Search Results (1,612)

Background: Rheumatic diseases (RDs) are associated with increased cardiovascular morbidity, including a 40% higher risk of atrial fibrillation (AF). While ablation has become the cornerstone of rhythm control, its safety in patients with rheumatic diseases remains poorly defined. Methods: Adults with a primary admission diagnosis of AF catheter ablation from 2016 to 2022 were identified using the National Inpatient Sample. We excluded patients with other forms of supraventricular tachycardia, pacemaker/defibrillator procedures, and atrioventricular junction ablations. Sociodemographic, clinical characteristics, and outcomes were compared between groups. Multivariate logistic regression adjusted for age, race, sex, and potential comorbid confounders was used to assess for independent associations. Results: A weighted total of 48,855 patients were included, 2.5% of which had RD. These patients were predominantly female, older, and had higher rates of renal dysfunction, hypertension, heart failure, history of stroke, ischemic heart disease, heart failure, and obstructive sleep apnea (all p < 0.001). Patients with RD had higher complication rates (12.9% vs. 8.8%, p < 0.001); specifically, bleeding (p < 0.001), infection (p = 0.008), pericardial (p = 0.003), and respiratory complications (p < 0.001). RDs were not found to be an independent predictor of complications, though there was a trend towards more complications (odds ratio 1.43, 95% confidence interval 0.97–2.11, p = 0.070). Conclusions: Patients with RD undergoing AF ablation were older, female, and had higher rates of comorbidities. This translated to higher unadjusted periprocedural complications in patients with rheumatic diseases. While RDs were not independently associated with adverse outcomes, a trend towards increased complications was observed. Full article

Background/Objectives: Sleep-disordered breathing (SDB), including obstructive sleep apnea, is common in children and is associated with mouth breathing, snoring, and neurobehavioral disturbances. In pediatric orthodontic patients, oral habits and craniofacial imbalances may contribute to airway dysfunction, making orthodontic evaluation a potential setting for early identification of SDB. This study aimed to estimate the prevalence of SDB and to evaluate its associations with parent-reported behavioral symptom profiles in a cohort of pediatric orthodontic patients. Methods: A multicenter cross-sectional study was conducted in 186 children aged 7–13 years attending orthodontic clinics in Oradea and Târgu Mureș, Romania. Parents completed a structured questionnaire on oral habits, the 22-item Pediatric Sleep Questionnaire (PSQ), with SDB defined as 8 or more positive responses, and a parent-reported behavioral screening form assessing ADHD symptom subtypes, oppositional-defiant disorder (ODD), conduct disorder, and anxiety/depression. These behavioral outcomes were based on screening measures and were not intended as clinical psychiatric diagnoses. Associations were analyzed using chi-square or Fisher’s exact tests, and multivariable logistic regression analyses were performed adjusting for age, sex, and weight status. Results: Mouth breathing was reported in 61.8% of participants, snoring in 26.9%, and SDB in 13.4%. Positive screens for ADHD-inattentive (p < 0.001), ADHD-hyperactive/impulsive (p < 0.001), ADHD-combined (p < 0.001), ODD (p < 0.001), and anxiety/depression (p < 0.001) were significantly more frequent among children with SDB. In multivariable analysis, SDB remained independently associated with ADHD-combined subtype (OR = 6.22), ADHD-hyperactive/impulsive symptoms (OR = 5.84), oppositional-defiant disorder (OR = 4.91), and anxiety/depression (OR = 4.38). Conclusions: SDB was identified in a meaningful proportion of pediatric orthodontic patients and was significantly associated with multiple screening-defined behavioral symptom domains. These findings support consideration of brief airway- and sleep-oriented screening during orthodontic assessment, particularly in school-aged children presenting with mouth breathing, snoring, or behavioral concerns. Given the cross-sectional and questionnaire-based design, the findings should be interpreted as associative and warrant confirmation in prospective studies using objective sleep measures. Full article

