Purpose: To evaluate the short and long term cross sectional associations between COVID19 infection and multidimensional sleep health. Methods: Data from the COVID19 Outbreak Public Evaluation (COPE) initiative were used to examine the association between a novel multidimensional sleep health measure (COPE Multidimensional Sleep Health Scale, CMSHS) modeled from the RuSATED instrument and (1) COVID19 infection and (2) post acute sequelae of SARS CoV 2 infection (PASC). Results: Data from 11,326 respondents were used for this study. The cohort was comprised of 51% women, 61% non-Hispanic White, and 17% Hispanic adults. COVID 19 infection was more prevalent among participants who had not received a booster vaccination (55.4% vs. 30.2%, p<0.001); the number of comorbid conditions was higher among those who had been infected (2.2% vs. 1.7%, p<0.001). Participants with COVID 19 infection had significantly lower CMSHS scores indicative of worse sleep health compared with uninfected participants (3.52 ± 1.37 vs. 3.78 ± 1.30; p < 0.001). Participants with PASC had lower CMSHS scores in comparison to those without PASC (2.72 ± 1.30 vs. 3.82 ± 1.28, p<0.001). In adjusted models, a progressive decline in CMSHS scores was observed over 12 months following infection (3.52 ± 0.05 vs. 2.98 ± 0.04; p < 0.001 for <1 month vs. 6 to 12 months). Conclusion: Compared with uninfected individuals, multidimensional sleep health was worse among persons who had a COVID 19 infection. Individuals with PASC had greater and persistent reductions in sleep health for up to 12 months post-infection. ### Competing Interest Statement MDW reports institutional support from the US Centers for Disease Control and Prevention National Institutes of Occupational Safety and Health and Delta Airlines as well as consulting fees from the Fred Hutchinson Cancer Center and the University of Pittsburgh. MEC reported personal fees from Nychthemeron L.L.C. research grants or gifts to Monash University from WHOOP Inc. Hopelab Inc. CDC Foundation and the Centers for Disease Control and Prevention. SMWR reported receiving grants and personal fees from Cooperative Research Centre for Alertness Safety and Productivity receiving grants and institutional consultancy fees from Teva Pharma Australia and institutional consultancy fees from Vanda Pharmaceuticals Circadian Therapeutics BHP Billiton and Herbert Smith Freehills. SFQ has served as a consultant for Teledoc Bryte Foundation Jazz Pharmaceuticals Summus Apnimed SleepRes and Whispersom. He receives compensation as editor for Frontiers in Sleep. RR serves on medical or scientific advisory boards to Ouraring Ltd. Equinox Fitness Clubs the Institute for Healthier Living Abu Dhabi A-Life Alife S.r.l. Somnum Pharmaceuticals Takeda Pharmaceuticals and Willow Health. CAC serves as the incumbent of an endowed professorship provided to Harvard Medical School by Cephalon Inc. and reports institutional support for a Quality Improvement Initiative from Delta Airlines and Puget Sound Pilots education support to Harvard Medical School Division of Sleep Medicine and support to Brigham and Womens Hospital from Jazz Pharmaceuticals PLC Inc Philips Respironics Inc. Optum and ResMed Inc. research support to Brigham and Womens Hospital from Axome Therapeutics Inc. Dayzz Ltd. Peter Brown and Margaret Hamburg Regeneron Pharmaceuticals Sanofi SA Casey Feldman Foundation Summus Inc. Takeda Pharmaceutical Co. LTD Abbaszadeh Foundation CDC Foundation educational funding to the Sleep and Health Education Program of the Harvard Medical School Division of Sleep Medicine from ResMed Inc. Teva Pharmaceuticals Industries Ltd. and Vanda Pharmaceuticals personal royalty payments on sales of the Actiwatch 2 and Actiwatch Spectrum devices from Philips Respironics Inc personal consulting fees from Axome Inc. Bryte Foundation With Deep Inc. and Vanda Pharmaceuticals honoraria from the Associated Professional Sleep Societies LLC for the Thomas Roth Lecture of Excellence at SLEEP 2022 from the Massachusetts Medical Society for a New England Journal of Medicine Perspective article from the National Council for Mental Wellbeing from the National Sleep Foundation for serving as chair of the Sleep Timing and Variability Consensus Panel for lecture fees from Teva Pharma Australia PTY Ltd. and Emory University and for serving as an advisory board member for the Institute of Digital Media and Child Development the Klarman Family Foundation and the UK Biotechnology and Biological Sciences Research Council. CAC has received personal fees for serving as an expert witness on a number of civil matters criminal matters and arbitration cases including those involving the following commercial and government entities Amtrak Bombardier Inc. C&J Energy Services Dallas Police Association Delta Airlines/Comair Enterprise Rent-A-Car FedEx Greyhound Lines Inc./Motor Coach Industries/FirstGroup America PAR Electrical Contractors Inc. Puget Sound Pilots and the San Francisco Sheriffs Department Schlumberger Technology Corp. Union Pacific Railroad United Parcel Service Vanda Pharmaceuticals. CAC has received travel support from the Stanley Ho Medical Development Foundation for travel to Macao and Hong Kong equity interest in Vanda Pharmaceuticals With Deep Inc and Signos Inc. and institutional educational gifts to Brigham and Womens Hospital from Johnson & Johnson Mary Ann and Stanley Snider via Combined Jewish Philanthropies Alexandra Drane DR Capital Harmony Biosciences LLC San Francisco Bar Pilots Whoop Inc. Harmony Biosciences LLC Eisai Co. LTD Idorsia Pharmaceuticals LTD Sleep Number Corp. Apnimed Inc. Avadel Pharmaceuticals Bryte Foundation f.lux Software LLC Stuart F. and Diana L. Quan Charitable Fund. CACs interests were reviewed and are managed by the Brigham and Womens Hospital and Mass General Brigham in accordance with their conflict-of interest policies. The remaining authors have no relevant financial interests to disclose. ### Funding Statement This work was supported by the Centers for Disease Control and Prevention. Dr. M. Czeisler was supported by an Australian–American Fulbright Fellowship, with funding from The Kinghorn Foundation. The salary of Drs. C. Czeisler, Robbins and Weaver were supported, in part, by NIOSH R01 OH011773 and NHLBI R56 HL151637. Dr. Robbins also was supported in part by NHLBI K01 HL150339. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All procedures were in accordance with the ethical standards of Monash University Human Research Ethics Committee (Study #24036) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained electronically from all individual participants included in the study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

