Sleep and Breathing最新文献

Objective: This study aims to investigate the potential association between obstructive sleep apnea hypopnea syndrome (OSAHS) and bone metabolism in male patients with type 2 diabetes mellitus (T2DM), and to further analyze the mediating role of body mass index (BMI) in this relationship. By elucidating the interaction mechanisms between OSAHS and bone metabolism, this study seeks to provide a scientific basis for early screening and intervention of bone metabolism abnormalities in male T2DM patients, thereby improving their clinical outcomes.

Methods: This study analyzed 418 male T2DM inpatients from the Department of Endocrine and Metabolic Diseases at the First People's Hospital of Changzhou between May 2020 and May 2024. Patients were categorized into the pure T2DM group and the T2DM with OSAHS group based on their apnea-hypopnea index (AHI). Linear correlation and multiple linear regression analyses were employed to evaluate the relationships among OSAHS, BMI, and bone metabolism indicators. Finally, mediation analysis was conducted to assess the mediating effect of BMI.

Results: Among OSAHS indicators, nocturnal lowest oxygen saturation (LSaO2) correlated with total N-terminal propeptide of type I collagen (TP1NP). A 1-SD increase in LSaO2 was associated with a 2.532 ng/ml increase in TP1NP (95% CI: 0.232 ~ 4.832, P < 0.05). While BMI was positively correlated with bone mineral density (BMD), no correlation was found between BMI and bone turnover markers (BTMs). The oxygen desaturation index (ODI) and proportion of cumulative sleep time with oxygen saturation below 90% in total sleep time (T90) was initially correlated with BMD at the different sites, but the association was nullified after adjusting for BMI. Mediation analysis showed that BMI fully mediated the relationship between ODI T90 and BMD, with no influence on the association between LSaO2 and BTMs.

Conclusion: OSAHS-induced hypoxia may inhibit osteoblastic activity, which warrants further investigation. Additionally, while BMI fully mediates the relationship between ODI and BMD, further studies are needed to exclude the potential influence of BMI on BMD measurements.

Purpose: To establish a simple and noninvasive screening test for sleep apnea (SA) that imposes less burden on potential patients. The specific objective of this study was to verify the effectiveness of past and future single-lead electrocardiogram (ECG) data from SA occurrence sites in improving the estimation accuracy of SA and sleep apnea syndrome (SAS) using machine learning.

Methods: The Apnea-ECG dataset comprising 70 ECG recordings was used to construct various machine-learning models. The time window size was adjusted based on the accuracy of SA detection, and the performance of SA detection and SAS diagnosis (apnea‒hypopnea index ≥ 5 was considered SAS) was compared.

Results: Using ECG data from a few minutes before and after the occurrence of SAs improved the estimation accuracy of SA and SAS in all machine learning models. The optimal range of the time window and achieved accuracy for SAS varied by model; however, the sensitivity ranged from 95.7 to 100%, and the specificity ranged from 91.7 to 100%.

Conclusions: ECG data from a few minutes before and after SA occurrence were effective in SA detection and SAS diagnosis, confirming that SA is a continuous phenomenon and that SA affects heart function over a few minutes before and after SA occurrence. Screening tests for SAS, using data obtained from single-lead ECGs with appropriate past and future time windows, should be performed with clinical-level accuracy.

Purpose: Accurately identifying sleep states (REM, NREM, and Wake) and brief awakenings (arousals) is essential for diagnosing sleep disorders. Polysomnography (PSG) is the gold standard for such assessments but is costly and requires overnight monitoring in a lab. Home sleep testing (HST) offers a more accessible alternative, relying primarily on breathing measurements but lacks electroencephalography, limiting its ability to evaluate sleep and arousals directly. This study evaluates a deep learning algorithm which determines sleep states and arousals from breathing signals.

Methods: A novel deep learning algorithm was developed to classify sleep states and detect arousals from respiratory inductance plethysmography signals. Sleep states were predicted for 30-s intervals (one sleep epoch), while arousal probabilities were calculated at 1-s resolution. Validation was conducted on a clinical dataset of 1,299 adults with suspected sleep disorders. Performance was assessed at the epoch level for sensitivity and specificity, with agreement analyses for arousal index (ArI) and total sleep time (TST).

Results: The algorithm achieved sensitivity and specificity of 77.9% and 96.2% for Wake, 93.9% and 80.4% for NREM, 80.5% and 98.2% for REM, and 66.1% and 86.7% for arousals. Bland-Altman analysis showed ArI limits of agreement ranging from - 32 to 24 events/hour (bias: - 4.4) and TST limits from - 47 to 64 min (bias: 8.0). Intraclass correlation was 0.74 for ArI and 0.91 for TST.