Obesity and obstructive sleep apnea (OSA) frequently coexist and synergistically contribute to cardiovascular disease through interconnected mechanical, metabolic, and autonomic mechanisms. This interplay promotes myocardial electrical instability and structural remodeling, favoring the development and persistence of cardiac arrhythmias, particularly atrial fibrillation. Among the key mediators linking obesity to arrhythmogenesis, epicardial adipose tissue has emerged as a relevant factor that may contribute to local pro-inflammatory, pro-fibrotic, and autonomic effects on the myocardium. In parallel, OSA-related intermittent hypoxia and intrathoracic pressure swings further amplify electrical instability and autonomic imbalance, reinforcing a self-sustaining arrhythmogenic substrate. Therapeutic strategies are increasingly shifting toward upstream interventions targeting these underlying mechanisms. Metabolic therapies, including the dual GIP/GLP-1 receptor agonist tirzepatide, have demonstrated substantial weight reduction and improvement in OSA severity, with potential indirect benefits on arrhythmic risk through modulation of visceral adiposity, inflammation, and metabolic dysfunction. On the electrophysiological side, cardioneuroablation has emerged as a potentially investigational option in selected patients with vagally mediated bradyarrhythmias, although its role remains to be fully defined. Overall, these observations support an integrated, phenotype-driven approach combining respiratory therapy, metabolic modulation, and targeted electrophysiological interventions. This framework may help redefine therapeutic priorities, shifting from symptom control toward modification of the underlying arrhythmogenic substrate and improvement of long-term cardiovascular outcomes. Full article

Sleep disorders, such as insomnia, obstructive sleep apnea (OSA), narcolepsy, REM sleep behavior disorder, and circadian rhythm disturbances, represent a rapidly expanding global health burden that is strongly associated with cardiovascular, metabolic, neurological, and psychiatric diseases. Advancements in wearable sensing technologies and Internet of Medical Things (IoMT) infrastructures have expanded the possibilities for continuous, home-based sleep assessment beyond conventional polysomnography laboratories. These Sleep Health Internet of Things (S-HIoT) systems combine multimodal physiological sensing (EEG, ECG, SpO₂, respiratory effort and actigraphy) with wireless communication and cloud-based analytics for automated sleep-stage classification and disorder detection. Nonetheless, the digitization of sleep medicine brings about significant cybersecurity concerns. The constant transmission of sensitive biomedical information makes S-HIoT networks open to anomalous traffic flows, signal manipulation, replay attacks, spoofing, and data integrity violation. Existing studies mostly focus on analyzing physiological signals and network intrusion detection independently, resulting in a systemic vulnerability of cyber–physical sleep monitoring ecosystems. With the aim of addressing this empirical deficiency, this review integrates emerging advances (2022–2026) in the AI-assisted categorization of sleep phases and IoMT anomaly detector designs on the finer analysis of CNN, LSTM/BiLSTM, Transformer-based systems, and a component part of federated schemes and the lightweight, edge-deployable intruder assessor models available. The aim of this study is to uncover a gap in the literature: integrated architectures to trade off audiences of faithfulness of physiological modeling with communication-layer security. To counter it, we present a single framework to include CNN-based spatial feature extraction, Bidirectional Long Short-Term Memory (BiLSTM)-based temporal models and Random Forest-based ensemble classification using a dual task-learning approach. We propose a multi-objective optimization framework to jointly optimize the performance of sleep-stage prediction and that of network anomaly detection. Performance on publicly available datasets (Sleep-EDF and CICIoMT2024) confirms that hybrid integration can be tailored to achieve high accuracy [99.8% sleep staging; 98.6% anomaly detection] whilst being characterized by low inference latency (<45 ms), which is promising for feasibility in real-time deployment in view of targeting edge devices. This work presents a comprehensive framework for developing secure, intelligent, and clinically robust digital sleep health ecosystems by bridging chronobiological signal modeling with cybersecurity mechanisms. Furthermore, it highlights future research directions, including explainable AI, federated secure learning, adversarial robustness, and energy-aware edge optimization. Full article

