bluuebunny/crossref_metadata_2025_split huggingface dataset:
0439 Analysis of Responders to Self-Help Sleep Interventions in a Stepped-Care Clinical Trial Among Schoolteachers
Authors: Yu Yee Man Branda , Chan Christian S 
Published: April 2024

Abstract

Introduction
Schoolteachers often struggle with inadequate sleep or poor sleep quality, placing them at a heightened risk of depression and other mental health conditions. Cognitive behavioral treatment for insomnia (CBTi) has been found to be effective for alleviating depression while bypassing the associated stigma toward mental illnesses. Given the potential of CBTi, we tested the efficacy of delivering CBTi using a stepped-care approach among schoolteachers.

Methods
This study utilized preliminary data from a group of schoolteachers (N = 118) who received stepped care sleep treatment in an on-going assessor-blinded, randomized, waitlist-control trial. We examined the factors associated with clinical remission in sleep problems following self-help interventions (i.e., receiving sleep hygiene education as Step 1, and, if necessary, following with a 6-week self-help app-based CTBi (“proACT-S”) as Step 2). Remission was defined based on their responses after treatment (i.e., at the end of Step 1 or Step 2), classifying participants as responders (i.e., good sleepers) and non-responders (i.e., poor sleepers) using a cutoff value of 5 points on the Pittsburgh sleep quality index (PSQI).

Results
At baseline, participants reported mean scores of 10.7 on PSQI and 9.5 on The Kessler Psychological Distress Scale (K6), indicating poor sleep quality without noticeable mood symptoms. Out of 94 participants who completed end-of-treatment assessment, 16.0% achieved good sleep quality after receiving sleep hygiene education, while an additional 11.7% achieved good sleep quality through the completion of app-based self-help CBTi. Multivariate logistic regression with multiple imputations indicated that participants who reported poor sleep at baseline but without clinical-level insomnia (scored &lt; 8 on Insomnia Severity Index) had a higher odds of good sleep quality at the post-treatment follow-up (aOR = 13.2, 95% CI = 5.0–152.9, p = .04) compared to those with moderated insomnia symptoms. This association was controlled for teachers’ mood and stress symptoms, along with other demographic factors.

Conclusion
For teachers who had poor sleep but without clinical-level insomnia, offering online psychoeducation and, if necessary, self-help CBTi may prevent them from developing clinical insomnia.

Support (if any)
This project is supported by the Health and Medical Research Fund from the Food and Health Bureau,HKSAR (project no: 18191811).
0440 An Internet of Things Cognitive Behavioral Therapy-based Device Reduces Insomnia Severity and Increases Sleep Time
Authors: Kim Jean , Gartenberg Daniel , Bitonte Eben , Kushida Clete 
Published: April 2024

Abstract

Introduction
An estimated 34-million U.S. adults suffer from chronic insomnia. The first-line treatment for this disease is Cognitive Behavioral Therapy for Insomnia (CBT-I). However, poor access, high cost, and low adherence prevent its widespread use. Full Sleep is a novel Internet of Things (IoT) device that includes an intelligence-sensing radar to passively track sleep patterns and deliver in the moment behavioral prompting to promote adherence to CBT-I directives.

Methods
The effect of the IoT device was examined on participants with moderate to severe insomnia symptoms (n = 65). Participants were recruited through a website and consented to a 6-8 week program. The IoT device was hypothesized to improve the Insomnia Severity Index (ISI) (primary outcome), evaluated at baseline and post-treatment. The IoT device was also hypothesized to improve consensus sleep diary metrics. Exploratory hypotheses included increasing total sleep time and reducing depression and anxiety on survey assessments.

Results
A within-groups paired-comparison t-test showed significant improvements in the ISI from baseline 19.3 (SD = 2.5) to post-treatment 7.4 (SD = 4.6), t(43) = 16.89, p &lt; .001, d = 2.5, a 62% decrease. A clinically significant change is 6-points, demonstrating a dramatic improvement, and a larger effect than reported by digital therapeutics like Somryst, which found a 45% decrease in the ISI. There was also evidence of a causal relationship between improvements in the ISI and the use of the IoT device, where the more that participants engaged with the feature that promoted getting out of bed during restless nights, the greater the improvement in the ISI score r(42) = .37, p &lt; .05. Importantly, the intervention also increased total sleep time, from 6.3 hours (SD = 1.4) to 6.8 hours (SD = 1.4), t(51) = 4.14, p &lt; .05, and sleep efficiency from 73.6% (SD = 13.7%) to 88.6% (SD = 8.9%), t(51) = 9.9, p &lt; .05. Participants had a reduction in dysfunctional beliefs about sleep, depressive symptoms, and anxious symptoms (ps &lt; .05).

