The association between mobile phone use and sleep is still contested, especially for youth. While most existing studies predominantly rely on self-reported smartphone duration using traditional statistical methods, the potential association between mobile phone unlock counts and sleep has been neglected in prior studies primarily due to the difficulty of estimating the data. This relationship has been largely overlooked due to objective measurement challenges. To examine the associations of mobile phone duration and unlock counts with sleep quality and sleep time. This multi-center investigation included 16,668 participants from six Chinese universities. Objective mobile phone duration and unlock counts were assessed by mobile phone use record screenshots. The Pittsburgh Sleep Quality Index was used to assess sleep quality and time. Double Machine Learning (DML), linear regression, and restricted cubic splines (RCS) models were applied. DML revealed that a 7-h/week increase in mobile phone duration was associated with higher PSQI scores (ATE = 0.03, 95% CI: 0.02 to 0.03) and shorter sleep time (ATE = -4.76, 95%CI: -6.13 to -3.65). Similarly, a 50-time/week increase in unlock counts was linked to increased PSQI scores (ATE = 0.42, 95%CI: 0.21 to 0.63) and reduced sleep time (ATE = -0.89, 95%CI: -1.32 to -0.46). RCS models identified non-linear associations of mobile phone duration with poor sleep and sleep time, notably an inverted U-shaped relationship with sleep time (P for non-linearity < 0.001). Mobile phone unlock counts showed a significant non-linear association with odds of poor sleep (P for non-linearity < 0.01), but a predominantly monotonic decline with sleep time (P for non-linearity = 0.50). Both mobile phone duration and unlock counts are associated with sleep quality and sleep time. Mobile phone duration exhibited non-linear associations with sleep time and poor sleep, showing an inverted U-shaped relationship with sleep time. Mobile phone unlock counts exhibited a non-linear relationship with sleep time, but a predominantly monotonic inverse relationship with odds of poor sleep.
Individuals with a fragile X premutation (PM) are at an increased risk for a variety of physical and mental health conditions, including sleep problems. Sleep problems in children in the general population have been shown to adversely affect development, cognition, behavior, and mood. Because information on the impact of sleep problems in children with a PM is limited, this study aimed to explore the extent of sleep problems in an unreferred cohort of children with a PM and with no PM (NP) and the relationship between sleep and mental health. Using the parent-completed Child Behavior Checklist, sleep and mental health were assessed across two distinct study samples. First, a cross-sectional preschool cohort (n = 324; ages 3-5 years) was used to identify early associations and CGG-moderated effects. Second, a longitudinal cohort (n = 128) was assessed at Time 1 (3-7 years) and Time 2 (8-13 years) to examine cross-sectional and longitudinal associations of sleep and mental health outcomes. Females with a PM exhibited significantly more sleep problems than females with NP at ages 3-5 years. In the preschool cohort, CGG repeat size moderated the relationship between sleep and mental health in a sex- and symptom-specific manner. Longitudinal trajectories differed by PM status: for children with NP, early sleep problems appear stable and predict later sleep outcomes. In contrast, for children with a PM, later sleep problems appear emergent and were associated with concurrent mental health symptoms independent of earlier sleep difficulties. The results demonstrate that females with a PM are more likely than females with NP to experience sleep problems at young ages, and the relationship between sleep and mental health in children with a PM is moderated by CGG repeat size. Children with a PM appear to follow a unique developmental pathway characterized by longitudinal trajectories that diverge from those of children with NP, suggesting different underlying mechanisms.
