Sleep and Breathing最新文献

Background: Polysomnography (PSG) is resource-intensive but remains the gold standard for diagnosing Obstructive Sleep Apnea (OSA). We aimed to develop a screening tool to better allocate resources by identifying individuals at higher risk for OSA, overcoming limitations of current tools that may under-diagnose based on self-reported symptoms.

Methods: A total of 884 patients (490 diagnosed with OSA) were included, which was divided into the training, validation, and test sets. Using multivariate logistic regression analyses, we developed a scoring system incorporating male sex, age, sawtooth pattern, area under the inspiratory flow-volume curve (AreaFI), and neck circumference to objectively identify patients at higher risk of OSA. Sensitivity and specificity were evaluated using area under the curve (AUC) metrics. The M-APNE Score was compared to other non-symptom-based tools, the No-Apnea Score and the Symptomless Multivariable Apnea Prediction (sMVAP) model, using the Delong test.

Results: The M-APNE Score showed sensitivity rates of 79.3% in the training set, 70.8% in the test, and 80% in the validation set. ROC analysis for M-APNE score yielded AUCs of 0.82 in the training, 0.76 in the test, 0.82 in the validation set. The discriminative accuracy of M-APNE Score were found to be better than the No-Apnea Score (AUC = 0.82 vs. 0.76, p < 0.001) and the sMVAP (AUC = 0.82 vs. 0.75, p = 0.001) in the training set. Hosmer Lemeshow test indicated good calibration for M-Apne Score (p = 0.46).

Conclusions: The M-APNE Score is a robust and objective tool for OSA screening, potentially reducing classification errors and improving accuracy.

Background: Fatigue, sleep disorders, and daytime sleepiness are interconnected, posing significant risks to occupational health and workplace safety. However, the literature on their relationships remains fragmented, with notable gaps, particularly concerning working populations. This descriptive cross-sectional study aimed to evaluate sleep quality (SQ), daily sleep time in hours (DST), daytime sleepiness, fatigue levels among employees in an automotive workplace, and their interrelationships.

Methods: This study assessed fatigue, DST, SQ, and daytime sleepiness (DTS) among employees aged 21-51 years working under the same conditions. Data were collected using questionnaires and two validated scales: the Check Individual Strength Scale (CIS) for fatigue and the Epworth Sleepiness Scale (ESS) for excessive daytime sleepiness.

Results: None of the Check Individual Strength Scale (CIS), or SQ points, mean values or DST hours values significantly differ due to any sociodemographic independent variables. Epworth Sleepiness Scale (ESS) points mean values differ significantly due to BMI values. However, statistically significant relationships were identified among CIS, ESS, SQ points, and DST hours. Additionally, a positive correlation was observed between ESS and CIS scores. These findings suggest reciprocal effects among fatigue, SQ, DST, and daytime sleepiness.

Conclusion: While sleep problems cause fatigue also chronic fatigue syndrome may be the reason of worse SQ. Further research is necessary to emphasize the importance of addressing the interplay between fatigue, excessive daytime sleepiness, SQ, and DST in hours to improve workplace safety and employee well-being.

Background and objective: There is no satisfactory treatment for obstructive sleep apnea (OSA) in patients with interstitial lung disease (ILD) because of poor tolerance of positive airway pressure (PAP) therapy. Supplemental oxygen therapy has been shown to reduce hypoxemia and is well tolerated in patients with ILD. However, little is known about the effect of nocturnal oxygen supplementation (NOS) on OSA in patients with ILD. In this study, we evaluated one night of oxygen therapy in ILD patients with OSA.

Methods: Forty-one patients with fibrotic ILD and OSA were randomized to receive supplemental oxygen or air for one night each in a crossover design separated by a washout period of one week. Polysomnography was performed, and sleep-disordered breathing, nocturnal desaturation, sleep architecture, and cardiovascular reactions were monitored.

Results: During nights with sham oxygen, the median (interquartile range) apnea-hypopnea index (AHI) was 14.1/h (10.4/h-24.1/h). The percentage of patients in the N3 sleep stage (N3%) was 19.5% (14.0-31.2%). NOS significantly decreased the AHI by a median of 9.3/h (95% CI, 7.6/h-14.4/h; P < 0.001), increased N3% by 4.4% (95% CI, 0.3-10.1%; P = 0.049), and lowered the sleep stage change index by 1.6/h (95% CI, 0.0/h-4.8/h; P = 0.036). NOS improved the oxygen desaturation index (ODI) by -8.8/h (95% CI, -13.4/h to -5.9/h; P < 0.001) and the mean SpO₂ by 3.0% (95% CI, 2.6-4.5%; P < 0.001). The mean heart rate during sleep was reduced with the NOS; however, total sleep time and nocturnal blood pressure did not change.