RATIONALE:Advanced polysomnographic (PSG) metrics reflecting the physiological causes and consequences of sleep apnea may enable precision medicine in research settings, but their feasibility in routine clinical practice has yet to be demonstrated. OBJECTIVE:Assess (1) the generalizability of PSG metrics from research to clinical cohort, and (2) their associations with a broad range of comorbid diseases, many of which have not been previously examined. METHODS:PSG metrics including endotypes (eg, loop gain) and physiological burdens (eg, hypoxic burden) were estimated from diagnostic polysomnographs of 6,427 participants at Mass General Brigham (MGB; Boston, MA). Comorbid conditions analyzed from MGB's medical record system included 9 representative cardio-metabolic and respiratory diseases, as well as 408 prevalent diseases. Associations were assessed using modified Poisson and LASSO regression. RESULTS:The sample included 62% females, age: 52.9 ± 16.8 years, and apnea-hypopnea index (AHI) 21.4 ± 15.9 events/hr. Associations between endotypes and demographics/obesity-related factors were consistent with prior observational studies (median difference in β = 0.03SD). After adjusting for AHI, older age was associated with lower heart rate (-0.40SD) and arousal burdens (-0.23SD), while higher BMI was associated with increased hypoxic burden (0.25SD). Having demonstrated that there is reasonable concordance with published data, our subsequent analysis identified distinct and clinically meaningful associations between advanced PSG metrics and comorbid conditions. Specifically, elevated loop gain, ventilatory burden, and hypoxic burden were associated with hypertension, diabetes, and renal failure; increased ventilatory instability was associated with cardiovascular disease; and reduced collapsibility and ventilatory instability with chronic airway obstruction. Even after LASSO-based selection, no single PSG metric consistently predicted risk across all comorbidities; ventilatory instability showed the most associations among endotypic traits, and heart rate burden among physiological burdens, underscoring the heterogeneity of OSA pathophysiology. CONCLUSIONS:Phenome-wide analyses of a large clinical cohort demonstrate the real-world feasibility and clinical relevance of extracting advanced PSG metrics, supporting their potential to identify personalized, mechanism-specific intervention targets for sleep apnea.

