More Than the Sum of the Respiratory Events: Personalized Medicine Approaches for Obstructive Sleep Apnea

The prevalence of obstructive sleep apnea-hypopnea syndrome in patients with multiple sclerosis: a systematic review and meta-analysis

Objective

Obstructive sleep apnea-hypopnea syndrome is the most common respiratory disorder in patients with multiple sclerosis. The purpose of this meta-analysis was to evaluate the prevalence of OSAHS in MS patients and to analyze their sleep monitoring indicators of patients.

Methods

Online databases such as PubMed, EMBASE, Web of Science, CNKI, and WanFang were used to review the Chinese and English literature about OSAHS in MS patients in detail. Two researchers analyzed the Quality of included studies based on the Quality Assessment of Diagnostic Accuracy Studies. The prevalence and sleep monitoring data were analyzed using STATA 11.0 software. Based on the I2 values, pooled analyses were performed using either random (I2 > 50%) or fixed-effect models (I2 ≤ 50%).

Results

Fourteen articles were selected for the final analysis. Our study shows that different diagnosis methods of OSAHS lead to different incidences. When the screening method was PSG, the incidence of OSAHS in MS patients was 36%; when the method was STOP-BANG, the incidence of OSAHS in MS patients was 26%; when the method was Berlin questionnaire, the incidence of OSAHS in MS patients was 30%. We performed subgroup analyses based on race, age, OSAHS severity, and BMI of patients with MS. The results suggested that the incidence of OSAHS was different in different subgroups of MS patients. In addition, we found that patients with MS generally had poorer sleep monitoring indicators.

Conclusion

The current literature shows that the incidence of OSAHS is higher in MS patients. MS may affect the progression of OSAHS.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=551500, CRD42024551500.

Sleep apnea endotypes and their implications for clinical practise

Obstructive sleep apnea (OSA) is now recognized to be a multifactorial disorder caused by several endotypes that differ between individuals and patient populations. In order to understand the current clinical implications of OSA endotypes, this review aims to examine the current state of play in endotype measurements, endotype modification and their impact on clinical outcomes/prognosis. In summary, the field has developed multiple techniques to measure the endotypes over the last few decades. There is now good proof-of-concept evidence that a priori knowledge of an individual's OSA endotype traits may be useful in helping to guide treatment decisions. However, in order to truly deliver a personalized medicine approach to the treatment of OSA, we need to address critical gaps in: understanding OSA endotype treatment thresholds, and the impact of OSA modification on patient centred outcomes and hard clinical endpoints. Such efforts will benefit from a united, collaborative approach that involve partnerships between academics and consumers (i.e. patients, healthcare providers, industry).

Influence of sleep on physiological systems in atherosclerosis

Sleep is a fundamental requirement of life and is integral to health. Deviation from optimal sleep associates with numerous diseases including those of the cardiovascular system. Studies, spanning animal models to humans, show that insufficient, disrupted or inconsistent sleep contribute to poor cardiovascular health by disrupting body systems. Fundamental experiments have begun to uncover the molecular and cellular links between sleep and heart health while large-scale human studies have associated sleep with cardiovascular outcomes in diverse populations. Here, we review preclinical and clinical findings that demonstrate how sleep influences the autonomic nervous, metabolic and immune systems to affect atherosclerotic cardiovascular disease.

Heterogeneous Effects of Continuous Positive Airway Pressure in Non-Sleepy Obstructive Sleep Apnea on Cardiovascular Disease Outcomes: Post Hoc Machine Learning Analysis of the ISAACC Trial (ECSACT Study)

Rationale: Randomized controlled trials of continuous positive airway pressure (CPAP) therapy for cardiovascular disease (CVD) prevention among patients with obstructive sleep apnea (OSA) have been largely neutral. However, given that OSA is a heterogeneous disease, there may be unidentified subgroups demonstrating differential treatment effects. Objectives: We sought to apply a novel data-drive approach to identify nonsleepy OSA subgroups with heterogeneous effects of CPAP on CVD outcomes within the Impact of Sleep Apnea Syndrome in the Evolution of Acute Coronary Syndrome (ISAACC) study. Methods: Participants were randomly partitioned into two datasets. One for training (70%) our machine-learning model and a second (30%) for validation of significant findings. Model-based recursive partitioning was applied to identify subgroups with heterogeneous treatment effects. Survival analysis was conducted to compare treatment (CPAP vs. usual care [UC]) outcomes within subgroups. Results: A total of 1,224 nonsleepy OSA participants were included. Of 55 features entered into our model, only two appeared in the final model (i.e., average OSA event duration and hypercholesterolemia). Among participants at or below the model-derived average event duration threshold (19.5 s), CPAP was protective for a composite of CVD events (training hazard ratio [HR], 0.46; P = 0.002). For those with longer event duration (>19.5 s), an additional split occurred by hypercholesterolemia status. Among participants with longer event duration and hypercholesterolemia, CPAP resulted in more CVD events compared with UC (training HR, 2.24; P = 0.011). The point estimate for this harmful signal was also replicated in the testing dataset (HR, 1.83; P = 0.118). Conclusions: We discovered subgroups of nonsleepy OSA participants within the ISAACC study with heterogeneous effects of CPAP. Among the training dataset, those with longer OSA event duration and hypercholesterolemia had nearly 2.5 times more CVD events with CPAP compared with UC, whereas those with shorter OSA event duration had roughly half the rate of CVD events if randomized to CPAP.

Positional Treatment of Obstructive Sleep Apnea

Positional sleep apnea (POSA), a distinctive subtype of obstructive sleep apnea, underscores the critical influence of a patient's sleeping position on the severity of their condition. In the management of POSA, compliance with positional therapy (PT) is paramount, as it wields a profound impact on the treatment's efficacy and the overall alleviation of the disease. The advent of new-generation PT devices offers a promising alternative to conventional methods like the tennis ball technique, boasting higher compliance rates and substantial disease alleviation.

