Nature and Science of Sleep最新文献

{"title":"Impact of Circadian Rhythm and Sleep Architecture Changes on Prognosis in Patients with Acute Hemorrhagic Stroke.","authors":"Xiaodong Yuan, Yongshan Fu, Ya Ou, Jing Xue, Na Yang, Hongrui Liu, Tiantian Wang, Jing Wang, Cuiping Yan, Pingshu Zhang","doi":"10.2147/NSS.S533202","DOIUrl":"10.2147/NSS.S533202","url":null,"abstract":"<p><strong>Objective: </strong>Research is limited on whether circadian rhythm and sleep architecture alterations during acute intracerebral hemorrhage (ICH) influence patient outcomes. This study aims to characterize these changes and explore their association with clinical prognosis, offering new insights for diagnosis and treatment.</p><p><strong>Methods: </strong>We enrolled 100 acute hemorrhagic stroke patients who underwent continuous, contactless sleep monitoring via a smart mattress for 3-5 consecutive days. Prognosis was evaluated at discharge using the modified Rankin Scale (mRS), and patients were classified into favorable or unfavorable outcome groups. Circadian rhythm parameters (IS, IV, RA) and sleep metrics (eg, total sleep time, sleep latency, REM latency) during day and night were compared between groups. Multivariate logistic regression identified independent prognostic factors, and ROC analysis evaluated their predictive value.</p><p><strong>Results: </strong>Group comparisons revealed statistically significant differences in RA and nighttime sleep latency between the favorable and unfavorable prognosis groups (P < 0.05). Binary logistic regression analysis identified nighttime sleep latency as an independent predictor of functional outcome (95% CI: 1.066 ~ 1.128, P < 0.05), which remained significant after adjusting for potential confounders (95% CI: 1.016 ~ 1.148, P < 0.05). The mean nighttime sleep latency was 18.14 minutes in the favorable group and 12.30 minutes in the unfavorable group. The area under the ROC curve (AUC) for nighttime sleep latency was 0.642 (95% CI: 0.526-0.757, P = 0.028), with an optimal cutoff value of 10.95 minutes, yielding a sensitivity of 72.2% and specificity of 53.6%.</p><p><strong>Conclusion: </strong>Hemorrhagic stroke patients show disrupted circadian stability, with greater RA reductions in those with worse outcomes. Nighttime sleep latency independently predicts poor prognosis with moderate accuracy. Circadian rhythm stability may serve as a prognostic marker in hemorrhagic stroke to avoid implying causality.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1655-1668"},"PeriodicalIF":3.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12282543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144691029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to \"Exploring New Avenues for OSA Screening: Optimization and Future Perspectives of Nomogram for Hypertensive Patients\" [Response to Letter].","authors":"Weilong Ye, Jinhua Liang, Zhenzhen Zheng, Weifeng Liao, Yitian Yang, Mingdi Chen, Weimin Yao, Riken Chen","doi":"10.2147/NSS.S531471","DOIUrl":"10.2147/NSS.S531471","url":null,"abstract":"","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1669-1670"},"PeriodicalIF":3.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144682801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationships Between Self-Reported Sleep Quality, Quantity and Timing on Workdays vs Work-Free Days and Lifestyle Factors in Healthy Adults.","authors":"Diana Aslamyar, Luísa K Pilz, Charlotte von Gall","doi":"10.2147/NSS.S537593","DOIUrl":"10.2147/NSS.S537593","url":null,"abstract":"<p><strong>Purpose: </strong>Sufficient quantity and quality of sleep are crucial for physical and mental health and performance. The ideal duration and time of sleep varies from person to person, with the latter depending on chronotype. However, rather than accommodating these needs, everyday life is often structured around rigid societal times that can result in sleep deficits and poor sleep quality. This survey study in healthy adults investigated the relationships between sleep duration, quality, and timing and how they relate to chronotype, lifestyle, perceived workload and anxiety/depression symptoms.</p><p><strong>Patients and methods: </strong>Participants (N =315) were recruited from a large German metropolitan region. Sleep quality and quantity were evaluated separately on workdays and work-free days using assessments of tiredness upon waking and the Pittsburgh Sleep Quality Index (PSQI). Sleep time, duration, chronotype, sleep loss, and social jetlag were assessed using the Munich ChronoType Questionnaire (MCTQ). Lifestyle variables assessed in this study included exercise and substance use. Self-reported sleep quality, timing and duration were compared between work and work-free days. The relationships between variables were explored using correlation and correlation-based network analyses.