Sleep Medicine

Background: Emerging evidence suggested the role of sleep and circadian rhythm in the development of mental resilience, but the association of an integrated analysis of objective sleep and circadian measures with multifaceted mental resilience in healthy adults has been underexplored. Objective: This study aims to explore the associations between multifaceted mental resilience and sleep and circadian rhythm in healthy adults. Methods: A total of 156 healthy adults (Age: Mean (SD): 29.54 (5.28) years; 60.9% female) underwent 14-day actigraphy, one night polysomnography (PSG) and dim light melatonin onset (DLMO) assessments. Resilience was operationalized as both a coping capacity and a positive mental health outcome in the context of accumulative adversity (life stressful events and childhood adversities). We first identified the covariance patterns between multiple sleep and circadian health domains (Sleep macro- and microstructures, dim light melatonin onset, rest activity pattern) and multifaceted mental resilience using partial least squares regression (PLSR), and followed by univariate analysis as complementary to illustrate the distribution trends of sleep and circadian rhythm parameters across integrative resilience score derived from principal component analysis (PCA). Findings: The PLSR model identified a modest but significant association of greater mental resilience with a sleep and circadian profile (Bootstrapping r = 0.15, 95%CI: 0.02-0.28), characterized by greater frontal-central slow waves activity in NREM sleep, greater frontal theta activity in REM sleep, lower occipital spectral power across fast and slow frequency bands in NREM and REM sleep, and probably earlier dim light melatonin onset timing. Conclusions: Sleep and circadian metrics, specifically frontal slow waves and REM theta activity, attenuated overall occipital spectral power during sleep, and earlier dim light melatonin onset time, represent quantifiable targets that may serve to improve resilience and stress-related mental health in adults. Longitudinal and interventional studies are needed to establish whether sleep interventions can be endorsed as evidence-based approaches for resilience enhancement. Clinical implications: Targeting sleep and circadian aspects may be an important approach to promote stress-related mental health.

Study Objectives: To characterize neural correlates of memory and emotion reactivity in individuals with insomnia disorder (INS) compared to good sleepers (GS) and to investigate associated short- and long-term changes following cognitive-behavioural therapy for insomnia (CBTi). Methods: This randomized controlled trial included 56 INS and 20 GS. At baseline, participants underwent resting-state and task-based functional magnetic resonance imaging, including working memory, emotion reactivity, and face-name associative memory tasks. They filled out sleep diaries and self-report questionnaires about sleep, cognition, and emotions, and underwent in-lab polysomnography. Subsequently, participants with INS were randomized to either the 3-month treatment group (TX) or wait-list control group (WL). Both TX and WL groups repeated baseline assessments at three months post-randomization and completed sleep diaries and questionnaires one year after finishing CBTi. Results: At baseline, the INS group reported higher insomnia severity, greater subjective cognitive impairment, and perceived sleep-related stimuli as more negative than GS. Contrasting with these subjective evaluations, no group differences were found in memory performance, task-based brain activity, or resting-state functional connectivity. At three months post-randomization and one-year follow-up, CBTi significantly improved subjective, but not objective, cognitive functioning and sleep in adults with INS. No significant treatment-related changes were observed in valence ratings of sleep images, task-based brain activity, or resting-state functional connectivity. Conclusions: Beyond its primary role in improving insomnia symptoms, CBTi may have long-term benefits for individuals with INS who experience concerns about their cognitive functioning, even in the absence of objective changes in neural processing of cognitive and emotional tasks.

