI, except for PNN50. All PRV metrics had PCCs ≥0.90 in subjects on HR-affecting medications except for LF/HF.

Conclusion

BR-PRV metrics can serve as surrogates for ECG-HRV in patients suspected of OSA who do not have significant arrhythmias. PRV-RMSSD and LF/HF may be less robust than the rest of the PRV metrics but still showed strong correlations in most subgroups. BR-PRV can be a useful clinical and research tool in assessing autonomic nervous system function.

Support (if any)

This study is supported by a Grant from Belun Technology Company
0956 Evaluation of a novel automated oxygen desaturation analysis
Authors: Zin Gaia , Swaenpoel Pauline , Verbraecken Johan , Wittevrongel Benjamin
Published: May 2023

Introduction

The oxygen desaturation index (ODI) quantifies the number of desaturations per hour of sleep and is a valuable parameter in diagnosing sleep-related breathing disorders. While oximetry alone is insufficient for an accurate diagnosis, it provides meaningful insights for Obstructive Sleep Apnea (OSA) and the ODI has been shown to correlate with the Apnea-Hypopnea Index (AHI). The close relationship between the ODI and other parameters is especially interesting for home-based sleep studies and/or screening, which typically use a limited set of sensors (but almost always include oximetry) and are becoming increasingly more prevalent. An accurate and automated tool for oximetry analysis will thus be paramount for the sleep clinician.

Methods

The current study aims to evaluate a novel automated solution for oxygen desaturation scoring, provided by Somnilog. We selected 20 overnight recordings, a mix of hospital- and home-based recordings from a dataset from the Antwerp University hospital and an internal database collected from several French sleep centers. The analyzed population (10 females, age 53.0±16.7 years old, BMI of 28.8±4.8 kg/m²) had a variety of diagnoses, including non-apneic snoring and central and obstructive sleep apnea. Each recording was also scored for oxygen desaturations by a sleep expert, using the AASM guidelines and a 3% drop criterion.

Results

The automated solution accurately detected desaturation events with a precision and recall of 0.97 and 0.96, respectively. The reported ODI had an intraclass correlation (ICC) of 0.99 with the index found by the expert. The difference in the number of events reported by the automated solution and the expert was not significant between the lab- and home-recorded patients (p=0.23). We furthermore validated the novel solution with another well-used commercial package and obtained similar performance metrics: precision and recall of 0.96 and ICC of 0.99.

Conclusion

The current study demonstrates the validity of the novel commercial package for oxygen desaturation scoring. The automated tool achieved near-perfect agreement with the sleep experts, and a similar performance to another existing solution in the market. The tool is robust for home-based recordings which are typically more artifact-prone, thereby supporting the increasing demand for out-of-centre overnight studies.

Support (if any)

n/a
0957 Sleeping for one week on a temperature-controlled mattress cover improves slow wave sleep, heart rate, and heart rate variability
Authors: Moyen Nicole , Ediger Tatiana , Hancock Erin , Holden Lucas , Kotzen Kevin , Irick Charles , He David
Published: May 2023

Introduction

Body temperature should be tightly regulated for optimal sleep. A decline in core temperature during sleep onset can increase slow wave sleep (SWS) and decrease heart rate (HR). Passive solutions such as high-heat capacity mattresses are difficult to maintain temperature control during sleep. Thus, we examined how sleeping on an active temperature-controlled mattress cover (TCMC; i.e., the Eight Sleep Pod) for one week affected sleep and cardiovascular health.

Methods

49 participants [24 men, 25 women; mean±SD (range): age = 34.4±11.5 (21.8-64.6) years] slept for 16 nights each (784 total nights) with TCMC temperature-control off (OFF) for the first week as baseline, TCMC temperatures on (ON) at their desired temperatures for the second week, and TCMC OFF for two nights. Participants wore a home sleep test device (HST) for eight nights total: four nights during each OFF and ON for ground truth sleep-staging. Participants wore a Fitbit device throughout the study to collect nightly HR and heart rate variability (HRV). Paired t-tests compared each participant’s sleep and HR/HRV for TCMC ON vs. OFF, separating for biological sex and TCMC temperature. A multiple linear regression was used to evaluate the percent change in SWS from OFF to ON.