</p><p><strong>Results: </strong>Our data suggest that workday sleep duration is a significant determinant of self-reported sleep quality, which in turn is negatively correlated with daytime dysfunction, anxiety/depression, and perception of workload. Moreover, physical activity and not smoking were significantly associated with self-reported sleep quality as well as with depression and anxiety symptoms.</p><p><strong>Conclusion: </strong>In addition to a healthy lifestyle, strategies to advance bedtime and/or adapt working hours to chronotype may improve sleep quality and thus mental health.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1641-1654"},"PeriodicalIF":3.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12276750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144675316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Fractional Exhaled Nitric Oxide (FeNO) and Cognitive Function in Patients with Obstructive Sleep Apnea.","authors":"Qilin Zhu, Lili Huang, Licheng Zhu, Xiaobai Zhang, Honghua Ji, Donghua Niu, Wangfei Ji, Qingqing Ma, Rong Chen, Haiyan Shi, Yihua Wang, Lina Xu","doi":"10.2147/NSS.S524831","DOIUrl":"10.2147/NSS.S524831","url":null,"abstract":"<p><strong>Purpose: </strong>Obstructive sleep apnea (OSA) is characterised by intermittent hypoxia and sleep fragmentation, both of which can impair cognition. This study aimed to investigate the association between fractional exhaled nitric oxide (FeNO), a non-invasive marker of airway inflammation, and memory performance in patients with OSA.</p><p><strong>Methods: </strong>A total of 102 participants were enrolled: 62 with moderate or severe OSA (apnea-hypopnea index, AHI≥15) and 40 with snoring or mild OSA (AHI <15). Memory was assessed with the Rey-Osterrieth Complex Figure Test (RCFT), Digit Ordering Test (DOT), and Logical Memory Test (LMT). FeNO was measured at 50mL/s (FeNO₅₀) and 200mL/s (FeNO₂₀₀); alveolar NO (CaNO) was calculated. Group comparisions used <i>t</i>-tests and chi-square tests, cognitive scores employed mixed-design ANOVA, and associations were examined with Spearman correlation plus hierarchical regression.</p><p><strong>Results: </strong>Compared with the snoring or mild OSA group, participants with moderate or severe OSA had larger neck circumference, higher body-mass index, greater daytime sleepiness, and elevated FeNO₅₀ and FeNO₂₀₀ (<i>P</i> < 0.05). They also showed poorer immediate and delayed visual memory (both <i>P</i>< 0.05), which correlated negatively with AHI (<i>r</i> = -0.088/-0.103, <i>P</i> < 0.05) and FeNO₅₀ (<i>r</i> = -0.286/-0.302, <i>P</i> < 0.05). RCFT scores fell over time (<i>F</i> = 271.171, <i>P</i> < 0.05), with a significant group × time interaction (<i>F</i> = 3.065, <i>P</i> < 0.05). FeNO₅₀ independently predicted poorer immediate recall (<i>β</i> = -0.28, <i>P</i> = 0.018), whereas FeNO₂₀₀ was not significant.</p><p><strong>Conclusion: </strong>Moderate or severe OSA is associated with impaired immediate and delayed visual memory. Higher FeNO₅₀ correlates with memory decline, supporting a link between airway inflammation and cognitive dysfunction in OSA.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1603-1614"},"PeriodicalIF":3.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Model to Bedside: What Kind of OSA Risk Prediction Tools Do We Need More of? [Letter].","authors":"Hongyu Pan, Yuchang Fei","doi":"10.2147/NSS.S549821","DOIUrl":"10.2147/NSS.S549821","url":null,"abstract":"","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1601-1602"},"PeriodicalIF":3.4,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating ADHD Symptoms and Sleep Disturbances in Young Adults: A Cross-Sectional Study.","authors":"Arda Kazim Demirkan, Umit Basar Semiz","doi":"10.2147/NSS.S537569","DOIUrl":"10.2147/NSS.S537569","url":null,"abstract":"<p><strong>Purpose: </strong>Attention-deficit/hyperactivity disorder (ADHD), a prevalent condition affecting 2.5-5% of adults, impacting daily functioning. Sleep quality is essential for cognitive and socio-emotional well-being, and the association between ADHD symptoms and sleep disturbances necessitates identifying populations at risk. This study aimed to assess the associations between ADHD symptoms and sleep disorders by conducting a thorough assessment of sleep measures in a cross-sectional group of university students.