Conclusion
These results support that innovative technologies that work alongside CBT-I directives can reduce insomnia severity and increase total sleep time.

Support (if any)
This research was supported by Koko Home Inc.
0446 Improving Adherence to Sleep Restriction in Digital CBT-I
Authors: Bayoneto Alec , Treger Marleigh , Fellman-Couture Cynthia , Batra Arjun , Drake Christopher , Cheng Philip 
Published: April 2024

Abstract

Introduction
Treatment adherence has been a proposed barrier to the success of digital CBT-I (dCBT-I). Adherence to sleep restriction may be particularly important for treatment gains. One model of improving treatment adherence is to enhance dCBT-I with a nurse coach. This study compared adherence to sleep restriction between those with and without access to a nurse coach.

Methods
288 individuals with insomnia (DSM-5 diagnostic criteria) were randomized into two conditions: enhanced dCBT-I (access to a nurse coach: n=148) and control (online program only: n=140). Those in the coaching model had an initial consult with the nurse coach focused on motivational enhancement, and then received feedback via email after each session based on sleep diary reports. Those who miss two consecutive sessions were stepped-up to telehealth coaching focused on implementing sleep restriction. All participants included in this preliminary analysis completed at least 3 sleep diary entries per week throughout the study. Sleep restriction was measured with sleep diary data, operationalized as the change in standard deviation of time in bed and wake time before and after the introduction of sleep restriction.

Results
Results indicate that those in the coaching group showed a greater mean reduction in the standard deviation of time in bed (coaching group: -53.3 min, control reduction: -35.9 min; Cohen’s d = 0.23). Similarly mean changes in standard deviations of wake time was greater in the coaching group compared to the control group (coaching group: -19.0 min, control reduction: 1.2 min; Cohen’s d = 0.22).

Conclusion
Results provide preliminary support that enhancing dCBT-I with nurse coaching may produce better adherence to sleep restriction. Future research should include sensitivity analyses, and examine the relationship between adherence to sleep restriction and improvements in symptoms.

Support (if any)
Support for this study was provided from the National Heart Lung and Blood Institute R01HL159180 awarded to Dr. Philip Cheng.
0449 Pilot Study: AI-Enhanced COMISA Diagnosis in Hong Kong Public Hospitals Using Objective Sleep and HRV Metrics
Authors: Young Betty Hai Ka , Kwok Isaac Chak Yan , Tsai Chih-Wei , Leung Lydia , Cheung Cynthia , Chan Po Shan , Kwok Amy Pui Ling 
Published: April 2024

Abstract

Introduction
The underdiagnosed and high overlapping prevalence of comorbid insomnia and obstructive sleep apnea (COMISA) often suffer worst cardiovascular outcomes than patients with either OSA or Insomnia. The scarcity of multi-disciplinary clinics addressing both conditions may impede timely COMISA diagnosis and treatment efficacy. This study explored the feasibility of leveraging objective sleep and HRV metrics through Belun Ring (BR), the AI-powered wearable, to facilitate COMISA diagnosis and personalized treatment.

Methods
Consecutive suspected OSA or Insomnia cases were co-screened by clinical psychologist and pulmonologist. Participants were categorized into the OSA group if PSG-AHI ≥ 15 events/h, insomnia if Insomnia Severity Index (ISI) ≥ 15 or diagnosed based on the International Classification of Sleep Disorders, third edition (ICSD-3), or COMISA if meeting both conditions. All subjects completed a 3-night (≥ 100 mins/night) sleep assessment using the BR. Kruskal-Wallis tests and PCA analyses were conducted for comparative analyses among the three groups.