Obstructive sleep apnea (OSA) is associated with a wide range of comorbidities, but the extent to which these follow predictable, age-dependent patterns is not well understood. Identifying such patterns could provide insight into OSA heterogeneity and its links to physiological measures of OSA. We trained age-dependent topic models (ATM) on longitudinal electronic health records from 36,426 patients with OSA in the Mass General Brigham Biobank. ATM organizes incident diagnoses into distinct comorbidity "topics," whose age-specific disease loadings represent predictive patterns linking related diagnoses across the life course. We applied the trained model to compute individual-level topic scores in independent data: a cohort of 11,689 OSA cases and 22,695 matched controls, and a cohort of 6,220 patients with polysomnography (PSG)-derived physiological measures. We identified 19 distinct age-dependent comorbidity profiles, all significantly associated with OSA case status (FDR-adjusted p<0.05). Topics reflected recognizable clusters including metabolic, neuropsychiatric, and immune-mediated conditions, and several were distinguished by age-of-onset of key comorbidities, such as early- vs late-onset asthma. Seventeen of the 19 topics were significantly associated with at least one of 13 PSG-derived physiological measures, including associations between cardiometabolic topics and the apnea-hypopnea index, sleep apnea specific hypoxic burden, and respiratory event-specific heart rate burden. These findings indicate that age-dependent comorbidity patterns distinguish meaningful OSA subtypes with differing prognoses and endophenotype associations. ATM offers insight into complex OSA comorbidity and suggests that age-informed, topic-based stratification may improve individualized risk assessment, interpretation of PSG findings, and targeting of clinical interventions.

Abstract Introduction High continuous positive airway pressure (CPAP) adherence is central to the effective management of obstructive sleep apnea (OSA). However, considerable variability in adherence persists that cannot be explained by known factors such as sleepiness, disease severity, or socio-economic characteristics. Preliminary analyses of endotypic traits as predictors of CPAP adherence have provided conflicting results. To overcome gaps in the literature related to the heterogeneity of data sources and designs, this study uses real-world clinical data to comprehensively analyze OSA endotypes and burdens on CPAP adherence at multiple timescales of compliance. Methods Participants consisted of patients at Brigham and Women’s Faulkner Hospital with available polysomnography and CPAP adherence data for the first 30 nights (n=1,754) and first year (n=1,527) of use. Endotypes and burdens were calculated from polysomnography recordings using PUPBeta. Adherence was defined as using the device for at least 4 hours on at least 70% of nights. Bivariate logistic regressions were performed between CPAP adherence at both time scales and each endotype/burden metric. An elastic net Cox proportional hazards analysis was performed, including all endotypes and burdens as potential predictors of night to last CPAP use and censoring at one year. Both analyses adjusted for sex, ancestry, BMI, age, and duration between PSG and CPAP dates. Results No endotypes/burdens were associated with 30-day adherence. However, each one-unit increase in ventilatory response to arousal (VRA) was associated with a 1.007-fold increased odds (95% CI=1.003-1.012) of one-year CPAP adherence. Increased hazard of stopping CPAP was associated with: (per one-standard deviation increase) lower arousal threshold (HR=0.851; 95% CI=0.752-0.971), and higher loop gain (HR=1.123; 95% CI=1.009-1.354) and circulatory delay (HR=1.088; 95% CI=1.009-1.218). Conclusion One-year but not 30-day adherence, as well as CPAP discontinuation rate, were associated with several OSA mechanistic traits. Overall, these findings underscore CPAP adherence associations with OSA mechanistic heterogeneity. The results may help inform risk assessments of patients’ likelihood of CPAP therapy adherence based on OSA endotypes and, secondarily, support strategies to improve overall adherence. Support (if any) American Academy of Sleep Medicine 338-SR-24, NIH/NHLBI R01 HL15380.