Sleep-disordered breathing (SDB) is common in childhood and is associated with attentional and behavioral impairments despite largely preserved sleep macrostructure and minimal abnormalities in conventional electroencephalographic measures. This discrepancy has contributed to the perception that sleep is relatively preserved in pediatric SDB and has limited understanding of the physiological mechanisms underlying morbidity. To determine whether pediatric SDB is associated with disruption of the regional organization and homeostatic dynamics of slow-wave activity (SWA), a key physiological marker of sleep- dependent neural recovery and development. Cross-sectional study of 62 children aged 4 to 12 years who underwent overnight polysomnography with high-density electroencephalography in a laboratory setting. Participants were recruited from clinical referrals and the community, spanning the full spectrum of SDB severity. SDB severity indexed by hypopnea index (HI), apnea-hypopnea index (AHI), and obstructive apnea index (OAI). Regional electroencephalogram-derived SWA (0.5-4 Hz) topography and exponential decay parameters derived from frontal and posterior cortical regions. The frontal-to-posterior decay- rate ratio was evaluated as a summary measure of regional sleep homeostasis. In children with lower hypopnea index, SWA demonstrated the expected developmental pattern, with posterior predominance in younger children and a progressive shift toward a more balanced anterior-posterior distribution with age. Increasing HI was associated with attenuation or reversal of this spatial organization. Global SWA showed no meaningful association with SDB severity. In contrast, regional frontal and posterior decay parameters were strongly associated with HI (adjusted R² = 0.53; p < 1 × 10⁻⁶) but not OAI (adjusted R² = 0.05; p = .95). The frontal- to-posterior decay-rate ratio showed the strongest association with HI β = 4.15; 95% CI, 3.17- 5.13; p < 1 × 10⁻¹⁰; adjusted R² = 0.55. Pediatric SDB was associated with regional disruption of slow-wave sleep homeostasis rather than global loss of deep sleep. These alterations affected both the spatial organization and temporal dynamics of SWA during a period of active cortical maturation and were not captured by conventional sleep metrics. Regional SWA dynamics may provide a developmentally sensitive marker of physiological disease burden in children with SDB. Question: Does pediatric sleep-disordered breathing disrupt the regional organization and homeostatic dynamics of slow-wave activity during development in ways that are not captured by conventional sleep metrics?Findings: In this cross-sectional study of 62 children across the spectrum of sleep-disordered breathing, hypopnea burden was associated with altered regional organization and overnight dissipation of NREM slow-wave activity (SWA) despite preserved global SWA. A frontal-to- posterior SWA decay-rate ratio was strongly associated with hypopnea severity, whereas global SWA was not.Meaning: Pediatric sleep-disordered breathing may disrupt sleep physiology in a regional, developmentally meaningful manner not captured by conventional polysomnography, suggesting a potential physiological marker of disease burden beyond event counts.
Sleep disturbances are associated with increased fatigue, reduced quality of life, and neurocognitive dysfunction and have emerged as a common complication among pediatric cancer survivors. Sleep disturbances are particularly concerning given their potential to exacerbate existing neurocognitive impacts of cancer treatments. This pilot study examined the feasibility and acceptability of a home-wearable EEG-based sleep device (Sleep ProfilerTM) for acute lymphoblastic leukemia (ALL) survivors as well as associations between specific sleep parameters and neurocognitive functioning. Children (ages 8-12; M = 10 years, SD = 1.6; N = 23) >6 months post-treatment for ALL were enrolled at clinical visits and wore the Sleep ProfilerTM for two consecutive nights at home, followed by neurocognitive testing of attention, inhibitory control, working memory, and processing speed. Parents completed subjective measures of child sleep, anxiety, depression, and acceptability. Feasibility reflected the percentage of children wearing the device at least one night and the percentage of nights with good EEG quality data. All participants wore the device both nights, with 84% meeting the threshold for good quality measurement. Few children met recommended quantity and quality sleep thresholds based on objective measurement, including 5 patients with elevated snoring levels; 43.5% of subjective ratings fell above the threshold for sleep disturbance. Greater sleep latency was associated with worse inhibitory control (r = -0.42, p = 0.046), and total sleep time was positively associated with inhibitory control and attention. Findings confirm the feasibility and acceptability of home EEG sleep monitoring in school-age survivors, and associations of sleep latency and snoring with reduced neurocognitive functioning may offer modifiable risk factors for aspects of neuropsychological dysfunction common in pediatric survivorship. At the time this study was conducted, we were not required to register the study on ClinicalTrials.gov. It was a single-institution feasibility study without intervention, which was not considered a clinical trial.