Background and Objectives: Pregnancy causes various physiological and hormonal changes that disrupt sleep architecture and modify respiratory patterns, increasing the risk of sleep-related breathing disorders (SBDs) such as obstructive sleep apnea (OSA) and potentially exacerbating pre-existing conditions. These disorders have been linked to adverse maternal and fetal outcomes. However, current screening tools remain inadequate, and data, including from Portugal, remain limited. This study aimed to assess the prevalence of SBD symptoms suggestive of sleep-disordered breathing during pregnancy, characterize the population, and explore associations with demographic and anthropometric parameters. Materials and Methods: A prospective observational study was conducted from July to December 2024 at Hospital da Luz Lisboa, involving pregnant women ≥ 18 years attending routine consultations. Participants completed a structured questionnaire that assessed demographic and anthropometric data, comorbidities, ten SBD symptoms, and the Epworth Sleepiness Scale (ESS). Results: The cohort included 289 participants, with a mean age of 34.4 years and pre-pregnancy body mass index (BMI) of 23.6 kg/m². On average, women reported 3.1 SBD symptoms, with fatigue (65.4%), memory/concentration impairment (52.2%), and non-restorative sleep (50.5%) being the most common. Excessive daytime sleepiness (ESS >10) was present in 22.8% of the population. Snoring was significantly associated with older age and higher BMI (p = 0.0009 and p < 0.0001, respectively). Both the number of symptoms and ESS scores tended to increase with gestational age, particularly in the third trimester. Women with diabetes had higher odds of reporting snoring, nocturnal dyspnea, and witnessed apneas, with odds ratios of 4.65, 8.77, and 11.38, respectively. Conclusions: SBD symptoms and daytime sleepiness are highly prevalent in pregnancy and typically increase with advancing gestation. These findings emphasize the need for improved clinical strategies to enable early identification and management of SBD in pregnant women, thereby reducing maternal-fetal complications. Full article

Background/Objectives: Pediatric obstructive sleep apnea (OSA) is a complex disorder with a variable presentation and often challenging diagnostic testing. The history and physical examination in pediatric OSA frequently differ from those in adults. The treatment options are multifaceted and must be tailored to the individual patient. Artificial intelligence (AI) modalities currently employed in pediatric sleep medicine face several important limitations: modality fragmentation, lack of explainability, and limited semantic integration. Method: Our team proposes a new vision for AI and pediatric sleep medicine. This platform is based on a knowledge graph (KG) framework integrating structured and unstructured data to enable reasoning, personalization, and clinical decision support. Results: This framework represents a conceptual architecture; it has not yet been empirically implemented, and the use cases described herein are illustrative of its intended capabilities. Components of the infrastructure developed for similar applications have been successfully implemented. The quantitative feasibility pilot KG represented 100% multimodal data with >90% semantic completeness. Conclusions: Fully realized and deployed into the clinical space, this pediatric OSA KG system will enhance tertiary care programs and help project tertiary-level pediatric care into underserved regions. Full article

