Sleep-related hypermotor epilepsy （SHE） is a rare type of epilepsy with a prevalence rate of approximately 1.8/100 000. This disease mainly manifests as complex motor behaviors during non-rapid eye movement sleep， such as leg kicking， arm waving， and sitting up. Since such symptoms are similar to non-epileptic disorders such as night terrors and sleepwalking and abnormal discharges may not be observed on electroencephalography， the diagnosis of SHE is quite challenging. Currently， there is still a lack of evidence from large-scale randomized controlled studies to support pharmacological treatment strategies for SHE， and related data in China remain scarce. This article reports a case of SHE， in order to provide a clinical reference for the diagnosis and medication treatment of this disease.
Polysomnography

Objective To investigate the sleep architecture of sleep related bruxism（SB）in adults and the sleep architecture of SB comorbid with obstructive sleep apnea hypopnea syndrome（OSAHS），as well as their correlation with age and other factors. Methods A total of 51 subjects with SB and 67 controls were included in this study to analyze the sleep architecture of SB and compare the sleep architecture of SB comorbid with different severities of OSAHS. Results Compared with the control group，the SB group had a younger age，increases in N1（%TST）and N2（%TST），a reduction in N3（%TST），and an increase in arousal index. The SB group was divided into non-OSAHS group（group 1），mild OSAHS group（group 2），and moderate-to-severe OSAHS group（group 3）. Group 1 had a younger age than group 2 and group 3，and group 3 had increases in body mass index（BMI），N1（%TST），oxygen desaturation index（ODI），and arousal index and a reduction in N3（%TST）. The Spearman's rank correlation analysis showed that BMI，N1（%TST），arousal index，and ODI increased with the increase in apnea-hypopnea index（AHI），while N3（%TST）decreased with the increase in AHI. The binary logistic regression analysis showed that SB was negatively correlated with age and was positively correlated with arousal index. Conclusion SB may affect sleep architecture by increasing light sleep，reducing deep sleep，and increasing the number of awakenings. There are changes in sleep architecture in case of SB comorbid with different severities of OSAHS. SB is negatively correlated with age and is positively correlated with arousal index.
Polysomnography

INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings. Machine learning (ML) models have strengths in disease prediction and early diagnosis. We explored the use of ML with oximetry, demographic and anthropometric data to diagnose OSA. METHODS: A total of 2,996 patients were included for modelling and divided into test and training sets. Seven commonly used supervised learning algorithms were trained with the data. Sensitivity (recall), specificity, positive predictive value (PPV) (precision), negative predictive value, area under the receiver operating characteristic curve (AUC) and F1 measure were reported for each model. RESULTS: In the best performing four-class model (neural network model predicting no, mild, moderate or severe OSA), a prediction of moderate and/or severe disease had a combined PPV of 94%; one out of 335 patients had no OSA and 19 had mild OSA. In the best performing two-class model (logistic regression model predicting no-mild vs. moderate-severe OSA), the PPV for moderate-severe OSA was 92%; two out of 350 patients had no OSA and 26 had mild OSA. CONCLUSION Our study showed that the prediction of moderate-severe OSA in a tertiary setting with an ML approach is a viable option to facilitate early identification of OSA. Prospective studies with home-based oximeters and analysis of other oximetry variables are the next steps towards formal implementation.
Humans ; Oximetry/methods* ; Sleep Apnea, Obstructive/diagnosis* ; Male ; Female ; Middle Aged ; Machine Learning ; Polysomnography ; Adult ; Anthropometry ; ROC Curve ; Aged ; Algorithms ; Predictive Value of Tests ; Sensitivity and Specificity ; Neural Networks, Computer ; Demography