Conclusion: The algorithm identifies sleep states and arousals from breathing signals with agreement comparable to established variability in manual scoring. These results highlight its potential to advance HST capabilities, enabling more accessible, cost-effective and reliable sleep diagnostics.

Purpose: Both obstructive (OSA) and central sleep apnea (CSA) are associated with considerable cardiovascular morbidity which argues for treatment initiation with a positive airway pressure (PAP) device even in the absence of significant day-time sleepiness. While the long-term consequences of PAP treatment in patients with sleep disordered breathing have been investigated in several studies, less is known about the immediate hemodynamic effects. Therefore, the present study intended to investigate the immediate effect of PAP treatment on non-invasively measured hemodynamic parameters in 10 patients with either OSAS or CSA.

Methods: During diagnostic and therapeutic conditions, the routine polysomnographic assessment was extended with an impedance cardiography (ICG) system. Statistical analysis was performed to find differences between both groups and conditions. In addition, the relationship between the treatment associated effect on stroke volume (SV) with biometric, polysomnographic, and cardiovascular parameters was assessed.

Results: Comparing both subgroups, we found statistically significant differences for biometric, polysomnographic, and cardiovascular parameters. Patients with CSA were older (p = 0.0005) and had higher values for diagnostic (p = 0.015) and therapeutic (p = 0.029) pulse pressure and the pre-ejection period under diagnostic conditions (p = 0.031). In contrast to patients with CSA who exhibited a slight increase of SV and derived parameters under therapeutic conditions, a pronounced decrease was observed in patients with OSAS which was statistically significant for the cardiac index (p = 0.038).

Conclusion: Our results indicate that patients with OSAS and CSA who are characterized by unique clinical features may show a distinguishable hemodynamic response to PAP treatment that can be measured non-invasively with ICG.

Purpose: Positive airway pressure (PAP) treatment for obstructive sleep apnea syndrome (OSAS) is often burdened by lower adherence rates. Patients' perception and acceptance of PAP therapy play a crucial role in achieving acceptable adherence.

Method: We conducted a prospective cohort study to assess patients' initial impressions of PAP therapy using a six-item questionnaire. The questionnaire evaluated CPAP tolerance, interface comfort, titration pressure, likelihood of CPAP use, expected health benefits, and overall attitude toward PAP therapy. Patients underwent a baseline awake PAP therapy trial (T0) followed by titration with an automatic device (APAP). After one month of titration, a fixed CPAP value was set (T1). Follow-ups occurred at 1 (T2), 3 (T3), and 6 (T4) months after the start of treatment. Adherence to PAP therapy was considered sufficient if the mean device usage was ≥ 4 h/night at T4.

Results: After six months, 77% of the enrolled patients achieved high PAP treatment adherence. Questionnaire scores generally improved from T0 to T4, particularly in CPAP tolerance, likelihood of treatment adherence, expected health benefits, and overall judgment of PAP therapy. Time-to-event analysis revealed that higher baseline scores in titration pressure comfort, likelihood of CPAP adherence, and overall judgment of PAP therapy were significantly associated with higher adherence likelihood.

Conclusion: Patients' first judgement on PAP therapy could significantly influence short-term adherence. Early identification and management of patients' complaints and discomforts could improve adherence rates and PAP perception over time.

Purpose: To determine the association of religious service attendance with sleep quality and disorders, and test whether lifestyle and health-related factors mediate this association.

Methods: This cross-sectional study included 5,520 adults surveyed through a virtual, exploratory, population-based survey (Sonar-Brazil, 2023-2024). Multivariate regression models were used to assess the association among religious service attendance, hypothesized mediators (depression, smoking, alcohol use, drug use, diet quality, body mass index, and screen time) and sleep outcomes. We computed estimates for the total effect, average direct effect, average causal mediation effect, and the percentage of the effect mediated by the mediators using the quasi-Bayesian Monte Carlo method, employing a normal approximation with 5000 simulations.

Results: Decreasing frequency of religious attendance was associated with poorer sleep quality and higher probabilities of sleep disorders, depression, smoking, drug use, increased alcohol consumption frequency, and longer screen time (p < 0.01). Depression had the greatest influence on sleep outcomes in the multivariate analyses and was identified as the primary mediator in the relationship between religious attendance and sleep quality (24%), followed by smoking (3%) and screen time (7%). Similarly, the effect on sleep disorders was mediated by depression, alcohol consumption, and screen time at 12%, 10%, and 3%, respectively.