Background: Surfactant Protein D (SP-D) is a critical immunomodulatory collectin maintaining alveolar homeostasis. Obstructive sleep apnea (OSA)-related intermittent hypoxia (IH) disrupts pulmonary surfactant integrity; however, severity-dependent SP-D dynamics remain incompletely characterized. This study explores SP-D as a potential indicator of IH-induced alveolar stress and evaluates whether Galectin-3 (Gal-3) inhibition modulates surfactant homeostasis. Methods: Forty adult male Sprague-Dawley rats (8 per group) were randomized to Control (normoxia), Moderate IH (MIH; 15–30 events/hour), Severe IH (SIH; 30–60 events/hour), MIH + Gal-3 inhibitor (Modified Citrus Pectin, 800 mg/kg/day), or SIH + Gal-3 inhibitor. IH exposure lasted 8 h/day for 10 days. Outcomes included circulating SP-D, Surfactant Protein B (SP-B), inflammatory markers, physiological parameters, and histopathological lung injury scores assessed via American Thoracic Society guidelines. Results: SP-D levels showed numerical reductions with increasing IH severity (Control: 1969.07 pg/mL [IQR: 262.15]; SIH: 1404.30 pg/mL [IQR: 351.88]), representing a 28.6% decrease. However, between-group variability resulted in non-significant omnibus testing (Kruskal–Wallis p = 0.187). Gal-3 inhibition elevated SP-D levels, particularly in severe IH (2133.95 pg/mL [IQR: 1240.70]), though high inter-individual variability was observed (CV = 58.1%). SP-B showed significant suppression under moderate IH (p = 0.019) with restoration by treatment. Exploratory correlation analysis revealed moderate positive associations between SP-D and heart rate (r = 0.587) and respiratory rate (r = 0.419) in severe IH, though these did not reach statistical significance (p = 0.126 and p = 0.301, respectively). Histologically, severe IH induced diffuse alveolar damage (total lung score: 19.67 ± 0.82). Gal-3 inhibition produced context-dependent effects: protective in severe IH but paradoxically exacerbating inflammation under moderate IH (29.20 ± 4.64 vs. 20.00 ± 4.34; p < 0.05). Gal-3 inhibition significantly attenuated cardiac injury (injury score: 0.00 ± 0.00 vs. 7.17 ± 0.75 in severe IH; p < 0.001, η² = 0.859). Conclusions: SP-D demonstrates severity-associated alterations consistent with alveolar epithelial stress during IH, though high variability limits definitive biomarker validation in this sample. Gal-3 inhibition modulates surfactant homeostasis and attenuates cardiopulmonary injury in a context-dependent manner. These findings support further investigation into SP-D as a component of multimodal severity stratification in OSA and highlight Gal-3 inhibition as a context-dependent anti-inflammatory strategy, pending validation in larger cohorts with tissue-level confirmation. Full article

Background/Objectives: This study analyzes the relationship between obesity phenotypes and sleep apnea risk in the Korean population. Methods: This study utilized data from the Korean National Health and Nutrition Examination Survey (KNHANES) collected between 2019 and 2021 (n = 10,970 adults; age ≥ 40 years). Obesity phenotypes were classified into four groups based on body mass index (BMI) and the presence of metabolic syndrome: metabolically healthy normal weight (MHNW), metabolically abnormal normal weight (MANW), metabolically healthy obese (MHO), and metabolically abnormal obese (MAO). Sleep apnea risk was assessed using the STOP-Bang questionnaire, and multivariate logistic regression analyses were performed to evaluate the association between obesity phenotypes and sleep apnea. Results: Among the 10,970 participants, the phenotypes were as follows: MHNW, 51.1%; MANW, 10.3%; MHO, 15.8%; and MAO, 21.8%. Baseline characteristics differed significantly across phenotypes, with the metabolically unhealthy groups (MANW and MAO) being older and exhibiting more cardiometabolic risk factors than the metabolically healthy groups. The prevalence of STOP-Bang questionnaire components differed significantly across phenotypes (all p < 0.001), and the mean STOP-Bang score increased from MHNW to MAO. In multivariate logistic regression analyses, the odds (adjusted odds ratio [95% CI]) of high sleep apnea risk were significantly elevated in all non-MHNW phenotypes: MAO (10.27 [7.71–13.68]), MHO (6.17 [4.35–8.75]), and MANW (1.91 [1.22–2.98]). Notably, MAO conferred a significantly higher risk than MHO (OR 1.69 [1.34–2.13]), highlighting the synergy of obesity and metabolic dysfunction. Obesity phenotypes, defined by BMI and metabolic health status, were differentially associated with sleep apnea risk in Korean adults. The highest risk was observed in individuals with both obesity and metabolic syndrome, while metabolically abnormal normal-weight adults also showed a significantly increased risk. Conclusions: Metabolic dysfunction may contribute to sleep apnea risk beyond body size alone and may be considered in risk stratification strategies. Full article