Borderline personality disorder (BPD) is a serious mental illness that often emerges in adolescence. Although efficacious treatments have been developed, they are often lengthy, expensive, inaccessible, and require specialized training to deliver. Optimizing BPD prevention and early treatment is an important public health priority. Disrupted sleep is closely linked to key BPD features, and prior research has documented a range of sleep problems among BPD samples that appear to worsen symptom course and duration. This intervention trial (NCT04507308) assessed the effects of a single-session sleep-focused treatment on adolescent sleep and BPD-related symptoms. Fifty-seven adolescents (ages 13-18) with 3+ clinically impairing BPD features and at least some self-reported sleep-related difficulties participated with a caregiver. Participants completed baseline surveys, interviews, and 10-day ecological momentary assessment (EMA) protocol to examine BPD symptoms and sleep in daily life. Youth also collected at-home ambulatory electroencephalogram (EEG) recordings before undergoing the treatment informed by the Transdiagnostic Sleep and Circadian Intervention. Post-treatment, youth practiced their new sleep routine for approximately one month before undergoing reassessment (EMA, EEG, surveys). Many indices of sleep quantity and quality improved across both objective (EEG) and subjective assessments (EMA and self- and caregiver-report). Youth reported an earlier bedtime and waketime, more sleep, and fewer awakenings in daily life. Every sleep-related questionnaire score improved at post-intervention and was maintained at one-month follow-up. Multiple indices of BPD symptoms also improved significantly. Findings suggest sleep may be a promising intervention target for at-risk youth.

Sleep disturbances are a significant but underrecognized burden for individuals with Lennox-Gastaut Syndrome (LGS) and their caregivers. We conducted a large LGS caregiver survey to assess sleep quality, duration, specific sleep-related issues, and management strategies. Quantitative analysis revealed a significant association between nocturnal seizures and overall seizure frequency, but general sleep metrics in individuals with LGS (e.g., sleep hours, sleep quality) were not associated with seizure burden. In contrast, caregiver sleep was frequently disrupted - particularly in families who co-slept or reported frequent seizures. Nearly 40% of caregivers experienced nightly sleep disturbances. Respondents reported a range of strategies to manage sleep problems, including medication, environmental adjustments, and behavioral routines. Many also expressed frustrations over the limited effectiveness of strategies and inadequate support for sleep issues. These findings underscore the dual impact of LGS-related sleep disturbances on patients and caregivers, and highlight the need for comprehensive, family-centered approaches to sleep health.

Introduction Maintaining long-term positive airway pressure (CPAP) adherence is a major challenge when treating obstructive sleep apnea (OSA). We evaluated factors associated with one-year CPAP adherence and developed models predicting Month-12 adherence and CPAP-use trajectories. Methods CPAP-naive adults with OSA (apnea-hypopnea index[≥]5) at Kaiser Permanente Southern California with 364-day observation period were analyzed (development/internal-validation cohort, n=14,906; temporal holdout, n=1,676). Logistic regression evaluated baseline associations with Month-12 adherence (mean[≥]4 hours/night during days 331-360). XGBoost models utilized baseline features (clinical, sleep-study, questionnaire data), early CPAP data (days 1-7), or combined to predict long-term CPAP use. A latent-class model identified trajectories over days 8-364. Predictive models were evaluated in both random and temporal holdouts. Results About one-third (34.6%) of the primary cohort (49.7{+/-}13.8 years, 63.2% male) were adherent during Month-12. Higher AHI and longer self-reported sleep duration favored adherence while greater comorbidity burden, depression, and substance-use disorder were associated with lower adherence. In held-out testing, adherence prediction using baseline features yielded an AUROC of 0.678. Using CPAP-only data, AUROCs were higher from 0.787 with seven days of usage data to 0.816 and 0.854 with 14 and 30 days. Models combining CPAP and baseline features increased Day-7 AUROC to 0.810. We identified four one-year trajectories: Early-Decliners (42.9%), Gradual-Decliners (17.4%), Stable-Moderate (19.0%), Stable-High (20.7%). Models predicting patient trajectory revealed macro-average AUROCs of 0.619, 0.756, and 0.770 for baseline, CPAP-only, and combined models. Conclusion Baseline predictors may identify strategies for adherence support, while early CPAP data substantially improved predictive performance. These models may guide personalized follow-up but should not restrict CPAP access. External and implementation validation are needed.