Mild-to-moderate obstructive sleep apnea and mortality risk in a general population sample: The modifying effect of age and cardiovascular/cerebrovascular comorbidity

About 5.4%-45.7% of the general population has mild-to-moderate obstructive sleep apnea (mmOSA), which is highly comorbid with cardiovascular and/or cerebrovascular diseases (CBVD). We examined the association between mmOSA and all-cause mortality and the modifying effect of age and CBVD. A total of 1681 adults 20-88 years old from the Penn State Adult Cohort (PSAC) (41.9% male) were followed up for 20.1 ± 6.2 years for all-cause mortality. Mild and moderate OSA were defined as an apnea/hypopnea index (AHI) 5-14.9 and 15-29.9 events/hour, respectively. CBVD was defined as a report of a physician diagnosis or treatment for heart disease and/or stroke. Cox proportional hazards regression models were used to estimate all-cause mortality adjusted for confounders. All-cause mortality risk was significantly increased in the mmOSA group in young and middle-aged adults (<60 years) (HR = 1.59, 95%CI 1.08-2.04) but not in older adults (≥60 years) (HR = 1.05, 95%CI 0.80-1.39). A synergistic effect between mmOSA and CBVD was stronger in those <60 years (HR = 3.82, 95%CI 2.25-6.48 in <60 years vs 1.86 95%CI 1.14-3.04 in ≥60 years). There was an additive effect between moderate OSA and hypertension in <60 but not in those ≥60 years. Mild OSA was associated with all-cause mortality only in the presence of CBVD. Mortality risk is increased in young and middle-aged adults with moderate OSA, whereas the mortality risk associated with mild OSA is elevated only, regardless of age, in the presence of comorbid CBVD. AHI cut-offs warranting treatment of mmOSA may need to be adjusted based on age and comorbidities.

Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"?

Paediatric sleep diagnostics is performed using complex multichannel tests in specialised centres, limiting access and availability and resulting in delayed diagnosis and management. Such investigations are often challenging due to patient size (prematurity), tolerability, and compliance with "gold standard" equipment. Children with sensory/behavioural issues, at increased risk of sleep disordered breathing (SDB), often find standard diagnostic equipment difficult.SDB can have implications for a child both in terms of physical health and neurocognitive development. Potential sequelae of untreated SDB includes failure to thrive, cardiopulmonary disease, impaired learning and behavioural issues. Prompt and accurate diagnosis of SDB is important to facilitate early intervention and improve outcomes.The current gold-standard diagnostic test for SDB is polysomnography (PSG), which is expensive, requiring the interpretation of a highly specialised physiologist. PSG is not feasible in low-income countries or outwith specialist sleep centres. During the coronavirus disease 2019 pandemic, efforts were made to improve remote monitoring and diagnostics in paediatric sleep medicine, resulting in a paradigm shift in SDB technology with a focus on automated diagnosis harnessing artificial intelligence (AI). AI enables interrogation of large datasets, setting the scene for an era of "sleep-omics", characterising the endotypic and phenotypic bedrock of SDB by drawing on genetic, lifestyle and demographic information. The National Institute for Health and Care Excellence recently announced a programme for the development of automated home-testing devices for SDB. Scorer-independent scalable diagnostic approaches for paediatric SDB have potential to improve diagnostic accuracy, accessibility and patient tolerability; reduce health inequalities; and yield downstream economic and environmental benefits.

The Present and Future of the Clinical Use of Physiological Traits for the Treatment of Patients with OSA: A Narrative Review

People with obstructive sleep apnea (OSA) are a heterogeneous group. While many succeed in the treatment of their OSA, many others struggle with therapy. Herein, we discuss how anatomical and physiological factors that cause sleep apnea (OSA traits) impact treatment response and may offer an avenue for more precise care. These OSA traits, including anatomical (upper-airway collapsibility) and physiological (loop gain, airway muscle responsiveness, and arousal threshold) factors, may help determine who can succeed with continuous positive airway pressure, oral appliances, hypoglossal nerve stimulation, or pharmacotherapy. In the future, identifying OSA traits before initiating treatment may help guide the selection of the most effective and tolerable therapy modalities for each individual.

Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that.

Age-related differences in the association of mild-to-moderate sleep apnea with incident cardiovascular and cerebrovascular diseases

BACKGROUND

Mild-to-moderate obstructive sleep apnea (mmOSA) is highly prevalent in the general population. However, studies on its association with incident cardiovascular and/or cerebrovascular disease (CBVD) are limited. We examined the association between mild-to-moderate OSA and incident cardiovascular and/or cerebrovascular (CBVD) in a general population sample, and whether age modifies this association.

METHODS

A total of 1173 adults from the Penn State Adult Cohort (20-88 years) without CBVD or severe OSA at baseline were followed-up after 9.2 (±4.1) years. Incident CBVD was defined based on a self-report of a physician diagnosis or treatment for heart disease and/or stroke. Logistic regression examined the association of mild-to-moderate OSA (AHI 5-29.9) with incident CBVD and the combined effect of mmOSA and MetS on incident CBVD after adjusting for multiple confounders.

RESULTS

Age significantly modified the association between mmOSA with incident CBVD (p-interaction = 0.04). Mild-to-moderate OSA was significantly associated with incident CBVD in adults aged <60 years (OR = 1.74, 95%CI = 1.06-2.88, p = 0.029), but not in adults aged ≥60 years (OR = 0.71, 95%CI = 0.39-1.27, p = 0.247). Even mild OSA (AHI 5-14.9) carried a significant risk for incident CBDV in adults aged <60 years (OR = 1.86, 95%CI = 1.05-3.28, p = 0.032). An additive effect was found between mmOSA and MetS with incident CBVD in those aged <65 years (OR = 3.84, 95%CI = 1.95-7.56, p<0.001).

CONCLUSIONS

The risk of incident CBVD is increased in young and middle-aged but not older adults with mmOSA, which may affect the way we currently diagnose and treat this highly prevalent sleep-related breathing disorder.

The interaction between neuromuscular forces, aerodynamic forces, and anatomical motion in the upper airway predicts the severity of pediatric OSA

Upper airway neuromuscular response to air pressure during inhalation is an important factor in assessing pediatric subjects with obstructive sleep apnea (OSA). The neuromuscular response's strength, timing, and duration all contribute to the potential for airway collapses and the severity of OSA. This study quantifies these factors at the soft palate, tongue, and epiglottis to assess the relationship between neuromuscular control and OSA severity in 20 pediatric subjects with and without trisomy 21, under dexmedetomidine-induced sedation. The interaction between neuromuscular force and airflow pressure force was assessed based on power transferred between the airway wall and airflow calculated from airway wall motion (from cine magnetic resonance images) and air pressure acting on the airway wall (from computational fluid dynamics simulations). Airway wall motion could be asynchronous with pressure forces due to neuromuscular activation, or synchronous with pressure forces, indicating a passive response to airflow. The obstructive apnea-hypopnea index (oAHI) quantified OSA severity. During inhalation, the normalized work done through asynchronous dilation of the airway at the soft palate, tongue, and epiglottis correlated significantly with oAHI (Spearman's ρ = 0.54, 0.50, 0.64; P = 0.03, 0.03, 0.003). Synchronous collapse at the epiglottis correlated significantly with oAHI (ρ = 0.52; P = 0.02). Temporal order of synchronous and asynchronous epiglottis motion during inhalation predicted the severity of OSA (moderate vs. severe) with 100% sensitivity and 70% specificity. Subjects with severe OSA and/or trisomy 21 have insufficient neuromuscular activation during inhalation, leading to collapse and increased neuromuscular activation. Airflow-driven airway wall motion during late inhalation likely is the main determinant of OSA severity.NEW & NOTEWORTHY This is the first study that combines cine MRI and computational fluid dynamics with in vivo synchronous respiratory flow measurement to quantify the interaction between airway neuromuscular forces, aerodynamic forces, and airway anatomy noninvasively in pediatric patients with obstructive sleep apnea (OSA). The results indicate power transfer predicts OSA severity.

