Nature and Science of Sleep最新文献

Purpose: Obstructive sleep apnoea (OSA) is a common disease that benefits from early treatment and patient support in order to prevent secondary illnesses. This study assesses the capability of the large language model (LLM) ChatGPT-4o to offer patient support regarding first line positive airway pressure (PAP) and second line hypoglossal nerve stimulation (HGNS) therapy.

Methods: Seventeen questions, each regarding PAP and HGNS therapy, were posed to ChatGPT-4o. Answers were rated by experienced experts in sleep medicine on a 6-point Likert scale in the categories of medical adequacy, conciseness, coherence, and comprehensibility. Completeness of medical information and potential hazard for patients were rated using a binary system.

Results: Overall, ChatGPT-4o achieved reasonably high ratings in all categories. In medical adequacy, it performed significantly better on PAP questions (mean 4.9) compared to those on HGNS (mean 4.6) (p < 0.05). Scores for coherence, comprehensibility and conciseness showed similar results for both HGNS and PAP answers. Raters confirmed completeness of responses in 45 of 51 ratings (88.24%) for PAP answers and 28 of 51 ratings (54.9%) for HGNS answers. Potential hazards for patients were stated in 2 of 52 ratings (0.04%) for PAP answers and none for HGNS answers.

Conclusion: ChatGPT-4o has potential as a valuable patient-oriented support tool in sleep medicine therapy that can enhance subsequent face-to-face consultations with a sleep specialist. However, some substantial flaws regarding second line HGNS therapy are most likely due to recent advances in HGNS therapy and the consequent limited information available in LLM training data.

Purpose: This study aims to develop a deep learning methodology for quantitative assessing adenoid hypertrophy in nasopharyngoscopy images and to investigate its correlation with the apnea-hypopnea index (AHI) in pediatric patients with obstructive sleep apnea (OSA).

Patients and methods: A total of 1642 nasopharyngoscopy images were collected from pediatric patients aged 3 to 12 years. After excluding images with obscured secretions, incomplete adenoid exposure, 1500 images were retained for analysis. The adenoid-to-nasopharyngeal (A/N) ratio was manually annotated by two experienced otolaryngologists using MATLAB's imfreehand tool. Inter-annotator agreement was assessed using the Mann-Whitney U-test. Deep learning segmentation models were developed with the MMSegmentation framework, incorporating transfer learning and ensemble learning techniques. Model performance was evaluated using precision, recall, mean intersection over union (MIoU), overall accuracy, Cohen's Kappa, confusion matrices, and receiver operating characteristic (ROC) curves. The correlation between the A/N ratio and AHI, derived from polysomnography, was analyzed to evaluate clinical relevance.

Results: Manual evaluation of adenoid hypertrophy by otolaryngologists (p=0.8507) and MATLAB calibration (p=0.679) demonstrated high consistency, with no significant differences. Among the deep learning models, the ensemble learning-based SUMNet outperformed others, achieving the highest precision (0.9616), MIoU (0.8046), overall accuracy (0.9182), and Kappa (0.87). SUMNet also exhibited superior consistency in classifying adenoid sizes. ROC analysis revealed that SUMNet (AUC=0.85) outperformed expert evaluations (AUC=0.74). A strong positive correlation was observed between the A/N ratio and AHI, with the correlation coefficients for SUMNet-derived ratios ranging from r=0.9052 (tonsils size+1) to r=0.4452 (tonsils size+3) and for expert-derived ratios ranging from r=0.4590 (tonsils size+1) to r=0.2681 (tonsils size+3).

Conclusion: This study introduces a precise and reliable deep learning-based method for quantifying adenoid hypertrophy and addresses the challenge posed limited sample sizes in deep learning applications. The significant correlation between adenoid hypertrophy and AHI underscores the clinical utility of this method in pediatric OSA diagnosis.

Purpose: Benzodiazepine receptor agonists (BZRAs), including benzodiazepines (BZDs) and Z drugs, are widely prescribed for anxiety and sleep. Therefore, issues of tolerance, dependence and adverse effects are of concern. Recent studies suggested a potential link between BZRAs and hearing problems. However, the actual relationship was still unclear. Accordingly, this study aims to investigate the actual association between BZRA use and risk of sudden sensorineural hearing loss (SSNHL) using population data.