Study Objectives: Sleep disturbances are common in youth with anxiety disorders, yet most prior work relies on subjective measures and does not capture underlying neural processes. We examined whether alterations in non-rapid eye movement (NREM) sleep oscillations are present in children with anxiety disorders and whether these features relate to internalizing symptoms and emotional functioning. Methods: Children aged 9-13 years with diagnosed anxiety disorders (ANX; n = 17) and typically developing non-psychiatric comparison participants (NC; n = 26) completed overnight polysomnography. Slow oscillations (SO) and slow and fast sleep spindles were characterized using validated automated detection algorithms. Participants also completed a pre-sleep emotional processing task, and parents provided standardized measures of youth mental health. Group differences and dimensional associations between NREM oscillations, internalizing symptoms, and behavioral indices of emotional processing were examined. Results: Sleep architecture did not differ between groups. Slow spindle duration was shorter in the ANX group. Across the full sample, shorter slow spindle duration was associated with greater internalizing symptoms, whereas higher SO density was positively associated with internalizing symptoms. Children in the ANX group exhibited greater facial emotional arousal and more frequent look-away behavior during the emotional processing task. Across participants, greater emotional arousal and look-away behavior were associated with shorter spindle duration during subsequent sleep. Conclusions: Specific features of NREM microarchitecture were associated with individual differences in internalizing symptoms and emotional functioning during early adolescence. These findings highlight the potential relevance of NREM oscillations for understanding developmental links between sleep and youth psychopathology.

For sleep scoring in rodents, the use of electromyography (EMG) is considered the gold standard to assess muscle tone; however, EMG electrodes require invasive surgical implantation, are sensitive to muscular placement, can have extensive noise due to non-muscular signal contamination, and are at risk of failure due to mechanical stress. The use of an accelerometer (Acc) integrated on the recording headstage offers an alternative for movement detection. However, the degree of agreement between these two approaches has never been systematically evaluated. To understand if these tools allow similar scoring outcomes, seven trained scorers manually classified mouse sleep recordings using hippocampal local field potential (LFP) together with EMG or Acc. When comparing scoring between EMG and Acc, overall epoch-by-epoch accuracy exceeded 90% with a kappa score above 0.8, indicating excellent agreement. However, Acc was found to under classify Wake by 4.92% while overclassifying NREM sleep by 3.29%, possibly reflecting a decreased sensitivity of Acc to subtle changes in muscle tone used in distinguishing Wake from NREM sleep. Comparing EMG and Acc signal for agreed epochs vs disagreed epochs revealed a weaker correlation between the two signals for disagreed epochs, especially for Wake and NREM, suggesting that disagreements reflected genuine signal differences rather than scorer subjectivity. These findings support LFP/Acc as a valid approach to sleep scoring, however, it is noted that Acc based scoring slightly underestimated Wake epochs, favoring NREM sleep, relative to traditional EMG approach.

Background: Sleep-wake-circadian disorders are prevalent and contribute substantially to morbidity, mortality and reduced quality of life. Evaluation in real-world settings is essential to capture their complexity and association with long-term outcomes. Most sleep-wake registries are restricted to selected populations, lack systematic integration of objective sleep-wake-circadian assessments with the clinical data and provide limited follow-up. To address these limitations, we established the Bern Sleep-Wake Registry based on real-world data from a tertiary University Hospital sleep center. Methods: The registry includes data from patients referred to the multidisciplinary Sleep- Center at Inselspital, University Hospital Bern (funded in 1990), from the year 2000 onwards who underwent at least one objective assessment such as polysomnography, daytime sleep-wake recordings, vigilance tests, and actigraphy. The registry integrates clinical information, questionnaire scores, outputs of objective assessments and raw signal data, and is regularly updated to incorporate new patients and longitudinal follow-up information. Results: As of September 2025, records from over 11000 patients were evaluated (median age: 50 years (interquantile range 36, 61); 65% male). The most common sleep-wake-circadian disorders were sleep-related breathing disorders (67%), insomnia disorders (15%) and central disorders of hypersomnolence (9%). Available assessments included more than 12000 polysomnographies, 2400 multiple sleep latency tests, 2100 maintenance of wakefulness tests, 1800 vigilance tests and 4500 actigraphies. Conclusions: By longitudinally integrating multimodal deep clinical phenotyping with objective assessments and raw physiological signals, the Bern Sleep-Wake Registry provides a foundation for investigating disease trajectories, identifying novel biomarkers and developing data-driven approaches to precise diagnosis, prognosis and individualized treatment.