High-energy trauma is characterized by severe injuries, complex clinical conditions, and high mortality rates. Trauma exposure itself induces stress and excessive alertness, leading to sleep disturbances, which in turn exacerbate anxiety, depression, and the risk of post-traumatic stress disorder, while delaying natural recovery after trauma. However, screening for sleep disorders in hospitalized children with high-energy trauma remain insufficient. This study aimed to explore early post‑traumatic sleep status and its associations with related symptoms in children with high‑energy trauma using ecological momentary assessment (EMA). A longitudinal observational design was adopted. Children with high‑energy trauma admitted to our hospital from July 1, 2024, to May 15, 2025 were recruited using convenience sampling. Sleep status and related symptoms were continuously monitored for the first five days post‑trauma. Data were analyzed using generalized estimating equations (GEE) and multivariate linear regression. A total of 69 patients were included in the final analysis. Pain was the most severe symptom, followed by anxiety, fear, and fatigue. GEE revealed that pain, anxiety, fear, and dizziness were significantly associated with sleep quality (P < 0.001, P = 0.033, P = 0.012, P = 0.034); pain, itching, and numbness were significantly associated with reduced sleep efficiency (P < 0.001, P = 0.003, P = 0.004), whereas fatigue was significantly associated with improved sleep efficiency (P = 0.032); pain and fear were significantly associated with nocturnal awakenings (P < 0.001, P = 0.009). Moreover, symptoms were often inter‑related. Multivariate linear regression showed that factors affecting sleep quality included pain on day 1 and day 3 (P = 0.001, P = 0.018), fear on day 4 (P = 0.045), and fear and itching on day 5 (P = 0.011, P = 0.017). Regarding sleep efficiency, the primary influencing factor were: pain on day 1 post-trauma (P = 0.001), numbness at the affected site on day 2 (P = 0.004), fear, pruritus, and numbness at the affected site on day 4 (P = 0.034, P < 0.001, P < 0.001), and pruritus on day 5 (P < 0.001). Children with high‑energy trauma exhibit certain sleep disturbances in the early post‑traumatic period, and the main factors influencing sleep change over time. Close attention should be paid to sleep disorders and their associated influencing factors, and appropriate interventions should be implemented.
Infant sleep is disrupted around the onset of motor milestones, but the causal mechanisms underlying this relationship are unclear. This study aims to corroborate prior reports of the link between locomotor milestone onset and sleep disruptions and expand the literature by asking whether language milestones are also associated with sleep disruptions. Time-series changepoint detection analyzed parent reported milestone onset data and sleep data of two age cohorts collected remotely through an online app and baby monitor system. Disruptions to sleep were found relative to the onsets of first crawling steps, first walking steps, walking mastery, babbling, cooing, expressive jargon, new word use, and object labeling. These results replicate evidence for a relationship between sleep disruption and locomotor milestone onset and offer the first evidence of disruptions to sleep associated with language milestones. To our knowledge this is the first study to show that skill acquisition affects infants' sleep prior to the expression of the skill. Changes in sleep patterns demonstrate that prior to skill onset skill-relevant behaviors are marshaled and coordinated to facilitate the emergence of new skills. After skill onset, sleep functions to consolidate new knowledge and skills and support the process of mastery.
Sleep disturbances are common in people with diabetes, yet their relationship to automated insulin delivery (AID) use has not been well described in large, real-world cohorts. We assessed subjective sleep quality, fear of hypoglycemia, and their associations with glycemic outcomes among adults with diabetes using open-source and commercial AID compared with non-users. We conducted a cross-sectional analysis of 529 adults from the OPEN Project (2020-2023). Participants completed the Pittsburgh Sleep Quality Index (PSQI) and Hypoglycemia Fear Survey-II (HFS-II) short form. All participants self-reported glycated hemoglobin (HbA1c) levels; a subsample of 60 AID users contributed ≥25 days of continuous glucose monitoring (CGM) data. Free-text responses to PSQI item 5j were thematically coded. AID users reported better sleep (median 5 [IQR 3-7] vs. 7 [IQR 5-9], p < .001) and lower fear of hypoglycemia (median 7 [IQR 3-11] vs. 13 [IQR 8-19], p < .001) than non-users. Nevertheless, 43% of AID users and 69% of non-users exceeded poor sleep thresholds. Women reported worse PSQI and HFS-II scores than men (both p < .001). Diabetes-related causes of sleep disruption were more common among non-users (p < .05). PSQI and HFS-II scores correlated with HbA1c in the subsample, but associations with CGM metrics were not significant. Adults using AID systems reported better sleep quality and lower fear of hypoglycemia than those managing diabetes without automation, yet a large proportion of all participants continued to experience poor sleep. Diabetes-related nocturnal disruptions remained common among non-users, suggesting that AID may alleviate-but not eliminate-the nighttime diabetes burden.
Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder marked by recurrent episodes of upper-airway obstruction, leading to intermittent hypoxia, recurrent arousals, and fragmented sleep. It is highly prevalent worldwide and remains underdiagnosed, particularly when symptoms such as fatigue, poor concentration, and nonrestorative sleep overlap with obesity, chronic pain, depression, or inflammatory disease. These diagnostic challenges are clinically relevant in rheumatology, where pain, fatigue, poor sleep, and immune activation frequently coexist. This narrative review examines OSA as a potentially modifiable contributor to chronic pain and fatigue in rheumatologic disease. We synthesize evidence on intermittent hypoxia, oxidative stress, systemic inflammation, cytokine-mediated nociceptor sensitization, impaired endogenous pain inhibition, and central sensitization. Disease-specific evidence is reviewed for rheumatoid arthritis, psoriatic arthritis, systemic lupus erythematosus, axial spondyloarthritis, and fibromyalgia. We also evaluate continuous positive airway pressure (CPAP) therapy, distinguishing established benefits for respiratory events, oxygenation, sleepiness, and sleep-related quality of life from less certain pain-related effects. Current evidence suggests that CPAP may improve inflammatory biomarkers, fatigue, and pain sensitivity in selected populations, but direct rheumatology-specific evidence for pain reduction remains limited. An evidence-informed clinical framework is proposed to guide targeted OSA screening, diagnostic referral, treatment as adjunctive care, and follow-up in patients with persistent pain, fatigue, or nonrestorative sleep despite otherwise having appropriate rheumatologic management. As much of the available evidence is observational or mechanistic, future prospective studies should include standardized OSA testing, rheumatology-relevant pain outcomes, inflammatory biomarkers, disease activity measures, and long-term CPAP adherence.
Obstructive sleep apnea (OSA) is a significant medical and social problem with worldwide importance. The following research article aims to demonstrate that nurse involvement can contribute to the identification of OSA risk using an online survey. For the study, an online questionnaire was developed comprising 15 questions focused on the main symptoms of sleep apnea. The survey is intended for patients aged 30 and older, regardless of sex. The survey card was posted online for 1 month. According to the International Classification of Sleep Disorders, there are over 100 disorders. Insufficient and poor-quality sleep can cause several health disorders: fatigue, inability to concentrate, irritability, changes in metabolism, sexual disorders, depression, and anxiety. Sleep apnea is often characterized by loud snoring followed by periods of breathing cessation. Eventually, the decrease or pause in breathing signals the person to wake up, and the awakening is accompanied by loud snoring or gasping. The nurse developed an algorithm/protocol to determine the risk of OSA and to specify the professional behavior she should have toward the patient. Nurses can administer the online survey and, if there is an established risk for OSA, refer patients to sleep medicine specialists for investigation and treatment, following a developed algorithm/protocol. Sleep apnea is a complex medical problem, and the nurse can be part of the team.
Excessive daytime sleepiness (EDS) is a frequent complaint in the general population. Other than being a common symptom associated with various sleep disorders, EDS may be a consequence of chronic sleep deprivation or the primary symptom of central disorders of hypersomnolence (CDH). In addition to narcolepsy type 1 (NT1), the other conditions within the CDH spectrum are less well-defined and share considerable clinical and neurophysiological similarities. Herein, we describe the clinical management of a complex case that highlights several challenges in the diagnostic process of a patient with EDS and a history of obsessive-compulsive disorder (OCD). In the absence of other sleep disorders, secondary structural causes, and orexin deficiency as possible causes for EDS, the patient was initially diagnosed with NT2 based on electrophysiological criteria. However, the clinical course, which showed only a partial response to various stimulant medications for subjective and objective daytime sleepiness, led us to question the diagnosis. A detailed psychiatric and neuropsychological assessment revealed, in addition to the previously identified severe OCD and anxiety, a diagnosis of attention deficit hyperactivity disorder (ADHD), subsequently leading to a revised diagnosis of hypersomnia associated with a psychiatric disorder (HPSY). The literature regarding OCD and sleep disorders remains scarce but the connection between ADHD and hypersomnia, as well as narcolepsy, is well-established. Our case report illustrates that a psychiatric and neuropsychological assessment should be considered mandatory for patients with objective EDS.