Results
Among 54 subjects, 31 had insomnia, 13 had OSA, and 10 had COMISA. Marked discrepancies between subjective and AI-generated sleep statistics (concordance rate= 0.07) COMISA exhibited the highest wake after sleep onset (median, mins) compared to insomnia and OSA (76.5 vs. 48.1 vs. 21.2, P&lt; 0.001). COMISA and insomnia had upregulated wakefulness (median, count) compared to OSA (14.9 vs. 15.2 vs. 8.3, P&lt; 0.05). Moreover, COMISA exhibited the lowest SDNN (median, ms) and RMSSD (median, ms) compared to insomnia and OSA (SDNN: 49.0 vs. 63.8 vs. 92.9, P&lt; 0.01; RMSSD: 44.9 vs. 53.8 vs. 79.8, P&lt; 0.01). COMISA had dropped PRR50 (median, %) compared to OSA (6.6 vs. 24.8, P&lt; 0.05). Normalized LF and LF/HF did not differ across the three groups. The novel workflow reduced waiting time for consultation from 104 to 45 weeks.

Conclusion
This is the first study to demonstrate the use of AI-assisted sleep and HRV parameters to single-out COMISA for better personalized treatment and efficient workflow. The worst cardiovascular outcomes in COMISA patients were objectively reflected by the lowest SDNN and RMSSD findings. This novel study elucidated the potential how AI can assist to identify COMISA patients even in monodisciplinary settings for better patient care.

Support (if any)
0454 In Cognitively Normal Elderly, Obstructive Sleep Apnea Worsens Spatial Navigational Memory Performance
Authors: Valencia Daphne , Datta Anjona , Mullins Anna , Wickramaratne Sajila , Bubu Omonigho , Kam Korey , Parekh Ankit , Osorio Ricardo , Ayappa Indu , Rapoport David , Varga Andrew 
Published: April 2024

Abstract

Introduction
Normal sleep has a favorable effect on the consolidation of spatial navigational memory. Previous work suggests normal overnight sleep enhances spatial navigation performance in a hippocampus-dependent manner. Our group has previously demonstrated post-sleep spatial navigational performance may be affected by obstructive sleep apnea (OSA). Here we aim to replicate these findings in a much larger sample size.

Methods
Using a virtual 3D Maze, 162 subjects (66.8 ± 6.5 years, 88 female) completed spatial navigational encoding and recall across their nocturnal polysomnography visit. Participants were instructed to find the maze exit within a ten-minute period and were given three trials pre- and post-sleep. We compared overnight changes and trial-by trial completion times between participants with and without OSA (AHI4% &gt; 5) using Wilcoxon signed-rank test.

Results
Of the 162 participants, 76 had OSA (10.5± 16.12 AHI4). There was no statistically significant difference in overnight change in completion time (%) between OSA/non-OSA groups (OSA: 2.5 ± 58.3, non-OSA: 9.9 ± 52.1). However, the average completion time worsened with each successive trial during encoding (pre-sleep) in OSA [T1: 305 ± 18, T2: 328 ± 21, T3: 345 ± 23 seconds] as compared to non-OSA [T1: 369 ± 20, T2: 324 ± 19, T3: 320 ± 20 seconds]. Further, we observed that the average completion time worsened with each successive trial during recall (post-sleep) in the OSA group [T4: 306 ± 20, T5: 296 ± 20, T6: 332 ± 20 seconds] as compared to the non-OSA group [T4: 331 ± 19, T5: 312 ± 20, T6: 277 ± 18 seconds], such that, in the final post-sleep trial (T6), OSA patients had significantly slower completion times than the those without OSA (p = 0.034).

Conclusion
Despite no difference in overnight change in completion time between non-OSA and OSA, the pattern of performance during encoding and recall was different; These observations suggest OSA may be creating a working memory deficiency more strongly than an offline processing deficiency. Future analyses evaluating PVT performance in the OSA and non-OSA groups may be instructive to probe whether a different domain of executive is also impacted and its relationship to subjective sleepiness.

Support (if any)
R01AG066870,R01AG056682,R01HL118624,R01AG056531,R01AG056031,U01OH011852
0456 Impact of Hypertension and Sleep-disordered Breathing on Cognitive Decline in Older Adults
Authors: Noda Akiko , Okuda Masato , Iwamoto Kunihiro , Miyata Seiko , Yasuma Fumihiko 
Published: April 2024

Abstract

Introduction
Hypertension is a major risk factor for cardiovascular diseases. Sleep disruption, circadian dysfunction, sleep-disordered breathing (SDB), and cognitive decline are increased with aging. Repeated episodes of end-apneic arousal or hypoxia and consequent sleep fragmentation are associated with increased nocturnal blood pressure, possibly leading to sustained hypertension and atherosclerosis. The relationship between blood pressure levels and cognitive function differs across the lifespan in observational studies. However, the roles of hypertension and SDB on the pathogenesis of age-related cognitive decline remain unclear. We investigated the effect of hypertension and SDB on cognitive decline in older adults.