</p><p><strong>Patients and methods: </strong>Recruiting participants from a Turkish university (n=503; mean age=21.3 ± 1.8 years), subgroups were formed based on ADHD scores from the Adult ADHD Self-report Scale. Sleep was assessed using the Van Dream Anxiety Scale, Pittsburgh Sleep Quality Index (PSQI), and Epworth Sleepiness Scale (ESS). Beck Depression Inventory (BDI) was employed to evaluate depressive symptoms.</p><p><strong>Results: </strong>ADHD symptoms group exhibited higher dream-related anxiety, PSQI, ESS, and BDI scores. Nightmares were more prevalent in the ADHD symptoms group. Subjective sleep measures showed differences in various domains, emphasizing poorer sleep quality in the ADHD symptoms group. Correlation analyses revealed intricate relationships between socio-economic factors, psychiatric health, family history, ADHD symptoms, nightmares, and sleep aspects.</p><p><strong>Conclusion: </strong>University students with ADHD symptoms face increased susceptibility to insufficient sleep, impacting daytime functioning and academic performance. Findings underscore the need for increased attention to sleep health in this population.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1615-1627"},"PeriodicalIF":3.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266080/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction and Validation of a Machine Learning-Based Risk Prediction Model for Sleep Quality in Patients with OSA [Letter].","authors":"Hejia Wan, Yifan Li, Fei Xu","doi":"10.2147/NSS.S547799","DOIUrl":"10.2147/NSS.S547799","url":null,"abstract":"","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1639-1640"},"PeriodicalIF":3.4,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of Automated Respiratory Event Scoring in Type 3 Home Sleep Apnea Testing.","authors":"Nanako Shiroshita, Ryoko Obata, Fusae Kawana, Mitsue Kato, Akihiro Sato, Sayaki Ishiwata, Shoichiro Yatsu, Hiroki Matsumoto, Jun Shitara, Azusa Murata, Megumi Shimizu, Takao Kato, Shoko Suda, Yasuhiro Tomita, Masaru Hiki, Ryo Naito, Takatoshi Kasai","doi":"10.2147/NSS.S541933","DOIUrl":"10.2147/NSS.S541933","url":null,"abstract":"<p><strong>Purpose: </strong>Home sleep apnea tests (HSATs) using polygraphy devices are becoming increasingly important for evaluating obstructive sleep apnea. Alice NightOne, a widely used polygraphy device, includes automatic scoring software; however, more reliable scoring results can be provided by incorporating advanced algorithmic systems like Somnolyzer. Despite this, the accuracy of automatic scoring of this polygraphy device using such applications has not been specifically investigated. Thus, in this study, we aimed to compare the respiratory event indices (REIs) obtained via automatic scoring versus manual scoring.</p><p><strong>Patients and methods: </strong>Data of eligible patients who underwent HSAT with this polygraphy device were retrospectively analyzed using the following three methods: 1) manual scoring; 2) default automatic scoring of the analysis software; and 3) automatic scoring with the Somnolyzer system. The REIs were calculated using these three methods and expressed as mREI, aREI, and sREI, respectively. Correlations and agreements between the aREI, sREI, and mREI were assessed.</p><p><strong>Results: </strong>Data from 20 patients were analyzed. The mean mREI, aREI, and sREI were 14.7±13.3, 13.7±11.8, and 14.3±13.4 events/h, respectively. A strong correlation was found between aREI and mREI (coefficient, 0.976; P<0.01), with a mean difference between them of 1.0 and a limit of agreement of -5.3 to 7.3. The correlation between sREI and mREI was more prominent (coefficient, 0.996; P<0.001); their mean difference was 0.1, with a limit of agreement of -2.1 to 2.9.</p><p><strong>Conclusion: </strong>Automatic scoring of REI using this polygraphy device showed good correlation and agreement with manual scoring. The favorable correlation and agreement were more pronounced with the Somnolyzer system.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1629-1637"},"PeriodicalIF":3.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12264349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations Between Obstructive Sleep Apnea and Metabolic Dysfunction-Associated Fatty Liver Disease: Insights from Comprehensive Mendelian Randomization and Gene Expression Analysis.","authors":"Tianyu Ma, Chunyan Liao, Wenhui Chen, Jia Feng","doi":"10.2147/NSS.S511115","DOIUrl":"10.2147/NSS.S511115","url":null,"abstract":"<p><strong>Background: </strong>Obstructive sleep apnea (OSA) is linked to metabolic dysfunction-associated fatty liver disease (MAFLD), yet their exact causality and underlying mechanisms remain inconclusive. We aimed to investigate their causal associations and shared biomarkers using Mendelian randomization (MR) and bioinformatics approaches.