To compare biopsychosocial burden, depressive symptoms, and masticatory muscle pain sensitivity between patients with good and poor sleep quality in myogenous temporomandibular disorders (TMD). In this cross-sectional study, 95 adults with myogenous TMD according to the Diagnostic Criteria for TMD were classified into good or poor sleepers based on the Pittsburgh Sleep Quality Index. Pain intensity, biopsychosocial burden, insomnia severity, and pain catastrophizing were evaluated using validated instruments. Masticatory muscle pressure pain thresholds (PPT) assessed pain sensitivity. Poor sleepers reported higher pain intensity, depressive symptoms, anxiety, somatic burden, oral parafunctions, and insomnia severity. No significant differences emerged in pain catastrophizing, functional limitation, or PPT. Poor sleep quality remained associated with depressive symptoms but not pain intensity after adjusting for psychosocial domains. In this sample of myogenous TMD patients poor sleep quality appeared associated with greater psychological burden, particularly depressive symptoms, but not with reduced PPT.
Work-related musculoskeletal disorders (WMSDs) are highly prevalent among nurses and threaten workforce stability. Although sleep disturbance is known to be associated with WMSDs, the psychosocial pathways underlying this relationship remain poorly understood. This study aims to examine whether sense of agency and perceived social support mediate the relationship between sleep quality and WMSDs among hospital nurses, using a structural equation modeling approach. A convenience sample of staff nurses was recruited from six tertiary hospitals in three Chinese cities. Participants self-reported sociodemographics, the Pittsburgh Sleep Quality Index (PSQI), sense of personal control, perceived social support, and the 12-month prevalence/number of WMSDs. Structural equation modeling with maximum likelihood estimation was constructed to examine the hypothesized pathways, and bias-corrected bootstrap analysis was conducted to analyze the mediating effect of the sense of agency and perceived social support between sleep quality and the number of WMSDs. Our study included information from 1,388 nurses working in clinical settings. After controlling the factors of gender, length of service, night shift, frequent trunk flexion, frequent heavy lifting, and perceived work fatigue, the PSQI of nurses showed a direct negative association with the sense of agency and perceived social support. Perceived social support had a direct positive impact on the sense of agency, and perceived social support and agency had a direct negative impact on the number of WMSDs in nurses (p < 0.001), χ2/df = 7.466, CFI = 0.906, RMSEA = 0.070, and the model demonstrated acceptable fit indices. The direct effect accounted for 81.8% of the total effect, while the indirect effects through three significant mediation paths accounted for 18.2% of the total effect (indirect effect = 0.035, total effect = 0.192). Even after accounting for established ergonomic and occupational covariates, poor sleep quality was not only directly associated with a higher number of WMSD sites among nurses but also showed an indirect association with WMSDs through lower sense of agency and perceived social support. Interventions that protect and bolster these psychosocial resources should be embedded within integrated musculoskeletal-health frameworks addressing biological, psychological, and social determinants.
Preoperative anxiety is a prevalent clinical problem linked to adverse surgical outcomes, including elevated pain, prolonged hospital stays and increased risk of postoperative delirium. Current assessments rely heavily on subjective measures, necessitating objective biomarkers. We investigated whether baseline electroencephalography (EEG) and sleep-wake profiles can predict anxiety levels in a mouse model. Fifty male C57BL/6N mice were implanted with EEG and electromyography (EMG) electrodes, recorded for 24 h post-recovery before undergoing a cued fear-conditioning protocol. Six behavioural indices, capturing freezing during tone and intertone epochs in both conditioning and retrieval, were used in k-medoids clustering to classify mice into high-anxiety or low-anxiety groups. Comparative analysis revealed pronounced group differences in baseline sleep architecture. HA mice exhibited diminished rapid eye movement sleep (REMS) proportions and elevated NREMS in the dark period, alongside altered bout lengths. Spectral analysis underscored lower delta (0.5-2 Hz) power in high-anxiety mice, with heightened eta/beta (~15-30 Hz) activity during REMS suggesting aberrant cortical arousal. Moreover, high-anxiety mice showed significantly longer and higher-amplitude sleep spindles, reinforcing the interplay between disrupted sleep microstructure and enhanced anxiety-like responses. These findings illustrate that specific EEG and sleep-wake parameters prior to a conditioned stimulus can forecast distinct anxiety phenotypes in a widely used inbred mouse model. Although our study focuses on fundamental mechanisms in laboratory animals, this line of research may lead to objective markers of anxious behaviour susceptibility in broader contexts, potentially identifying individuals at higher risk for heightened anxiety in clinically relevant settings, for example, preoperative anxiety.