Results

Four factors explained 64% of the variance in the percent change in SWS from OFF to ON (r2=0.64; P< 0.001): participants’ baseline SWS during OFF, age, average mattress-cover temperature, and sex. Men sleeping at cooler temperatures (< 26°C) increased SWS by 17 min (P=0.0001; cohen’s-d=0.65), decreased HR by 1.5 beats/minute (P=0.007, cohen’s-d=0.20), and increased HRV by 13% (P=0.045; cohen’s-d=0.23). Women’s sleep was unaffected by TCMC ON (all P>0.05); however, sleeping at warmer mattress-cover temperatures (>27°C) decreased HR by 1.5 beats/minute (P=0.021; cohen’s-d=0.18).

Conclusion

Sleeping on an active temperature-controlled mattress cover at cooler temperatures significantly improved SWS in males, especially those with below-average SWS at baseline and increasing age. One week of sleeping on the TCMC improved HR in both sexes similar to exercise-training.

Support (if any)

Eight Sleep, Inc.
0958 Use of a Hybrid Mattress Improves Objective and Perceived Sleep Outcomes
Authors: Danoff-Burg Sharon , Rus Holly , Burke Colin , Weaver Morgan , Carmon Kiara , Upadhyaya Devanshi , Ledesma Duvia Lara
Published: May 2023

Introduction

Previous research has shown that comfort, including comfort of the sleep surface, is essential to sleep quality. In addition to comfort, the structure and firmness of a mattress may also play a role when it comes to sleep quality. More empirical research is needed to establish the impact of particular mattresses on both objective and self-reported measures of sleep quality. This study compared sleep on a hybrid mattress to participants’ prior sleep on their original mattress.

Methods

Healthy adults (81% female, ages 25-67) who reported sleeping hot participated in a 10-week field study, using a pre-post intervention design. During the 4-week baseline period, participants used their regular mattress at home. During the 4-week intervention period, which occurred following a 2-week adjustment period, they used a Serta iSeries mattress at home. This hybrid mattress includes materials designed to help the user feel cool. Sleep was measured objectively using SleepScore Max every night and by daily and pre-post self-report. Multilevel regression and paired t-tests were used to test for statistical significance.

Results

There were over 1,400 nights of tracked sleep across 39 participants. Objective sleep measurements showed increased time in bed (+10 minutes, p=.001) and total sleep time (+14 minutes, p=.002), as well as increased REM, both in duration (+6 minutes, p=.004) and proportion of the night (p=.023). Improvements also were observed in two objective sleep quality measures: SleepScore (p=.002) and MindScore (p=002). Self-report measures revealed that the hybrid mattress felt cooler (p<.001) and more comfortable (p<.001). Improvements also were found for a variety of perceived sleep outcomes, including time to fall asleep, waking less often, spending less time awake, longer sleep duration, better sleep quality, and feeling more rested in the morning (ps<.05).

Conclusion

Objectively-measured sleep and self-reported sleep improved when using the hybrid mattress compared to healthy adults’ original mattresses. Furthermore, qualitative and quantitative self-report results suggested that the intervention was perceived as comfortable and felt cool. These perceptions likely are what led to more time in bed, which in turn led to the key sleep improvements.

Support (if any)

Mattress Firm INC
0964 Anxiety and Poor Sleep Quality are associated with Cortisol in University Students during the COVID-19 pandemic
Authors: Okun Michele , Sollenberger Alaric , Raval Foram , Dominguez Ahria , Dupy Cameron , Feliciano Leilani
Published: May 2023

Introduction

Students experience a disproportionate amount of stress. The COVID-19 pandemic exacerbated and introduced stressors rarely encountered by students, including quarantining, and switching to remote learning. Psychological stress, mood, and sleep issues are known to have a negative effect on a variety of physiological biomarkers of stress, especially cortisol and a less studied marker, dehydration, (e.g., urine specific gravity levels (USG)).