Background:Obstructive sleep apnea (OSA) is associated with a wide range of comorbidities, but large-scale phenome-wide analyses in clinical biobanks remain under-reported. In this study, we identified common comorbidities enriched in patients with OSA, tested the temporality of these associations, and analyzed relevant associations with summary sleep recording data. Methods:48,251 participants with OSA in the Mass General Brigham healthcare system were identified using a natural language processing phenotyping algorithm and/or evidence of an elevated apnea-hypopnea index (AHI). Controls were matched (2:1) on demographics, body mass index (BMI), and healthcare utilization. Associations with 358 incident and 563 cross-sectional diseases were tested using Modified Poisson regression, adjusting for covariates. Sensitivity analyses examined timing by binning data in years relative to the first OSA diagnosis. Selected laboratory results were obtained based on associated diseases. Associated diseases were tested with sleep recording statistics (n ≤18,348). Findings:179 incident and 421 cross-sectional diseases were associated with OSA at Bonferroni significance. 37 diseases had Bonferroni-significant sex interactions. Several associations were significant years before the first recorded OSA diagnosis. Four red blood cell laboratory measures were significant ten years prior to the first diagnosis. One incident and 47 cross-sectional diseases were associated with the AHI and/or chronic hypoxemia. Interpretation:Obstructive sleep apnea is associated with enrichment of hundreds of diseases, several of which are supported by orthogonal polysomnographic evidence. Leveraging early signs of OSA in clinical data may help to identify at-risk patients.

Obstructive sleep apnea poses significant health risks, warranting effective treatment strategies. Continuous positive airway pressure therapy is widely used, but assessing treatment effectiveness remains complex. This study aimed to establish reference values for mean disease alleviation (MDA) in a large cohort treated with continuous positive airway pressure. Data from the Apnea Positive Pressure Long-term Efficacy Study were analyzed. A total of 352 participants underwent 6 months of continuous positive airway pressure therapy, with adherence and efficacy monitored objectively. MDA, calculated as the product of treatment efficacy and percentage adherence, was assessed. Age and sex differences in MDA and its association with sleepiness (Epworth Sleepiness Scale scores > 10) were evaluated using logistic regression and linear regression models. The mean MDA in the 352 participants at 6 months was 53.85

Obstructive sleep apnea (OSA) is a prevalent disorder associated with numerous comorbidities, including cardiometabolic and neuropsychiatric diseases. Heterogeneity in presentation and multi-morbidity complicates disease management. This analysis adopts a validated data-driven approach, age-dependent topic modeling (ATM; PMID 37814053), to group OSA-related diagnoses into longitudinal trajectories, elucidating comorbidity progression and its relationship with OSA. We analyzed longitudinal electronic health records (EHR) from 38,600 OSA patients in the Mass General Brigham (MGB) system using 411 diagnoses previously associated with OSA. OSA status was ascertained with a validated algorithm incorporating EHR and available polysomnography (PSG). ATM analysis then grouped incident EHR diagnoses into age-dependent patterns (topics) optimized to predict future diagnoses from any given age. Model weights were used to calculate individualized risk scores for each topic, which were standardized and tested for association with OSA in a separate validation cohort of 7,774 OSA cases and 15,294 controls, matched 2:1 on propensity score (accounting for age, sex, BMI, ancestry, and healthcare utilization), and further adjusted for residual confounding. ATM identified 17 distinct age-dependent comorbidity topics in OSA patients. Of these, 14 were significantly associated (p< 0.05/17) with higher scores in OSA cases, representing greater risk for diverse conditions including neuropsychiatric, cardiometabolic, and respiratory disorders. The strongest associations were observed for: 1. A neuropsychiatric topic (β=0.43, p< 1.88e-222), progressing from mood disorders (early-adulthood) to insomnia (middle-age) and cognitive decline (old-age). 2. A respiratory-cardiovascular topic (β=0.35, p< 1.35e-147), progressing from chronic respiratory infections (childhood) to hearing loss and hypertension (middle-age), and cardio-vascular disease (old-age). For example, a 60-year-old with prior mood disorders and incident insomnia is expected to score high in the neuropsychiatric topic, a scenario observed more frequently in OSA, suggesting risk of later cognitive decline. This study highlights associations between OSA and distinct multimorbidity patterns and suggests age-dependent comorbidity progression as a framework for understanding comorbidity burden in OSA. These findings have potential to guide targeted management strategies and interventions. Future work will integrate longitudinal data and OSA endotypes to further investigate disease heterogeneity and explore physiologically relevant pathways. This study was supported by NIH R01HL153805 and the AASM Foundation 338-SR-24.

