bluuebunny/crossref_metadata_2025_split huggingface dataset:
670 Changes in Childhood Sleep Patterns in an Intervention Study Prior to and During COVID19 Restrictions
Authors: Mitchell Jonathan , Morales Knashawn , Williamson Ariel , Jawahar Abigail , Juste Lionola , Zemel Babette , Dinges David , Fiks Alexander 
Published: May 2021

Abstract

Introduction
We conducted a childhood sleep promotion study between March 2019 and December 2020 in Philadelphia. COVID19 was first detected in Pennsylvania in March 2020 and non-essential services were strictly curtailed (including school closures), with easing of curtailments by the fall 2020 (including hybrid schooling in some districts). We determined if changes in sleep duration were consistent during pre-, earlier, and later COVID19 periods.

Methods
Typically developing children (9-12y) with sleep duration &lt;8.5 hours per weeknight were enrolled. Sleep was measured using Fitbit devices during a baseline week and a 7-week intervention period. A factorial design was used to test five candidate intervention components: 1) sleep goal; 2) electronic device reduction messaging; 3) daily routine messaging; 4) child-directed financial incentive; and 5) parent-directed financial incentive. Sleep data were transmitted to a mobile health platform that automated delivery of the intervention components. We categorized participants when they completed the study: 1) Spring-Fall 2019 semesters (pre-COVID19); 2) Spring 2020 semester (started pre-COVID19, with strict restrictions impacting intervention periods); or 3) Fall 2020 semester (easing of COVID19 restrictions). Mixed effect modelling determined sleep changes.

Results
Mean age of participants was 11.6y (51% female and 29% Black participants). Pre-COVID19 (N=59), average sleep duration increased from baseline by 21 (95% CI: 10, 30) minutes per weeknight during the intervention. In spring 2020 (N=18), the average sleep duration increase was two times larger in magnitude at 41 (95% CI: 25, 59) minutes per weeknight. For fall 2020 (N=20), the average sleep duration increase was 24 (95% CI: 7, 40) minutes per weeknight. Changes in sleep timing from baseline during the intervention were consistent pre-COVID19 and in the fall 2020 (e.g., ≈15 minutes earlier sleep onset throughout the intervention period), whereas sleep timing changes were dynamic in the spring 2020 (e.g., 41 minutes earlier for week 1, and 44 minutes later for week 7).

Conclusion
This sleep intervention demonstrated increases in sleep duration pre-COVID19, with marked duration increases and dynamic timing changes coinciding with COVID19 restrictions during earlier (Spring 2020), but not later (Fall 2020), weeks of the COVID19 pandemic in Pennsylvania.

Support (if any)
K0 1 HL1 2 3 6 1 2 and CHOP
675 COVID-19 Instruction Style (In-Person, Virtual, Hybrid), School Start Times, and Sleep in a Large Nationwide Sample of Adolescents
Authors: Meltzer Lisa , Wahlstrom Kyla , Owens Judith , Wolfson Amy , Honaker Sarah , Saletin Jared , Seixas Azizi , Wong Patricia , Carskadon Mary 
Published: May 2021

Abstract

Introduction
The COVID-19 pandemic significantly disrupted how and when adolescents attended school. This analysis used data from the Nationwide Education and Sleep in TEens During COVID (NESTED) study to examine the association of instructional format (in-person, virtual, hybrid), school start times, and sleep in a large diverse sample of adolescents from across the U.S.

Methods
In October/November 2020, 5346 nationally representative students (grades 6–12, 49.8% female, 30.6% non-White) completed online surveys. For each weekday, participants identified if they attended school in person (IP), online-scheduled synchronous classes (O/S), online-no scheduled classes (asynchronous, O/A), or no school. Students reported school start times for IP or O/S days, and bedtimes (BT) and wake times (WT) for each applicable school type and weekends/no school days (WE). Sleep opportunity (SlpOpp, total sleep time proxy) was calculated from BT and WT. Night-to-night sleep variability was calculated with mean square successive differences.