A review of supine position related obstructive sleep apnea: Classification, epidemiology, pathogenesis and treatment

Supine related obstructive sleep apnea (OSA) is the most common clinical and physiological phenotype of OSA. This condition is recognizable by patients, their families and through polysomnographic recordings. Commonly used definitions distinguish the presence of supine related OSA when respiratory events occur at twice the frequency when the patient lies in the supine compared to non-supine sleeping positions. Recent physiology studies have demonstrated that airway obstruction arises more commonly in the supine position particularly at the level of the soft palate and epiglottis. Increased airway collapsibility is reliability observed supine relative to lateral position. To a lesser extent, changes in control of breathing favour less stable ventilation when the supine sleeping posture is adopted. Many treatments have been developed and trialled to help patients avoid sleeping on their back. The last 10 years has seen the emergence of vibrotactile warning devices that are worn on the patients' neck or chest. High quality randomized controlled trial data is accumulating on the efficacy and common pitfalls of the application of these treatments.

Clinical Application of the Multicomponent Grading System for Sleep Apnea Classification and Incident Cardiovascular Mortality

Objective  To evaluate the clinical utility of the Baveno classification in predicting incident cardiovascular mortality after five years of follow-up in a clinic-based cohort of patients with obstructive sleep apnea (OSA). Materials and Methods  We evaluated the reproducibility of the Baveno classification using data from the Santiago Obstructive Sleep Apnea (SantOSA) study. The groups were labeled Baveno A (minor symptoms and comorbidities), B (severe symptoms and minor comorbidities), C (minor symptoms and severe comorbidities), and D (severe symptoms and comorbidities). Within-group comparisons were performed using analysis of variance (ANOVA) and post hoc tests. The associations between groups and incident cardiovascular mortality were determined through the Mantel-Cox and Cox proportional hazard ratios (HRs) adjusted by covariables. Results  A total of 1,300 OSA patients were included (Baveno A: 27.7%; B: 28%; C: 16.8%; and D: 27.5%). The follow-up was of 5.4 years. Compared to Baveno A, the fully-adjusted risk of cardiovascular mortality with Baveno B presented an HR of 1.38 (95% confidence interval [95%CI]: 0.14-13.5; p  = 0.78); with Baveno C, it was of 1.71 (95%CI: 0.18-16.2; p  = 0.63); and, with Baveno D, of 1.04 (95%CI: 0.12-9.2; p  = 0.98). We found no interactions involving Baveno group, sex and OSA severity. Discussion  Among OSA patients, the Baveno classification can describe different subgroups. However, its utility in identifying incident cardiovascular mortality is unclear. Long-term follow-up studies and the inclusion of demographic variables in the classification could improve its ability to detect a high-risk phenotype associated with cardiovascular mortality. Conclusion  The Baveno classification serves as a valuable method for categorizing varying groups of patients afflicted with OSA. Nevertheless, its precision in identifying occurrence of cardiovascular mortality is still unclear.

Update on the genetic basis of obstructive sleep apnoea - hype or hope?

PURPOSE OF REVIEW

The obstructive sleep apnoea syndrome (OSAS) is a chronic, common condition in western societies which can lead to adverse cardiometabolic effects if left untreated and is one of the commonest causes of excessive daytime somnolence.

RECENT FINDINGS

The presentation of OSAS is diverse and is thought to comprise of different intermediate phenotypes and endotypes in varying proportions in each individual. Unfortunately, due to its heterogeneity and the changing definitions of the disorder by workers in the field, attempts at revealing the genetic basis of OSAS has been fraught with difficulty.

SUMMARY

This brief review presents a short update on the achievements of the past three decades in this understudied and underfunded area of endeavour in respiratory sleep medicine. The genetic underpinnings of OSAS remain elusive.

Anatomical phenotype of obstructive sleep apnea patients based on cluster analysis

OBJECTIVES

To generate a novel subtype of obstructive sleep apnea (OSA) based on anatomical features and verify the differences in the response of different subtypes to orthodontic treatment, thus providing a theoretical reference for clinical decision-making.

MATERIALS AND METHODS

A K-means cluster analysis was performed for this retrospective serial study, which includes 722 OSA patients, aged 44.0 (36.0, 54.0) years, 80.2% male, with apnea-hypopnea index (AHI) of 23.2 (13.4, 39.6) events·h-1 , and body mass index (BMI) of 25.47 ± 3.00 kg·m-2 . All samples were divided into three subtypes based on AHI, BMI, and five variables of craniofacial measurements. Sixty-seven cases with mandibular advancement devices (MAD) therapeutic results were further applied to validate the efficacy and side effects of this treatment in different subtypes.

RESULTS

Two hundred and thirty patients (31.9%) were characterized as cluster 1: AHI of 17.65 (11.80, 30.42) events·h-1 , BMI of 23.65 ± 2.62 kg·m-2 , with skeletal Class II high-angle shape. Cluster 2 included 278 patients (38.5%): AHI of 17.00 (11.00, 26.48) events·h-1 , BMI of 25.36 ± 2.53 kg·m-2 , soft palate length (SPL) of 39.25 mm (36.12, 42.20), with basically normal skeleton and normal airway size. Cluster 3, consisting of 214 patients (29.6%), exhibited a combination of anatomical deformity and obesity, with the highest AHI and BMI of 45.35 (30.42, 62.53) events·h-1 and 27.57 ± 2.59 kg·m-2 respectively, but less deformity degree than cluster 1. Cluster 2 had the highest response rate and relatively mild side effects with MAD.

CONCLUSIONS

Orthodontic treatment based on anatomical morphology could exert a better effect on mild-moderate OSA patients with mild skeletal deformity.

Respiratory effort during sleep and the rate of prevalent type 2 diabetes in obstructive sleep apnoea

AIM

To determine the association between total sleep time (TST) spent in increased respiratory effort (RE) and the prevalence of type 2 diabetes in a large cohort of individuals with suspected obstructive sleep apnoea (OSA) referred for in-laboratory polysomnography (PSG).

MATERIALS AND METHODS

We conducted a retrospective cross-sectional study using the clinical data of 1128 patients. Non-invasive measurements of RE were derived from the sleep mandibular jaw movements (MJM) bio-signal. An explainable machine-learning model was built to predict prevalent type 2 diabetes from clinical data, standard PSG indices, and MJM-derived parameters (including the proportion of TST spent with increased respiratory effort [REMOV [%TST]).