Obtaining an adequate amount of sleep is necessary for optimal alertness, performance, and safety. Inability to get sufficient sleep can be due to work type or schedule, socioeconomic factors, timing of the sleep period, or the presence of sleep disorders. Insufficient sleep contributes to decreased performance, increased accidents, decreased productivity, and higher healthcare costs. Certain occupations influence the sleep duration or timing for workers. Safety in some occupations is influenced by the adequacy and quality of sleep and thus protocols are required to reduce potential errors. Implementation of a fatigue management program (FMP) can improve productivity and safety. Including a sleep disorders screening program can further maximize the benefits of an FMP.

Poor sleep quality and excessive daytime sleepiness are commonly reported by individuals with cystic fibrosis. The potential impact of comorbid sleep-disordered breathing (SDB), particularly obstructive sleep apnea (OSA), has not been extensively studied in the CF population. At present, there are no specific recommendations available to help clinicians identify patients with CF who are at increased risk of sleep disorders. Home sleep apnea testing using a validated peripheral arterial tonometry (PAT) device may offer an accurate diagnosis of OSA in a more convenient and low-cost method than in-lab polysomnography. In this single-center study of 19 adults with CF, we found an increased prevalence of OSA among individuals with CF compared to general population estimates. Although associations with an FEV < 70% predicted and a modified Mallampati score ≥ 3 were observed, these odds ratios did not reach statistical significance, likely reflecting limited power in this small pilot sample. There was no association found between the self-reported presence of nocturnal cough or snoring and OSA. We also found no association between OSA and abnormal scores on commonly used, validated sleep questionnaires, suggesting that CF-specific scales may be needed for effective screening in the CF clinic.

OBJECTIVE:To examine the long-term impact of Coronavirus disease-2019 (COVID-19) on sleep patterns and the prevalence of sleep disorders and to increase public health awareness of long-term COVID-19. MATERIAL AND METHODS:Using the Massachusetts General Brigham Research Patient Data Registry, Severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) positive patients were surveyed about their sleep patterns before and after the viral infection. Information related to comorbid conditions and medications was obtained through chart review. RESULTS:Two hundred and forty-six completed surveys were analyzed. Average age was 53.3±16.3 years, and they were predominantly non-hispanic white (84.1%) and female (74.3%). The mean body mass index (kg/m2) was 29.9±6.9, and a greater proportion were non-smokers (63.2%). After COVID-19, there was an increase in the percentage of participants reporting difficulty initiating (39±49% vs. 31±46% prior to COVID-19 infection P = 0.01). Similarly, the participants reported difficulty in maintaining sleep after COVID infection (57% vs. 43% prior to infection P < 0.001). Additionally, there was an increase in the use of sleep aids (30% vs. 24% before the infection P = 0.003). The participants also reported a decrease in feeling rested and an increase in the need for napping (58% vs. 36%, P < 0.0001) and (27% vs. 40%, P < 0.0001) respectively. The sleep symptoms persisted beyond 12 months in 28% of the participants. CONCLUSION:SARS-CoV-2 infection had negative effects on sleep, and a significant proportion of adults experienced insomnia and daytime sleepiness beyond 12 months after recovering from the initial infection.