Methods
The participants were 50 consecutive volunteers aged 60 years or older (mean age 69.2 ± 4.7 years) without impairment in daily living activities. Sleep apnea screenings were conducted using a portable monitor. We evaluated the respiratory event index (REI) as the number of apnea and hypopnea events per hour during the recording time, with the minimum oxygen saturation. Sleep complaints were assessed using the Pittsburg sleep quality Index (PSQI). Excessive daytime sleepiness was evaluated by the Epworth sleepiness scale (ESS). Cognitive performance was assessed using the Wisconsin card sorting test (WCST), continuous performance test-identical pairs (CPT-IP), and N-back task. Hypertension and diabetes mellitus were evaluated via questionnaire. We measured systolic and diastolic blood pressure using pulse wave test.

Results
The percentage of correct answers on the 1-back tasks was significantly lower in the hypertension group than the non-hypertension group. The WCST category achievement was significantly lower in the participants with minimum oxygen saturation &lt; 90% than those with minimum oxygen saturation ≥ 90%. Minimum oxygen saturation was correlated with category achievement on the WCST. Multiple regression analysis including age, REI, minimum oxygen saturation, ESS, hypertension, and diabetes mellitus revealed that hypertension was the most significant factor for percentage of correct answers on the 1-back tasks. There were no significant correlations between the REI or ESS and the parameters of WCST or N-back tasks.

Conclusion
Hypertension and SDB may negatively affect cognitive function in older adults. Our findings suggest that the appropriate management of hypertension and SDB is important in mid- and late-life.

Support (if any)
0462 Polysomnographic Biomarkers of Sleep Disruption and Incident Migraine in a Large Clinical Cohort
Authors: Khazaie Sepideh , Bena James , Ryan Delaney , saab Carl , Mehra Reena 
Published: April 2024

Abstract

Introduction
The relationship between sleep disruption characterized by polysomnography and migraine development remains unclear. This study elucidates this association, examining whether indices of sleep disturbance could serve as predictors of migraine.

Methods
In this longitudinal study, 132,705 participants (2000 to 2023) without pre-existing migraines were analyzed. Predictors included Apnea-Hypopnea Index (AHI), Mean SaO2, arousal index, and Epworth Sleepiness Scale (ESS) scores. Covariates for adjustment comprised age, sex, body mass index (BMI), race, neck size, end-tidal CO2, sleep stage percentages, and household income. Migraine incidence was ascertained using ICD diagnosis codes. Analysis employed univariable and multivariable Cox regression models.

Results
The cohort averaged 50.2 ± 19.0 years, was 54% male, and 76% Caucasian. Mean follow-up was 4.8 ± 4.1 years until migraine incidence. Adjusted regression showed higher AHI (per 5 units) was associated with a 1% reduction in migraine risk (HR=0.989, 95% CI 0.986-0.992). Also, higher mean SaO2 predicted a 4% increase in migraine incidence (HR=1.04, 95% CI 1.03-1.06). Reduced N1 percentage (HR=0.993, 95% CI 0.988-0.999), lower arousal index (per 1 unit, HR=0.993, 95% CI 0.991-0.996), and higher income (per $10,000, HR=0.96, 95% CI 0.94-0.98) also decreased migraine development. However, elevated ESS scores (HR=1.04 per unit increase) and larger neck sizes (HR=1.005 per 1 cm) augmented migraine risk (both p&lt; 0.001).

Conclusion
More severe sleep disruption correlated with reduced migraine incidence, contrasting expectations. Apnea-induced vasoconstriction may trigger protective vascular changes in calcitonin gene-related peptide (CGRP)/serotonin pathways. Further study on mediating mechanisms is warranted.

Support (if any)
0468 CRASH: Cancer Reoccurrence Is Accelerated by Episodic Hypoxemia
Authors: Rodriguez Fernando Figueroa , Lim Kaiser , Peikert Tobias , Escalante Patricio , Morgenthaler Timothy 
Published: April 2024

Abstract

Introduction
Several studies have shown a positive association between Obstructive Sleep Apnea (OSA) and malignancies such as lung cancer. However, the effects of intermittent hypoxemia in cancer-free survival following curative therapy are not known. We propose that OSA-related episodic hypoxemia and hypoxic burden are independent risk factors for accelerated lung cancer reoccurrence (&lt; 2 years).