Patients and methods: This study used the Taiwan Longitudinal Health Insurance Database. 137,277 BZRA users and 1,328,554 nonusers were identified for relevant analyses. We used cohort design with inverse-probability treatment weighting (IPTW) strategy to balance the baseline differences of demographics and comorbidities between two groups. The 5-year incidence of SSNHL was followed. Cox proportional-hazard regression analyses were used to estimate the hazard ratios (HRs).

Results: BZRA users showed an increased 5-year SSNHL risk (adjusted HR: 1.244) after weighting. Subgroup and sensitivity analyses produced consistent results. Notably, SSNHL risk was higher among young BZRA users (adjusted HR: 1.397). BZRA users had the highest SSNHL risk in the first year (adjusted HR: 2.037) after IPTW.

Conclusion: BZRA use elevated the risk of SSNHL, particularly in young adults and in the first year. This emphasises the importance for physicians and policymakers should be aware of the potential hearing difficulties among BZRA users and take necessary examinations.

Background: Multimorbidity, defined as the coexistence of two or more chronic diseases, is highly prevalent among the elderly population and is associated with adverse outcomes. However, little is known about its relationship with sleep issues, particularly in this demographic. Therefore, this study aimed to investigate its association with sleep quality and duration among the elderly.

Methods: This cross-sectional study was conducted in Emin County, Xinjiang, China, which included a population aged 60 years and above. We employed the Pittsburgh Sleep Quality Index (PSQI) score to assess sleep quality and duration. Multimorbidity was determined through self-reports, physical examination, blood tests, and imaging. Logistic regression analyses were used to explore the association between multimorbidity and sleep patterns, adjusting for confounders.

Results: A total of 8205 elderly participants were included, of whom 66.8% suffered from multimorbidity. Participants with multimorbidity exhibited higher total PSQI scores [6 (3,9)], and a higher percentage of poor sleep quality (50.6%), compared to those without multimorbidity. Multimorbidity was significantly associated with the presence of poor sleep quality (OR = 1.27, 95% CI: 1.14-1.41, P < 0.001) before and after adjusting for confounders. The risk of having poor sleep quality significantly increased as the number of multimorbidities increased. The OR (95% CI) values were 1.16 (1.02,1.32) for two diseases, 1.54 (1.26,1.90) for ≥5 diseases. In the adjusted model for total participants, having four diseases (OR = 1.26, 95% CI: 1.05-1.51, p = 0.013) and five or more diseases (OR = 1.29, 95% CI: 1.03-1.61, p = 0.029) were associated with shorter sleep duration. Furthermore, those with five or more diseases associated with longer sleep duration (OR = 1.40, 95% CI: 1.00-1.95, p = 0.057).

Conclusion: There is a significant association between multimorbidity and poor sleep quality in older community dwellers, which may provide clues for disease prevention.

Objective: Sleep disorders are common in Alzheimer's disease (AD) patients and can impair the glymphatic system, leading to cognitive decline. This study aimed to investigate whether AD patients with sleep disorders exhibit worse glymphatic function and more severe cognitive impairment compared to those without sleep disorders and to explore the underlying molecular imaging mechanisms.

Methods: This study included 40 AD patients with sleep disorders (ADSD), 39 cognitively matched AD patients without sleep disorders (ADNSD), and 25 healthy middle-aged and elderly controls (NC). Participants underwent functional magnetic resonance imaging (fMRI), and cognitive and sleep assessments. The ALPS (Along the Perivascular Space) index was calculated, followed by intergroup comparisons, correlation analyses, and mediation analyses. The diagnostic utility of the ALPS index was assessed using a receiver operating characteristic (ROC) curve.

Results: The ALPS index was lower in the ADNSD and ADSD groups compared to the NC group. In the ADSD group, PSQI scores were negatively correlated with MMSE scores. The ALPS index was positively correlated with MMSE scores and negatively with PSQI scores. Mediation analyses indicated that the ALPS index partially mediated the effect of sleep disturbances on cognitive impairment (indirect effect = -0.134; mediation effect = 30.505%). The area under the ROC curve (AUROC) for distinguishing ADSD from ADNSD was 0.86, with a cutoff ALPS index value 1.309.

Conclusion: Sleep disorders worsen glymphatic function and cognitive impairment in AD patients. The ALPS index partially mediates the impact of sleep disorders on cognitive function and shows moderate accuracy in distinguishing between patients with ADSD and ADNSD.