Results
Significant differences for teens’ sleep across instructional formats were found for all three sleep variables. With scheduled instructional formats (IP and O/S), students reported earlier BT (IP=10:54pm, O/S=11:24pm, O/A=11:36pm, WE=12:30am), earlier WT (IP=6:18am, O/S=7:36am, O/A=8:48am, WE=9:36am), and shorter SlpOpp (IP=7.4h, O/S=8.2h, O/A=9.2h, WE=9.2h). Small differences in BT, but large differences in WT were found, based on school start times, with significantly later wake times associated with later start times. Students also reported later WT on O/S days vs. IP days, even with the same start times. Overall, more students reported obtaining sufficient SlpOpp (&gt;8h) for O/S vs. IP format (IP=40.0%, O/S=58.8%); when school started at/after 8:30am, sufficient SlpOpp was even more common (IP=52.7%, O/S=72.7%). Greater night-to-night variability was found for WT and SlpOpp for students with hybrid schedules with &gt;1 day IP and &gt;1 day online vs virtual schedules (O/S and O/A only), with no differences in BT variability reported between groups.

Conclusion
This large study of diverse adolescents from across the U.S. found scheduled school start times were associated with early wake times and shorter sleep opportunity, with greatest variability for hybrid instruction. Study results may be useful for educators and policy makers who are considering what education will look like post-pandemic.
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688 Pediatric Obstructive Sleep Apnea (OSA) and COVID-19-Related Adverse Clinical Outcomes
Authors: Shah Vaishal , Foldvary-Schaefer Nancy , Wang Lu , Jehi Lara , Obrea Cynthia Pena , Milinovich Alex , Mehra Reena 
Published: May 2021

Abstract

Introduction
The relationship of OSA and human coronavirus (COVID-19) in the pediatric population is unknown. We postulate that OSA is associated with SARS-CoV-2 positivity and with adverse COVID-19 outcomes in children.

Methods
A retrospective review of 120 consecutive patients (&lt;18 years) with prior polysomnogram (PSG) and COVID-19 testing from the Cleveland Clinic COVID-19 registry was conducted. Using a case control design of SARS-CoV-2 positive and negative pediatric patients, we examined COVID-19 and pre-existing OSA (dichotomized AHI≥1) using logistic (OR,95%CI) regression and as continuous measures: AHI, oxygen(SpO2) nadir, %time SpO2&lt;90%) using linear regression(beta+/-SE). In those positive for SARS-CoV-2(cases only), we assessed the association of OSA and World Health Organization(WHO) COVID-19 clinical outcome composite score (hospitalization, requiring supplemental oxygen, non-invasive ventilation/high-flow oxygen, invasive ventilation/ECMO or death) using Wilcoxon rank sum test for ordinal data.

Results
Cases (n=36) were 11.8±4.4 years, 61% male, 27.8% black and 88.9% with OSA, while 85.7% of controls (n=84) had OSA. OSA was not associated with increased SARS-CoV-2 positivity: OR=1.33(0.40, 4.45,p=0.64). No significant difference between cases and controls for mean AHI 3.7(1.5,6.0) vs 3.5(1.5,7.1),p=0.91,SpO2 nadir 88.6±5.4 vs 89.1±4.4,p=0.58,%time SpO2&lt;90% 0.05[0.00,1.00) vs 0.10 (0.00,1.00, p=0.65) respectively was noted. WHO-7 COVID-19 clinical outcome did not meet statistical significance in relation to OSA due to the low event frequency (p=0.49). Of note, those with OSA vs without OSA had a higher WHO-7 outcome score of 2 vs 0 and prevalence of hospitalization: 12.5 vs 0% respectively. Of hospitalized patients, the following was observed: 23% had moderate/severe OSA vs 4.3% mild OSA, 50% required supplemental oxygen and 25% required intubation/invasive ventilation. No deaths or readmissions were reported. High risk conditions included: 75% obesity, 50% asthma, 25% sickle cell disease and 25% hypoplastic left heart.