INTRODUCTION: Arrhythmias, especially atrial fibrillation (AF) and ventricular arrhythmias, are independent risk factors of mortality in patients with ischaemic heart disease (IHD). While there is a growing body of evidence that suggests an association between obstructive sleep apnoea (OSA) and cardiac arrhythmias, evidence on this relationship in patients with IHD has been scant and inconsistent. We hypothesised that in patients with IHD, severe OSA is associated with an increased risk of nocturnal arrhythmias. METHODS: We studied 103 consecutive patients with IHD who underwent an overnight polysomnography. Exposed subjects were defined as patients who had an apnoea-hypopnoea index (AHI) ≥30/h (severe OSA), and nonexposed subjects were defined as patients who had an AHI <30/h (nonsevere OSA). All electrocardiograms (ECGs) were interpreted by the Somte ECG analysis software and confirmed by a physician blinded to the presence or absence of exposure. Arrhythmias were categorised as supraventricular and ventricular. Arrhythmia subtypes (ventricular, atrial and conduction delay) were analysed as dichotomous outcomes using multiple logistic regression models. RESULTS: Atrial fibrillation and AF/flutter (odds ratio 13.5, 95% confidence interval 1.66-109.83; P = 0.003) were found to be more common in the severe OSA group than in the nonsevere OSA group. This association remained significant after adjustment for potential confounders. There was no significant difference in the prevalence of ventricular and conduction delay arrhythmias between the two groups. CONCLUSION In patients with IHD, there was a significant association between severe OSA and nocturnal AF/flutter. This underscores the need to evaluate for OSA in patients with IHD, as it may have important implications on clinical outcomes.
Humans ; Sleep Apnea, Obstructive/diagnosis* ; Atrial Fibrillation/diagnosis* ; Male ; Female ; Middle Aged ; Polysomnography ; Electrocardiography ; Myocardial Ischemia/complications* ; Aged ; Risk Factors ; Logistic Models

Objective:The variability of the apnea-hypopnea index（AHI） measured in the first and second halves of the night is significant in patients with obstructive sleep apnea hypopnea syndrome（OSAHS）. This variation may be related to fluid redistribution caused by the supine position during sleep. Methods:Eighty-nine adult subjects were enrolled. Circumferences（neck, chest, waist, and calf） were measured before sleep onset and upon awakening. Polysomnography（PSG） was performed, and the night was divided into two halves based on the midpoint of total sleep time to calculate AHI for each half. The correlation between changes in AHI and changes in circumferences was analyzed. Results:Twenty simple snorers and sixty-nine OSAHS patients were included, with a median AHI of 22.6（11.8, 47.3） events/hour. Compared to pre-sleep measurements, there was no significant change in neck circumference upon awakening in the control group（P=0.073）, while reductions were observed in the other three measurements（P=0.006, P=0.038, P<0.001）. In the OSAHS group, neck circumference increased（P<0.001）, and reductions were noted in the other three measurements（P<0.001 for all）, with the most significant change observed in calf circumference 40.0（37.1, 42.0） cm to 38.0（35.8, 40.5） cm. Compared to the first half of the night, total AHI, supine AHI, and NREM AHI significantly decreased in the second half（P=0.010, P=0.031, P=0.001）, while no significant changes were observed in lateral AHI and REM AHI（P=0.988, P=0.530）. Further analysis revealed a significant relationship between increased chest circumference and decreases in NREM AHI, supine AHI, and supine NREM AHI（P=0.036, P=0.072, P=0.034）, as well as between decreased lateral position AHI and increased waist circumference（P=0.048）. Additionally, this study found a negative correlation between changes in calf circumference and changes in AHI（R=-0.24, P=0.048）, while neck circumference changes positively correlated with changes in AHI（R=0.26, P=0.03）. Conclusion:In OSAHS patients during the second half of sleep compared to before sleeping, chest circumference, waist circumference, and calf circumference decrease while neck circumference increases; total AHI, supine position AHI, and NREM period AHI decrease; increases in chest circumference are associated with decreases in NREM period AHI, supine position AHI, supine position NREM period AHI. There is nocturnal variability in AHI among OSAHS patients that may be associated with fluid shifts during sleep.
Humans ; Sleep Apnea, Obstructive/physiopathology* ; Male ; Female ; Polysomnography ; Fluid Shifts/physiology* ; Adult ; Middle Aged ; Neck ; Severity of Illness Index ; Sleep/physiology* ; Snoring/physiopathology*