Methods
We performed a retrospective record review of patients 18 years and older from January 2016 to September 2023 with history of non-small cell lung cancer who received an overnight oximetry study (OXY) within three years prior to undergoing curative malignancy treatment. Subjects with history of central sleep apnea, baseline oxygen saturation (SpO2) below 90%, receiving supplemental oxygen or treatment for OSA were excluded.

Results
403 patients met inclusion criteria (52% female vs 48% males; median age 74 y). The most common histologic subtypes were adenocarcinoma (68%) followed by squamous cell carcinoma (22%). Most patients fell into Stage IA1 (35%) followed by IA2 (24.1%) and IB (19%) as per TNM 8th edition classification. Over this period, 68 patients (22%) had lung cancer recurrence (median 19 months). A 4% oxygen desaturation index (ODI) of &gt;15 and time spent in desaturation events were found to be a risk factor for cancer reappearance in less than 2 years (p&lt; 0.001). Measures of hypoxic burden such as time spent below 89% SpO2, average SpO2 value below 89%, and single nadir oxygen levels, showed a similar association (p&lt; 0.001). This was irrespective of histologic subtype, stage at diagnosis, and all studied demographic variables. Basal SpO2 demonstrated no correlation. A multivariate proportional hazard survival model showed that ODI&gt;15 was no longer significant, however average SpO2 below 89% and single minimum oxygen level remained strongly correlated with accelerated recurrence.

Conclusion
This study showed a strong, positive association between accelerated lung cancer recurrence and OSA-related episodic hypoxemia and hypoxic burden on our univariate analysis. The multivariate model demonstrated correlation with hypoxic load measures only, suggesting the need for a larger sample to elucidate the involvement of this highly treatable risk factor. To our knowledge, this is the first study revealing this potential link.

Support (if any)
0472 Association of U.S. Military Burn Pit Smoke Exposure with Polysomnography Extracted Oxygen Saturation
Authors: Kokonda Manasa , Sharafkhaneh Amir , Razjouyan Javad , Helmer Drew , Nowakowski Sara 
Published: April 2024

Abstract

Introduction
Burn pits (BPs) have been widely utilized by the U.S. military for waste disposal. Due to toxic nature of the BP emissions, exposure may contribute to adverse health conditions, including nocturnal breathing problems. This study aimed to examine the association between self-estimated amount of BP emission exposure and oxygen (O2) levels during sleep.

Methods
Using polysomnography reports in the Veteran Affairs electronic medical records, oxygen saturation (SaO2) measures were extracted for 4940 Veterans and active-duty personnel (age 39.7±9.2 y, BMI 29.3±4.6 kg/m2, 16% female, 66% white) registered on the VA/DoD Airborne Hazards and Open Burn Pit Registry. Outcomes included nadir and mean SaO2. Cumulative BP exposure (BPe) variable was calculated by multiplying the response (in hours) to a question about burn pit exposure by number of deployment days, summing across deployments, and categorized into quartiles by ranking (Q1-Q3, with Q0 as reference). Inverse probability treatment weighing method was used to adjust the imbalances of covariates age, BMI, sex, race, ethnicity, military branch, and duty status between treatment groups. We performed separate weighted logistic regression models to determine the association between cumulative BPe days and SaO2 (≤90%). Additional analyses were performed on current smoking subgroup.

Results
We observed higher odds of nadir (OR:1.2, p=.045) and mean (OR:1.29, p&lt;.0001) SaO2 in prolonged BPe quartile (Q3). Subgroup analyses revealed similar findings as prolonged BPe quartile in current smokers predicted higher odds of nadir (OR:1.69, p=0.02) and mean SaO2 (OR:1.97, p=.0003)

Conclusion
Higher levels of BP emission exposure was associated with lower oxygen saturation during sleep. Compared to former and never smokers, veterans with current smoking status and higher BPe had significant lower SaO2. Hence, smoking may exert a synergistic effect with BPe on nocturnal SaO2.

Support (if any)
This work is supported by the Department of emi Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413), Michael E DeBakey Veteran Affairs Medical Center Bridge Grant, and the VA Airborne Hazards and Burn Pit Center of Excellence Pilot Grant (PI:Nowakowski).