Conclusions: In patients with OSA and ILD, one night of oxygen therapy significantly improved sleep-disordered breathing, sleep architecture, nocturnal oxygenation, and heart rate. NOS may be a therapeutic option for ILD patients with OSA.

Background: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA, our goal is to investigate the molecular significance of the condition. Machine learning is a useful approach to understanding complex gene expression data to find biomarkers for the diagnosis of OSA.

Methods: Differentially expressed analysis for OSA and DM data sets obtained from GEO were carried out firstly. Then four machine algorithms were used to screen candidate biomarkers. The diagnostic model was constructed based on key genes, and the accuracy was verified by ROC curve, calibration curve and decision curve. Finally, the CIBERSORT algorithm was used to explore immune cell infiltration in OSA.

Results: There were 32 important genes that were considered to be related both in OSA and DM datasets by differentially expressed analysis. Through enrichment analysis, the majority of these genes are enriched in immunological regulation, oxidative stress response, and nervous system control. When consensus characteristics from all four approaches were used to predict OSA diagnosis, STK17A was thought to have a high degree of accuracy. In addition, the diagnostic model demonstrated strong performance and predictive value. Finally, we explored the immune cells signatures of OSA, and STK17A was strongly linked to invasive immune cells.

Conclusion: STK17A has been discovered as a gene that can differentiate between individuals with OSA and DM based on four machine learning methods. In addition to offering possible treatment targets for DM-induced OSA, this diagnostic approach can identify high-risk DM patients who also have OSA.

Background: Our aim was to determine the effect of obstructive sleep apnea syndrome (OSAS) risk on sialorrhea in patients with Parkinson's disease (PD).

Methods: A total of 75 patients with PD (mean age 66.36 ± 8.07) were included. Sialorrhoea was evaluated using the "Sialorrhoea Clinical Scale for Parkinson's Disease" and OSAS risk was determined using the STOP-Bang questionnaire. Diurnal and nocturnal sialorrhoea, drooling severity, speech impairment, eating impairment frequency of drooling, and social discomfort were evaluated. Patients were classified as having low, moderate, or high risk of OSAS. One-way analysis of variance, Tukey's multiple comparison test, Kruskal-Wallis test, Bonferroni-Dunn tests, and Fischer's exact test were used to compare groups according to the normality of the data.

Results: Patients were classified as low risk (n = 10), intermediate risk (n = 29) and high risk (n = 36). The clinical characteristics were similar in all risk groups. The highest rate of nocturnal sialorrhea was observed in all risk groups. The lowest-risk group scored 4.30 ± 3.09, whereas the intermediate- and high-risk groups scored 4.21 ± 4.46, 6.94 ± 4.81 respectively for sialorrhea (p = 0.034). A significant difference in sialorrhea between the groups was found in the intermediate and high-risk groups (p = 0.034).

Conclusion: This study showed that sialorrhea changes were significant in patients with PD in the intermediate-and high-risk OSAS groups. It may be suggested that sialorrhoea be assessed and included in the treatment program in patients at high risk of OSAS or that PD patients with high levels of sialorrhoea should be tested for OSAS. Patients may benefit from treatment methods that address both conditions.

Purpose: Obstructive sleep apnea-hypopnea syndrome (OSAHS) is the most common sleep-related breathing disorder. Longer term, repeated episodes of hypercapnia and hypoxemia during sleep are associated with inflammatory and atherosclerosis-related factors. The aim of this study was to explore the effect of continuous positive airway pressure (CPAP) therapy on cerebral vasoreactivity and early atherosclerosis in patients with severe OSAHS.

Methods: Forty-one patients with severe OSAHS were enrolled. The mean follow-up time was 39.8 ± 9.1 months. Cardiovascular risk factors were assessed, and laboratory tests, carotid artery intima-media thickness (CIMT) measurement and cerebrovascular reserve capacity (CRC) measurement were performed. After the baseline examination, 28 patients received CPAP therapy (treated group), which was not available for 13 patients (untreated group). Parameters were compared before and after treatment, between treated and untreated patients.

Results: Cardiovascular risk factors, baseline polysomnographic parameters, laboratory values, CIMT and CRC of the two groups were similar at baseline. At the follow-up, CRC did not differ between the two groups, but CIMT was significantly lower in the treated group than in the untreated group (0.73 ± 0.11 mm vs. 0.84 ± 0.21 mm, p = 0.027). The CIMT of both groups increased significantly during the follow-up period (from 0.65 ± 0.11 mm to 0.73 ± 0.11 mm in the treated group, and from 0.69 ± 0.11 mm to 0.84 ± 0.21 mm in the untreated group), but the increase in the treated group was smaller than in the untreated group (0.09 ± 0.09 mm vs. 0.15 ± 0.15 mm).

Conclusion: In patients with severe OSAHS, CPAP treatment significantly reduced the progression of CIMT.

