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Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear. We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over three subsequent nights. Scores on OSA indices—namely, the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into three groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons, and their correlations were examined by Pearson’s correlation coefficient. The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All three groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment, compared with the hospital-based assessment. The percentage of supine sleep time (∆Supine%) exhibited a significant but weak to moderate positive correlation with each of the OSA indices. A significant but weak-to-moderate correlation between the ∆Supine% and ∆Rx index was still observed among the patients with high sleep efficiency (≥80%), who could reduce the effect of short sleep duration, leading to underestimation of the patients’ OSA severity. The high supine percentage of sleep may cause OSA indices’ overestimation in the hospital-based examination. Sleep recording at home with patch-type wearable devices may aid in accurate OSA diagnosis.

Background Symptoms of obstructive sleep apnoea (OSA) overlap significantly with those of psychiatric disorders, making accurate diagnosis of OSA challenging within psychiatric settings. Diagnosing OSA in psychiatric patients is crucial because untreated OSA can exacerbate psychiatric symptoms, reduce treatment efficacy, and impair overall quality of life. This study aimed to determine the diagnostic accuracy of a readily accessible procedure for psychiatric patients in a real-world clinical setting by comparing the Somnocheck micro CARDIO ® (SCm) portable cardiorespiratory polygraphy device with the gold standard polysomnography (PSG). Methods This observational cohort study included consecutive psychiatric patients at intermediate to high risk for OSA based on screening with the STOP-Bang questionnaire, admitted to a single tertiary care centre between June 1, 2016 and December 31, 2022. The Apnoea-Hypopnoea-Index (AHI), Apnoea-Index (AI), Oxygen-Desaturation-Index (ODI), and minimum oxygen saturation were measured sequentially by SCm and PSG. Results A total of 57 patients were analysed (median age 62.0 [Interquartile Range (IQR), 51.5–72.5] years; 34 [59.6%] men). Regarding AHI, no significant differences (AHI measured by PSG, median, 16.6 [IQR, 6.2–26.7] vs. AHI measured by SCm, median, 14.9 [IQR, 10.0-22.8]; p  = 0.812; r  = 0.71) were found between SCm and PSG. AI, ODI and minimum oxygen saturation differed significantly between SCm and PSG. Using optimised cut-off values (any OSA: AHI SCm ≥ 9.25), SCm showed high sensitivity (0.894) and high specificity (0.800) for the diagnosis of OSA, with an area under the receiver operating characteristic curve of 0.877. Conclusions This study found that the SCm portable device was accurate in identifying psychiatric patients with OSA. AHI measurement by SCm provided reliable diagnostic performance in comparison with the gold standard polysomnography. These findings support the integration of polygraphic measurements into the routine sleep assessment of psychiatric patients. Early and accurate diagnosis of OSA in this population can significantly improve the management of both sleep disorders and psychiatric conditions, potentially enhancing overall treatment outcomes and quality of life for these patients.

Many patients with obstructive sleep apnoea (OSA) remain undiagnosed and thus untreated, and in part this relates to delay in diagnosis. Novel diagnostic strategies may improve access to diagnosis. In a multicentre, randomised study, we evaluated time to treatment decision in patients referred for suspected OSA, comparing a mandibular movement (MM) monitor to respiratory polygraphy, the most commonly used OSA detection method in the UK. Adults with high pre-test probability OSA were recruited from both northern Scotland and London. 40 participants (70 % male, mean±SD age 46.8 ± 12.9 years, BMI 36.9 ± 7.5 kg/m2, ESS 14.9 ± 4.1) wore a MM monitor and respiratory polygraphy simultaneously overnight and were randomised (1:1) to receive their treatment decision based on results from either device. Compared to respiratory polygraphy, MM monitor reduced time to treatment decision by 6 days (median(IQR): 13.5 (7.0–21.5) vs. 19.5 (13.7–35.5) days, P = 0.017) and saved an estimated 29 min of staff time per patient.