RESULTS

Original data were randomly assigned to training (n = 853) and validation (n = 275) subsets. The classification model based on 18 input features including REMOV showed good performance for predicting prevalent type 2 diabetes (sensitivity = 0.81, specificity = 0.89). Post hoc interpretation using the Shapley additive explanation method found that a high value of REMOV was the most important risk factor associated with type 2 diabetes after traditional clinical variables (age, sex, body mass index), and ahead of standard PSG metrics including the apnoea-hypopnea and oxygen desaturation indices.

CONCLUSIONS

These findings show for the first time that the proportion of sleep time spent in increased RE (assessed through MJM measurements) is an important predictor of the association with type 2 diabetes in individuals with OSA.

Disparities in Sleep-Disordered Breathing: Upstream Risk Factors, Mechanisms, and Implications

Sleep-disordered breathing (SDB) refers to a spectrum of disorders ranging from habitual snoring without frank episodes of obstructed breathing or desaturation during sleep to obstructive sleep apnea, where apneas and hypopneas repetitively occur with resultant intermittent hypoxia, arousal, and sleep disruption. Disparities in SDB reflect its overall high prevalence in children and adults from racially and ethnically minoritized or low socioeconomic status backgrounds coupled with high rates of underdiagnosis and suboptimal treatment.

Relationship between Symptom Profiles and Endotypes among Patients with Obstructive Sleep Apnea: A Latent Class Analysis

Rationale: Obstructive sleep apnea (OSA) is a heterogeneous syndrome with various endotypic traits and symptoms. A link among symptoms, endotypes, and disease prognosis has been proposed but remains unsupported by empirical data. Objectives: To link symptom profiles and endotypes by clustering endotypic traits estimated using polysomnographic signals. Methods: We recruited 509 patients with moderate to severe OSA from a single sleep center. Polysomnographic data were collected between May 2020 and January 2022. Endotypic traits, namely arousal threshold, upper airway collapsibility, loop gain, and upper airway muscle compensation, were retrieved using polysomnographic signals during non-rapid eye movement periods. We used latent class analysis to group participants into endotype clusters. Demographic and polysomnographic parameter differences were compared between clusters, and associations between endotype clusters and symptom profiles were examined using logistic regression analyses. Results: Three endotype clusters were identified, characterized by high collapsibility/loop gain, low arousal threshold, and low compensation, respectively. Patients in each cluster exhibited similar demographic characteristics, but those in the high collapsibility/loop gain cluster had the highest proportion of obesity and severe oxygen desaturation observed in polysomnographic studies. The low compensation cluster was characterized by fewer sleepy symptoms and exhibited a lower rate of diabetes mellitus. Compared with the excessively sleepy group, disturbed sleep symptoms were associated with the low arousal threshold cluster (odds ratio, 1.89; 95% confidence interval, 1.16-3.10). Excessively sleepy symptoms were associated with the high collapsibility/loop gain cluster (odds ratio, 2.16; 95% confidence interval, 1.39-3.37) compared with the minimally symptomatic group. Conclusions: Three pathological endotype clusters were identified among patients with moderate to severe OSA, each exhibiting distinct polysomnographic characteristics and clinical symptom profiles.

Translation of obstructive sleep apnea pathophysiology and phenotypes to personalized treatment: a narrative review

Obstructive Sleep Apnea (OSA) arises due to periodic blockage of the upper airway (UA) during sleep, as negative pressure generated during inspiration overcomes the force exerted by the UA dilator muscles to maintain patency. This imbalance is primarily seen in individuals with a narrowed UA, attributable to factors such as inherent craniofacial anatomy, neck fat accumulation, and rostral fluid shifts in the supine posture. Sleep-induced attenuation of UA dilating muscle responsiveness, respiratory instability, and high loop gain further exacerbate UA obstruction. The widespread comorbidity profile of OSA, encompassing cardiovascular, metabolic, and neuropsychiatric domains, suggests complex bidirectional relationships with conditions like heart failure, stroke, and metabolic syndrome. Recent advances have delineated distinct OSA phenotypes beyond mere obstruction frequency, showing links with specific symptomatic manifestations. It is vital to bridge the gap between measurable patient characteristics, phenotypes, and underlying pathophysiological traits to enhance our understanding of OSA and its interplay with related outcomes. This knowledge could stimulate the development of tailored therapies targeting specific phenotypic and pathophysiological endotypes. This review aims to elucidate the multifaceted pathophysiology of OSA, focusing on the relationships between UA anatomy, functional traits, clinical manifestations, and comorbidities. The ultimate objective is to pave the way for a more personalized treatment paradigm in OSA, offering alternatives to continuous positive airway pressure therapy for selected patients and thereby optimizing treatment efficacy and adherence. There is an urgent need for personalized treatment strategies in the ever-evolving field of sleep medicine, as we progress from a 'one-size-fits-all' to a 'tailored-therapy' approach.

Domiciliary transcutaneous electrical stimulation in patients with obstructive sleep apnoea and limited adherence to continuous positive airway pressure therapy: a single-centre, open-label, randomised, controlled phase III trial

Background

Hypoglossal nerve stimulation (HNS) for obstructive sleep apnoea (OSA) is a novel way to manage the condition. We hypothesised that in patients with OSA and limited adherence to continuous positive airway pressure (CPAP) therapy, domiciliary transcutaneous electrical stimulation (TESLA) would control sleep apnoea and provide health benefits.

Methods

We undertook a single-centre, open-label, randomised, controlled phase III trial in patients with OSA (apnoea-hypopnoea-index [AHI] 5-35 h-1), a BMI of 18.5-32 kg∗m-2, and a documented lack of adherence to CPAP therapy (<4 h∗night-1) at Guy's & St Thomas' NHS Foundation Trust (hospital), UK. Patients were randomly assigned (1:1) using minimisation (gender and OSA severity) to receive TESLA or usual care (CPAP) for at least 3 months; sleep study analysis was provided without knowledge of the assignment arm. The primary outcome was change in AHI at 3-months. The primary outcome and safety were analysed in the intention-to-treat population. Data are reported as median (interquartile range), unless otherwise explained. This trial is registered at ClinicalTrials.gov, NCT03160456.