Methods

This cross-sectional study examined associations between psychological and physiological markers of stress in university students during the latter part of the COVID-19 pandemic. Students completed online questionnaires on stress, depression, anxiety (DASS-21), and sleep quality (PSQI), followed by home collection of saliva (8 samples for 2 days) and urine (first catch). Three cortisol indices were evaluated: CAR, diurnal slope, and AUCg. Urine specific gravity was assessed as a marker of dehydration. Bivariate correlations assessed associations and independent t-tests were used to compare the 25th and 75th percentiles on cortisol indices and dehydration levels.

Results

A total of 43 female students (22.7 ± 6.9 years old) completed the study. Levels of depression (70.7%), anxiety (75.8%), stress (90.2%) fell in the normal range. Sleep quality was poor (9.4 ± 2.8), but TST = 7.74 ± 1.2 hours and SE = 88.1 ± 1.0%. About 20% had symptoms of insomnia. There was a significant difference in AUCg between the 25th and 75th percentile of anxiety (t = -1.90, p = .037; 154.26 ± 17.0 vs 228.12 ± 35.0, ug/dL) indicating those with highest levels of anxiety had higher overall diurnal cortisol than those with lowest levels. Sleep quality was also significantly associated with AUCg. Those with poor sleep (PSQI > 5) had higher cortisol levels than those with good sleep (t = -2.17, p = .019; 236.4 ± 21.2 vs 120.1 ± 10.6 ug/dL). There were no significant associations between the psychological measures and USG levels.

Conclusion

Findings suggest that while stress, depression, and anxiety levels may have leveled off 1 ½ years into the pandemic, those with residual high anxiety and poor sleep quality may continue to be at risk for poor health due to high levels of cortisol.

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0965 Changes in sleep status and the effects of obesity indexed by sex before and after COVID-19: a 2-year follow-up cohort study
Authors: Baek Younghwa , Jung Kyoungsik , Kim Jimi , Lee Siwoo
Published: May 2023

Introduction

The COVID-19 pandemic has changed people’s lifestyles. This study aimed to examine the changes in sleep status before and after COVID-19 according to sex in middle-aged Koreans, and investigate the effect of sleep status on obesity indicators.

Methods

This prospective cohort study was the Korean Medicine Daejeon Citizen Cohort study and included participants aged 30-59. A baseline survey was conducted from 2017 to 2019 before COVID-19, and a follow-up survey from 2020 to 2021 after the outbreak of COVID-19. This study analyzed the data of 1436 people, with 422 males and 1014 females completing follow-up. Using the Pittsburgh Sleep Quality Index (PSQI) questionnaire with validity, we evaluated sleep, sleep duration, sleep quality score, and group (categorized into good sleep and poor sleep, based on a PSQI score of 5). Body mass index (BMI), waist circumference (WC), body fat mass (BFM), and percent body fat (PBF) were measured to determine obesity indices. For changes in sleep status before and after COVID-19, Fisher's exact test and Paired t-test were conducted. ANCOVA was performed to determine changes in the obesity index according to sleep quality groups in the baseline survey, which was age-adjusted. All analyses were stratified by sex.

Results

Sleep duration decreased significantly by 13.88 minutes for males and 11.23 minutes for females to 6.54 hours (SD=1.2) and 6.48 hours (SD=1.2), respectively. Sleep quality scores increased by 1.03 points and 0.7 points for males and females, respectively, to 5.2 points and 5.7 points, respectively. The distribution of poor sleep increased from 25.6% before COVID-19 to 38.6% after COVID-19 for males (p < 0.001), and from 36.5% before COVID-19 to 43.1% after COVID-19 for females (p< 0.001). Significant changes in the obesity index were observed according to the sleep quality group only in males. In the male poor PSQI group, WC (Δ3.4 cm), BFM (Δ1.3 kg), and PBF (Δ1.2%) increased significantly more than those in the good PSQI group indices changes.

Conclusion

COVID-19 has negatively impacted sleep, and such sleep changes have contributed to an increase in the obesity index for males.

Support (if any)

This was funded by the Korea Institution of Oriental Medicine, KSN2023120.
0967 Do Pre-existing Sleep Disorders Worsen Long COVID Fatigue and Brain Fog?
Authors: Carter Isabelle , Strohl Kingman , Rosenberg David , Patil Susheel , Torer Juliane , Griggs Stephanie , Decker Michael , May Anna
Published: May 2023

Introduction

Long COVID is common after COVID-19 infection and leads to functional limitations with most reporting substantial symptom burden from fatigue. Symptoms in sleep disorders are attributed to inflammatory dysregulation and may predispose to fatigue expression. We hypothesize prior diagnoses of sleep disorders are associated with severity of long COVID fatigue.