Purpose: It is presumed by many that acute sleep loss results in degraded in-game esports (competitive, organized video game play) performance. However, this has not been experimentally investigated to date. The objective of the current experiment was to elucidate whether ~29hrs of total sleep deprivation impacts in-game performance for the popular esport Rocket League.

Patients and methods: Twenty skill-matched pairs (N = 40 total) were recruited. Within each pair, one participant was assigned to an intervention group (TSD), while the other was assigned to a control group (CON). Two test sessions occurred; one while both participants were rested (baseline), and the other while the CON participant was rested but the TSD participant was sleep deprived (experimental).

Results: Following total sleep deprivation, TSD participants reported higher Karolinska Sleepiness Scale-measured subjective sleepiness and lower subjective alertness and motivation, as well as worsened PVT response speed and ~5 times greater PVT lapse incidence, and worsened response speed on a two-choice categorization task. However, overall in-game Rocket League performance did not worsen due to total sleep deprivation. Exploratory analyses of performance indicators suggest a potential shift toward a simpler and safer strategy following sleep deprivation.

Conclusion: Following a bout of ~29hrs total sleep deprivation, overall in-game Rocket League performance remained unaffected. This presents as a promising finding given the high potential for acute pre-competition sleep disturbance in esports, though habitual sleep remains a concern for esport athletes.

Purpose: Numerous studies have identified a correlation between sleep and delirium; however, the causal relationship remains ambiguous. This bidirectional two-sample Mendelian randomization (MR) study was conducted to examine the possible causal relationships between sleep traits and delirium.

Patients and methods: Utilizing genome-wide association studies (GWAS), we identified ten sleep traits: chronotype, sleep duration, short sleep duration, long sleep duration, daytime napping, daytime sleepiness, insomnia, number of sleep episodes (NSE), sleep efficiency, and rapid eye movement sleep behavior disorder (RBD). In this MR study, genetic variants independently associated with exposures were selected as instrumental variables (IVs). To establish causal inferences, three regression models were employed-inverse variance weighted (IVW), MR Egger, and weighted median (WM) -and conducted sensitivity analyses to assess the robustness of our findings.

Results: Our results suggest no significant causal association between the ten sleep traits and the risk of delirium. The reverse MR analysis revealed that delirium is associated with an increased propensity for morning chronotype [OR_IVW, 1.025; 95% CI, 1.012-1.036; p = 1.50E-05; adjusted p values (p_adjusted)= 1.35E-04] and a decreased risk of long sleep duration [OR_IVW, 0.996; 95% CI, 0.993-0.999; p = 0.013; p_adjusted= 0.059]. However, no robust evidence currently exists to substantiate a causal relationship between delirium and other sleep traits.

Conclusion: Our bidirectional, two-sample MR analysis study did not provide definitive evidence that sleep traits may augment the susceptibility to delirium. However, the reverse MR results indicate that delirium may predispose patients to an earlier sleep-wake cycle. Additional large-scale investigations are necessary to examine the bidirectional causality between delirium and sleep traits.

Purpose: Aimed to analyze the developmental characteristics of craniofacial structures and soft tissues in children with obstructive sleep apnea (OSA) and to establish and evaluate prediction model.

Methods: It's a retrospective study comprising 747 children aged 2-12 years (337 patients and 410 controls) visited the Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Xi'an Jiaotong University (July 2017 to March 2024). Lateral head radiographs were obtained to compare the cephalometric measurements. The clinical prediction model was constructed using LASSO regression analysis. We analyzed 300 children from the Xi'an Children's Hospital for external validation.

Results: Children with OSA had a higher body mass, a higher tonsil grade, larger AN ratio (ratio of the adenoids to the skeletal upper airway width), larger radius of the tonsils, a smaller angle between the skull base and maxilla (SNA) and smaller angle between the skull base and mandible (SNB), a larger distance from the hyoid to the mandibular plane (H-MP) and smaller distance between the third cervical vertebra and hyoid (H-C), a larger thickness of the soft palate (SPT) and smaller inclination angle of the soft palate than those of the controls (all p < 0.05). A prediction model was constructed for 2-12 years group (AUC of 0.812 [95% CI: 0.781-0.842]). Age-specific prediction models were developed for preschool children (AUC of 0.769 [95% CI: 0.725-0.814]), for school-aged children (AUC of 0.854 [95% CI: 0.812-0.895]).

Conclusion: Our study findings support the important role of craniofacial structures such as the hyoid, maxilla, mandible, and soft palate in pediatric OSA. Age-stratified predictive models for pediatric OSA indicated varying parameters across different age groups which underscore the necessity for stratifying by age in future research. The prediction model designed will greatly assist health care practitioners with rapidly identifying.