Despite improvement in US healthcare, racial and ethnic minorities have experienced health disparities including sleep health disparities. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We searched three electronic databases (PubMed, Embase, Web of Science) from the earliest available date to September 2023 using the keywords sleep inequity, gender, race, and socioeconomic status. Studies published in languages other than English were excluded. Meta analysis, case reports, and editorials were also excluded. Medical Subject Headings (MeSH) of the National Library of Medicine and Keywords were used to search PubMed, Embase, and Web of Science. We also searched the reference lists of the selected articles. Using the search strategy, we identified 52 articles. After excluding 11 duplicate studies, we screened 41 articles. The studies not relevant to our search were further excluded and we finally assessed 16 full-text articles. Twelve of the 16 studies were cross sectional and 4 were prospective studies. Compared to Whites, increased prevalence of shorter sleep duration was found among people of diverse racial background. Similarly, individuals with lower socioeconomic status have been shown to have a disproportionate increase in insufficient sleep (1.62 times). Additionally, compared to White women, Black women were more likely to report short sleep (37% vs. 27%) and were less likely to obtain the recommended amount of sleep (52% vs. 64%). This review demonstrates disparities in sleep based on race/ethnicity as well as the effect of gender and socioeconomic status on the quality of sleep.

STUDY OBJECTIVES Machine learning (ML) models have been employed in the setting of sleep disorders. This review aims to summarize the existing data about the role of ML techniques in the diagnosis, classification, and treatment of sleep related breathing disorders. METHODS A systematic search in MedLine, EMBASE, and Cochrane databases through January 2022 was performed. RESULTS Our search strategy revealed 132 studies that were included in the systematic review. Existing data show that ML models have been successfully used for diagnostic purposes. Specifically, ML models showed good performance in diagnosing sleep apnea using easily obtained features from the electrocardiogram, pulse oximetry and sound signals. Similarly, ML showed good performance for the classification of sleep apnea into obstructive and central categories, as well as predicting apnea severity. Existing data show promising results for the ML-based guided treatment of sleep apnea. Specifically, the prediction of outcomes following surgical treatment and optimization of continuous positive airway pressure therapy, can be guided by ML models. CONCLUSIONS The adoption and implementation of ML in the field of sleep related breathing disorders is promising. Advancements in wearable sensor technology and ML models can help clinicians predict, diagnose and classify sleep apnea more accurately and efficiently.

STUDY OBJECTIVES Philips Respironics issued a voluntary recall of positive airway pressure (PAP) devices used to treat obstructive sleep apnea in June 2021. We surveyed sleep medicine clinicians from the American Academy of Sleep Medicine membership to assess the impact of the recall on clinicians and patients. METHODS One hundred and thirty-six clinicians participated between June 2022 and November 2022. Participants reported their treatment recommendations for patients impacted by the recall; their patients' behaviors regarding the recall; the recall's impact on themselves as clinicians and on their patients; and the approximate time their patients were waiting for a replacement device. RESULTS Clinicians most commonly reported first learning about the recall from Philips (25.0%), while patients most commonly first heard about the recall from news sources (34.5%). Most clinicians (62.4%) reported that they recommended patients continue using a recalled device. In comparison, only 9.3% of clinicians reported encouraging patients to stop using their recalled device. Clinicians reported that patients continued (59.9%) treatment with their recalled device, while 26.5% stopped treatment. Clinicians reported that over one-third of their patients are still waiting for a replacement machine. 86.8% of clinicians reported their stress levels were impacted due to the recall and 91.5% of clinicians reported the recall impacted their patients' health and well-being. 83.3%of clinicians reported the recall impacted their patients' trust in medicine. CONCLUSIONS Clinicians reported that the Philips recall impaired the vast majority of their patients' health and trust in medicine and that many patients are still waiting for replacement devices.