Study objectives: Rapid eye movement (REM) sleep is commonly divided into phasic and tonic substates based on higher and lower oculomotor activity, respectively. Our previous study described an alternative framework in which REM temporal structure forms a continuum of infraslow rhythms (~0.01 Hz) across brain and body physiology. We now ask whether these infraslow rhythms vary with neuropsychiatric symptoms, given the long-standing but still inconsistent links between REM and mood- or trauma-related disorders. Methods: Using a cross-sectional polysomnographic dataset from male veterans, we examined 59 participants for correlations between REM infraslow rhythms and neuropsychiatric symptom scores, excluding participants with moderate/severe apnea. Results: Oscillations in REM respiratory rate, but not cardiac rate or electroencephalogram beta power, showed higher infraslow frequencies in participants with multiple symptoms, including posttraumatic stress, pain, anxiety, depression, and cognitive difficulties. No significant correlations were found between these symptoms and conventional REM metrics (e.g., REM density, latency and duration). To further examine REM beyond phasic/tonic binarization, we analyzed the timing between oculomotor activity and infraslow oscillations. Eye movements occurred preferentially during periods of high respiratory rate, low beta power and intermediate cardiac rate, with no changes in these temporal relationships across symptom severity. Conclusions: Neuropsychiatric associations with REM infraslow rhythms spanned multiple symptom domains but were physiologically specific, with respiratory rate oscillations representing the strongest readout of symptom burden. Furthermore, REM infraslow cycles across brain and body were differentially aligned with eye movements: a temporal pattern that may serve as a physiological target for neuropsychiatric and mechanistic research.

Seasonal daylight saving time (DST) transitions abruptly alter the alignment between clock time, environmental light, and sleep. In preregistered analyses, we used longitudinal Fitbit data from the All of Us Research Program to compare sleep around 13 seasonal transitions in Colorado, New Mexico, and Utah with sleep on the same dates in Arizona, where clocks do not change. The sample included 1,522 participants and 6,658 participant-transition windows. Following the spring transition, sleep duration changed more from one night to the next in Mountain states than in Arizona (14.6 minutes, 95% CI [7.2, 22.0]), even though sleep duration itself on day +1 showed little evidence of a DST-related reduction (-8.4 minutes, 95% CI [-17.3, 0.6]). Sleep timing shifted later after the spring transition and about 28 minutes earlier after the fall transition. Among Mountain-state observations with a large post-transition departure from usual sleep duration, the median return to the usual range was two nights. Nearly the same two-night pattern appeared in Arizona after similarly large sleep departures, indicating that this return pattern was not specific to DST. Greater baseline sleep-duration variability predicted a greater likelihood of remaining outside the usual range at days +7 and +14. Seasonal clock changes produced acute sleep disruption, while the Arizona comparison shows that a rapid return to baseline should not be interpreted as the duration of recovery from DST itself.