</p><p><strong>Methods: </strong>We used OSA-related and MAFLD-related GWAS data to explore their causal relationship and the role of body mass index (BMI) through two-sample and network MR analysis. Gene expression profiles were analyzed to identify intersection genes through differential expression analysis and weighted gene co-expression network analysis (WGCNA). Functional enrichment (GO and KEGG), protein-protein interaction (PPI) networks, and immune cell infiltration analyses (ssGSEA) were performed on the intersecting genes. We then conducted MR analysis to assess the relationship between immune cells and both diseases. Inverse variance weighting (IVW) served as the primary MR method, supplemented by MR-Egger regression, weighted median, and weighted mode.</p><p><strong>Results: </strong>MR analysis revealed that OSA increased the risk of MAFLD [odds ratio (OR)=1.40, 95% CI 1.14-1.73, p= 0.002], with OSA potentially mediating the effect of BMI on MAFLD, accounting for 62.3% of the mediation. Bioinformatics identified 42 intersection genes. Four hub genes (FOS, EGR1, NR4A1, JUN) were ultimately obtained by PPI network, which were strongly linked to immune cell infiltration. Additionally, three immune cell phenotypes (CD4RA on TD CD4+, HLA DR on CD14+ CD16-monocytes, and HLA DR on CD14+ monocytes) were found to be associated with both OSA and MAFLD.</p><p><strong>Conclusion: </strong>OSA may causally influence MAFLD and mediate the effect of BMI on MAFLD. Four key genes and three immune cell phenotypes play crucial roles in the shared pathogenesis of both diseases.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1571-1585"},"PeriodicalIF":3.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12255352/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144626745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Locally Run Large Language Models for Obstructive Sleep Apnea Diagnosis and Treatment: A Real-World Polysomnography Study.","authors":"Christopher Seifen, Tilman Huppertz, Katharina Bahr-Hamm, Haralampos Gouveris, Johannes Pordzik, Jonas Eckrich, Christoph Matthias, Harry Smith, Tom Kelsey, Andrew Blaikie, Sebastian Kuhn, Christoph Raphael Buhr","doi":"10.2147/NSS.S536823","DOIUrl":"10.2147/NSS.S536823","url":null,"abstract":"<p><strong>Purpose: </strong>Sleep medicine is a highly resource-intensive field where large language models (LLMs) could offer a promising solution by supporting diagnostic processes. As web-based LLMs have obvious data protection constraints, locally run LLMs are essential for clinical implementation. This study is the first to investigate the performance of locally run LLMs in the interpretation of real-world polysomnographic (PSG) results.</p><p><strong>Methods: </strong>We randomly selected N=30 patients (18 male, 12 female, mean age 50.5 ± 11.1 years, mean body mass index 29.7 ± 5.5 kg/m², mean apnea hypopnea index 30.9 ± 23.8) from the clinical database of our sleep laboratory who underwent PSG due to clinical complaints typical of obstructive sleep apnea (OSA). The board-certified sleep physician's interpretations of diagnosis, suitable first-line therapy or alternative therapy were compared with those of three locally run LLMs (Gemma2, Llama3 and Mistral Nemo) assessing the level of concordance.</p><p><strong>Results: </strong>Gemma2 showed the lowest concordance of 33% (10/30 patients) with the board-certified sleep physician regarding OSA severity, followed by Mistral Nemo at 47% (14/30 patients) and Llama3 at 50% (15/30 patients). For automatic positive airway pressure (aPAP) recommendations, Mistral Nemo showed the highest concordance at 90% (27/30 patients), followed by Gemma2 and Llama3 with 83% (25/30 patients) each.</p><p><strong>Conclusion: </strong>Although locally run LLMs bypass data security constraints and show promising potential for clinical practice, their performance needs significant improvement prior to real-world implementation. Therefore, at present, the routine implementation of locally run LLMs in sleep medicine needs more refinement and fine tuning before they can be used for interpretation of real-world PSG results.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1587-1599"},"PeriodicalIF":3.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12257169/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}