Conclusion
In this first report of which we are aware focused on COVID-19 in pediatric OSA, we use a case control design leveraging COVID-19 and sleep laboratory registries. Albeit not statistically significant, pediatric patients with OSA had a higher percentage of worse clinical outcomes. Larger network studies are needed to clarify whether poorer COVID-19 outcomes may be attributable to OSA or modulated via high risk health conditions.
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691 Associations of Sleep Quality and Burnout in Clinicians during the COVID-19 Pandemic
Authors: Shechter Ari , Rosenfeld Adam , Chang Bernard , Norful Allison 
Published: May 2021

Abstract

Introduction
Clinicians have faced unprecedented challenges in care delivery during the COVID-19 pandemic due to increases in patient volume/acuity, alongside fears of COVID-19 exposure. Increased burnout rates are associated with chronic health condition risk and adverse organizational outcomes. It remains unclear whether sleep is associated to burnout in clinicians treating COVID-19 patients.

Methods
A cross-sectional electronic survey was distributed via email across 3 hospital listserves from September to November, 2020. Clinicians delivering direct care to COVID-19 patients were eligible. Clinician burnout was measured using a single item from AHRQ’s Mini-Z survey. We assessed sleep using the Pittsburgh Sleep Quality Index (PSQI). Binary logistic regressions were used to determine the relationship between PSQI global score (global sleep quality) and burnout, controlling for age, race/ethnicity, gender, length of time employed, whether clinical role changed during COVID-19, and anxiety. In a separate model, we investigated the association between burnout and independent PSQI subcomponents: 1) sleep duration (“Hours of sleep per night”), and 2) subjective sleep quality (“How would you rate your sleep quality overall”) entered together, with the above covariates.

Results
The final sample included 315 clinicians, predominantly nurses (57% White, 15% Hispanic/Latino, 89% female). Burnout symptoms were reported by 61.6%, and poor global sleep quality (PSQI global score &gt;5) in 84.4% of participants. Poor global sleep quality (PSQI global score &gt;5 vs. ≤5) was significantly associated with the presence of burnout symptoms (OR: 2.52, 95% CI: 1.20–5.28, p=0.015). In the secondary model, self-reported sleep quality (rating of fairly or very bad vs. rating of fairly or very good) was significantly associated with burnout (OR: 4.13, 95% CI: 2.33–7.32, p&lt;0.05), whereas short sleep duration (&lt;6 h vs. ≥6 h) was not (OR: 0.726, 95% CI: 0.41–1.30, p=0.28).

Conclusion
Poor sleep quality is common and associated with increased burnout in clinicians delivering care to COVID-19 patients. Interestingly, sleep quality appears to be more strongly related to burnout than sleep duration. Increased evidence about the negative implications of poor sleep and burnout are emerging. Interdisciplinary efforts aimed at promoting effective sleep quality in clinicians during this pandemic may lead to improvements in long-term clinician physical and psychological health.
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703 From in-lab to at-home: Measuring sleep and memory in the time of SARS-COVID-19
Authors: Mullins Anna , Parekh Ankit , Kam Korey , Schoenholz Reagan , Valencia Daphne , Roberts Zachary , Castillo Bresne , Rapoport David , Ayappa Indu , Osorio Ricardo , Varga Andrew 
Published: May 2021

Abstract

Introduction
The SARS-COVID-19 pandemic restricted in-lab research activities especially in older individuals who are considered at-risk for severe disease. To continue longitudinal sleep research in this population we sought to test the feasibility of remotely conducting at-home sleep and memory research and to compare two ambulatory polysomnography (PSG) devices for ongoing home sleep testing.

Methods
20 older (age=65.6±5.5 years) cognitively normal adults (65% female) who had previously undergone 2 nights in-lab sleep, memory and vigilance testing were delivered equipment for 2 nights at-home, technician-guided remote PSG set-up (1 night each for Somté [EEG: Fp1-M2, Cz-M1] and Sleep Profiler (SP) [EEG: Fp1-Fp2] devices- randomized presentation), and 6 timed trials on a 3D spatial maze navigation memory plus morning psychomotor vigilance testing (PVT). The night-to-night differences for devices and in-lab versus at-home testing environments were compared for sleep macro and EEG microarchitecture using paired Wilcoxon rank sum and t-tests where appropriate. First-night maze completion time (CT) and PVT reaction time and lapses were also compared.