Conclusion: Our findings offer unprecedented insights into the relationship between religious attendance and sleep quality among Brazilian adults and contribute to previous research by showing that religious attendance may protect against sleep disturbance through enhancements in mental health, reduced substance use, and a more active lifestyle, illuminating pathways through which religious involvement may impact sleep outcomes.

Objective: To conduct a systematic review and meta-analysis to evaluate long term effect of soft tissue surgery on blood pressure (BP) in adults with obstructive sleep apnea (OSA).

Search methods: PubMed, Scopus, the Cochrane library, and Ovid Medline databases were searched through January 2024. Manual searches were also obtained. This review included studies assessing impact of soft tissue surgery for the treatment of OSA in adults on long-term BP.

Result: A total of five studies (299 patients) met our inclusion criteria. Pooled random effects analysis demonstrated a statistically significant long-term postoperative reduction of BP, with average systolic BP reduction of 14.04 mmHg [95%CI (-21.97, -6.11); P = 0.0005]. Pooled random effects analysis of data from four studies (277 patients) also demonstrated statistically significant long-term postoperative reduction of diastolic BP by 6.88 mmHg compared with preoperative baseline [95%CI (-13.31, -0.45); P = 0.04].

Conclusion: Soft tissue surgery for OSA treatment in adults significantly resulted in long-term blood pressure reduction.

Objectives: Excessive daytime sleepiness (EDS) is a key symptom of Obstructive Sleep Apnoea (OSA). Both EDS and OSA affect, and are affected by, physical activity (PA). This study explores physical activity patterns in OSA patients and the association between activity and EDS.

Methods: This is a retrospective analysis of cross-sectional data from the Sydney Sleep Biobank, which recruited sleep clinic patients between August 2018 and June 2022. Participants aged > 18 years with untreated OSA were included, while those with other sleep disorders or whose medication/work affected sleepiness were excluded. PA was assessed with the International Physical Activity Questionnaire (IPAQ), with intensity quantified by metabolic equivalent of task (MET). Subjective daytime sleepiness with quantified by the Epworth Sleepiness Scale (ESS).

Results: Of 487 patients with OSA, 21% reported low (< 600 MET-min/week), 32% medium (600-2999 MET min/week), and 47% high PA ( > = 3000 MET-min/week). Participants with mild OSA were the most likely to be in the high PA group. ESS was not significantly associated with physical activity nor OSA severity, after adjustment for sex, age, body mass index, and sleep duration. Consideration of a potential interaction between physical activity and OSA severity did not change these results. However, in subgroup analysis of women only, severe OSA and medium and high levels of PA were linked to higher ESS scores.

Conclusions: Greater physical activity was associated with higher daytime sleepiness in women, but not men. However, further research is needed to reproduce these findings using objective measures of physical activity and to examine if physical activity has direct benefits for daytime symptoms of OSA beyond sleepiness.

Purpose: Night-to-night adherence to sleep-disordered breathing (SDB) treatment with either continuous positive airway pressure (CPAP) or mandibular advancement splints (MAS) in pregnancy has not been well characterized. The objective of this study was to assess night-to-night adherence patterns from existing CPAP and MAS data in pregnancy.

Methods: Three separate pregnancy cohorts evaluating treatment for SDB in the second and third trimester were used: 1) CPAP in gestational diabetes mellitus (GDM), 2) CPAP in hypertensive disorders of pregnancy (HDP), and 3) mandibular advancement splints (MAS). The first 30 days of objective adherence data obtained from CPAP and MAS devices were used in this descriptive analysis.

Results: Data from 37 CPAP users and 15 MAS users was analyzed. For the GDM and HDP cohorts, three patterns of adherence were observed: 1) consistent CPAP users (38%), 2) improved CPAP usage after initial adaptation (16%), and 3) inconsistent CPAP users (46%). For the MAS cohort, the three observed patterns of adherence were: 1) consistent MAS users (47%), 2) initial usage with subsequent decrease in adherence (20%), and 3) inconsistent MAS users (33%). Participant characteristics (demographics, disease severity) were similar between adherence groups, with the exception of longer total sleep time in consistent CPAP users of the GDM cohort and greater gestational age in consistent CPAP users of the HDP cohort.

Conclusion: Overall, objective night-to-night adherence patterns revealed that almost half of CPAP and MAS users had difficulty adapting to treatment in the first 30 days of treatment. Early usage patterns in pregnancy may provide insight into identifying patients who are at risk for poor adherence and for developing tailored and timely interventions to enhance adherence to therapy.

Trial registration: ClinicalTrials.gov Identifiers: NCT02245659, NCT03309826, NCT03138291.