Assessing sleep posture, a critical component in sleep tests, is crucial for understanding an individual\'s sleep quality and identifying potential sleep disorders. However, monitoring sleep posture has traditionally posed significant challenges due to factors such as low light conditions and obstructions like blankets. The use of radar technolsogy could be a potential solution. The objective of this study is to identify the optimal quantity and placement of radar sensors to achieve accurate sleep posture estimation. We invited 70 participants to assume nine different sleep postures under blankets of varying thicknesses. This was conducted in a setting equipped with a baseline of eight radars-three positioned at the headboard and five along the side. We proposed a novel technique for generating radar maps, Spatial Radio Echo Map (SREM), designed specifically for data fusion across multiple radars. Sleep posture estimation was conducted using a Multiview Convolutional Neural Network (MVCNN), which serves as the overarching framework for the comparative evaluation of various deep feature extractors, including ResNet-50, EfficientNet-50, DenseNet-121, PHResNet-50, Attention-50, and Swin Transformer. Among these, DenseNet-121 achieved the highest accuracy, scoring 0.534 and 0.804 for nine-class coarse- and four-class fine-grained classification, respectively. This led to further analysis on the optimal ensemble of radars. For the radars positioned at the head, a single left-located radar proved both essential and sufficient, achieving an accuracy of 0.809. When only one central head radar was used, omitting the central side radar and retaining only the three upper-body radars resulted in accuracies of 0.779 and 0.753, respectively. This study established the foundation for determining the optimal sensor configuration in this application, while also exploring the trade-offs between accuracy and the use of fewer sensors.

UNASSIGNED: Obstructive sleep apnea (OSA) is common in patients with chronic thromboembolic pulmonary hypertension (CTEPH), but the pathological determinants of adverse outcomes remain unknown. This study aimed to investigate the prognostic significance of various sleep parameters in patients with CTEPH undergoing pulmonary endarterectomy.
UNASSIGNED: Consecutive patients diagnosed with CTEPH who underwent overnight cardiorespiratory polygraphy for the assessment of OSA were enrolled. Time-to-event analysis was performed investigating cardiorespiratory indices (e.g., apnea-hypopnea index [AHI], time percentage with oxygen saturation below < 90% [T90]) and clinical worsening using the log-rank test, and multivariable Cox proportional hazard models adjusted for multiple confounders.
UNASSIGNED: Of the 71 patients with operable CTEPH who underwent overnight cardiorespiratory polygraphy, 36 (50.7%) had OSA (AHI of ≥ 5) and 32 (45.1%) had nocturnal hypoxemia (T90 of ≥ 30%). A 10% increase in T90 was associated with a 27% greater risk of worse hemodynamics, as quantified by mean pulmonary artery pressure of ≥ 46 mmHg (odds ratio: 1.27, 95% confidence interval [CI]: 1.07-1.50, p = 0.006). Clinical worsening (CW) was experienced by 19 (26.8%) patients over a median follow-up of 26.8 months. AHI did not predict a higher risk of CW (hazard ratio [HR]: 1.00, 95% CI: 0.93-1.06, p = 0.906). A higher cumulative incidence of CW was seen in patients with nocturnal hypoxemia than in those with normoxemia (43.8% vs. 12.8%, log-rank p = 0.017). Cox regression analysis revealed the association between nocturnal hypoxemia and an increased risk of CW (HR: 3.27, 95% CI: 1.17-9.13, p = 0.024), and these associations persisted after covariate adjustment.
UNASSIGNED: Nocturnal hypoxemia quantified by T90 was a risk predictor of short- and long-term CW events among patients with operable CTEPH.