Findings

Between 6 June 2018 and 7 February 2023, 56 participants were enrolled and randomly assigned (29 patients in the intervention group and 27 in the usual care group). Patients were followed up for a median of 3.0 months (IQR 3.0; 10.0). The groups were similar in terms of age (55.8 (48.2; 66.0) vs 59.3 (47.8; 64.4) years), gender (male:female, 19:10 vs 18:9) and BMI (28.7 (26.4; 31.9) vs 28.4 (24.4; 31.9) kg∗m-2). The unadjusted group difference in the Δ AHI was -11.5 (95% CI -20.7; -2.3) h-1 (p = 0.016). Adjusted for the baseline value, the difference was Δ AHI -7.0 (-15.7; 1.8) h-1 (p = 0.12), in favour of the intervention. Minor adverse events were found in one of the participants who developed mild headaches related to the intervention.

Interpretation

Domiciliary TESLA can be used safely and effectively in OSA patients with poor adherence to CPAP, with favourable impact on sleepiness and sleep fragmentation. Despite pandemic-related limitations of the amended protocol this trial provides the evidence that TESLA improves clinically meaningful outcomes over the observed follow up period, and the transcutaneous approach is likely to offer an affordable alternative for responders to electrical stimulation in clinical practice.

Funding

British Lung Foundation, United Kingdom Clinical Research Collaboration-registered King's Clinical Trials Unit at King's Health Partners.

Beyond CPAP: modifying upper airway output for the treatment of OSA

Obstructive Sleep Apnea (OSA) is exceedingly common but often under-treated. Continuous positive airway pressure (CPAP) has long been considered the gold standard of OSA therapy. Limitations to CPAP therapy include adherence and availability. The 2021 global CPAP shortage highlighted the need to tailor patient treatments beyond CPAP alone. Common CPAP alternative approaches include positional therapy, mandibular advancement devices, and upper airway surgery. Upper airway training consists of a variety of therapies, including exercise regimens, external neuromuscular electrical stimulation, and woodwind instruments. More invasive approaches include hypoglossal nerve stimulation devices. This review will focus on the approaches for modifying upper airway muscle behavior as a therapeutic modality in OSA.

Pulmonary Function Test and Obstructive Sleep Apnea Hypopnea Syndrome in Obese Adults: A Retrospective Study

Objective

We explore risk factors related to severe obstructive sleep apnea (OSA) in obese patients, including pulmonary ventilation function, diffusion function, and impulse oscillometry (IOS) data.

Methods

The medical records of 207 obese patients who were prepared to undergo bariatric surgery in a hospital from May 2020 to September 2021 were retrospectively reviewed. Polysomnography (PSG), pulmonary ventilation function, diffusion function, and IOS parameters were collected according to the ethical standards of the institutional research committee (registration number: KYLL-202008-144). Logistic regression analysis was used to analyze the related independent risk factors.

Results

There were significantly statistical difference in a number of pulmonary ventilation and diffusion function parameters among the non-OSAHS group, the mild-to-moderate OSA group, and the severe OSA group. However, only airway resistance parameters R5%, R10%, R15%, R20%, R25%, and R35% increased with increasing OSA severity and were positively correlated with apnea hypopnea index (AHI). Age (P = 0.012, 1.104 (1.022, 1.192)), body mass index (P< 0.0001, 1.12 (1.057, 1.187)), gender (P = 0.003, 4.129 (1.625, 10.49)), and R25% (P = 0.007, 1.018 (1.005, 1.031)) were independent risk factors for severe OSA. In patients aged 35 to 60, RV/TLC (P = 0.029, 1.272 (1.025, 1.577)) is an independent risk factor for severe OSA.

Conclusion

R25% was an independent risk factor for severe OSA in obese individuals, while RV/TLC was also an independent risk factor in those aged 35 to 60. Pulmonary function tests (PFTs), particularly IOS levels, are recommended to assess severe OSA in obese patients.

The placebo effect in pharmacological treatment of obstructive sleep apnea, a systematic review and meta-analysis

OBJECTIVE

New drug treatments are under development in obstructive sleep apnea (OSA). The placebo effect is well recognized in various conditions, but its relevance in OSA is debated. In the current study we determined the influence of a placebo effect in studies of drug therapy in OSA.

METHODS

A systematic review and meta-analysis (PROSPERO CRD42021229410) with searches in MEDLINE, Scopus, Web of Science and Cochrane CENTRAL from inception to 2021-01-19. Inclusion criteria were (i) RCTs of adults with OSA, (ii) drug intervention with placebo baseline and follow-up sleep study (iii) outcomes: apnea hypopnea index (AHI), mean oxygen saturation (mSaO2), oxygen desaturation index (ODI) and/or Epworth Sleepiness Scale (ESS). Risk-of-bias was assessed with Cochrane RoB 2.

RESULTS

7436 articles were identified and 29 studies included (n = 413). Studies were generally small (median n = 14), with 78% men, baseline AHI range 9-74 events/h and treatment duration range 1-120 days. Meta-analyses were conducted for main outcomes. Mean change of the primary outcome, AHI, was -0.84 (95% CI -2.98 to 1.30); mSaO2 and ODI estimations were also non-significant. ESS showed a trend towards a reduction of -1 unit. Subgroup analysis did not show significant differences. Risk-of-bias assessment indicated mostly low risk but studies were small with wide confidence intervals.

CONCLUSIONS

In this meta-analysis we did not identify systematic placebo effects on the AHI, ODI or mSaO2 while ESS score showed a trend for a small reduction. These results have an impact on the design and interpretation of drug trials in OSA.

The Effect of Bite Raise on AHI Values in Adult Patients Affected by OSA: A Systematic Review with Meta-Regression

Obstructive sleep apnea (OSA) is a highly prevalent sleep breathing disorder characterized by the collapse of the pharyngeal walls that entails recurrent episodes of cessation of breathing or decrease in airflow while sleeping. This results in sleep fragmentation, decreased oxygen saturation and an increase in the partial pressure of carbon dioxide, causing excessive daytime sleepiness, hypertension and increased prevalence of cardiovascular morbidity and mortality. Mandibular advancement devices (MAD) represent a valid alternative therapy to Continuous Positive Airway Pressure, thrusting the mandible forward, increasing the lateral diameter of the pharynx and reducing the collapsibility of the airway. Several investigations have focused on the detection of the best mandibular advancement amount in terms of effectiveness and tolerance, but few and contrasting data are available on the role of occlusal bite raise in reducing the apnea/hypopnea index (AHI). The aim of this systematic review with meta-regression analysis was to investigate the effect of the bite raise of MAD on AHI values in adult patients affected by OSA. An electronic search was performed in MEDLINE, the Cochrane Database, Scopus, Web of Science and LILACS. Randomized controlled trials (RCT) investigating the effectiveness of MAD in OSA patients were included. The quality of evidence was evaluated with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) and the risk of bias with the Cochrane risk-of-bias tool for randomized trials (RoB2). Six RCT were included. The success rate of each study was computed: (mean baseline AHI - mean post treatment AHI)/mean baseline AHI. The GRADE scores indicated that the quality of evidence was very low. The meta-regression analysis showed that there was no correlation between the occlusal bite raise and the AHI improvement.