Objective:To investigate the relationship between the Palatopharyngeal Arch Staging System（PASS） and the severity of Obstructive Sleep Apnea（OSA）, as well as the patterns of airway collapse, while further assessing its clinical applicability. Methods:A total of 98 patients diagnosed with OSA at the Department of Otorhinolaryngology Head and Neck Surgery, Shenzhen University Affiliated Shenzhen Hospital, were recruited for this study. Data collected included basic demographic information, oropharyngeal laryngoscopy videos, results from awake laryngoscopy Muller tests, and indicators from sleep respiratory monitoring. The distribution of each PASS stage among patients with varying severities of OSA was compared. Additionally, both objective and subjective sleep indicators along with occurrences of airway collapse in OSA patients across different PASS stages were analyzed. Results:In total, 98 patients participated in this study. Statistically significant differences were observed in neck circumference, weight, Body Mass Index（BMI）, tongue position, and PASS stage when comparing mild-to-moderate OSA patients to those with severe OSA（P<0.05）. Furthermore, there were statistically significant variations in Apnea-Hypopnea Index（AHI）, minimum blood oxygen saturation levels, average blood oxygen saturation levels, oxygen desaturation index values, and total oxygen desaturation indices among OSA patients categorized by different PASS stages. Multiple comparisons revealed statistically significant differences in AHI as well as minimum and average blood oxygen saturation levels between patients at PASS 1 versus those at PASS 3（P<0.05）. Additionally, notable differences regarding oropharyngeal collapse rates among OSA patients across various PASS stages were identified; specifically between those at PASS stage 1 and those at PASS stage 3. Conclusion:The proportion of PASS stages for OSA varies across different severity levels. The severity of OSA and the degree of airway collapse in patients with varying PASS stages also exhibit significant differences. Patients classified as PASS 3 demonstrate a more severe form of OSA compared to those at PASS 1, with stage 3 being more susceptible to oropharyngeal collapse than its stage 1 counterpart. This assessment system is anticipated to address the current limitations in evaluating the lateral pharyngeal wall within the oropharynx.
Humans ; Sleep Apnea, Obstructive/pathology* ; Male ; Severity of Illness Index ; Female ; Middle Aged ; Polysomnography ; Adult ; Pharynx/physiopathology* ; Aged

Objective:To analyze the efficacy, influencing factors, and risk warning of multi-plane low-temperature plasma radiofrequency ablation（MLT-RFA） in the treatment of obstructive sleep apnea hypopnea syndrome（OSAHS）. Methods:A total of 118 OSAHS patients admitted from October 2022 to June 2024 were selected as the research subjects. They were divided into mild group（n=46）, moderate group（n=52）, and severe group（n=20） according to the severity of their condition. MLT-RFA treatment was used for all patients. After surgery, the results of polysomnography（PSG） and the changes in the Calier Sleep Apnea Quality of Life Index（SAQLI） were observed before and after treatment. The incidence of complications after treatment was recorded, and the clinical efficacy of the patients was evaluated. At the same time, they were divided into a treatment effective group（n=106） and an ineffective group（n=12） according to their effects. The general clinical data of the two groups were compared, and binary logistics regression analysis was conducted to identify independent factors that affect treatment efficacy and construct a model. ROC curve analysis was used to evaluate the diagnostic efficacy of the model. Results:The treatment effectiveness rate of the mild group was 93.48%, the moderate group was 90.38%, and the severe group was 80.00%. There was no statistically significant difference in the treatment effectiveness rate among the three groups（P>0.05）. The AHI of the mild group, moderate group, and severe group increased sequentially, while the LSaO2and SAQLI scores decreased sequentially. After treatment, the AHI of all three groups decreased compared to before treatment, while the LSaO2and SAQLI scores increased compared to before treatment, and the differences were statistically significant（P<0.05）. The pre-treatment AHI of the effective group was lower than that of the ineffective group, and the pre-treatment LSaO2and SAQLI were higher than those of the ineffective group, with statistically significant differences（P<0.05）. Pre-treatment LSaO2and pre-treatment SAQLI are independent factors affecting the efficacy of MLT-RFA（P<0.05）. The AUC of pre-treatment LSaO2, pre-treatment SAQLI, and combined prediction were 0.907, 0.763, and 0.947, respectively, with sensitivities of 0.896, 0.840, and 0.917, and specificities of 0.833, 0.667, and 0.887, respectively. Conclusion:MLT-RFA has a significant effect on the treatment of OSAHS, and the AHI, LSaO2, and SAQLI of patients before treatment can predict the treatment effect, with LSaO2 and SAQLI being independent influencing factors. The combinerd prediction model exhibits high diagnostic efficiency, sensitivity, and specificity.
Radiofrequency Ablation/methods* ; Plasma Gases ; Sleep Apnea, Obstructive/surgery* ; Polysomnography ; Postoperative Complications/epidemiology* ; Quality of Life ; Severity of Illness Index ; Treatment Outcome ; Humans