Although pediatric hematopoietic stem cell transplantation (HSCT) patients often experience sleep disruptions during hospitalization, no clinical guidelines exist for how to manage their sleep. We sought to learn how clinicians approach inpatient sleep disruptions by surveying 111 pediatric HSCT medical prescribers, nurses, and psychosocial staff from across the United States. Clinicians estimated 58% of inpatients developed sleep issues. Although they rated external factors (e.g., noise) as most impactful, clinicians were most likely to implement patient-level interventions (e.g., melatonin). Research is needed to assess the efficacy of commonly delivered treatments, as well as to develop and implement systems-level changes addressing external sleep barriers.
The entopeduncular nucleus (EP) is a major output nucleus of the basal ganglia and plays a critical role in integrating motor, emotional, and behavioral processes. Although traditionally linked to motor control, accumulating evidence indicates that the EP is deeply involved in psychiatric disorders, sleep regulation, addiction, and mood-related behaviors. As the rodent homolog of the human internal Globus pallidus (GP) the EP represents a key translational structure bridging preclinical and clinical neuroscience. This narrative review was conducted following established narrative review methodology. Relevant literature was identified through a structured search of major biomedical databases. Peer-reviewed experimental and clinical studies investigating EP anatomy, connectivity, neurotransmitter systems, and functional roles were included. The review synthesizes findings from mouse and rat models employing optogenetic and chemogenetic manipulation, electrophysiological recording, neuroanatomical tracing, molecular approaches, and behavioral assays, alongside human neuroimaging, lesion, and deep brain stimulation studies. Evidence from rodent models demonstrates that the EP functions as a convergence hub integrating GABAergic, glutamatergic, dopaminergic, serotonergic, and endocannabinoid signaling. EP projections to the lateral habenula regulate aversive processing, addiction-related behaviors, and mood states. Cell-type-specific mouse studies identify entopeduncular circuits implicated in anxiety regulation. Dysregulation of EP circuits is implicated in depression, anxiety, and Parkinsonian motor dysfunction. Clinical and preclinical neuromodulation studies further support the therapeutic relevance of targeting EP circuits. The EP is a multifunctional neural hub extending beyond motor control. Integrating evidence from rodent and human studies highlights its importance in psychiatric and sleep disorders and supports its potential as a translational therapeutic target. The entopeduncular nucleus (EP) functions extend beyond motor control to psychiatric regulation and sleep modulation.EP-lateral habenula projections are crucial for addiction and aversive behaviors.EP’s endocannabinoid system plays a vital role in sleep regulation and mood control.Deep brain stimulation of EP shows therapeutic potential for Parkinson’s disease and treatment-resistant depression.Novel therapeutic approaches targeting EP circuits are emerging for psychiatric disorders, including anxiety, Obsessive-compulsive disorder (OCD), and schizophrenia.Translation of preclinical findings to human applications remains a key challenge.
BackgroundLight offers a promising approach to sleep and circadian disturbances in mild cognitive impairment (MCI).ObjectiveTest a home-based lighting intervention in people living with MCI.MethodsIn a randomized, placebo-controlled trial, 61 participants received active or placebo light for 24 weeks, with assessments for cognition, sleep, depression, and quality of life at baseline, week 13, 25, and, post-intervention, at week 37. Light exposure was measured as area under the curve (AUC) for morning circadian stimulus (CS).ResultsActive light participants (mean age 69.7 years; 52% male; mean MoCA 21.4) showed greater improvement in ADAS-Cog memory scores than placebo (p = 0.035), higher morning CS AUC by week 25 (0.021 vs -0.030; p = 0.025), and better sleep percent (-0.21 vs -1.29; p = 0.042), wake percent (-0.10 vs 1.19; p = 0.023), and wake after sleep onset (2.19 vs 8.23 min; p = 0.031).