Outcome of nasal measurements in patients with OSA - Mounting evidence of a nasal endotype

BACKGROUND

Increased nasal resistance as measured by 4-phase rhinomanometry is associated with a paucity of apneas relative to hypopneas in obstructive sleep apnea (OSA) patients. The ratio of hypopneas to apneas for a given apnea hypopnea index (AHI) may influence treatment choice. This study aimed to investigate if OSA patients with an elevated hypopnea apnea ratio are associated with differences in acoustic rhinometry measurements.

METHODS

One hundred and thirty-nine (n = 139) OSA patients (AHI >5) were enrolled in this prospective case-control study (all male). OSA Diagnosis was established through a type three sleep study. Both acoustic rhinometry and 4-phase rhinomanometry were performed on all patients at baseline and after decongestion. Possible associations between apnea-hypopnea index, oxygen desaturation index, nadir oxygen saturation, apnea index, hypopnea index, hypopnea to apnea ratio and body mass index and were analysed using multiple logistic and linear regression models.

RESULTS

The acoustic rhinometry measurements minimal cross-sectional area, total volume and minimal cross-sectional areas are significantly smaller in patients with increased nasal resistance as measured by 4-phase rhinomanometry (P < 0.01). No consistent statistically significant associations were found between the acoustic rhinometry variables, and the respiratory variables analysed in the sleep studies. OSA patients with an elevated hypopnea apnea ratio are more than 4 times more likely to present with increased nasal resistance measured by 4-phase rhinomanometry (OR = 4.4, 95% CI [1.5-13.2], P < 0.01).

CONCLUSIONS

Acoustic rhinometry is significantly associated with 4-phase rhinomanometry. However, acoustic rhinometry measurements are not associated with the respiratory indices routinely measured in OSA in a clinical setting. 4-phase rhinomanometry is a more suitable method for detecting clinically relevant nasal obstruction in obstructive sleep apnea patients.

Extraction of cardiac-related signals from a suprasternal pressure sensor during sleep

Objective.The accurate detection of respiratory effort during polysomnography is a critical element in the diagnosis of sleep-disordered breathing conditions such as sleep apnea. Unfortunately, the sensors currently used to estimate respiratory effort are either indirect and ignore upper airway dynamics or are too obtrusive for patients. One promising alternative is the suprasternal notch pressure (SSP) sensor: a small element placed on the skin in the notch above the sternum within an airtight capsule that detects pressure swings in the trachea. Besides providing information on respiratory effort, the sensor is sensitive to small cardiac oscillations caused by pressure perturbations in the carotid arteries or the trachea. While current clinical research considers these as redundant noise, they may contain physiologically relevant information.Approach.We propose a method to separate the signal generated by cardiac activity from the one caused by breathing activity. Using only information available from the SSP sensor, we estimate the heart rate and track its variations, then use a set of tuned filters to process the original signal in the frequency domain and reconstruct the cardiac signal. We also include an overview of the technical and physiological factors that may affect the quality of heart rate estimation. The output of our method is then used as a reference to remove the cardiac signal from the original SSP pressure signal, to also optimize the assessment of respiratory activity. We provide a qualitative comparison against methods based on filters with fixed frequency cutoffs.Main results.In comparison with electrocardiography (ECG)-derived heart rate, we achieve an agreement error of 0.06 ± 5.09 bpm, with minimal bias drift across the measurement range, and only 6.36% of the estimates larger than 10 bpm.Significance.Together with qualitative improvements in the characterization of respiratory effort, this opens the development of novel portable clinical devices for the detection and assessment of sleep disordered breathing.

Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective

BACKGROUND

The past few years have seen a rapid emergence of artificial intelligence (AI)-enabled technology in the field of sleep medicine. AI refers to the capability of computer systems to perform tasks conventionally considered to require human intelligence, such as speech recognition, decision-making, and visual recognition of patterns and objects. The practice of sleep tracking and measuring physiological signals in sleep is widely practiced. Therefore, sleep monitoring in both the laboratory and ambulatory environments results in the accrual of massive amounts of data that uniquely positions the field of sleep medicine to gain from AI.

METHOD

The purpose of this article is to provide a concise overview of relevant terminology, definitions, and use cases of AI in sleep medicine. This was supplemented by a thorough review of relevant published literature.

RESULTS

Artificial intelligence has several applications in sleep medicine including sleep and respiratory event scoring in the sleep laboratory, diagnosing and managing sleep disorders, and population health. While still in its nascent stage, there are several challenges which preclude AI's generalizability and wide-reaching clinical applications. Overcoming these challenges will help integrate AI seamlessly within sleep medicine and augment clinical practice.

CONCLUSION

Artificial intelligence is a powerful tool in healthcare that may improve patient care, enhance diagnostic abilities, and augment the management of sleep disorders. However, there is a need to regulate and standardize existing machine learning algorithms prior to its inclusion in the sleep clinic.

Persistent obstructive sleep apnoea in children: treatment options and management considerations

Unresolved obstructive sleep apnoea (OSA) after an adenotonsillectomy, henceforth referred to as persistent OSA, is increasingly recognised in children (2-18 years). Although associated with obesity, underlying medical complexity, and craniofacial disorders, persistent OSA also occurs in otherwise healthy children. Inadequate treatment of persistent OSA can lead to long-term adverse health outcomes beyond childhood. Positive airway pressure, used as a one-size-fits-all primary management strategy for persistent childhood OSA, is highly efficacious but has unacceptably low adherence rates. A pressing need exists for a broader, more effective management approach for persistent OSA in children. In this Personal View, we discuss the use and the need for evaluation of current and novel therapeutics, the role of shared decision-making models that consider patient preferences, and the importance of considering the social determinants of health in research and clinical practice. A multipronged, comprehensive approach to persistent OSA might achieve better clinical outcomes in childhood and promote health equity for all children.

Effect of switching from continuous to bilevel positive airway pressure on sleep quality in patients with obstructive sleep apnea: the prospective POP IN VAuto study

Background

Issues with tolerability and side effects can decrease continuous positive airway pressure (CPAP) device usage and the benefits of therapy. Different positive airway pressure (PAP) therapy modes providing expiratory pressure relief or using a different pressure during inspiration vs. expiration (bilevel PAP) may alleviate some of these issues. This multicenter, prospective study evaluated the effects of switching from CPAP to bilevel PAP (VAuto mode) on respiratory parameters, device usage, side effects and patient-reported outcomes in patients with obstructive sleep apnea (OSA).