OBJECTIVE: Our objective was to create a machine learning architecture capable of identifying obstructive sleep apnea (OSA) patterns in single-lead electrocardiography (ECG) signals, exhibiting exceptional performance when utilized in clinical data sets.
METHODS: We conducted our research using a data set consisting of 1656 patients, representing a diverse demographic, from the sleep center of China Medical University Hospital. To detect apnea ECG segments and extract apnea features, we utilized the EfficientNet and some of its layers, respectively. Furthermore, we compared various training and data preprocessing techniques to enhance the model\'s prediction, such as setting class and sample weights or employing overlapping and regular slicing. Finally, we tested our approach against other literature on the Apnea-ECG database.
RESULTS: Our research found that the EfficientNet model achieved the best apnea segment detection using overlapping slicing and sample-weight settings, with an AUC of 0.917 and an accuracy of 0.855. For patient screening with AHI > 30, we combined the trained model with XGBoost, leading to an AUC of 0.975 and an accuracy of 0.928. Additional tests using PhysioNet data showed that our model is comparable in performance to existing models regarding its ability to screen OSA levels.
CONCLUSIONS: Our suggested architecture, coupled with training and preprocessing techniques, showed admirable performance with a diverse demographic dataset, bringing us closer to practical implementation in OSA diagnosis. Trial registration The data for this study were collected retrospectively from the China Medical University Hospital in Taiwan with approval from the institutional review board CMUH109-REC3-018.

BACKGROUND: Pneumoconiosis is associated with pulmonary and cardiovascular diseases; however, the link between pneumoconiosis and sleep disorders is not well understood. This study aimed to investigate the connection between pneumoconiosis and subsequent risk of sleep disorders.
METHODS: This population-based retrospective cohort study used data from the National Health Insurance database in Taiwan. The pneumoconiosis cohort consisted of 13,329 patients newly diagnosed between 2000 and 2015. The comparison group included 53,316 age-, sex-, and diagnosis date-matched individuals without pneumoconiosis. The development of sleep disorders was monitored until the end of 2018. Cox proportional hazard regression models were used for risk assessment.
RESULTS: The incidence of sleep disorders was 1.31 times higher in the pneumoconiosis cohort than in the comparison cohort (22.8 vs. 16.2 per 1000 person-years). After controlling for age, sex, comorbidity, and medication, the adjusted hazard ratio (aHR) was 1.24 (95% confidence interval [CI] = 1.17-1.32). Stratified analyses by age group, sex, and comorbidity status showed significant associations between pneumoconiosis and sleep disorders (aHRs, 1.19-1.64). In addition, patients with pneumoconiosis had a significantly increased risk of developing sleep apnea (aHR = 1.71, 95% CI = 1.31-2.22).
CONCLUSIONS: This study demonstrates that patients with pneumoconiosis are at a higher risk of developing sleep disorders and sleep apnea. Healthcare professionals should pay close attention to sleep quality and disturbances in patients with pneumoconiosis.

BACKGROUND: The effect of sleep apnea treatment on reducing cardiovascular disease risk remains inconclusive. This study aims to assess if the effective apnea hypopnea index (eAHI), a measure of residual sleep apnea burden post-treatment, is a factor in determining blood pressure (BP) response to continuous positive airway pressure therapy. The eAHI integrates time on therapy, residual apnea, and % of sleep time untreated.
METHODS: A secondary analysis of the Heart Biomarker Evaluation in Apnea Treatment (HeartBEAT) study, a randomized, controlled, parallel group assessment of continuous positive airway pressure (CPAP), oxygen and sleep hygiene. The Delta-AHI (▲AHI) was defined as the difference between baseline AHI and effective AHI at 12 weeks. Logistic and linear regression models estimated the predictors for nocturnal systolic BP change following sleep apnea therapy.
RESULTS: One hundred and sixty-nine subjects with a mean age of 62.82 ± 6.99 years were included in the final analysis. Fifty subjects had ▲AHI ≤8/hour of sleep and 119 subjects were higher. After adjustment, baseline mean nighttime systolic blood pressure (OR 1.036, 95% CI 1.015-1.058, p: 0.001) and ▲AHI ≥8/hour (OR 2.406, 95% CI 1.116-5.185, p:0.025) were independent predictors for mean nighttime systolic blood pressure change >3 mm Hg. The higher effective AHI was negatively related with BNP (β: -2.564, SE: 1.167, p: 0.029) and positively related with troponin change (β: 0.703, SE: 0.256, p: 0.007).
CONCLUSIONS: The ▲AHI was an independent predictor of the blood pressure response to sleep apnea treatment.
UNASSIGNED: NCT01086800.