Background: Reduced forced vital capacity (FVC) is associated with morbidity and mortality in individuals with Duchenne muscular dystrophy (DMD). Non-invasive ventilation (NIV) is often prescribed for the treatment of sleep-disordered breathing (SDB), and chronic respiratory insufficiency. Despite the common practice of initiating NIV later in the progression of DMD, the factors influencing FVC subsequent to the commencement of NIV remain unclear.

Objective: To evaluate the demographic, clinical and socioeconomic determinants of FVC% predicted across several cohorts of DMD children and adults prescribed NIV.

Methods: A multicenter retrospective review of individuals with DMD prescribed NIV was performed between February 2016 to October 2020. Patients were identified from three sites: The Hospital for Sick Children, Canada; Rady Children's Hospital San Diego, USA; and University of California San Diego Health, USA. Multivariate regression analysis was performed to determine factors that influence FVC.

Results: Fifty-nine male patients with DMD prescribed NIV (mean ± SD for age and BMI was 20.1 ± 6.7 years and 23.8 ± 8.8 kg/m²) were included. Following multivariate analysis, a lower FVC% predicted was associated with older age (β = -1.44, p = 0.001), presence of scoliosis (β = -16.94, p = 0.002), absent deflazacort prescription (β = 14.43, p = 0.009), and use of in-ex sufflator (β = -39.73, p < 0.001), respectively.

Conclusion: In our study, several factors were associated with reduced FVC% predicted in a DMD population using NIV. Future, prospective, longitudinal studies are imperative to comprehend the trajectory of FVC% predicted over time in individuals with DMD using NIV.

Purpose: The effect of allergic rhinitis (AR) on autonomic nervous system in patients with obstructive sleep apnea (OSA) remains unclear. We utilized heart rate variability (HRV) analysis to assess cardiac autonomic activity in patients with OSA, comparing those with and without allergic rhinitis (AR).

Methods: We enrolled 182 patients who visited our sleep clinic complaining of habitual snoring or apnea during sleep. All patients underwent full-night polysomnography (PSG) and multiple allergen simultaneous tests. We calculated the HRV extracted from the electrocardiography of the PSG. Participants were divided into a normal group and an AR group, and HRV indices were compared according to OSA severity in each group.

Results: The low-frequency (LF) to high-frequency (HF) ratio (LF/HF; r = 0.336, p < 0.001), LF normalised unit (LFnu; r = 0.345, p < 0.001), and HFnu (r = -0.345, p < 0.001) were significantly correlated with the apnea-hypopnea index. The HRV index comparison between non-severe and severe OSA in the normal group showed significant differences in LFnu (64.7 ± 12.5 in non-severe and 72.4 ± 11.7 in severe, p < 0.001), LF/HF (2.3 ± 1.6 in non-severe and 3.3 ± 2.0 in severe, p = 0.002), and HFnu (35.3 ± 12.5 in non-severe and 27.6 ± 11.7 in severe, p < 0.001). However, in the AR group, LFnu (p = 0.648), LF/HF (p = 0.441), and HFnu (p = 0.648) were comparable between non-severe and severe OSA.

Conclusion: Considering that LFnu, HFnu, and LF/HF represent sympathetic activity, parasympathetic activity, and sympathovagal balance, respectively, AR may attenuate the sympathetic predominance and sympathovagal imbalance associated with cardiovascular morbidity in severe OSA.

Background: Obstructive sleep apnea has been associated with various urinary system diseases, including prostatic hyperplasia and nocturia. Recently, it has been linked to prostate cancer. This study investigated the relationship between the apnea hypopnea index, prostate-specific antigen (PSA) levels, and changes in PSA.

Methods: A total of 673 male patients who received portable sleep monitoring were assessed. All participants underwent thorough health assessments, including PSA testing. Individuals in Study 1 were divided into OSA and control groups based on an REI (Respiratory event index) ≥ 15 events/h. In Study 2, 176participants from the initial study were retested for PSA after three years.

Results: In Study 1, patients with OSA had significantly higher ln-transformed PSA levels than controls (P < 0.05). Ln-transformed PSA levels showed a positive correlation with the REI (r = 0.184, p = 0.015). In Study 2, after three years, the ln-transformed PSA level increased by 0.13 ng/ml in the OSA group, while it decreased by -0.05 ng/ml in the control group. The change in ln-transformed PSA was significantly higher in patients with OSA (p = 0.014). Even after adjusting for age, body mass index (BMI), smoking, hypertension, and diabetes, REI remained a significant predictor of PSA level changes (β = 0.226, 95% CI = 0.001-0.009; p = 0.008).

Conclusions: This study highlights the close relationship between REI and PSA levels in individuals with obstructive sleep apnea, indicating that REI is an independent risk factor for PSA levels. Obstructive sleep apnea may be associated with the incidence of prostate cancer.