Obstructive sleep apnea (OSA) is marked by daytime sleepiness, loud snoring, gasping or choking, and at least 5 obstructive breathing events per hour of sleep. Though polysomnography is the "gold standard" for diagnosing OSA, it is costly and time-consuming; alternatives like cone-beam computed tomography (CBCT) exist. CBCT, provides a large field of view of upper airway, making it a valuable adjunctive tool for airway evaluation in patients at risk for OSA. To evaluate the upper airway dimensions of patients with snoring and controls using CBCT and the role of CBCT as an adjunctive screening tool. Study was done on 20 patients, 10 snoring subjects and 10 without snoring. Berlin questionnaire was given to the patients, to assess the risk for OSA. CBCT was used to measure the airway dimensions. Length of ramus and body of mandible was also estimated. Out of 10 snoring patients, 9 were at high risk for OSA. Snoring subjects had significantly smaller mean A-P oropharynx dimensions, lateral dimensions, and oropharynx volume, but a longer oropharynx and shorter mandibular length than controls. Additionally, their mean BMI was higher. The findings highlight 3D imaging's role in identifying patients at risk for OSA by showing differences in airway dimensions, volume, and mandibular morphology.
Machine learning models for Obstructive Sleep Apnea (OSA) diagnosis have largely inherited some structural limitations: reliance on generic, opportunistically collected feature sets; use of the Apnea-Hypopnea Index (AHI) as the sole ground truth; poor performance in multi-class severity grading; and predictions that offer clinicians no mechanistic insight. This study addresses these gaps by prospectively assembling a multi-domain dataset that, alongside established demographic, anthropometric, and questionnaire-based predictors, incorporates a panel of craniofacial and intraoral metrics specifically designed to capture the structural-anatomical contributors to OSA - integrating these into an interpretable framework for three-class severity classification evaluated against both AHI and the Oxygen Desaturation Index (ODI). In this single-center study, 233 treatment-naïve adults from a tertiary referral cohort (61.8% severe OSA prevalence) underwent in-laboratory polysomnography (PSG). All predictor variables were collected prior to PSG outcome disclosure through a standardized clinical examination, requiring no overnight recording or specialized equipment. An Artificial Neural Network (ANN) was independently trained for three-class severity classification (No/Mild, Moderate, Severe) for each index. Model performance was evaluated on an independent test set (n = 47; 20% of the sample), with interpretability assessed using SHapley Additive exPlanations (SHAP). Comparison with an anatomy-excluded ablation model was conducted to establish the added value of the full feature set. The AHI-based model achieved 87.2% overall accuracy (sensitivity/specificity: No/Mild 0.93/0.97, Moderate 0.80/0.91, Severe 0.88/0.93). The ODI-based model achieved 76.6% accuracy, offering reliable exclusion of severe desaturation burden (No/Mild specificity: 0.94). Univariate analyses confirmed significant associations between OSA severity and STOP-BANG score, age, BMI, neck circumference, observed apnea, loud snoring, high blood pressure, Cervico-Mental Angle, Mentocervical Distance, and submental fat (all p ≤ .034 for both indices). SHAP analysis further identified V-shaped maxillary arch, Mallampati score, increased overjet, and alcohol use as influential model predictors - several reaching high model rankings despite modest univariate significance. Notably, AHI and ODI models diverged in their feature weighting - anatomy-driven features dominated AHI prediction while body habitus and comorbidity markers dominated ODI. Against a conventional demographic and questionnaire-based ablation model, the full anatomy-inclusive ANN achieved substantially higher accuracy (87.2% vs. 72.3%), with the largest gain at the Moderate-class boundary (sensitivity: 0.80 vs. 0.58). As a proof-of-concept, this study demonstrates that an interpretable ML framework integrating craniofacial and intraoral assessments with standard clinical predictors can classify OSA severity across three classes and provide feature-level explanations to support clinical reasoning. By developing parallel AHI and ODI models, the framework moves beyond AHI-only paradigms, though both remain frequency-based surrogates; hypoxic burden - quantifying the cumulative oxygen desaturation load per sleep period - is the more physiologically complete target toward which this line of work should progress. Findings are limited by single-center design, spectrum bias from a tertiary referral cohort, modest sample size, and absence of inter-rater reliability data. External validation in larger, more representative populations is needed to confirm the robustness and clinical utility of this approach.
