Objective:To investigate the incidence of collateral circulation in high-risk patients with sleep apnea and stroke treated by continuous positive airway pressure （CPAP） ventilation and to analyze the influencing factors. Methods:A total of 152 patients diagnosed with obstructive sleep apnea-hypopnea syndrome （OSAHS） combined with acute ischemic stroke （AIS） who were admitted to our hospital from January 2020 to June 2022 were selected for this study. Based on the apnea-hypopnea index （AHI）, the patients were divided into three groups: mild （n=44）, moderate （n=72）, and severe （n=36）. After treatment, the patients were further classified into a group without collateral circulation （n=30） and a group with collateral circulation （n=26）, which included those with moderate collateral circulation （n=69） and good collateral circulation （n=27）. Clinical data across the different groups were compared, and multiple factor analysis was performed to identify factors affecting the occurrence of collateral circulation. Results:The AHI and IL-6 levels in the severe group were significantly higher than those in the mild and moderate groups, while the levels of NO and PO2 were significantly lower in the severe group compared to the mild and moderate groups, with statistically significant differences among the three groups （P<0.05）. After treatment, all groups showed improvement, and the proportion of patients with collateral circulation was 84.09% in the mild group, 81.94% in the moderate group, and 72.22% in the severe group. Significant differences in age, AHI, NIHSS, NO, MoCA, and MMSE scores were observed between the groups with and without collateral circulation （P<0.05）. In the group with collateral circulation, the scores for age, AHI, and NIHSS in the good collateral circulation subgroup were significantly lower than those in the poor collateral circulation and moderate collateral circulation subgroups, while the scores for NO, MoCA, and MMSE were significantly higher in the good collateral circulation subgroup. Multi-factor analysis revealed that age, AHI, and NIHSS were independent risk factors for collateral circulation, whereas NO, MoCA, and MMSE served as protective factors that were negatively correlated with collateral circulation. Classification tree model results indicated that AHI had the greatest influence on the occurrence of collateral circulation among the five influencing factors, demonstrating good predictive capability. Conclusion:Most high-risk patients with sleep apnea and stroke are likely to develop collateral circulation following continuous positive airway pressure ventilation. Factors such as age, AHI, NIHSS, NO, MoCA, and MMSE are important determinants affecting the occurrence of collateral circulation.
Humans ; Collateral Circulation ; Continuous Positive Airway Pressure ; Stroke/physiopathology* ; Sleep Apnea, Obstructive/physiopathology* ; Risk Factors ; Male ; Incidence ; Female ; Middle Aged ; Aged ; Sleep Apnea Syndromes/physiopathology* ; Interleukin-6/blood*

Objective:To explore the interaction between pediatric sleep-disordered breathing（SDB）, the intestinal microbiota, and pediatric non-alcoholic fatty liver disease（NAFLD）. Methods:A total of 63 non-obese children（47 children with SDB in the experimental group and 16 without SDB in the control group） were enrolled in this study. The liver function and degree of SDB were assessed in both groups. High-throughput 16S rRNA sequencing was conducted to detect the composition and functional variations of the intestinal microbiota in the two groups of children. Results:Compared with children in the experimental group, serum ALT and AST levels were higher in the control group. and the relative proteobacteria abundance of intestinal flora increased, and the relative abundance of Bacteroidetes decreased significantly. Function including membrane transport, carbohydrate metabolism and lipid metabolism, were enriched in the intestinal microbiota of children with SDB. Conclusion:The composition and functional annotation of the pediatric liver functional status and gut microbiota were significantly different between the two groups of children with and without SDB. Changes in SDB-associated intestinal bacterial abundance may be related to the pathogenesis of pediatric NAFLD.
Humans ; Non-alcoholic Fatty Liver Disease/microbiology* ; Gastrointestinal Microbiome ; Child ; Male ; Sleep Apnea Syndromes/microbiology* ; Female ; RNA, Ribosomal, 16S/genetics* ; Bacteroidetes ; Proteobacteria/isolation & purification* ; Lipid Metabolism