NREM slow waves emerge from the synchronization of neuronal activity across multiple spatial scales. During childhood, local synchronization and large-scale propagation undergo distinct maturational trajectories, paralleling cortical synaptic remodeling and the maturation of long-range brain connectivity. How alterations in this local-to-global organization relate to arousal instability remains poorly understood. Here, we used 256-channel high-density EEG to characterize NREM oscillatory organization in 17 children with disorders of arousal (DOA) and 17 age- and sex-matched healthy controls. Children with DOA showed a marked dissociation between local synchronization and large-scale coordination: slow waves were locally larger, steeper and more synchronized, yet recruited the cortex less globally and exhibited a more spatially restricted distribution of origins. This phenotype preferentially involved Type 1 slow waves, a subtype associated with widespread cortical and subcortico-cortical recruitment and late developmental maturation. Children with DOA also showed reduced centro-posterior slow spindle density, providing convergent evidence for altered coordination of distributed NREM oscillations. These microstructural abnormalities occurred despite largely preserved conventional sleep architecture. Together, our findings reveal an altered local-to-global organization of NREM sleep in pediatric DOA and suggest that vulnerability to incomplete arousals may emerge when strong local synchronization is not matched by effective large-scale network coordination during brain development.

Background: Although sleep disorders are generally associated with cognitive decline, definitions of sleep conditions and cognitive function vary greatly across studies. Therefore, we evaluated associations between consensus definitions of sleep and cognitive outcomes across multiple studies. Methods: Consensus sleep measures were ascertained at baseline visits in three cohort studies (HCHS/SOL, MESA and ARIC, N=11,563): short and long sleep ([≤]6hours and [≥]9hours), insomnia (Women's Health Initiative Insomnia Rating Scale [≥]10 or [≥]6 for 3 questions), daytime sleepiness (Epworth Sleepiness [≥]11) and obstructive sleep apnea (OSA, Apnea-Hypopnea Index [≥]15). Cognitive measures were ascertained at baseline and follow-up visits in each study and used to calculate harmonized outcomes: global cognitive function (GCF) at baseline, change in GCF between baseline and follow-up, poor GCF at baseline ([≥]1SD below the median), and incident poor GCF at follow-up. Study-specific analyses were adjusted for age, sex, center, education, race/ethnicity, APOE4 and language of cognitive assessments as needed. Results were meta-analyzed across studies. Results: Long sleep was consistently associated with lower baseline GCF ({beta}=-0.19, SE=0.03, p=3.78x10-14, FDR p=7.56x10-13, p-heterogeneity=0.78) and increased odds of poor baseline GCF (OR=1.77, 95% CI=1.49-2.09, p=2.96x10-11, FDR p=2.96x10-10, p-heterogeneity=0.22) across cohorts. Insomnia was also suggestively associated with lower baseline GCF ({beta}=-0.051, SE=0.02, p=0.01, FDR p=0.07, p-heterogeneity=0.005) and increased odds of poor baseline GCF (OR=1.22, 95% CI=1.06-1.41, p=6.76x10-3, FDR p=0.05, p-heterogeneity=0.03). Sleep measures were not associated with change in cognitive function. Discussion: Associations of long sleep and insomnia with harmonized cross-sectional GCF across three large, multiethnic cohorts suggest that cognitive function may be associated with distinct sleep phenotypes.

Background: Adolescent mental health problems have risen alongside increasing sleep disruption and widespread social media use (SMU). However, the mechanisms linking these factors remain unclear. This study concurrently examined objectively measured sleep and SMU in relation to psychopathology to test whether SMU moderates the sleep-mental health association and to characterize day-to-day bidirectional relations among sleep, affect, mood, and SMU during the school year. Methods: Eighty-five adolescents (ages 12-18) completed 14 days of wrist actigraphy, smartphone-based ecological momentary assessments of mood and affect, and objective SMU duration tracking. Cross-sectional models tested whether SMU moderated associations between sleep and psychopathology, and multilevel daily models examined within-person lagged associations among sleep, SMU, and affect, controlling for age and sex. False discovery rate correction was applied. Results: Shorter average sleep duration and greater variability in sleep duration between weekdays and weekends were associated with higher psychopathology symptoms, primarily externalizing problems. SMU duration neither moderated nor directly predicted psychopathology or sleep. Within-person analyses showed that longer-than-usual sleep predicted more positive and less negative affect and lower next-day SMU, though these associations did not survive correction for multiple comparisons. Conclusions: Sleep disruption showed consistent associations with adolescent psychopathology, whereas the amount of time spent on social media did not. These findings suggest that duration-based measures of SMU may incompletely capture adolescents digital experiences and highlight the need for more granular, context-sensitive indicators of online behavior in understanding youth mental health.