Purpose: Obstructive sleep apnea (OSA) is a contributing factor to nonalcoholic fatty liver disease (NAFLD). This study aimed to investigate the clinical and polysomnographic characteristics of OSA patients with and without NAFLD, focusing on the relationships between sleep fragmentation, arousal and NAFLD.

Materials and methods: We consecutively enrolled patients who underwent polysomnography, anthropometry, blood sampling, and abdominal ultrasonography. Patients were categorized into NAFLD and non-NAFLD groups. A comparative analysis of clinical and polysomnographic profiles was conducted, followed by multivariate binary logistic regression to explore the relationship between sleep disturbance indices and NAFLD.

Results: A total of 403 subjects were included, including 92 patients with NAFLD and 311 with non-NAFLD. NAFLD patients exhibited a greater apnea-hypopnea index (AHI) (51.19/h vs 33.60/h, p = 0.002) and oxygen desaturation index (ODI) (37.90/h vs 21.40/h, p=0.034) compared to non-NAFLD patients. Specifically, NAFLD patients had a higher rapid eye movement (REM)-AHI (53.70/h vs 43.60/h, p=0.001) and greater arousal index (AI) (32 vs 25, p = 0.009). Additionally, sleep latency (SL) was significantly lower in the NAFLD group (p < 0.05). Multivariate logistic regression analysis confirmed that REM-AHI (OR=1.023, p = 0.024), AI (OR=1.140, p = 0.01), and SL (OR=0.956, p = 0.035) were significantly associated with NAFLD in OSA patients.

Conclusion: This study revealed that sleep disturbance indices, especially AI, REM-AHI and SL, were closely related to NAFLD. When evaluating whether OSA patients are complicated with NAFLD, more attention should be given to sleep fragmentation and arousal.

Purpose: Intermittent hypoxia (IH), a defining feature of obstructive sleep apnea (OSA), is associated with heart damage and linked to transient receptor potential canonical channel 5 (TRPC5). Nonetheless, the function of TRPC5 in OSA-induced cardiac injury remains uncertain. For this research, we aimed to explore the role and potential mechanism of TRPC5 in cardiomyocyte injury induced by intermittent hypoxia.

Methods: 30 patients with newly diagnosed OSA and 30 patients with primary snoring(PS) were included in this study. Participants were subjected to polysomnography (PSG) for OSA diagnosis. Echocardiography was used to evaluate the structure and function of the heart, while peripheral blood samples were obtained. Additionally, RT-qPCR was utilized to quantify the relative expression level of TRPC5 mRNA in peripheral blood. H9c2 cells experienced IH or normoxia. TRPC5 levels in H9c2 cells were determined via RT-qPCR and Western blotting (WB) methods. H9c2 cells overexpressing TRPC5 were subjected to either normoxic or intermittent hypoxia conditions. Cell viability was determined by CCK8, the apoptosis rate, reactive oxygen species(ROS) levels, and Ca²⁺ concentration were assessed by flow cytometry, and the protein levels of TRPC5, Bcl-2, Bax, and Caspase-3 were analyzed by WB. Mitochondrial membrane potential(MMP), mitochondrial membrane permeability transition pore(mPTP), and transmission electron microscopy(TEM) were employed to observe mitochondrial function and structure. After inhibiting ROS with N-acetylcysteine (NAC), apoptosis, mitochondrial function and structure, and the concentration of Ca²⁺ were further detected.

Results: TRPC5 and left atrial diameter (LAD) were higher in OSA individuals, while the E/A ratio was lower(all P<0.05). IH impaired cell viability, triggered cell apoptosis, and enhanced TRPC5 expression in H9c2 cells(all P<0.05). The effects of IH on apoptosis, cell viability, mitochondrial function and structure damage, and oxidative stress (OxS) in H9c2 cells were accelerated by the overexpression of TRPC5(all P<0.05). Furthermore, cell apoptosis and mitochondrial structural and functional damage caused by overexpression of TRPC5 were attenuated by ROS inhibition.

Conclusion: TRPC5 is associated with structural and functional cardiac damage in patients with OSA, and TRPC5 promotes IH-induced apoptosis and mitochondrial damage in cardiomyocytes through OxS. TRPC5 may be a novel target for the diagnosis and treatment of OSA-induced myocardial injury.