Humans ; Child ; Sleep Apnea Syndromes/complications* ; Medulla Oblongata/pathology* ; Neoplasms/complications*

Sleep-related breathing disorder (SRBD) is a sleep disease with high incidence and many complications. However, patients are often unaware of their sickness. Therefore, SRBD harms health seriously. At present, home SRBD monitoring equipment is a popular research topic to help people get aware of their health conditions. This article fully compares recent state-of-art research results about home SRBD monitors to clarify the advantages and limitations of various sensing techniques. Furthermore, the direction of future research and commercialization is pointed out. According to the system design, novel home SRBD monitors can be divided into two types: wearable and unconstrained. The two types of monitors have their own advantages and disadvantages. The wearable devices are simple and portable, but they are not comfortable and durable enough. Meanwhile, the unconstrained devices are more unobtrusive and comfortable, but the supporting algorithms are complex to develop. At present, researches are mainly focused on system design and performance evaluation, while high performance algorithm and large-scale clinical trial need further research. This article can help researchers understand state-of-art research progresses on SRBD monitoring quickly and comprehensively and inspire their research and innovation ideas. Additionally, this article also summarizes the existing commercial sleep respiratory monitors, so as to promote the commercialization of novel home SRBD monitors that are still under research.
Humans ; Polysomnography ; Sleep ; Sleep Apnea Syndromes/diagnosis* ; Sleep Wake Disorders

The impact of respiratory function on children's craniofacial growth has received increasing attention from orthodontists and parents. There is a higher pediatric sleep-disordered breathing risk prevalence in the orthodontic population compared with a general population sample, and orthodontic practitioners need to pay close attention to the respiratory function of their pediatric patients. For children with upper airway obstruction and related dentofacial and functional abnormalities, clinicians should comprehensively consider the site and severity of upper airway obstruction, the clinical feature of malocclusion and other factors to develop an individual, multidisciplinary treatment plan, providing favorable conditions for the development of the children's craniofacial morphology and the whole body.
Airway Obstruction/therapy* ; Child ; Humans ; Malocclusion/therapy* ; Prevalence ; Sleep Apnea Syndromes/therapy*

OBJECTIVE: To study the clinical features of sleep-disordered breathing (SDB) in children with neuromuscular disease (NMD). METHODS: A retrospective analysis was performed on the medical data of 18 children who were diagnosed with NMD and underwent polysomnography (PSG) (NMD group). Eleven children without NMD who had abnormal sleeping habit and normal sleep structure on PSG were enrolled as the control group. The two groups were compared in terms of the daily and nocturnal symptoms of SDB, incidence rate of obstructive sleep apnea (OSA), pulmonary function, end-tidal partial pressure of carbon dioxide (PetCO RESULTS: In the NMD group, 16 children (89%) had related daily and nocturnal symptoms of SDB, and the youngest age was 1 year at the onset of such symptoms. Compared with the control group, the NMD group had significant reductions in total sleep time and sleep efficiency ( CONCLUSIONS There is a high proportion of children with SDB among the children with NMD, and SDB can be observed in the early stage of NMD, which results in the damage of sleep structure and the reduction in sleep efficiency. Respiratory events are mainly obstructive events, and oxygen reduction events are mainly observed during REM sleep.
Child ; Humans ; Neuromuscular Diseases/complications* ; Polysomnography ; Retrospective Studies ; Sleep ; Sleep Apnea Syndromes/etiology*

Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution layers, four pooling layers, two full connection layers and one classification layer. The automatic feature extraction and classification were realized by the structure of the proposed CNN model. The model was verified by the whole night single-channel sleep electrocardiogram (ECG) signals of 70 subjects from the Apnea-ECG dataset. Our results showed that the accuracy of per-segment SA detection was ranged from 80.1% to 88.0%, using the input signals of single-channel ECG signal, RR interval (RRI) sequence, R peak sequence and RRI sequence + R peak sequence respectively. These results indicated that the proposed CNN model was effective and can automatically extract and classify features from the original single-channel ECG signal or its derived signal RRI and R peak sequence. When the input signals were RRI sequence + R peak sequence, the CNN model achieved the best performance. The accuracy, sensitivity and specificity of per-segment SA detection were 88.0%, 85.1% and 89.9%, respectively. And the accuracy of per-recording SA diagnosis was 100%. These findings indicated that the proposed method can effectively improve the accuracy and robustness of SA detection and outperform the methods reported in recent years. The proposed CNN model can be applied to portable screening diagnosis equipment for SA with remote server.
Electrocardiography ; Humans ; Machine Learning ; Neural Networks, Computer ; Sensitivity and Specificity ; Sleep Apnea Syndromes/diagnosis*

As a low-load physiological monitoring technology, wearable devices can provide new methods for monitoring, evaluating and managing chronic diseases, which is a direction for the future development of monitoring technology. However, as a new type of monitoring technology, its clinical application mode and value are still unclear and need to be further explored. In this study, a central monitoring system based on wearable devices was built in the general ward (non-ICU ward) of PLA General Hospital, the value points of clinical application of wearable physiological monitoring technology were analyzed, and the system was combined with the treatment process and applied to clinical monitoring. The system is able to effectively collect data such as electrocardiogram, respiration, blood oxygen, pulse rate, and body position/movement to achieve real-time monitoring, prediction and early warning, and condition assessment. And since its operation from March 2018, 1 268 people (657 patients) have undergone wearable continuous physiological monitoring until January 2020, with data from a total of 1 198 people (632 cases) screened for signals through signal quality algorithms and manual interpretation were available for analysis, accounting for 94.48 % (96.19%) of the total. Through continuous physiological data analysis and manual correction, sleep apnea event, nocturnal hypoxemia, tachycardia, and ventricular premature beats were detected in 232 (36.65%), 58 (9.16%), 30 (4.74%), and 42 (6.64%) of the total patients, while the number of these abnormal events recorded in the archives was 4 (0.63%), 0 (0.00%), 24 (3.80%), and 15 (2.37%) cases. The statistical analysis of sleep apnea event outcomes revealed that patients with chronic diseases were more likely to have sleep apnea events than healthy individuals, and the incidence was higher in men (62.93%) than in women (37.07%). The results indicate that wearable physiological monitoring technology can provide a new monitoring mode for inpatients, capturing more abnormal events and provide richer information for clinical diagnosis and treatment through continuous physiological parameter analysis, and can be effectively integrated into existing medical processes. We will continue to explore the applicability of this new monitoring mode in different clinical scenarios to further enrich the clinical application of wearable technology and provide richer tools and methods for the monitoring, evaluation and management of chronic diseases.
Heart Rate ; Humans ; Monitoring, Physiologic ; Movement ; Sleep Apnea Syndromes ; Wearable Electronic Devices

Humans ; Polysomnography ; Sleep Apnea Syndromes/therapy*

In order to study the effects of sleep-disordered breathing on human physiology and function, and to accurately and objectively evaluate the level of human sleep quality at night, it can help patients with respiratory disorders improve sleep quality. This paper elaborates the development process of a new multi-parameter sleep quality evaluation system from the hardware circuit design, software and algorithm analysis design of the system. The system hardware platform collects the physiological signals of the 11-channel nighttime sleep period, and displays and stores them in real time on the monitoring platform. After collecting the sleep data of the whole night, it can effectively assist the sleep doctor to sleep by combining the judgment of the sleep-time respiratory disorder, the determination of the sleep cardiovascular event, the determination of the sleep-aware response event, and the sleep structure staging. The quality of sleep in patients with disorders was deeply evaluated.
Algorithms ; Humans ; Sleep ; Sleep Apnea Syndromes ; Software