Methods

A retrospective EMR review was performed of 210 consecutive adult patients (9/2021 to 2/2022) referred at least 3 months after COVID-19 infection seen in a new community-based long COVID clinic. The intake process collected demographics, past medical history, functional questionnaires, and symptom checklists. Primary outcome was Fatigue Severity Scale (FSS) score. Sleep disorders were evaluated as a composite of self-reported insomnia, sleep disordered breathing, and restless legs syndrome as well as subset analyses of each disorder. Secondary outcome was physical functioning measured by ECOG performance scale. Linear analyses were used for FSS and ECOG analyses. Adjustors included age, sex, body mass index (BMI), and whether patient had COVID-19 hospitalization.

Results

Cohort was female (66.2%), aged 51.6±SD14.4 yrs, BMI 29.8 [IQR 26.2, 37.7]). Prior chronic insomnia was present in 9%, sleep disordered breathing in 23%, and RLS in 4%; the pooled history of sleep disorders was 30%. Fatigue was reported in 76% with mean FSS score of 5.44 [interquartile range, IQR: 4.11,6.44]; 48% reported brain fog. The interval between acute COVID infection and clinic evaluation was 10.4±5.34 months and had no association to FSS severity (r = 0.07, p = 0.30). Sleep disorders in aggregate, insomnia, and restless legs syndrome had no associations with fatigue or functional status. Sleep disordered breathing had an association to fatigue in unadjusted (β = 0.68, 95% confidence interval, [CI]:0.13,1.24), but not adjusted models (β = 0.53, 95%CI: -0.06,1.13). Sleep disorders both in aggregate and evaluated individually had no associations to brain fog.

Conclusion

A prior history of sleep disorders contributed little to post-COVID fatigue reported in those presenting to a community-based Long COVID clinic.

Support (if any)

TEAMS institutional award, Department of Medicine, University Hospitals of Cleveland, VA CSRD IK2CX001882
0968 Relationship between Breakthrough COVID-19 Infections in Vaccinated Patients and Sleep Disturbances
Authors: Punj Mantavya , Desai Aakash , Hashash Jana , Farraye Francis , Castillo Pablo
Published: May 2023

Introduction

The COVID-19 pandemic caused by SARS-CoV-2 continues to result in significant morbidity and mortality on a global scale. Prior studies have examined the effectiveness of non-COVID vaccines in setting of sleep disturbances. This study evaluated data from a large national database to examine the relationship between the risk of breakthrough COVID-19 infections in patients with certain sleep related disturbances.

Methods

Real-time search and analysis using the TriNetX platform to evaluate risk of COVID-19 breakthrough infections (BTI) for patients having ICD-10 diagnoses relating to insomnia, circadian rhythm disorders, and inadequate sleep. The sleep disorder and control cohorts underwent propensity matching including factors for age, gender, race, ethnicity, and multiple co-morbid conditions.

Results

Of 24,720 patients identified as having a sleep disturbance relating to insomnia, circadian rhythm disorder, or inadequate sleep, 815 (3.2%) were found to have a developed a BTI. There was a significant increased risk of BTI noted between the sleep disorder and control cohorts (adjusted odds ratio (aOR) of 1.40, 95% confidence interval (CI) of 1.23-1.58). Subgroup analysis showed an elevated risk for BTI receiving two doses (aOR 1.53, 95% CI 1.24 – 1.89) versus three doses (aOR 1.45, 95% CI 1.24 – 1.69). Patients with the sleep disturbance were not found to be at an increased risk of hospitalization, intubation, death, or composite outcome of death and intubation.

Conclusion

The presence of having a diagnosis of insomnia, circadian rhythm disorder, or inadequate sleep was associated with increased risk of COVID-19 breakthrough infection.