Computational fluid dynamics (CFD) modelling has made significant contributions to the analysis and treatment of obstructive sleep apnoea (OSA). While several investigations have considered the flow field within the airway and its effect on airway collapse, the effect of breathing on the pharynx region is still poorly understood. We address this gap via a combined experimental and numerical study of the flow field within the pharynx and its impacts upon airway collapse. Two 3D experimental models of the upper airway were constructed based upon computerised tomography scans of a specific patient diagnosed with severe OSA; (i) a transparent, rigid model for flow visualisation, and (ii) a semi-flexible model for understanding the effect of flow on pharynx collapse. Validated simulation results for this geometry indicate that during inhalation, negative pressure (with respect to atmospheric pressure) caused by vortices drives significant narrowing of the pharynx. This narrowing is strongly dependent upon whether inhalation occurs through the nostrils. Thus, the methodology presented here can be used to improve OSA treatment by improving the design methodology for personalised, mandibular advancement splints (MAS) that minimise OSA during sleep.

Obstructive sleep apnea syndrome (OSAS) is a chronic disorder characterized by recurring episode obstruction and collapse of upper airways during sleep, leading to hypoxia and sleep disruption. OSAS is commonly associated with an increased prevalence of hypertension. The underlying mechanism in OSA with hypertension is related to intermittent hypoxia. This hypoxia induces endothelial dysfunction, overactivity of sympathetic effects, oxidative stress, and systemic inflammation. Hypoxemia triggers the sympathetic process's overactivity, leading to the development of resistant hypertension in OSA. Thus, we hypothesize to evaluate the association between resistant hypertension and OSA. The PubMed, ClinicalTrails.gov, CINAHL, Google Scholar, Cochrane Library, and Science Direct databases were searched from 2000 to January 2022 for studies demonstrating the association between resistant hypertension and OSA. The eligible articles underwent quality appraisal, meta-analysis, and heterogeneity assessment. This study comprises seven studies, including 2,541 patients ranged from 20 to 70 years. The pooled analysis of six studies demonstrated that OSAS patients with a history of increased age, gender, obesity, and smoking status are at an increased risk for resistant hypertension (OR: 4.16 [3.07, 5.64], :0%) than the non-OSAS patients. Similarly, the pooled effect demonstrated that patients with OSAS were at an increased risk of resistant hypertension (OR: 3.34 [2.44, 4.58]; :0%) than the non-OSAS patients when all associated risk factors were adjusted using multivariate analysis. This study concludes that OSAS patients with or without related risk factors demonstrated increased risk for resistant hypertension.