Communication between the brain and cardiovascular system is increasingly recognized as a fundamental determinant of health, yet the mechanisms coordinating neural and cardiac rhythms remain poorly understood. Sleep provides a unique physiological state for investigating neurovisceral integration because cortical slow oscillations (SOs), thalamocortical sleep spindles, and autonomic activity undergo profound reorganization during non-rapid eye movement (NREM) sleep. We analyzed overnight high-density electroencephalography and electrocardiography recordings from 30 healthy adults and quantified interactions among SOs, sleep spindles, cardiac R-peaks, heart rate variability (HRV), spectral slope, and Lempel-Ziv complexity. To assess integrated brain-heart coordination, we developed a Joint Phase-Amplitude Coupling (JPAC) metric that quantifies the corelation between SO phase-dependent modulation of spindle amplitude and cardiac timing. SO-spindle coupling showed the expected fronto-central distribution but was not significantly related to autonomic or cortical state markers. In contrast, SO-R-peak coupling and JPAC systematically tracked physiological state. Stronger JPAC was associated with higher high-frequency HRV, steeper spectral slopes, and lower neural complexity, indicating enhanced coupling during synchronized, parasympathetically dominated NREM sleep. These findings demonstrate coordinated organization of cortical, thalamocortical, and cardiac rhythms within a common oscillatory framework and identify NREM sleep as a state and potential treatment target of large-scale neurovisceral integration.

Abstract Background: Insomnia is highly prevalent in major depressive disorder (MDD), yet the clinical and biological significance of dysfunctional beliefs and attitudes about sleep (DBAS) in MDD remains poorly understood. We examined whether distinct DBAS dimensions are associated with insomnia severity, depressive phenotypes, and neuroimmune-metabolic-oxidative (NIMETOX) biomarkers. Methods: DBAS-30 dimensions, clinical phenotypes, and NIMETOX biomarkers were assessed in 87 hospitalized patients with MDD and 31 healthy controls. Principal component analysis (PCA) was used to ascertain DBAS cognitive dimensions, and associations were examined using multivariable analyses. Results: Compared with controls, MDD patients showed lower scores on "perceived consequences of insomnia," "sleep-related worry and helplessness," and "medication-related beliefs," but higher "causal attributions to aging or biochemical imbalance" scores. A composite DBAS score reflecting these 4 MDD-associated cognitive dimensions was constructed, labeled DBAS dimensional index (DBAS-DI). This score was lower in MDD and inversely associated with Insomnia Severity Index (ISI) scores, overall MDD severity, physiosomatic symptoms, current suicidal ideation, and recurrence of illness. DBAS-DI and the expectations domain jointly explained 35.4% of the variance in ISI scores, with inverse and positive associations, respectively. The DBAS-DI score was inversely associated with indices of the acute-phase inflammatory response, oxidative stress, fecal branched-chain short-chain fatty acids (SCFAs) and positively associated with serum antioxidant capacity and protective SCFAs, such as acetate, propionate, and butyrate. Conclusions: DBAS abnormalities in MDD extend beyond insomnia-related cognitions and are associated with illness severity, suicidality, recurrence, and NIMETOX alterations. These findings suggest that dysfunctional sleep-related cognitions are embedded within broader immune-oxidative and gut microbial-metabolic processes that may contribute to the insomnia-depression interface.