Methods

Eligible OSA patients had started CPAP ≥3 months previously, had good compliance (mean 6.1±2.0 h/night) and well-controlled OSA [residual apnea-hypopnea index (AHI) 4.9±3.1/h] but had pressure tolerance issues or persistent side effects/discomfort. All were switched from CPAP to bilevel PAP (AirCurve 10 VAuto; ResMed). Effectiveness (residual AHI), sleep quality, daytime sleepiness, fatigue, therapy-related side effects, and patient satisfaction/preference were assessed after 3 months and 1 year.

Results

Forty patients were analyzed (68% male, age 64±11 years, body mass index 30.7±5.8 kg/m²). At 3 months and 1 year after switching to bilevel PAP, median [interquartile range] residual AHI was 4/h [2-5.3] and 3.7/h [1.8-5], respectively, and device usage was 7.0 [4.9-7.5] and 6.4 [4.4-7.3] h/night, respectively. Device switch was associated with significant reductions from baseline in expiratory PAP {from 12 [11-13] to 8 [7-9] cmH₂O at 3 months (P<0.001) and 9 [8-12] cmH₂O at 1 year (P=0.005)}, 95^th percentile pressure {from 14 [12-14] to 10 [9-11] and 10 [8-11] cmH2O; P<0.001 and P=0.001, respectively} and leak {from 1 [0-6] to 0 [0-1] and 0 [0-2] L/min; P=0.049 and P=0.033, respectively}. The Pittsburgh Sleep Quality Index score decreased significantly from baseline to 3 and 6 months [7.2±4.0 to 5.0±3.2 (P=0.005) and 4.5±2.7 (P<0.001), respectively]. CPAP-related mouth dryness, choking sensation and aerophagia were significantly improved one year after switching to bilevel PAP. Bilevel PAP was preferred over CPAP by 90% of patients.

Conclusions

Switching to bilevel PAP had several benefits in patients struggling with CPAP, facilitating therapy acceptance and ongoing device usage.

The effectiveness of sleep breathing impairment index in assessing obstructive sleep apnea severity

STUDY OBJECTIVES

Using the apnea-hypopnea index (AHI) and the sleep breathing impairment index (SBII) to assess the severity of obstructive sleep apnea (OSA) to study how effective SBII is in assessing the severity and cardiovascular disease (CVD) prognosis.

METHODS

This study comprised a total of 147 patients with diagnosed OSA. The AHI and SBII were calculated from the polysomnography. Patients were enrolled in the cluster analysis using 20 symptoms and the SBII. The prognostic indicator was determined as the moderate-to-high Framingham 10-year CVD risk.

RESULTS

Cluster analysis revealed 3 separate groups: cluster 1 (n = 45, 30.61%) had the lowest symptoms complaints yet the highest PSQI score; cluster 2 (n = 70, 47.62%) had considerably increased symptom complaints but the lowest Epworth Sleepiness Scale score, intermediate PSG indices, a higher low arousal threshold possibility, and a lower SBII quantile; cluster 3 (n = 32, 21.77%) had the largest percentage of smokers, a predominant symptom of restless sleep, severe PSG characteristics, a lower low arousal threshold likelihood, a greater SBII quantile and a higher Framingham CVD risk. There were no differences in severity indicated by AHI between groups. Higher SBII rather than AHI is associated with an increased 10-year CVD risk.

CONCLUSIONS

SBII provides higher sensitivity when evaluating OSA severity and better predictive capabilities for CVD outcomes. SBII may be a more effective substitute for AHI in the future.

CITATION

Dai L, Cao W, Luo J, Huang R, Xiao Y. The effectiveness of sleep breathing impairment index in assessing obstructive sleep apnea severity. J Clin Sleep Med. 2023;19(2):267-274.

A Scoping Review of Sleep Apnea: Where Do We Stand?

Obstructive sleep apnea (OSA), a condition in which there is a recurrent collapse of the upper airway while sleeping, is a widespread disease affecting 5% to 10% people worldwide. Despite several advances in the treatment modalities for OSA, morbidity and mortality remain a concern. Common symptoms include loud snoring, gasping for air during sleep, morning headache, insomnia, hypersomnia, attention deficits, and irritability. Obese individuals, male gender, older age (65+), family history, smoking, and alcohol consumption are well recognized risk factors of OSA. This condition holds the ability to increase inflammatory cytokines, cause metabolic dysfunction, and increase the sympathetic output, all of which exacerbate OSA due to their effect on the cardiovascular system. In this review, we discuss its brief history, risk factors, complications, treatment modalities, and the role of clinicians in curbing its risk.

Relationships between respiratory and oromotor events differ between motor phenotypes in patients with obstructive sleep apnea

Purpose

The present study investigated the relationship between sleep bruxism (SB) and obstructive sleep apnea (OSA) in relation to the sleep architecture.

Methods

We conducted a cross-sectional study. Polysomnographic recordings were performed on 36 patients. Sleep, respiratory, and oromotor variables, such as rhythmic masticatory muscle activity (RMMA) and non-specific masticatory muscle activity (NSMA), were compared between OSA patients with or without SB. A correlation analysis of the frequency of respiratory and oromotor events in NREM and REM sleep was performed. The frequency of oromotor events following respiratory events was also assessed.

Results

The proportion of REM sleep was higher in OSA patients with SB than in those without SB (p = 0.02). The apnea-hypopnea index (AHI) did not significantly differ between the two groups; however, AHI was approximately 8-fold lower during REM sleep in OSA patients with SB (p = 0.01) and the arousal threshold was also lower (p = 0.04). Although the RMMA index was higher in OSA patients with than in those without SB (p < 0.01), the NSMA index did not significantly differ. The percentage of RMMA following respiratory events was significantly higher in OSA patients with than in those without SB, whereas that of NSMA did not significantly differ. The frequency of oromotor events throughout the whole night positively correlated with AHI. However, regardless of the sleep state, AHI did not correlate with the RMMA index, but positively correlated with the NSMA index.

Conclusion

In consideration of the limitations of the present study, the results obtained indicate that OSA patients with SB have a unique phenotype of OSA and also emphasize the distinct relationship of respiratory events with RMMA and NSMA.

Role of precision medicine in obstructive sleep apnoea

Obstructive sleep apnoea is a substantial clinical and public health problem because it contributes to harmful effects on quality of life, daytime symptoms, road traffic incidents, and cardiometabolic disease. Increasingly, obstructive sleep apnoea is recognised as a heterogeneous disease, and patients have varied susceptibility to long term complications and different responses to treatment. This narrative review summarises the current knowledge of precision medicine in obstructive sleep apnoea, particularly the role of symptom clusters, polysomnogram phenotypes, physiological endotypes, and circulating biomarkers in defining subtypes. In the near future, the prognostic accuracy of these measures in predicting long term complications in obstructive sleep apnoea will likely be improved, together with better matching of treatments to disease subtypes.