OSA is a heterogeneous disease with variable physio-pathological and clinical manifestations, and it is associated with numerous co-morbidities (1). It is a chronic inflammatory disease with a low degree of activity (2), in which the microbiome is now widely considered to play a role. In the last few decades, research into the microbiome has rapidly evolved and has become a hot topic in basic research, both pre-clinical and clinical. Some recent studies have demonstrated that the gut microbiota (GM), situated in the human gastrointestinal tract and consisting of bacteria, viruses, fungi and protozoa, serves important functions regarding the regulation of the immune and metabolic systems and cerebral physiopathology. It is an example of a dynamic complex system, connected to the organism on a cellular, metabolic, immune and nervous level, a sophisticated network regulated by delicate internal and external equilibria (3)(4). The gut microbiota (GM) is composed of microbial symbionts, commensal or mutualistic but also potentially harmful (i.e. pathobionts), whose equilibrium (homeostasis) is crucial to the modulation of various functions and the aetiology of numerous diseases (5). Two bacterial phyla, Bacteroidetes and Firmicutes, account for 90% of the groups present in the human intestine and are essential for the maintenance of intestinal homeostasis (6)(7). A growing scientific literature supports the existence of bidirectional interaction that unfolds via hormonal, neural and immunological pathways between the brain and the intestine, indicating that this relationship plays a fundamental role in modulating cerebral physiopathology via neuronal development and control of synaptic plasticity (8-9-10-11). Dysbiosis of the microbiota entails alteration of either the bacterial composition, with a reduction in bacterial diversity, or a proliferation of pathological bacteria that triggers the release of proinflammatory cytokines. Dysbiosis entails the release of pathological bacterial lipopolysaccharides (LPSs), called PAMPs (Pathogen Associated Molecular Patterns). PAMPs reduce the gene expression of proteins associated with the \"tight junctions\" of the intestinal epithelium (zonulin-1, occludin, claudin) via the activation of the nuclear factor NF-κB, while the pro-inflammatory cytokines IL-1β, IL-6 and TNF-α are responsible for \"minimal persistent inflammation\" (12-13-14). Experimental studies of model rats have shown that intestinal dysbiosis is implicated in the physio-pathological mechanisms of OSA (15-16-17). Dysbiosis alters the synthesis and degradation of neurotransmitters and the regulation of entero-endocrine signalling pathways that communicate with the central nervous system (CNS) via neurotransmission (18)(19).Here we summarise the possible molecular mechanisms underlying OSA-microbiome interactions and discuss how various factors interact with gut dysbiosis to influence OSA. The physiopathological mechanisms underlying OSA are intermittent nocturnal hypoxia (IH) and sleep fragmentation (SF), which can induce dysbiosis of the gut microbiota (GM), compromise the intestinal barrier, alter intestinal metabolites and generate neuroinflammation (20-21-22). These mechanisms, once activated, lead to secondary cellular oxidative stress, sympathetic activation and systemic inflammation (23-24-25-26).The effects of the microbiota on the brain There is abundant scientific evidence that on the intestinal level, thanks to their ability to produce molecules and neurotransmitters, bacteria can act directly on the CNS via the vagus nerve, the neuroendocrine system and bacterial metabolites (27)(28). Dinan et al. demonstrated in animal models that the GM can influence the physiology of the brain by regulating neurotransmission and synaptogenesis. In their study, they characterised the neurobiochemical profile of the forebrains of mice during three key phases of postnatal development, which coincide with the formation of the gut microbiota. They demonstrated that the molecules derived from intestinal microbes are able to cross the blood-brain barrier (BBB) and that the intestinal microbiome can thus influence cerebral neurodevelopmental trajectories (29)(30). A recent review and meta-analysis observed increased levels of biomarkers of intestinal barrier dysfunction in patients with OSA, and found that these markers correlate with polysomnographic parameters indicating the seriousness of OSA (31). Previous experimental studies performed in the laboratory using rodent-based OSA models had already suggested that the absorption and barrier functions that regulate the intestinal epithelium are sensitive to the intensity of intermittent hypoxia (IH) and that the depth and intensity of IH can directly compromise the integrity of the intestinal epithelium, thereby altering \"tight junctions\" and increasing intestinal permeability and the inflammatory process (32)(33).The systemic inflammatory mechanisms generated by intestinal dysbiosis that determine the neuroinflammatory response are described below (34-35-36). In detail, signal-ligands released by intestinal gram-negative bacteria during dysbiosis generate molecular structures such as lipopolysaccharides, called Pathogen-Associated Molecular Patterns (PAMPs). PAMPs bind to Pattern Recognition Receptors (PRRs) including Toll-Like Receptors (TLRs), which are found on Antigen-Presenting Cells (APCs) such as dendritic cells, macrophages and T lymphocytes. This bond between PAMPs and PRRs activates the APCs, which are involved in the epigenetic, immunological and metabolic reprogramming of the entire organism. At the same time, this activation of receptors is responsible for the release of inflammatory cytokines that reduce the gene expression of proteins associated with the tight junctions of the intestinal epithelium (37)(38). This in turn increases intestinal permeability (involving zonulin-1, occluding and claudin) and the release of the pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) responsible for systemic inflammation (39). In addition to the PAMP/TLR4 signalling pathways, PAMPs can activate another inflammatory mechanism by binding to dendritic cells (DCs), which produce the interleukins IL-1 and IL-18. These can generate biologically active molecules such as the inflammasome NLRP3. Inflammasomes modulate a multitude of signals causing chronic pro-inflammatory responses (40-41-42). Experimental studies conducted in the laboratory on animal models have demonstrated the role of nocturnal intermittent hypoxia (IH) and sleep fragmentation (SF) in causing intestinal dysbiosis, which in turn can intensify the development of the physio-pathological mechanisms of OSA and cause cardiorespiratory and metabolic co-morbidity (43-44-45).Intestinal bacteria produce mainly gamma acid aminobutyric acid (GABA), dopamine (DA), norepinephrine (NE), serotonin (5-HT) and histamine in order to communicate with the enteric nervous system (ENS) (46), but also intermediate compounds such as short-chain fatty acids (SCFAs) (47), tryptophan (48) and secondary bile acids (49). The signals generated by these neurotransmitters and molecules are transported to the brain via the fibres of the vagus nerve (VN). In response, the brain sends return signals to the enterochromaffin cells (ECCs) in the intestinal wall and to the immune system of the intestinal mucosae, again via the fibres of the vagus nerve (50). The activation of the VN improves the integrity of the intestinal wall, reduces peripheral inflammation and inhibits the release of pro-inflammatory cytokines such as IL-1β, IL-6 and TNF-α (51). The signals generated by the hypothalamus reach the pituitary and adrenal glands and communicate with the ECCs via the hypothalamic-pituitary-adrenal axis (HPA) (52). The complex control of entero-endocrine signalling and immune responses maintains the gut microbiota in a state of equilibrium. Although the vagus nerve is in contact with all the layers of the intestinal wall, its fibres do not cross the intestinal wall itself and thus are not in direct contact with the gut microbiota (53). The signals reach the microbiota via neurons ranging in number between 100 and 500 million belonging to the enteric nervous system (ENS). Although the ENS is associated with the VN, it functions independently from it. Recent laboratory studies have demonstrated that the ENS is dynamic and continuously changing (54). The neurons of the ENS represent the biggest nervous system in the human body. The neurons connected to the gastrointestinal tract (GIT) possess various chemical and mechanosensitive receptors that interact with regulatory hormones and peptides released by enterochromaffin cells (ECCs), also known as Kulchitsky cells. Although these cells represent just 1% of the epithelial cells of the GIT, they play an important role in maintaining the homeostasis of the GIT (55). To date, 10 different types of ECCs have been characterised. The receptors on these cells are expressed by enteric neurons, but also by the fibres of the vagus nerve, the brainstem and the hypothalamus (56,57). The ENS, also called the \"brain within the gut\" or \"second brain\" (58), is composed of the myenteric plexus and inner submucosal plexus. It is structurally similar to the brain and operates on the basis of a similar \"chemical platform\" (59). The modulation and development of the neurons of the ENS is controlled by the gut microbiota. The embryogenic development of enteric neurons is based on the presence of microbial cells, as shown in studies conducted on mice (60). The role played by the gut microbiota in association with acetylcholine-type neurotransmitters and neuro-regulatory peptides has been highlighted in recent research conducted on animal models. It has been seen that the secretion of Ach can be stimulated by some species of Lactobacillus (61,62). Lactobacillus rhamnosus jB-1 changes the expression of GABA A receptors in the brain