Objectives: Involuntary job loss is a stressful life event that can result in changes in nutritional intake. Both insomnia and obstructive sleep apnea (OSA) also are associated with alterations in dietary intake, but the extent to which this occurs in those who have experienced involuntary job loss is unclear. This study assessed nutritional intake in recently unemployed persons with insomnia and obstructive sleep apnea in comparison to those without a sleep disorder. Methods: Participants from the Assessing Daily Activity Patterns through Occupational Transitions (ADAPT) study were screened for sleep disorders using the Duke Structured Interview for Sleep Disorders. They were classified as having OSA, acute or chronic insomnia or no sleep disorder. Dietary data was collected using United States Department of Agriculture Multipass Dietary recall methodology. Results: A total of 113 participants had evaluable data and were included in this study. The cohort was comprised mainly of women (62%) and 24% were non-Hispanic white. Participants with OSA had a higher BMI compared with no sleep disorder (30.6 ± 9.1 vs 27.4 ± 7.1 kg/m2, p≤0.001). Those with acute insomnia had significantly decreased consumption of total protein (61.5 ± 4.7 vs. 77.9 ± 4.9 g, p≤0.05) and total fat (60.0 ± 4.4 vs. 80.5 ± 4.6 g, p≤0.05). Among the participants with chronic insomnia, there was little overall difference in nutrient consumption compared to the no sleep disorder group although there were several gender specific differences. There were no overall differences between participants with OSA in comparison to no sleep disorder, but women consumed less total fat (89.0 ± 6.7 vs. 57.5 ± 8.0 g, p≤0.01). The Healthy Eating Index of all groups was below the average value of Americans. Conclusion: Unemployed persons compared to those with sleep disorders differ in their consumption of major nutrients; the dietary composition of those with acute insomnia exhibited the greatest divergence. Additionally, the overall nutritional intake of recently unemployed persons is poor.

The aim of this retrospective analysis is to determine the most frequently prescribed medications for the treatment of NREM parasomnias and evaluate reported outcomes. We performed a retrospective chart review of all patients with NREM parasomnia diagnosed within Brigham and Women’s Hospital (BWH) clinics examining the date of diagnosis, date of starting therapy, comorbidities, type of medication prescribed, and the reported change in symptoms or side effects at follow-up visits. From 2012 to 2019, 110 patients (59 females, 51 male) at BWH clinics received a diagnosis of NREM parasomnia, including sleepwalking and night terrors. The mean age was 44. Comorbidities included obstructive sleep apnea (OSA) (46%), periodic limb movement syndrome (PLMS) (13%), insomnia (19%), Restless leg syndrome (RLS) (9%), epilepsy (4%), and REM behavior disorder (RBD) (9%). Initial treatment strategies include behavioral and safety counseling only (34%), pharmacological treatment (29%), treatment of any comorbidity (28%), and combined treatment of any of the above (9%). Improvement was reported with: treatment of OSA (n = 23 52% reported improvement), melatonin (n = 8, improvement reported by 88%.,benzodiazepine (n = 7, improvement reported by 57%). Treating comorbid conditions is a frequent treatment strategy, often associated with symptom improvement. The pharmacologic treatment most commonly included melatonin and benzodiazepines. Comprehensive management should include behavioral and safety recommendations, assessment of comorbid conditions, and individually tailored pharmaceutical treatment.

To examine how sleep quality and sleep duration affect caloric intake among those experiencing involuntary job loss. Methods Adequate sleep and self-reported dietary recall data from the Assessing Daily Activity Patterns through Occupational Transitions (ADAPT) study was analyzed. Primary sleep indices used were total sleep time, time spent in bed after final awakening, and sleep quality as measured by the Daily Sleep Diary (DSD). Mean Energy consumption (MEC) was the primary nutritional index. Secondary indices included diet quality using the Health Eating Index 2015 (HEI), and self-reported intake of protein, carbohydrates and fats. Results The study participants were comprised mainly of women (61%) and non-Hispanic white. The participants had at least 2 years of college education and mean body mass index of 30.2±8.08 (kg/m 2 (). The average time in bed was 541.8 (9 hrs) ±77.55 minutes and total sleep time was 461.1 (7.7 hrs) ±56.49 minutes. Mean sleep efficiency was 91±6%, self-reported sleep quality was 2.40±0.57 (0-4 scale, 4 = very good), and minutes earlier than planned morning awakening were 14.36±24.15. Mean HEI score was 47.41±10.92. Although the MEC was below national average for both men and women, male sex was associated with higher MEC. In a fully adjusted model sleep quality was positively associated with MEC. Conclusion Daily overall assessments of sleep quality among recently unemployed persons were positively associated with mean energy consumption. Additionally, the diet quality of unemployed persons was found to unhealthier than the average American and consistent with the relationship between poor socioeconomic status and lower diet quality.