This study explored risk factors associated with depressive symptoms in older patients with obstructive sleep apnea (OSA) and assessed correlations of mean pulse oxygen saturation (MSpO2) with depressive symptoms. In total, 1,085 older patients diagnosed with OSA via polysomnography (PSG) were included. Based on scores from the 12-item Geriatric Depression Scale (GDS-12), participants were classified into two subgroups to identify depressive symptom-related risk factors. Logistic regression analysis, restricted cubic splines, and subgroup analyses were performed to evaluate correlations of MSpO2 with depressive symptoms. Depressive symptoms were observed in 139 patients (12.8% of the sample). Logistic regression analysis indicated that age (per 1-year increase, odds ratio [OR] = 1.11, 95% confidence interval [CI]: 1.08-1.14; P < 0.001), smoking (OR = 1.66, 95% CI: 1.02-2.69; P = 0.041), MSpO₂ (per 1% increase, OR = 0.90, 95% CI: 0.85-0.94; P < 0.001), diabetes mellitus (OR = 1.61, 95% CI: 1.03-2.51; P = 0.038), and renal dysfunction (OR = 2.26, 95% CI: 1.10-4.66; P = 0.027) were significantly associated with depressive symptoms. Additionally, sleep parameters including AHI, ODI, and LSpO₂ were independently associated with depressive symptoms. Restricted cubic splines suggested a linear correlation between MSpO₂ and depressive symptoms (nonlinear P = 0.38). Compared with patients in the highest category (MSpO₂ ≥ 95.0%), those in the lowest category (MSpO₂ ≤ 91.7%) showed increased depressive symptom risk (OR = 2.25, 95% CI: 1.34-3.78, P = 0.002). Subgroup analyses confirmed this linear relationship. A linear correlation exists between MSpO2 and depressive symptoms in older patients with OSA. Additionally, age, smoking, diabetes mellitus, and renal dysfunction are strongly associated with depressive symptoms in this population.
Obesity, diabetes, and hypertension are major global health burdens influenced not only by lifestyle factors but also by genetic predisposition, sleep quality, chrononutrition, and circadian rhythms. This review examined how these factors interact in metabolic and cardiovascular diseases, with emphasis on sex-specific differences. A narrative review was conducted using PubMed, Scopus, and Web of Science databases for studies published between 2006 and 2026. A total of 112 studies were synthesized, including randomized trials, observational studies, systematic reviews, meta-analyses, Mendelian randomization, and mechanistic investigations. Evidence indicates that genetic susceptibility and circadian disruption contribute significantly to obesity, diabetes, and hypertension. Sleep deprivation, obstructive sleep apnea, and circadian misalignment were consistently associated with insulin resistance, appetite dysregulation, elevated blood pressure, and increased cardiometabolic risk, particularly among shift workers. Hormonal and metabolic pathways involving leptin, ghrelin, cortisol, and melatonin appear to mediate these effects. Important sex differences were observed, with women showing greater vulnerability to sleep-related appetite disturbances and men presenting a higher prevalence of visceral adiposity, sleep apnea, and hypertension. Chrononutrition strategies, including time-restricted eating and Mediterranean dietary patterns, showed beneficial effects on sleep quality, glycemic control, inflammation, and metabolic health. Emerging evidence also suggests bidirectional interactions between gut microbiota rhythmicity and circadian regulation. Genetic predisposition, sleep disturbances, and circadian disruption interact to influence metabolic and cardiovascular disease risk. Integrative approaches combining chrononutrition, sleep hygiene, circadian alignment, and personalized nutritional strategies may improve the prevention and management of cardiometabolic diseases.