OBJECTIVE: Randomized controlled trials have shown that combining norepinephrine reuptake inhibitors and antimuscarinics can ameliorate the severity of obstructive sleep apnea. This article explores whether the effectiveness and safety of combining norepinephrine reuptake inhibitors with antimuscarinic agents surpass monotherapy for treating obstructive sleep apnea.
METHODS: We searched randomized controlled trials including adult patients with obstructive sleep apnea who received combination therapy and monotherapy in 8 databases from inception until April 5, 2023 and evaluated the studies\' quality and conducted a meta-analysis and systematic review. The primary outcome was the apnea-hypopnea index. Secondary outcome measures included loop gain, hypoxic burden, oxygen desaturation index, and ventilation at low ventilatory drive, among other indicators. We assessed the quality of the studies using Cochrane Methods criteria.
RESULTS: We identified 4 randomized controlled trials for systematic review and 2 for meta-analysis. The results of the meta-analysis showed that norepinephrine reuptake inhibitors combined with antimuscarinic agents in patients with obstructive sleep apnea prolonged total sleep time by a mean of 28.20 minutes [95% confidence interval (5.78, 50.61), P = .01] and increased sleep efficiency by 4.73% [95% confidence interval (0.50, 8.97), P = .03] compared with norepinephrine reuptake inhibitors alone. Other indices and adverse events were of no statistical significance. The systematic reviews revealed that norepinephrine reuptake inhibitors combined with antimuscarinics may be superior to monotherapy in improving apnea-hypopnea index and endotypic traits.
CONCLUSIONS: This evaluation demonstrated the potential advantages of combining norepinephrine reuptake inhibitors plus antimuscarinics for treating OSA compared with norepinephrine reuptake inhibitors alone and revealed no statistically significant difference in drug safety.
BACKGROUND: Wang J, Ye Y, Shang Z, et al. Effect of norepinephrine reuptake inhibitors combined with antimuscarinic agents vs monotherapy for OSA: a systematic review and meta-analysis. J Clin Sleep Med. 2024;20(8):1363-1372.

UNASSIGNED: Antihypertensive medication is an effective way to control blood pressure. However, some studies reported that it may affect patients\' sleep quality during the treatment. Due to the inconsistency of present results, a comprehensive systematic review and network meta-analysis are needed.
UNASSIGNED: Electronic databases (MEDLINE, EMBASE, WEB OF SCIENCE, PUBMED) were searched up to April 10th, 2021 including no restriction of publication status. Randomized controlled trials (RCTs) or quasi-experimental studies or cohort studies were eligible. The network meta-analysis was used within a Bayesian framework.
UNASSIGNED: Finally, 16 publications (including 12 RCTs and 4 quasi-experimental studies) with 404 subjects were included in this study. Compared to placebo, the results of the network meta-analysis showed that diuretics were effective in improving sleep apnea with a mean difference (MD) of - 15.47 (95% confidence interval [CI]: - 23.56, - 6.59) which was consistent with the direct comparison result (MD: - 17.91; 95% CI - 21.60, - 14.23). In addition, diuretics were effective in increasing nocturnal oxygen saturation with an MD of 3.64 (95% CI 0.07, 7.46). However, the effects of β-blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, and the others on sleep apnea were not statistically significant. Additionally, the effects of antihypertensive medication on the total sleep time (min), rapid eye movement (%), and sleep efficiency (%) were not statistically significant.
UNASSIGNED: Our study found that diuretics could effectively reduce the severity of sleep apnea in hypertensive patients. However, the effects of antihypertensive drugs on sleep characteristics were not found.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s41105-022-00391-8.