Objective To investigate the correlations of circulating miRNA-205 expression with systemic immune-inflammation index(SII)and systemic inflammation response index(SIRI)in patients with severe obstructive sleep apnea(OSA). Methods The patients who attended the Hypertension Center of the People's Hospital of Xinjiang Uygur Autonomous Region from January to June 2023 and underwent complete overnight polysomnography were consecutively included in this study.Among them,30 patients had severe OSA,and 32 patients did not have OSA.Blood routine tests(white blood cells,neutrophils,monocytes,platelets,etc.)were performed and the expression of miRNA-205 was determined by quantitative reverse transcription PCR.Simple regression was adopted to analyze the correlations among miRNA-205,SII,SIRI,and OSA parameters.The potential regulatory effects of miRNA-205 on OSA and inflammation indices were further evaluated. Results The patients with severe OSA showed lower expression of circulating miRNA-205[1.910(1.240,2.403)vs.3.650(2.148,5.109),z=-3.874,P<0.001]and higher SIRI[1.090(0.775,1.573)vs.0.870(0.650,1.240),z=-2.031,P=0.041]and SII[555.200(451.780,936.350)vs.448.685(380.823,646.073),z=-2.029,P=0.042]than non-OSA patients.In the whole population,apnea-hypopnea index(AHI)showed a negative correlation with circulating miRNA-205(r=-0.391,P=0.002).Among severe OSA patients,each 1-unit increase in AHI was associated with a reduction of 0.030 in miRNA-205 and increases of 10.046 and 0.037 in SII and SIRI,respectively(SII:P=0.003;SIRI:P=0.037).Conversely,each 1-unit rise in miRNA-205 predicted a decrease of 121.093 in SII(β=-0.40,P=0.046).The low expression of miRNA-205 might have a negative moderating effect on elevated SII(β=-0.40,P=0.004). Conclusions Compared with the patients without OSA,those with severe OSA showed elevated SII and SIRI and down-regulated expression of miRNA-205.The low expression of miRNA-205 might have a negative moderating effect on the systemic inflammatory state associated with severe OSA.
Humans ; Sleep Apnea, Obstructive/blood* ; MicroRNAs/blood* ; Inflammation/blood* ; Male ; Polysomnography ; Middle Aged ; Female ; Adult