Study Objectives: Glucagon-like peptide-1 (GLP-1) receptor agonists raise resting heart rate. We asked whether, after semaglutide initiation, the increase is larger during rapid eye movement (REM) sleep than during non-rapid eye movement (NREM) sleep. Methods: In the Human Phenotype Project, an Israeli cohort of generally healthy adults aged 40 to 70 years, 96 of 494 self-reported semaglutide initiators had a home sleep study (WatchPAT; sleep stages estimated from peripheral arterial tone and actigraphy) before and at least three months after starting. Each was propensity-matched 1:1 to a never-user of GLP-1 drugs measured at the same visits. We estimated the initiators' change minus their controls' change (difference-in-differences). The REM minus NREM contrast was designated primary after an exploratory analysis. Results: Relative to controls (90 to 94 pairs), heart rate rose during nocturnal wake (+3.89 beats per minute [bpm], 95% confidence interval 2.35 to 5.44), NREM sleep (+4.82 bpm, 3.12 to 6.52) and REM sleep (+6.25 bpm, 4.42 to 7.91); the REM increase exceeded the NREM increase by 1.42 bpm (0.98 to 1.89). The excess persisted across matching designs and on a relative scale; the proportion of REM sleep did not change. Never-users with similar weight loss showed no REM sleep heart-rate rise (+0.40 bpm, -0.63 to 1.50). Heart-rate variability decreases disappeared after adjustment for heart rate. Conclusions: Semaglutide initiation was associated with higher heart rate throughout sleep, most during REM sleep, unexplained by weight loss. Clinic measurements may understate this effect. Confirmation with polysomnographic staging is needed.

Chronic pain and insomnia are common, each has serious consequences and they often coexist [1-5]. This novel study employed a phenomenological method to explore adults lived experiences of the core and meaning of comorbid insomnia and pain, here conceptualized as COMIP. The empirical data is based on 22 semi-structured interviews with adults with COMIP. Each interview was analysed, developing themes and analytical frameworks for all participants, which were then compared to construct one main analytical framework. The consolidated criteria for reporting qualitative research were used [6]. The essence of COMIP was: A vicious cycle of insomnia and pain driven by four intertwined primary factors with cross effects, which reduced sleep quality and quality of life. Four main themes emerged: Firstly, insomnia with hyperarousal like racing thoughts, and difficulties with finding comfortable sleeping positions due to pain, disturbed sleep and decreased sleep quality. Secondly, daytime symptoms like reduced energy, with reduced daytime function and reduced quality of life. Thirdly, 24-hour hyperarousal, stress and distressing experiences such as suffering. Finally, contextual factors like treatment reduced and/or increased COMIP. The main contribution of this research is three-fold; mapping of the experiences of living with COMIP, the conceptualization of COMIP, and introduction of novel concepts. Our findings indicate that, when evaluating patients with COMIP, there is value in exploring the four COMIP factors. Although, it varies between individuals which factor/s is central to their COMIP experience, we emphasize that COMIP is distressing, and patients are likely to need emotional support and validation. Keywords: COMIP, sleep, phenomenology, disability, rehabilitation, ICF.

Rationale: Obstructive sleep apnea (OSA) is highly prevalent yet largely under-diagnosed. Current screening strategies rely on effortful questionnaires with modest accuracy, and prior machine learning models often require resource-intensive inputs and lack external validation. Objectives: To develop and validate machine learning models to predict OSA (apnea-hypopnea index [AHI4%][&ge;]5) and moderate-severe OSA (AHI4%[&ge;]15) using only routinely collected electronic health record (EHR) data, test cross-system transferability and compare performance with clinical screeners and a Bayesian risk-updating framework. Methods: Three tree-ensemble families (XGBoost, random forests, and histogram-based gradient boosting) were trained on an adult cohort with sleep-study results at Kaiser Permanente (KPSC), using full (106-feature) and minimal (age, sex, body-mass index, race/ethnicity) predictor sets and tuned by nested cross-validation. XGBoost models were selected, internally and temporally validated, and externally validated at University of Kansas Medical Center (KUMC). Measurements and Main Results: On our internal hold-out set (n=53,048), the full XGBoost model reached a ROC-AUC of 0.791 for any OSA and 0.768 for moderate-severe OSA. The minimal model retained most performance (0.764 and 0.736). Temporal performance was stable. Externally, frozen models showed lower AUCs (0.718 and 0.690 for full models; 0.725 and 0.706 for minimal models) but similar to KUMC-native models and improved further with transfer learning. The models significantly outperformed STOP-BANG (AUC difference 0.06-0.09 for predicting any OSA; p<0.001). Bayesian updating with select patient-reported items further improved discrimination. Conclusions: Machine learning models based on EHR data can predict OSA probability that outperform existing screeners, transfers across systems, and offers potential for EHR implementation.