Obstructive sleep apnea (OSA) is a widely known sleep disorder that leads to serious health problems and complications. The standard diagnosis method of OSA is polysomnography. However, the process is time-intensive, expensive, and not readily accessible. Machine learning (ML) has been increasingly applied in various medical imaging modalities; however, there is still a lack of research on applying ML to ultrasound imaging for OSA classification. Previous studies on ML applications in medical imaging adopt X-rays, Computed Tomography, and Magnetic Resonance Imaging, leaving ultrasound as an underexplored area. Using the You-Only-Look-Once version 8 algorithm and static tongue ultrasound images, we classified OSA severity: normal, mild, moderate, and severe. A total of 280 ultrasound images were augmented to 838 images using brightness scaling, which enhanced the training process of the model. The system was tested on 60 images, achieving an overall classification accuracy of 85%. The results demonstrate the possibility and potential of using machine learning and ultrasound imaging for classifying the severity of OSA, suggesting potential assistance to clinicians in diagnosing and intervening in this condition. Full article

Background: Ultrasonography (US) has emerged as a non-invasive method for anatomical and functional evaluation of upper airway structures in adult obstructive sleep apnea (OSA). However, its role in severity stratification, dynamic assessment, elastographic characterization, and therapeutic monitoring remain to be investigated. Background/Objectives: The goal herein is thus to systematically review and synthesize available evidence on US assessment in adults with OSA, including structural parameters, dynamic measurements, correlation with the apnea–hypopnea index (AHI), integration with artificial intelligence, and evaluation of myofunctional therapy outcomes. Methods: A PRISMA-compliant systematic review of 19 studies (2007–2025) was conducted, evaluating US in adult patients with polysomnography-diagnosed OSA. Observational, pilot, case–control, and exploratory studies were included. Risk of bias was assessed using the National Institutes of Health Quality Assessment Tool for observational studies. Due to methodological heterogeneity, a structured qualitative meta-analytic synthesis was performed. Results: The tongue base was the most frequently studied structure. Increased tongue thickness, area, and stiffness were consistently associated with higher AHI. Elastography revealed increased intrinsic rigidity in patients with OSA. Dynamic US correlated with drug-induced sleep endoscopy findings and hyoid displacement. Machine learning integration improved severity prediction. A single study evaluated anatomical changes following myofunctional therapy, representing a nascent research area. US may become a complementary, non-invasive tool for anatomical and functional assessment of upper airway structures in adult OSA. Conclusions: Further standardization of acquisition protocols and well-designed longitudinal studies are needed to clarify the clinical role of US in phenotyping and therapeutic monitoring. Full article

Background/Objectives: This study aimed to investigate the impact of allergic diseases (AD) or obstructive sleep apnea (OSA) risk, as a host factor, on the development of severe Mycoplasma pneumoniae Pneumonia (SMPP) in children by analyzing the clinical data of pediatric patients with Mycoplasma pneumoniae Pneumonia (MPP). Methods: This retrospective study enrolled children hospitalized with Mycoplasma pneumoniae pneumonia (MPP) at Shanghai Ninth People’s Hospital from November 2024 to November 2025. Patients were classified into severe (SMPP) and mild (MMPP) groups. Demographic, clinical, laboratory, and questionnaire data were collected and compared between groups. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of SMPP and construct a nomogram. The model was validated for discrimination, calibration, and clinical utility using ROC curves, calibration plots, and decision curve analysis, with internal validation by bootstrap resampling. Results: Among the 150 enrolled children with MPP, 35 (23.3%) were classified as severe (SMPP) and 115 (76.7%) as mild (MMPP). Patients with SMPP exhibited significantly higher frequencies of allergic diseases, prolonged fever and steroid use, elevated inflammatory markers (CRP, LDH, D-dimer, ferritin, ALT), and higher PSQ and RQLQ scores (all p < 0.05). Disease severity was positively correlated with these clinical, laboratory, and questionnaire-based parameters. Multivariate logistic regression identified allergic diseases, PSQ score, LDH, and ferritin as independent predictors of SMPP. A nomogram incorporating these four factors demonstrated good predictive performance, with an internally validated C-index of 0.827, satisfactory calibration (Hosmer–Lemeshow p = 0.116), and clinical utility within a 0–25% threshold probability range on decision curve analysis. Conclusions: Children with MPP and comorbid AD or OSA risk are more likely to develop SMPP. Among children aged 6–12 years, RQLQ score is positively correlated with the severity of MPP. AD, PSQ score, LDH, and ferritin are independent risk factors for SMPP. Clinicians should be alert to the development of SMPP when children with MPP present with a history of AD, PSQ score >3.5, LDH >327.50 U/L, or ferritin >120.05 ng/mL. The visual nomogram model constructed by combining these risk factors demonstrates improved predictive performance for SMPP, with high predictive efficacy and accuracy. It has great clinical value and can be used for individualized risk assessment and early intervention. However, our proposed nomogram requires external validation prior to broader implementation. Full article

Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder and is increasingly recognized as a contributor to cognitive decline and a potential risk factor for neurodegeneration. Previous studies have also identified various associated comorbidities such as vascular dysfunction, metabolic alterations, and neuroinflammatory changes. Positive airway pressure (PAP) therapy has been associated with cognitive improvement in some studies, but its long-term effects on cognitive function remain uncertain. This study employs a prospective, observational, longitudinal cohort design to examine longitudinal associations between disease severity, PAP therapy and cognition. Additionally, we aim to examine the relationships between cognitive dysfunction, brain structure and associated OSA-related risk factors. A total of 100 eligible participants with mild to severe OSA will be recruited. All participants will undergo comprehensive assessments at baseline and after 12 months, including neurological, pulmonary, and ear, nose and throat clinical examinations, polysomnography, neuropsychological testing, brain magnetic resonance imaging with volumetry, anthropometric measurements, blood and saliva sampling for the assessment of the selected laboratory parameters, gut microbiome analysis, and evaluation of endothelial function and baroreflex sensitivity. This study may improve understanding of how PAP therapy and OSA-related pathophysiological processes influence cognitive outcomes. Full article

Background: Surgical palatal techniques are established alternatives to continuous positive airway pressure (CPAP) in selective patients with obstructive sleep apnea (OSA) with retropalatal airway collapse. Anterior palatoplasty (AP) stiffens and advances the soft palate, whereas radiofrequency-assisted uvulopalatoplasty (RF-UPP) uses thermal ablation to reduce palatal tissue. This study aimed to compare the 6-month efficacy and morbidity of AP vs. RF-UPP in treating mild-to-moderate OSA. Materials and Methods: We conducted a single-center retrospective cohort study (March 2023–March 2025) of 86 adults (mean age ~42 years; 69.8% male) with mild-moderate OSA (apnea–hypopnea index [AHI] 5–30) due to palatal obstruction; 43 patients underwent AP and 43 patients underwent RF-UPP. Polysomnographic AHI, Epworth sleepiness scale (ESS), snoring severity (0–10 visual analog scale, VAS) and sleep-related quality of life (functional outcomes of sleep questionnaire, FOSQ) were analyzed at baseline and 6 months postoperatively. Postoperative pain (0–10 VAS), recovery time, and bleeding events were also assessed. Results: Baseline characteristics were similar between groups (AHI ~22 vs. 21 events/h; ESS ~11 vs. 10; snoring VAS ~8.4 vs. 8.2 in AP vs. RF-UPP, all p > 0.1). At 6 months, the AP group achieved a greater mean AHI reduction than the RF-UPP group (−13.5 ± 7.5 vs. −8.0 ± 7.2, p < 0.001), with post-treatment AHI averaging 8.5 ± 6.0 vs. 13.2 ± 6.5 events/h (AP vs. RF-UPP). AP yielded a higher surgical success rate (34/43 (79.1%) vs. 23/43 (53.5%), p = 0.012), meeting the criteria of ≥50% AHI reduction to <15; p = 0.01. Subjective outcomes improved in both groups, but AP showed greater mean reductions in ESS (−5.5 vs. −3.1 points, p = 0.001) and snoring VAS (−5.7 vs. −3.1, p = 0.002). The improvements in ESS, snoring VAS, and FOSQ scores were observed in both groups, with significantly greater gains after AP. Postoperative pain and time to resumption of normal diet were higher in the AP group. No major complications occurred in either group. Conclusions: Anterior palatoplasty demonstrated superior efficacy to RF-UPP in mild-moderate OSA at the expense of increased postoperative pain and a longer recovery period. AP may offer a greater therapeutic benefit in appropriately selected patients with palatal obstruction. Full article