The COVID-19 pandemic has resulted in social isolation and reports of insomnia. However, reports of changes in sleep duration and associated factors are few. To determine the impact of COVID-19 on changes in sleep behavior, data were analyzed from an online survey of adults recruited via social media that included questions asking whether the respondent slept less or more after the onset of the pandemic as well as self-reported sociodemographic and occupational information; beliefs about COVID-19; and responses pertaining to loneliness, anxiety, and depression. There were 5,175 respondents; 53.9% had a change in sleep duration.17.1% slept less and 36.7% slept more. Sleeping more was related to greater education, being single/divorced/separated, unemployed or a student. Being retired, divorced/separated or a homemaker, and living in the Mountain or Central time zones were associated with less sleep. Beliefs that COVID-19 would result in personal adverse consequences was associated with both more and less sleep. However, the strongest associations for both more and less sleep were seen with depression, anxiety, and loneliness. In summary, changes in sleep duration since the start of the COVID-19 pandemic were highly prevalent among social media users and were associated with several sociodemographic factors and beliefs that COVID-19 would have adverse personal impacts. However, the strongest associations occurred with worse mental health suggesting that improvements may occur with better sleep. Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.2002800 .

Attended manual continuous positive airway pressure (CPAP) titration is the standard practice for determining optimal positive airway pressures for obstructive sleep apnea (OSA) treatment. However, an unattended single night auto-titrating positive airway pressure (APAP) titration is an alternative. The goal of this study was to determine whether therapeutic CPAP pressures determined during manual titrations are higher than APAP-generated surrogate pressures. We conducted a retrospective review of 165 adults with uncomplicated OSA who had full/split-night manual CPAP titrations prior to commencing treatment with APAP. Demographic and clinical data including 30-day APAP compliance data were obtained. We compared the recommended CPAP pressure from manual titrations with the 90th/95th percentile pressure generated from APAP usage over 30 days. The recommended CPAP pressures during the manual titrations were higher than the 90th/95th percentile pressures generated from APAP (11.4 ± 3.4 vs 10.3 ± 2.4 cmH2O; P = .000). Almost half the group (41.9

Background: A shortage of palliative pare (PC) specialists underscores the necessity that all clinicians feel comfortable with serious illness conversations (SICs). Objective: To assess the effect of an intensive PC curriculum with multiple teaching modalities on Internal Medicine residents' confidence with SICs and advance care planning documentation. Methods: Twelve PC modules consisting of didactic lectures, role-playing, and online interactive modules were integrated as continuing education during academic year 2018-2019. Surveys were administered precurriculum and at 3 and 6 months postcurriculum to measure the primary outcome of increasing resident preparedness for SICs. A retrospective chart review was used to analyze secondary outcomes of advance care planning documentation for patients cared for by residents exposed to the curriculum versus residents from the previous year who received monthly didactic PC lectures. Results: Postintervention surveys demonstrated statistically significant improvement in resident confidence. An increase in patient code status confirmation rates (odds ratio, 1.81; 95% confidence interval, 1.12-2.94; P = 0.02) and a decrease in PC consultation (odds ratio, 0.56; 95% confidence interval, 0.33-0.97; P=0.04) was observed when compared with the previous year. Conclusion: Among residents, the incorporation of an intensive PC curriculum that uses multiple teaching modalities improves confidence in SICs, which we believe is integral to the practice of goal-concordant patient care.