Results
19 people completed 2 nights at-home PSG, 18 completed PVT and 9 completed all 6 maze trials. Quality frontal EEG signals were obtained for 16 SP and 11 Somté recordings. There was no significant night to night differences (night 1–night 2) between in-lab and at-home environments for total sleep time (mean difference: in-lab= -0.27 vs at-home = 0.35 hours), wake after sleep onset (WASO) (median difference: in-lab= 3.0 vs at-home = 0.7 %WASO), or slow wave sleep (SWS) (mean difference: in-lab= -0.70 vs at-home = 2.3 %SWS). Relative frontal slow wave activity and spindle density were not significantly different between devices or environments. K-complex density (SP= 1.0 vs Somté =2.7/minNREM2, p=0.004) was significantly reduced with the SP device compared to Somté devices. There were no significant differences for maze CT and PVT measures between in-lab and at-home environments.

Conclusion
The night-to-night differences in sleep macroarchitecture do not appear to be influenced by environment or device however measures of EEG microstructure such as K-complexes, which are amplitude-dependent, may be underestimated with the Sleep Profiler device due to smaller EEG amplitude from a derivation with short inter-electrode distances.

Support (if any)
NIH (R01AG056031, R01AG056531, K24)
709 Healthy Sleep as an important resource and buffer for intersectional discrimination: Results from Covid 19 study
Authors: Pandey Abhishek , Littlewood Kerry , Spadola Christine , Rosenthal Michelle , Cooper Larry , Carter Shima , Bennett Russell , Hash Jonika , Kirtman Nissa , Ward Teresa 
Published: May 2021

Abstract

Introduction
Our previous studies have highlighted sleep disparities for this underserved population, including how Grandparents Raising Grandchildren (GRG) experience troubled and disruptive sleep. Intersectional types of discrimination facing these families during COVID 19, include: race/ethnicity of self and children, income, age, essential workforce status, and impairments (mobility, vision, and hearing). This current study intends to explore how healthy sleep is an important resource (potential buffer) for GRG experiencing intersectional discrimination during COVID 19.

Methods
We used community partnerships to recruit 600 GRG from all fifty states in USA and several tribes to complete an online survey on their experiences with caregiving and intersectional discrimination during COVID 19. We developed an index on intersectional discrimination based on GRG lived experiences to inform the survey and used descriptive and bivariate statistics to profile this group. Chi-square Automatic Interaction Detector (CHAID) analysis was used to build a predictive model to help determine how variables in our study best merge to explain intersectional discrimination.

Results
Of the GRGs’, 37% were between 54–65 years and 33% cared for children 6 to 10 years for at least 5 years. The types of discrimination that were more likely to be included in intersectional discrimination include: Black or African American [83.8% (31)], my child’s race [59.5% (22)], my lower economic status [56.8% (21)], and my status as a caregiver [56.8% (21)]. The resource needs that showed the most disparity (higher rate showed higher priority/extreme concern) between those with ID and those without included: Information on how COVID impacts race and ethnicity differently (6.0 vs. 3.61), ability to pay utilities (3.7 vs. 1.99), and information on how to achieve healthy sleep (4.19 vs. 2.64).

Conclusion
This study suggests that GRG facing intersectional discrimination identify the importance of attaining information on how to achieve healthy sleep as an important resource to them during COVID 19. These results can be used to help mobilize resources and disseminate information for this underserved group to improve healthy sleep and also model for their extended families and communities.

Support (if any)
This study was conducted by the Grandfamilies Outcome Workgroup, (GrOW), with support from Generations United and Collaborative Solutions.
720 Actigraphy to Evaluate Sleep in the Inpatient Setting: A Systematic Review
Authors: Sussman Sarah , Fares Elie , Ananth Ashwin , Boon Maurits , Fast Zhanna , Huntley Colin 
Published: May 2021

Abstract

Introduction
Sleep disruption is common among hospitalized patients due to psychological, physiological, and environmental reasons including illness, pain, anxiety, invasive interventions, frequent monitoring, and stimuli, especially noise and light. The AASM has published guidelines for the use of actigraphy in the outpatient setting, but there is a paucity of literature evaluating the validity of actigraphy in inpatients. We sought to summarize the evidence surrounding the use of actigraphy for inpatient sleep evaluation.