Background. Metabolic syndrome is a cluster of cardiometabolic risk factors that may increase the risk of cardiovascular disease and type 2 diabetes, and African studies report a higher prevalence in women than in men. Prevention may depend, in part, on whether women recognise the condition and its modifiable risk factors. Relatively little appears to be known about this among women using primary-level health facilities in fast-growing peri-urban areas of Ghana. Objective. To assess knowledge of metabolic syndrome, describe lifestyle risk behaviours, self-reported cardiometabolic conditions and preventive practices, and examine selected lifestyle correlates of self-reported diabetes and hypertension among women attending Kasoa Polyclinic, Ghana. Methods. A descriptive cross-sectional survey was conducted in June and July 2024 among 174 women aged 18-45 years recruited by convenience sampling. A structured, interviewer-assisted questionnaire covered knowledge, lifestyle behaviours, self-reported diagnoses and preventive practices. Data were summarised as frequencies and percentages, and associations were examined with Pearson's chi-square test. Results. Only 37 women (21.3%) described metabolic syndrome as a condition that raises the risk of heart disease and type 2 diabetes, 40 (23.0%) identified central (apple-shaped) fat as the high-risk pattern and 31 (17.8%) knew that dietary recommendations exist. Most reported no weekly physical activity (116; 66.7%), daily sugary drinks (109; 62.6%), daily processed or fast food (100; 57.5%), high stress (103; 59.2%), and less than six hours' sleep (94; 54.0%). Self-reported diagnoses were hypertension in 60 (34.5%) and type 2 diabetes in 49 (28.2%). Fifty-nine (33.9%) had never received advice on prevention and 105 (60.3%) did not monitor their weight or waist. Self-reported diabetes was associated with short sleep (36.2% among those sleeping under six hours; p = 0.035) and with stress level (p = 0.028), being most frequent among women reporting low stress. Self-reported hypertension was more common with high stress (42.7%; p = 0.022) and with some physical activity (p = 0.005). Conclusion. Women attending this polyclinic appeared to have limited understanding of metabolic syndrome and a high burden of modifiable risk behaviours. Routine counselling on diet, activity, sleep, and weight monitoring at the polyclinic may be warranted. The bivariate, self-reported associations should be interpreted cautiously.

Objective This study aimed to develop and validate a predictive model for sleep disorders in young and middle-aged adults with anemia, providing evidence for early identification, risk stratification, and individualized sleep management. Methods Data in the NHANES were analyzed and randomly divided into development and validation cohorts. LASSO regression was used to screen optimal predictors in the development cohort, followed by univariate and multivariate logistic regression to identify independent predictors and construct a nomogram. Model performance was evaluated using receiver operating characteristic curves, calibration curves, Brier scores, and decision curve analysis. Results The weighted prevalence of sleep disorders among young and middle-aged adults with anemia was 10.19%. Multivariate logistic regression identified seven independent predictors: sex, monocyte count, asthma, overweight, arthritis, congestive heart failure, and hypertension. The model showed good discrimination, with area under the curve values of 0.817 in the development cohort and 0.791 in the validation cohort. Calibration was satisfactory, with Brier scores of 0.074 and 0.075, respectively. Decision curve analysis indicated favorable clinical net benefit in both cohorts. Conclusion The proposed predictive model demonstrated good discrimination, calibration, and may help healthcare providers identify young and middle-aged adults with anemia who are at high risk for sleep disorders.