OBJECTIVE: Cardiac remodeling is a life-long process in hypertrophic cardiomyopathy (HCM), and if uncontrolled, would cause substantial morbidity and mortality. Sleep apnea (SA) is a common comorbidity in HCM. This study aimed to investigate the relationship between SA and cardiac remodeling in a large series of patients with HCM.
METHODS: A total of 606 patients with HCM who underwent sleep evaluations at Fuwai Hospital were included. Parameters of cardiac remodeling were evaluated by echocardiographic studies.
RESULTS: SA was present in 363 (59.9%) patients. Left ventricular (LV) end-diastolic diameter (P < 0.001), left atrial (LA) diameter (P = 0.024), ascending aortic diameter (P < 0.001) all increased and maximal end-diastolic wall thickness (P < 0.001) decreased with the severity of SA. After adjustment for sex, age, body mass index, hypertension, hyperlipidemia, diabetes, coronary artery disease and cigarette use, log (apnea-hypopnea index+1) was independently correlated with increasing LV end-diastolic diameter (β = 0.729, P = 0.003) and deceasing maximal end-diastolic wall thickness (β = -0.503, P = 0.009). Log (percentage of total sleep time spent with oxygen saturation<90% + 1) was independently correlated with increasing LV end-diastolic diameter (β = 0.609, P = 0.004) and LA diameter (β = 0.695, P = 0.006). Severity of SA (severe SA with odds ratio, 2.38; 95% CI, 1.20-4.70; P = 0.013), log (apnea-hypopnea index+1) (OR, 1.28; 95% CI, 1.01-1.63; P = 0.045) and log (percentage of total sleep time spent with oxygen saturation<90% + 1) (OR, 1.31; 95% CI, 1.08-1.59; P = 0.006) were also independently associated with LV enlargement.
CONCLUSIONS: Severity of SA is independently associated with cardiac remodeling indicating a trend toward enlarged chamber size and thinned wall. Clinical trials are required to determine whether treatment of SA improves cardiac remodeling and long-term outcomes in patients with HCM.