Methods
Systematic review was conducted according to the Preferred Reporting of Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Databases were queried by two independent reviewers for English-language studies published between 1990 and 2020. The initial search screened for all occurrences of “actigraphy AND sleep AND hospital” then was further refined to include studies of actigraphy used for monitoring in the inpatient hospital setting and exclude studies evaluating actigraphy in outpatient, rehabilitation, immediate postoperative, or intensive care unit settings.

Results
1221 were screened from initial search results. 48 articles were identified through screening of abstracts. Full-text review of the articles was then completed. Of the 48 articles, a total of 12 studies examined general medical inpatients, 12 studies examined inpatients with neurologic disorders, 5 studies examined inpatients with cancer, 6 studies examined patients with mental illness, 9 studies examined elderly patients, and 4 studies examined other defined populations (pregnancy, trauma, liver transplantation, and hip arthroplasty). We summarize the qualitative findings of inpatient actigraphy as it relates to each of these populations. Commonly reported outcome measures were total sleep time (TST), number of nighttime awakenings, and concordance with polysomnography (PSG).

Conclusion
We summarize the existing evidence for the use of actigraphy in the inpatient setting. Actigraphy may provide a simple and effective method for screening of sleep disorders in the inpatient setting. With regard to the published literature, there is support for the use of actigraphy in the inpatient setting in certain patient populations, especially traumatic brain injury. Variation in data output of actigraphy devices and outcome measures presents a barrier to meta-anaylsis of pooled data. Standardization of outcome measures will allow for effective synthesis of future studies.
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723 Sleep Apnea Care During the COVID-19 Pandemic: Perspectives on the Transition to Telemedicine from Clinicians and Patients
Authors: Bertisch Suzanne , Bakker Jessie , Hanes Sherry , Dos Santos Carolina , Bergrestresser Sloan , Siengsukon Catherine , Barwick Melanie , Redline Susan , Revette Anna 
Published: May 2021

Abstract

Introduction
Covid-19-related public health control measures have necessitated a rapid transition in healthcare delivery. We qualitatively explored clinicians’ and patients’ experiences of the pandemic’s impact on the delivery and receipt of obstructive sleep apnea (OSA) care.

Methods
Between September and December 2020, we conducted ten 90-minute virtual focus groups with sleep clinicians (n=19) and English and Spanish-speaking patients with OSA (n= 30) recruited through an urban academic sleep clinic, national organizations, social media, and snowball sampling. An interdisciplinary team conducted a rapid qualitative analysis that included prefigured and emergent domains. The team developed a comprehensive analytic matrix, identifying key themes within and between groups and triangulating them across participant types.

Results
Clinicians and patients across all groups confirmed a rapid shift to the adoption of telemedicine. Clinicians reported telemedicine enhanced evaluations by enabling direct observation of the home environment, providing opportunities to guide patients on medical equipment used in the home, and cultivating meaningful social connections for patients. Perceived benefits varied across patient subgroups (age, language, technological self-efficacy). The majority of clinicians reported that telemedicine’s initial uptake resulted in delays in care and revenue loss, but sustained use was thought to be feasible over time. Patients reported delays in care related to the pandemic’s disruption on healthcare and their personal safety concerns. Additionally, telemedicine’s adoption directly altered other elements of care, including the delivery of patient education materials and loss of tacit information gained during the in-person visit. All groups reported adequate mask fitting as a central challenge for patients using positive airway pressure therapy. Spanish-speaking patients noted concerns of increased difficulty accessing care and navigating the OSA care system due to limited English proficiency, in addition to the limited availability of OSA resources in Spanish.

Conclusion
During the Covid-19 pandemic, the rapid adoption of telemedicine largely facilitated OSA care but altered patient-clinician interactions, delivery of patient education materials, and mask fitting success. Given that telemedicine will likely be sustained post-pandemic, there are needs for targeted efforts aimed at addressing disparities in telemedicine, enhancing practitioner telepresence and education, and new approaches for mask fitting to ensure successful OSA care.

Support (if any)
Patient-Centered Outcomes Research Institute EADI-16493