Sleep and Breathing最新文献

Purpose: Obstructive Sleep Apnea Syndrome (OSAS) and Obesity Hypoventilation Syndrome (OHS) share common causal factors and comorbidities but may have a variable effect on physical activity and associated quality of life, due to differences in pathophysiology. The aim of this study was to compare the levels of physical activity, mental health and quality of life between matched obese patients with either OSAS or OHS, aiming to identify which of the two syndromes may impose the most severe impact on these variables, for the first time in literature.

Methods: A total of 76 obese patients (OSAS: Ν1 = 48, OHS: N2 = 26) of similar age (58.2 ± 12.2 vs. 63.6 ± 9.8; p > 0.05), BMI (37.2 ± 6.2 vs. 40.3 ± 7.3; p > 0.05), and Apnea-Hypopnea Index (AHI) under non-invasive ventilation, completed International Physical Activity Questionnaire (IPAQ), Short-Form Health Questionnaire (SF-36), Personal Well-Being (PWB) Scale and Hospital Anxiety and Depression Scale (HADS-A and HADS-D), in this cross-sectional study.

Results: Both groups had similar scores in SF-36, HADS-A and HADS-D, while prevalence of clinical cases of anxiety (HADS-A > 8) and depression (HADS-D > 8) were also similar. OSAS patients scored significantly higher in physical activity [absolute IPAQ values 1100.75(7753.5) for OSAS vs. 518(3806) for OHS; p = 0.029]. Group comparisons yielded significant differences in physical functioning (p < 0.05) and general health perceptions (p < 0.05), in favor of the OSAS group.

Conclusion: Both syndromes significantly affect patients' quality of life and physical activity, with the burden being heavier for OHS patients. Daily physical activity seems to be more impaired among obese OHS patients perhaps due to daytime hypercapnia.

Background: Mandibular advancement devices (MAD) are a well-established treatment option for obstructive sleep apnea (OSA). MAD are considered preferably for patients with mild to moderate OSA presenting with a elevated night-to-night variability (NNV). This study aimed to determine the treatment effect of MAD on NNV considering different protrusion distances and patient related outcome (PRO).

Methods: We conducted a prospective cohort analysis of patients before MAD with 60% and 80% of the maximum protrusion. OSA severity was assessed using a home-sleep test for two consecutive nights. PRO contained the Epworth Sleepiness Scale (ESS) and sleep related quality of life (FOSQ).

Results: Twenty patients with a median overweight body-mass-index of 27.1 (interquartile range (IQR) 16.3 kg/m²), with a mainly mild to moderate OSA with an apnea -hypopnea index (AHI) of 18.3 / h (IQR 17.7) and elevated ESS of 12.5 (IQR 8.0) were included. As opposed to 80%, 60% protrusion significantly but not 80% relevantly reduced AHI (60%%: 11.2 (IQR 5.5)/h, p = 0.01; 80%: 12.9 (IQR18,0)/h, p = 0.32) and improved the ESS (60%: 8.0 (IQR 10,0); 80%: 10 (IQR 9.0)), with therapy settings. No correlation could be detected between NNV and ESS, and FOSQ changes. Higher baseline NNV was associated with severe OSA (p = 0.02) but not with gender, overweight, or status post-tonsillectomy.

Conclusions: OSA improvement is associated with lower NNV; both OSA and NNV are connected to the degree of protrusion. Therefore, higher NNV does not justify the exclusion of candidates for MAD treatment. PRO changes are not visibly affected by NNV but by general OSA changes. These findings may help to define and optimize future study designs for the primary outcome decision between objective OSA parameters and PRO.

Purpose: This study aims to develop sleep apnea screening models with overnight SpO2 data, and to investigate the impact of the SpO2 data granularity on model performance.

Methods: A total of 7,718 SpO2 recordings from the SHHS and MESA datasets were used. Probabilistic ensemble machine learning was employed to predict sleep apnea status at three AHI cutoff points: ≥ 5, ≥ 15, and ≥ 30 events/hour. To investigate the impact of data granularity, SpO2 data were aggregated at 30, 60, and 300 s.

Results: Our models demonstrated good to excellent performance on internal test, with average area under the curve (AUC) values of 0.91, 0.93, and 0.96 for cutoffs ≥ 5, ≥ 15, and ≥ 30 at data granularity of 1 s, respectively. Both sensitivity (0.76, 0.84, 0.89) and specificity (0.87, 0.86, 0.90) ranged from good to excellent across three cutoffs. Positive predictive values (PPV) ranged from excellent to fair (0.97, 0.83, 0.66), and negative predictive values (NPV) ranged from low to excellent (0.43, 0.87, 0.98). Model performance on external test slightly dropped compared to internal test, but still achieved good to excellent AUC above 0.80 across all data granularity and all the three cutoffs. Data granularity of 300 s led to a reduction in performance metrics across all cutoffs.

Conclusion: Our models demonstrated superior performance across all three AHI cutoff thresholds compared to existing large sleep apnea screening models, even when considering varying SpO2 data granularity. However, lower data granularity was associated with decreased screening performance, indicating a need for further research in this area.