Background: The alternative Overlap Syndrome (aOVS), the coexistence of bronchial asthma and Obstructive Sleep Apnea (OSA), represents a distinct clinical phenotype associated with worse clinical outcomes, but little is yet known about its characteristics. We aimed to investigate differences in sleep stability and clinical burden between OSA and aOVS patients matched for age, gender, BMI and Apnea-Hypopnea Index (AHI). Methods: 45 aOVS and 45 OSA patients were compared using demographic, clinical and polysomnographic data. Results: Patients with aOVS exhibited significantly higher odds ratio product (ORP) values for total sleep time (ORPmed: 0.8 ± 0.2 vs. 0.5 ± 0.1, p < 0.001) and Non-Rapid Eye Movement (ORPnr: 0.7 ± 0.3 vs. 0.4 ± 0.1, p < 0.001) sleep compared with OSA patients. Furthermore, patients with aOVS showed a significantly higher risk of developing clinically significant anxiety and fatigue, showing a significantly higher General Anxiety Disorder-7 (GAD-7: 8.7 ± 5.6 vs. 5.7 ± 4.7, p = 0.02) and significantly higher prevalence of fatigue (71% vs. 41%, p = 0.01). These associations remained significant after multivariable adjustment and were independent of OSA severity (AHI). Conclusions: Our findings support the concept that aOVS is characterised by significantly more unstable sleep and a greater psychological burden, even after matching with OSA patients for age, gender, BMI and AHI. Our study also highlights the need to integrate traditional sleep measures with more recent ones, such as ORP, in order to better capture the multidimensional burden of aOVS. Full article

Background: Frequent nocturnal arousals are a core feature of comorbid insomnia and obstructive sleep apnea (COMISA), yet the underlying central mechanisms remain unclear. Identifying brain functional correlates of nocturnal awakenings may help clarify arousal-related mechanisms and inform potential interventional targets. Methods: A total of 99 participants (COMISA, insomnia alone, OSA alone, and healthy controls) underwent clinical assessments, polysomnography, and brain magnetic resonance imaging (MRI). MRI metrics were compared across groups, followed by correlation and regression analyses with the arousal index, adjusting for respiratory events and insomnia-related factors. Results: Patients with COMISA exhibited more severe insomnia symptoms, greater daytime dysfunction, and more frequent nocturnal awakenings than those with insomnia alone, although their arousal index did not differ from that of the OSA group. Patients with COMISA exhibited altered activity in the right cerebellar lobule VIII (Cerebelum_8_R), left middle temporal gyrus, and right inferior frontal gyrus, opercular part. Lower fractional amplitude of low-frequency fluctuations (fALFF) in the Cerebelum_8_R was associated with a higher arousal index. This association remained significant after controlling for insomnia severity and sleep efficiency but was attenuated after adjustment for AHI. Conclusions: Reduced functional activity in the Cerebelum_8_R was independently associated with sleep fragmentation in COMISA, independent of insomnia severity but potentially mediated by respiratory events. These findings suggest this region may be involved in arousal-related neural regulation and could represent a therapeutic target for the complex symptoms of COMISA. Trial Registration: Chinese Clinical Trial Registry, ChiCTR2500095809. Full article