Objective:To study the relationship between children\'s birth weight and obstructive sleep apnea（OSA）. Methods:The sleep data and birth information of children who underwent polysomnography in the Department of Otorhinolaryngology-Head and Neck Surgery of Henan Children\'s Hospital from October 2020 to July 2022 were retrospectively analyzed. The data of OSA detection rate, OSA severity, sleep structure and respiratory parameters in different birth weight groups were analyzed. Results:A total of 2 778 children met the inclusion criteria, including 1 833 males and 945 females. According to birth weight, the selected children were divided into three groups: 122 small for gestational age（SGA） group, 2 313 appropriate for gestational age（AGA）, and 343 large for gestational age（LGA） group. There was no significant difference in age between different groups（P=0.061）. In each group, boys are significantly more numerous than girls（P=0.001）. The difference in current body mass index（BMI） between groups was statistically significant: the current BMI was higher in the LGA group（17.51±4.01, P<0.001）. The severity of OSA was different in different birth weight groups（P=0.037）. There was a strong positive correlation between the severity of OSA and birth weight（r=0.992）. Children in the SGA group had shorter rapid eye movement（REM） sleep period（19.00[15.18, 23.33], P=0.012）, higher obstructive apnea-hypopnea index（OAHI） values（1.75[0.60, 5.13], P=0.019）, and had lower central apnea hypopnea index（CAHI） values（0.10[0.00, 0.50], P=0.020）. There were no significant differences in sleep structure and respiratory parameters between the LGA group and the AGA group. Multiple regression analysis of the factors affecting the OAHI index showed that the OAHI index of boys was higher than that of girls（95%CI 1.311-2.096, P<0.001）, and age was negatively correlated with the OAHI index（r=-0.105, 95%CI 0.856-0.946, P<0.001）, current BMI and OAHI index were positively correlated（r=0.037, 95%CI 1.010-1.065, P=0.007）. LGA was positively correlated with OAHI index（r=0.346, 95%CI 1.039-1.921, P=0.027）, and the correlation between LGA and OAHI（r=0.346） was higher than that between SGA and OAHI（r=0.340）. Conclusion:There was no significant difference in the incidence of OSA in children with different birth weight groups, but the OSA severity of LGA group was higher. Gender, age, BMI index and large for gestational age were the influencing factors for the occurrence of OSA in children, which should be paid more attention to in clinical practice.
目的：研究儿童出生体重与阻塞性睡眠呼吸暂停之间的关系。 方法：回顾性分析2020年10月至2022年7月在河南省儿童医院耳鼻咽喉头颈外科行多导睡眠监测（polysomnography，PSG）儿童的睡眠资料及出生信息，分析不同出生体重儿童阻塞性睡眠呼吸暂停（obstructive sleep apnea，OSA）的检出率、严重程度、睡眠结构和呼吸参数之间的关系。 结果：符合入选标准的儿童共2 778例，其中男1 833例，女945例。将入选的儿童按照出生体重分为小于胎龄儿（SGA）组122例，适于胎龄儿（AGA）组2 313例，大于胎龄儿（LGA）组343例。各组患儿之间行睡眠监测时的平均年龄差异无统计学意义（P=0.061），SGA组、AGA组和LGA组中的男性儿童均多于女性儿童（P=0.001）。各组之间的现平均体重指数（BMI）差异有统计学意义，LGA组儿童的现平均BMI较高（17.51±4.01，P<0.001）。不同出生体重组儿童的OSA严重程度不同（P=0.037），OSA严重程度和出生体重之间呈强正相关性（r=0.992）。SGA组儿童快速动眼睡眠（REM）期较少[19.00（15.18，23.33），P=0.012]，阻塞性呼吸暂停低通气指数（OAHI）较高[1.75（0.60，5.13），P=0.019]，中枢性呼吸暂停低通气指数（CAHI）较低[0.10（0.00，0.50），P=0.020]。LGA组和AGA组比较，睡眠结构和呼吸参数方面差异无统计学意义。对影响OAHI指数的因素进行多元回归分析发现，男童OAHI指数较女童高（95%CI 1.311～2.096，P<0.001），年龄与OAHI指数呈负相关（r=-0.105，95%CI 0.856～0.946，P<0.001），现BMI与OAHI指数呈正相关（r=0.037，95%CI 1.010～1.065，P=0.007）。LGA与OAHI指数呈正相关（r=0.346，95%CI 1.039～1.921，P=0.027），且LGA与OAHI的相关性（r=0.346）高于SGA与OAHI的相关性（r=0.340）。 结论：不同出生体重儿童的OSA发生率无明显差异，但大于胎龄儿的OSA严重程度更高。性别、年龄、BMI指数、大于胎龄儿均为儿童OSA发生的主要影响因素，临床应高度关注。.

OBJECTIVE: To evaluate the correlation between median frequency (MF) as a measure of genioglossus (GG) fatigue and overnight repetitive respiratory events in male patients with severe obstructive sleep apnea (OSA).
METHODS: GG electromyography (EMG) data were collected synchronously with polysomnography (PSG). Overnight respiratory events were divided based on whether they occurred during the first or second halves of the total number of overnight respiratory events, and differences in MF in the respiratory phase were compared in the same segments. Events were then sampled in pairs to compare MF. The correlation between MF and the order of respiratory events, as well as interindividual differences, were analyzed.
RESULTS: Twenty-two male patients were enrolled in this study and 2210 respiratory events were recorded. Before and during respiratory events, MF decreased significantly in the second half, especially during the inspiratory phase (segments 1-4: P = 0.014, P < 0.001, P < 0.001, P < 0.001, respectively). This trend was observed in non-rapid eye movement sleep and lateral position, but not in rapid eye movement sleep or the supine position, and remained after pairing for duration, stage, and position. MF correlated negatively with the order of respiratory events during the inspiratory phase. The trend of decrease in MF only existed in patients with apnea-hypopnea index > 30 events/h.
CONCLUSIONS: Overnight repetitive respiratory events were associated with increased GG fatigue, influenced by sleep stage and body position in male patients with severe OSA. GG fatigue depends on the order and frequency of respiratory events.