Purpose: The effect of various sleep traits on the risk of lung cancer differs among pre-existing studies. This study aims to systematically review and synthesise the association between sleep duration and insomnia with the incidence of lung cancer.

Methods: PubMed, Embase and The Cochrane Library were searched from inception to 23 April 2023 for observational studies examining the effect of sleep quantity or insomnia on lung cancer incidence. We pooled maximally-adjusted hazard ratios and odds ratios separately using random effects inverse variance weighted models. The risk of bias of observational studies was assessed using the Newcastle-Ottawa Scale.

Results: We included 11 observational studies with a pooled cohort of 5,049,141 patients. The mean age of the patients was 49.5 ± 17.7 years, and 51.4% were males. The risk of bias ranged from low-moderate. Individuals who slept for a shorter or longer duration than the reference range of sleep per night showed an increased risk of lung cancer by 11% (HR:1.11; 95%CI:1.00-1.23) and 16% (HR:1.16; 95%CI:1.06-1.27) respectively. Furthermore, individuals with insomnia symptoms had a 9% greater risk of lung cancer than those without symptoms (HR:1.09; 95%CI:1.05-1.13).

Conclusion: This study suggests that insufficient sleep, excessive sleep and insomnia may be associated with an increased risk of lung cancer. Physicians should be mindful of this association and encourage healthy sleep practises among patients. Given the observed heterogeneity among some pre-existing studies, future research with longer periods of follow-up, greater control for covariates and objective testing of sleep parameters may add value to this topic.

Aim: In patients with obstructive sleep apnoea (OSA), the benefits of continuous positive airway pressure (CPAP) therapy are increased for every additional hour of daily CPAP usage. However, the data of predictors of extensive usage is scarce, if any. Therefore, we evaluated potential predictors affecting extensive treatment usage.

Methods: In this retrospective study, we compiled an institutional cohort of consecutive patients diagnosed with who started CPAP therapy 1999-2022 and were included in a wireless telemonitoring system in May 2022 (N = 14,394). Patients using CPAP device ≥ 9 h/d were stratified into a younger (< 65 years; N = 124) and an older group (≥ 65 years; N = 131).

Results: We found 255 patients (male 61%) eligible for our study, with a median age of 65 (interquartile range, IQR 55-73) years, and mean body mass index (BMI) of 36 ± 6.9 kg/m². Median CPAP use was 10 h/d (IQR 10-11). BMI and depressive symptoms (DEPS) in the younger group were higher than in the older group (37.9 ± 7 vs. 34.6 ± 6.4 kg/m², p < 0.001 and 11 (IQR 5-20) vs. 7 (IQR 5-14), p = 0.01, respectively). During follow-up, the BMI of the younger group increased (39.9 ± 12.5 kg/m² vs. 37.9 ± 7 kg/m², p = 0.009). DEPS values decreased in the younger group and became comparable between the groups. In multivariate models, the baseline BMI independently predicted extensive CPAP use among the younger age group, and the mask leak among the older group.

Conclusion: BMI at baseline in the younger and mask leak in the older group could be independent predictive factors for extensive use of CPAP.

Purpose: To explore the influence of sleep conditions and sleep hygiene behaviors in early pregnancy on gestational diabetes mellitus (GDM) development.

Methods: This 1:1 propensity-score matched study included 1,216 pregnant women divided into GDM and control groups based on diagnosis via the oral glucose tolerance test at 24-28 gestational weeks. Sleep conditions and hygiene behaviors were evaluated using structural questionnaires, including the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Sleep Hygiene Practice Scale. Univariate and multivariate logistic regression analyses and Spearman's correlation were conducted to identify the associations.

Results: After adjusting for baseline clinical characteristics, women with GDM were more likely to have poor sleep quality (adjusted odds ratio [AOR] = 1.585, 95% confidence interval [CI]: 1.261-1.992) and higher scores for subjective sleep quality, latency, duration, efficiency, and sleep disturbances (all P < 0.01). Mild sleepiness (AOR = 1.311, 95% CI: 1.012-1.699) and worrying about not being able to fall asleep (AOR = 1.123, 95% CI: 1.005-1.255) were more likely to occur in the GDM group. Sleep quality and hygiene behaviors such as sleep-irrelevant activities, staying in bed after waking up, weekend catch-up sleep, and overeating before bedtime were significantly correlated with gestational diabetes variables.

Conclusion: Poor sleep conditions and specific sleep hygiene behaviors in early pregnancy may be independent risk factors for GDM. This suggests that sleep assessment and behavior education can be used as new approaches for the early implementation of surveillance and prevention of GDM.

Background: As the most common sleep disorder, chronic insomnia disorder (CID) has become a global health burden to the public. However, it remains unclear about the pathogenesis of this disease. Epigenetic changes may provide important insights into the gene-environment interaction in CID. Therefore, this study was conducted to investigate the DNA methylation pattern in CID and reveal the epigenetic mechanism of this disease.