Objective To investigate the differences in sleep structure and executive function between the patients with insomnia disorder and the individuals with normal sleep， as well as the potential mechanism of executive dysfunction in patients with insomnia disorder.Methods The patients with insomnia disorder who attended the outpatient service of Sleep Medicine Center， Chongqing Western Hospital， from March 2022 to December 2023 were enrolled as insomnia disorder group， and the individuals with normal sleep were enrolled as control group. All subjects were evaluated using Hamilton Anxiety Scale （HAMA）， Hamilton Depression Scale （HAMD）， polysomnography， and Stroop Color-Word Test. The two groups were compared in terms of anxiety， depression， sleep parameters （sleep latency， total sleep time， sleep efficiency， NREM1 and its percentage， NREM2 and its percentage， NREM3 and its percentage，as well as REM and its percentage）， executive function （time consumption and correct number of Stroop A，Stroop B，Stroop C， and interference test）， and a correlation analysis was also performed.Results There were 51 subjects in the insomnia disorder group and 25 subjects in the control group. Compared with the control group， the insomnia disorder group had significantly higher HAMA score， HAMD score， sleep latency， percentage of NREM1， and percentage of NREM2 （P<0.05）. Compared with the control group， the insomnia disorder group had significantly lower total sleep time， sleep efficiency， NREM3 duration， REM duration， and percentage of NREM3 （P<0.05）. Compared with the control group， the insomnia disorder group had significantly higher time consumption of Stroop Color-Word Test C and interference test （P<0.05）. In the insomnia disorder group， time consumption of Stroop C and interference test was negatively correlated with NREM3 duration and the percentage of NREM3 and was positively correlated with NREM2 duration and the percentage of NREM2， and time consumption of Stroop C was positively correlated with the percentage of NREM1（P<0.05）.Conclusion Patients with insomnia disorder tend to have a long sleep latency， a short total sleep time， low sleep efficiency，and reductions in deep sleep and executive function， and the reduction in executive function is associated with the reduction in slow-wave sleep.
Polysomnography

Objective:This study aimed to construct a risk prediction model for obstructive sleep apnea（OSA） related hypertension based on the nomogram, and to explore the independent risk factors for OSA-related hypertension, so as to provide reference for clinical treatment decision-making. Methods:The clinical data of OSA patients diagnosed by polysomnography from October 2019 to December 2021 were collected retrospectively and randomly divided into training sets and validation sets. A total of 1 493 OSA patients with 27 variables were included. The least absolute shrinkage and selection operator（Lasso） logistic regression model was used to select potentially relevant features and establish a nomogram for OSA-related hypertension.The performance and clinical benefits of this nomogram were verified in terms of discrimination, calibration ability and clinical net benefit. Results:Multivariate logistic regression showed that body mass index（BMI）, family history of hypertension, lowest oxygen saturation（LSaO2）, age and cumulative percentage of total sleep time with oxygen saturation below 90% were independent risk factors for OSA-related hypertension. Lasso logistic regression identified BMI, family history of hypertension, LSaO2 and age as predictive factors for inclusion in the nomogram. The nomogram provided a favorable discrimination, with a C-indexes of 0.835（95% confidence interval[CI ]0.806-0.863） 0.865（95%CI 0.829-0.900） for the training and validation cohort, respectively, and well calibrated. The clinical decision curve analysis displayed that the nomogram was clinically useful. Conclusion:Compared with cumulative percentage of total sleep time with blood oxygen saturation below 90%, LSaO2 may have a greater impact on the incidence of OSA-related hypertension, and the effects of different times and degrees of hypoxia on OSA-related hypertension should be further explored in the future. Apnea hypopnea index involvement is weak in predicting OSA-related hypertension, and the blood oxygen index may be a better predictor variable. Furthermore, we established a risk prediction model for OSA-related hypertension patients using nomogram, and demonstrated that this prediction model was helpful to identify high-risk OSA-related hypertension patients. This model can provide early and individualized diagnosis and treatment plans, protect patients from the serious.
Humans ; Sleep Apnea, Obstructive/complications* ; Nomograms ; Hypertension/epidemiology* ; Male ; Female ; Risk Factors ; Middle Aged ; Retrospective Studies ; Polysomnography ; Logistic Models ; Body Mass Index ; Adult