Continuous positive airway pressure (CPAP) has been the standard treatment of obstructive sleep apnoea/hypopnoea syndrome (OSA) for almost four decades. Though usually effective, this treatment suffers from poor long-term compliance. Therefore, the aim of our one centre retrospective study was to assess factors responsible for treatment failure and long-term compliance. Four hundred subsequent patients diagnosed with OSA and qualified for CPAP treatment were chosen from our database and compliance data were obtained from medical charts. Many differing factors kept patients from starting CPAP or led to termination of treatment. Overall, almost half of patients ended treatment during the mean time of observation of 3.5 years. Survival analysis revealed that 25% of patients failed at a median time of 38.2 months. From several demographic and clinical covariates in Cox’s hazard model, only the presence of a mild OSA, i.e., AHI (apnoea/hypopnoea index) below 15/h was a factor strongly associated with long term CPAP failure. The compliance results of our study are in line with numerous studies addressing this issue. Contrary to them, some demographic or clinical variables that we used in our survival model were not related to CPAP adherence.

Background This objective of this study was to diagnose Obstructive Sleep Apnoea (OSA) in pregnant women using Questionnaire-based methods and to determine any association of Sleep-Disordered Breathing (SDB) with Hypertensive Disorder of Pregnancy (HDP). Additionally, the study aimed to identify factors associated with OSA. Methods This case–control study was conducted in department of Obstetrics in tertiary care hospital in Delhi. We Identified SDB using Berlin Questionnaire and Modified Stop-Bang Questionnaire in 100 pregnant women with Hypertension and 100 normotensive controls. We compared the groups using appropriate statistical analysis. Results The mean age of women with HDP (25.46 ± 4.38) was found to be slightly higher than controls (24.13 ± 3.89) ( p value-0.02). Sleep apnoea as depicted by the presence of either high-risk STOP Bang or Berlin score was seen more often in hypertensive women in 45% as compared to controls in 8% ( p value < 0.001). Higher pre-pregnancy weight (58.58 ± 9.77 vs. 53.0 ± 6.59), higher BMI (24.03 ± 5.89 vs. 20.68 ± 1.49), higher mean neck circumference (14.97 vs. 14.27 inches) weight gain more than 11 kg during pregnancy (55.6% vs. 38.2%) were the high-risk factors more commonly associated with SDB as seen in women with OSA in hypertensive women. On logistic regression analysis, the presence of OSA was singularly responsible for development of Hypertension (Odds Ratio–13.014, 95% CI 5.237–32.337) ( p value < 0.001). Conclusion Gestational hypertension appears to be strongly associated with the presence of obstructive sleep apnoea. The recognition and treatment of OSA during pregnancy may lead to improved outcomes.