Methods: In this study, whole blood DNA was extracted from 8 CID patients (the CID group) and 8 healthy controls (the control group), respectively. Besides, genome-wide DNA methylation was detected by Illumina Human Methylation 850 K Beadchip. Moreover, the sleep quality and insomnia severity were evaluated by the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI), respectively.

Results: A total of 369 differentially methylated positions (DMPs) and 23 differentially methylated regions (DMRs) were identified between the CID and control groups. LHX6 was identified as the most important differentially methylated gene (DMG). The Gene Ontology (GO) analysis results corroborated that DMPs were significantly enriched in 105 GO terms, including cell signaling, homogenous cell adhesion of plasma membrane adhesion molecules, nervous system development, cell adhesion, and calcium ion binding. In addition, it was demonstrated that DMPs were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including the hippo signaling pathway, Ras signaling pathway, and vitamin B6 metabolism. The DMR-related GO analysis results revealed the positive regulation of protein kinase activities.

Conclusions: DNA methylation plays a critical role in the development of CID, and LHX6 is validated to be an important DMG.

Purpose: Sleep apnea headache can be defined as a persistent, widespread, throbbing headache that occurs recurrently, is not accompanied by any additional symptoms after waking up, and usually resolves within four hours. Diagnosis of the condition requires confirmation through polysomnography with an apnea-hypopnea index of at least 5, indicating the presence of obstructive sleep apnea syndrome (OSAS). While sleep apnea headaches are common in 10-15% of individuals with OSAS, morning headaches are experienced by 5% of this population. The aim of this study is to examine both polysomnographic and clinical features associated with sleep apnea headache in individuals confirmed to have OSAS by polysomnography.

Method: The study was conducted in the sleep center of University of Health Science, Erenköy Mental and Nervous Disease Training and Research Hospital. We have examined the clinical and polysomnographic data of the patients with sleep apnea headache (SAH) diagnosed according to IHS-3 criteria retrospectively and grouped the patients as mild, moderate and severe OSAS. Patients with morning headache except sleep apnea headache and under PAP titration treatment were excluded. The differences between the sleep macro structures of patients with (WSAH) and without sleep apnea headache (WOSAH) were examined.

Results: The WSAH group consisted of 384 participants and the control group (WOSAH) consisted of 294 participants The mean age was 46.29 ± 12.18 and 45.08 ± 12.62 years, respectively. Patients in the WSAH group had significantly higher scores on the Epworth Sleepiness Scale (ESS) (p = 0.004) and higher periodic limb movement index (PLMI) (p = 0.014) compared to the WOSAH group. WSAH patients exhibited shorter wake times after sleep onset (WASO) and lower scores on the sleep quality index, in contrast to WOSAH patients. Additionally, within the WSAH group, there was a negative correlation between age and several sleep parameters, including total sleep parameters. A positive correlation was observed between sleep duration (p = 0.009), waking up after sleep (p = 0.043), sleep efficiency (p = 0.001) and apnea-hypopnea index (AHI) (p = 0.018). Additionally, ESS scores were positively correlated with AHI and total awake time (p = 0.000 and p = 0.008, respectively), while negatively correlated with stage N3 sleep percentage and mean minimum oxygen level (p = 0.001 and p = 0.020, respectively) in the WSAH group.

Conclusion: The causes and possible mechanisms of sleep apnea headache are not fully clarified and the underlying processes are not fully understood. Sleep apnea headaches appear to be related to disturbances in nocturnal sleep. Dysregulation in regions that modulate sleep and nociception may be one possible mechanism.

Objective: To assess the association between obstructive sleep apnoea (OSA) and postoperative complications in patients after coronary artery bypass graft (CABG).

Methods: PubMed, Embase, Web of Science and Scopus databases were explored to identify relevant observational studies that reported incidences of OSA in CABG patients, and assessed OSA using standard objective methods such as polysomnography (PSG). The primary outcomes of interest were risk of major adverse cardiac and cerebrovascular events (MACCE) and all-cause mortality. Pooled effect sizes were reported as odds ratio (OR) with 95% confidence intervals.

Results: Twelve studies were included. All studies, except one, had a prospective cohort design. CABG patients with OSA had increased risk of MACCE (OR 1.71, 95% CI: 1.16, 2.53), myocardial infarction (MI) (OR 2.21, 95% CI: 1.19, 4.13), pulmonary complications (OR 1.86, 95% CI: 1.03, 3.38), renal complications (OR 8.14, 95% CI: 2.07, 32.1), heart failure (OR 1.86, 95% CI: 1.19, 2.89) and need for revascularization (OR 2.80, 95% CI: 1.01, 7.75). However, risk of all-cause mortality (OR 1.63, 95% CI: 0.75, 3.52) was comparable in all patients.

Conclusion: This study showed that OSA significantly correlates with the increased risk of major adverse events. Our results indicate that recognizing and managing OSA in CABG patients is crucial for mitigating associated risks.