Support (if any)
0970 The impact of the COVID-19 pandemic on healthcare academicians’ sleep quantity and quality
Authors: Macheledt Kait , Berge Jerica , Spencer Sade , Pusalavidyasagar Snigdhasmrithi
Published: May 2023

Introduction

The COVID-19 pandemic globally disrupted workplaces, including at academic institutions. Many clinical and research activities were paused and, when clinics and laboratories reopened, operations and workflows had changed. These changes were often stressful. We examined the changes in the quality and quantity of sleep for University of Minnesota health sciences faculty to understand the impact of these disruptions.

Methods

A cross-sectional survey of 291 University of Minnesota health sciences faculty was conducted over the months of April-June 2021 aimed at gaining insight into their lived experiences during the COVID-19 pandemic. The survey included validated measures and general questions developed using survey best practices. Information on personal demographics (gender, race, caregiver status etc.), academic demographics (rank, track, school, etc.), reflective sleep quantity (e.g. hours) and reflective sleep quality were collected through self-report. Associations between gender (e.g. men/women), sleep quantity and quality pre-COVID-19 and during COVID-19 were examined using summary statistics as well as the chi-square test and T-test with statistical significance set to < 0.05.

Results

In general, the study population reported fewer hours of sleep since the COVID-19 pandemic began (µ=6.96) in comparison to before the COVID-19 pandemic (µ=7.23), t(285) = -5.04, p<.001, 95% CI [-0.37.-0.16]. Survey respondents also reported that their quality of sleep was “moderately” restful (N=160) prior to the pandemic but only “somewhat” restful (N=120) during the pandemic, X2(9)=123.59, p<.0001. Demographics (gender and race), caregiver status, and academic attributes (rank, track, school) will be reported.

Conclusion

The COVID-19 pandemic impacted academicians’ sleep quality and quantity. Understanding these changes is important for promoting wellbeing and resilience in academic healthcare.

Support (if any)

N/A
0972 The Utility of CSF Orexin Testing in Investigating for Narcolepsy Type-1 in a Patient with Diencephalic Mass
Authors: Cheng Christopher , Avidan Alon
Published: May 2023

Introduction

Narcolepsy type 1 (NT1) is characterized by pathologic hypersomnolence, REM intrusion phenomena, including cataplexy, and orexin deficiency. The diagnosis of NT1 is established based on the presence of bone fide cataplexy and supportive PSG and MSLT testing which requires patients to achieve sufficient sleep duration and regularity and discontinue centrally acting medications that might alter REM sleep. In cases where there is a high index of suspicion for NT1, CSF orexin deficiency is helpful to support the diagnosis of NT1. This is particularly true when PSG-MSLT are not feasible, CNS medication cannot be discontinued, or cataplexy cannot be validated.

Report of case(s)

A 16 year old girl presented for evaluation of excessive daytime sleepiness in the setting of suprasellar germinoma which was resected and treated with chemoradiation at age 11. She subsequently developed panhypopituitarism and severe hypersomnolence in the setting of sleep-wake schedule irregularities, variability of sleep duration, refractory delayed sleep phase disorder, and snoring. She reported episodic weakness in the setting of negative triggers, which was atypical for cataplexy. Her medications included modafinil, amphetamine-dextroamphetamine, and the SSRI fluoxetine. Physical examination depicted normal airways. Epworth Sleepiness Scale score was 18. Screening polysomnography showed a sleep efficiency of 78%, sleep latency of 46.5 minutes, REM latency 2 hours, AHI of 0/hr, and periodic limb movements of 35/hr without arousals. While the REM latency on polysomnography was inconsistent with NT1, the clinical history of a diencephalic mass and chemoradiation was suggestive of secondary NT1. She was unable to proceed with PSG-MSLT due to her psychiatrist's advice against discontinuing her SSRI and her difficulty in maintaining sleep-wake regularity. An evaluation for CSF orexin was performed establishing a normal level of 337 pg/mL (reference level of 200 pg/mL in healthy individuals), ruling out orexin deficiency /narcolepsy type 1. The patient was subsequently improved with wake-promoting antidepressants and light therapy in the AM.

Conclusion

This case illustrates the value of CSF orexin testing in the setting of diencephalic lesions in patients unable to undergo formal narcolepsy testing.

Support (if any)