Obstructive sleep apnoea (OSA) involves impaired upper airway muscle function and is linked to several pathologies including systemic hypertension, daytime somnolence and cognitive decline. Selenium is an essential micronutrient that exerts many of its effects through selenoproteins. Evidence indicates that either deficient or excessive dietary selenium intake can result in impaired muscle function, termed nutritional myopathy. To investigate the effects of selenium on an upper airway muscle, the sternohyoid, rats were fed on diets containing deficient, normal (0.5 ppm sodium selenite) or excessive (5 ppm selenite) selenium for a period of two weeks. Sternohyoid contractile function was assessed ex vivo. Serum selenium levels and activity of the glutathione antioxidant system were determined by biochemical assays. The abundance of three key muscle selenoproteins (selenoproteins -N, -S and -W (SELENON, SELENOS and SELENOW)) in sternohyoid muscle were quantified by immunoblotting. Levels of these selenoproteins were also compared between rats exposed to chronic intermittent hypoxia, a model of OSA, and sham treated animals. Although having no detectable effect on selected organ masses and whole-body weight, either selenium-deficient or -excessive diets severely impaired sternohyoid contractile function. These changes did not involve altered fibre size distribution. These dietary interventions resulted in corresponding changes in serum selenium concentrations but did not alter the activity of glutathione-dependent antioxidant systems in sternohyoid muscle. Excess dietary selenium increased the abundance of SELENOW protein in sternohyoid muscles but had no effect on SELENON or SELENOS. In contrast, chronic intermittent hypoxia increased SELENON, decreased SELENOW and had no significant effect on SELENOS in sternohyoid muscle. These findings indicate that two-week exposure to selenium-deficient or -excessive diets drastically impaired upper airway muscle function. In the sternohyoid, SELENON, SELENOS and SELENOW proteins show distinct alterations in level following exposure to different dietary selenium intakes, or to chronic intermittent hypoxia. Understanding how alterations in Se and selenoproteins impact sternohyoid muscle function has the potential to be translated into new therapies for prevention or treatment of OSA.

Background Sleep disorders are common and associated with multiple metabolic and psychological derangements. Obstructive sleep apnoea (OSA) is among the most common sleep disorders and an inter-relationship between OSA, insulin resistance, obesity, type 2 diabetes (T2DM) and cardiovascular diseases has been established. Prevalence of sleep disorders in Kenyans, particularly in individuals with T2DM is unknown. We thus aimed to determine prevalence of poor quality of sleep (QOS) and high risk for OSA, among persons with T2DM and determine their associations with socio-demographic and anthropometric variables. Methods Utilising a Cross- Sectional Descriptive design, QOS and risk for OSA were determined in a randomly selected sample of patients with T2DM (cases) and an age and sex matched comparison group. The validated Pittsburgh Sleep Quality Index (PSQI) and Berlin Questionnaire (BQ) were used to measure QOS and risk for OSA respectively. Associations between poor QOS, high risk for OSA, and socio-demographic and anthropometric variables in cases were evaluated. Results From 245 randomly selected persons with T2DM attending outpatient clinics, aged over 18 years, 22 were excluded due to ineligibility thus 223 were included in the analysis; 53.8% were females, mean age was 56.8 (SD 12.2) years and mean BMI was 28.8 kg/m 2 (SD 4.4). Among them, 119 (53%, CI 95% 46.5–60.2) had poor QOS and 99 (44% CI 95% 37.8–50.9) were at high risk for OSA. Among 112 individuals in comparison group, 33 (29.5%, CI 95% 20.9–38.3) had poor QOS and 9 (8%, CI 95% 3.3–13.4) had high risk for OSA. Cases had a significantly higher probability for poor QOS [OR 2.76 (95% CI 1.7–4.4))] and high risk for OSA [OR 9.1 (95% CI 4.4–19.0)]. Higher waist circumference was independently associated with a high risk for OSA in cases. Conclusions We demonstrate a high burden of sleep disturbances in patients with T2DM. Our findings may have implications for clinicians to screen for sleep disorders when assessing patients with T2DM and warranting further attention by practitioners and researches in this field.