New Metrics from Polysomnography: Precision Medicine for OSA Interventions

Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.

Virtual consultations for patients with obstructive sleep apnoea: a systematic review and meta-analysis

BACKGROUND

The coronavirus disease 2019 pandemic has accelerated the adoption of virtual care strategies for the management of patients with obstructive sleep apnoea/hypopnoea syndrome (OSAHS).

RESEARCH QUESTION

What is the effectiveness of virtual consultations compared to in-person consultations for the management of continuous positive airway pressure (CPAP) therapy in adult patients with OSAHS?

METHODS

A systematic review and meta-analysis (PROSPERO; CRD42022297532) based on six electronic databases plus manually selected journals was conducted in January 2022. Two researchers independently selected, quality appraised and extracted data. The co-primary outcomes were patient-reported sleepiness, assessed by the Epworth Sleepiness Scale (ESS), and reported cost-effectiveness.

RESULTS

12 studies (n=1823 adults) were included in the review. Seven studies (n=1089) were included in the meta-analysis which showed no difference in the magnitude of improvement in patient-reported sleepiness scores between virtual and in-person consultations (mean difference -0.39, 95% CI -1.38-0.60; p=0.4), although ESS scores improved in both groups. Virtual care strategies modestly increased CPAP therapy adherence and were found to be less costly than in-person care strategies in the three Spanish trials that reported cost-effectiveness.

CONCLUSION

The findings of this review suggest that virtual care delivered by telephone or video consultations is as effective as in-person consultations for improving subjective sleepiness in patients with OSAHS treated with CPAP. This clinical management strategy may also improve CPAP adherence without increasing the costs, supporting its potential as a follow-up management strategy, where patients prefer this approach.

Sleep-Disordered Breathing and Cardiac Arrhythmias in Adults: Mechanistic Insights and Clinical Implications: A Scientific Statement From the American Heart Association

Sleep-disordered breathing (SDB), characterized by specific underlying physiological mechanisms, comprises obstructive and central pathophysiology, affects nearly 1 billion individuals worldwide, and is associated with excessive cardiopulmonary morbidity. Strong evidence implicates SDB in cardiac arrhythmogenesis. Immediate consequences of SDB include autonomic nervous system fluctuations, recurrent hypoxia, alterations in carbon dioxide/acid-base status, disrupted sleep architecture, and accompanying increases in negative intrathoracic pressures directly affecting cardiac function. Day-night patterning and circadian biology of SDB-induced pathophysiological sequelae collectively influence the structural and electrophysiological cardiac substrate, thereby creating an ideal milieu for arrhythmogenic propensity. Cohort studies support strong associations of SDB and cardiac arrhythmia, with evidence that discrete respiratory events trigger atrial and ventricular arrhythmic events. Observational studies suggest that SDB treatment reduces atrial fibrillation recurrence after rhythm control interventions. However, high-level evidence from clinical trials that supports a role for SDB intervention on rhythm control is not available. The goals of this scientific statement are to increase knowledge and awareness of the existing science relating SDB to cardiac arrhythmias (atrial fibrillation, ventricular tachyarrhythmias, sudden cardiac death, and bradyarrhythmias), synthesizing data relevant for clinical practice and identifying current knowledge gaps, presenting best practice consensus statements, and prioritizing future scientific directions. Key opportunities identified that are specific to cardiac arrhythmia include optimizing SDB screening, characterizing SDB predictive metrics and underlying pathophysiology, elucidating sex-specific and background-related influences in SDB, assessing the role of mobile health innovations, and prioritizing the conduct of rigorous and adequately powered clinical trials.

Associations of sleep apnea risk and oxygen desaturation indices with cerebral small vessel disease burden in patients with stroke

Background

Obstructive sleep apnea (OSA) is associated with cerebral small vessel disease (CSVD). Nonetheless, whether OSA-risk determined by a simple screening questionnaire or indices quantifying nocturnal hypoxemia other than the conventional apnea–hypopnea index (AHI) by the home sleep apnea test (HSAT) associated with CSVD burden remains uncertain.

Methods

From 2018 to 2021, we recruited patients with transient ischemic attack (TIA)/minor stroke from the Queen Mary Hospital Acute Stroke Unit and TIA/Stroke Outpatient Clinics. Logistic regression models were applied to determine the association of baseline OSA-risk (on STOP-BANG questionnaire) or HSAT-derived indices quantifying nocturnal hypoxemia with global burden/individual markers of CSVD on MRI. Indices included oxygen desaturation (≥3%) index (ODI), minimum oxygen saturation (SpO₂), percentage of total sleep time with an oxygen saturation <90% (CT90%), and desaturation duration (≥3%, DesDur).

Results

In 283 patients with TIA/minor stroke (mean age 65 years, 64% men), OSA-risk was significantly associated with total CSVD score (multivariate-adjusted odds ratio: 1.23, 95% confidence interval 1.01–1.51), presence of lacunes [1.39 (1.09–1.79)] and burden of basal ganglia PVSs [1.32 (1.06–1.67)]. In 85/283 patients who completed HSAT, neither AHI, minimum SpO₂ nor CT90% was associated with CSVD burden. Nonetheless, ODI and DesDur remained significantly associated with total CSVD score after covariate adjustment: ODI [1.04 (1.01–1.07)] and DesDur [1.04 (1.01–1.08)].

Conclusion

In patients with TIA/minor stroke, high OSA-risk was associated with a greater CSVD burden. Oxygen desaturation indices (ODI and DesDur) rather than AHI were independently associated with global CSVD burden, indicating that longer and more severe desaturations may contribute to the pathogenesis of CSVD.

Obstructive sleep apnea: personalizing CPAP alternative therapies to individual physiology

Introduction The recent continuous positive airway pressure (CPAP) crisis has highlighted the need for alternative obstructive sleep apnea (OSA) therapies. This article serves to review OSA pathophysiology and how sleep apnea mechanisms may be utilized to individualize alternative treatment options.Areas covered: The research highlighted below focuses on 1) mechanisms of OSA pathogenesis and 2) CPAP alternative therapies based on mechanism of disease. We reviewed PubMed from inception to July 2022 for relevant articles pertaining to OSA pathogenesis, sleep apnea surgery, as well as sleep apnea alternative therapies.Expert opinion: Although the field of individualized OSA treatment is still in its infancy, much has been learned about OSA traits and how they may be targeted based on a patient's physiology and preferences. While CPAP remains the gold-standard for OSA management, several novel alternatives are emerging. CPAP is a universal treatment approach for all severities of OSA. We believe that a personalized approach to OSA treatment beyond CPAP lies ahead. Additional research is needed with respect to implementation and combination of therapies longitudinally, but we are enthusiastic about the future of OSA treatment based on the data presented here.

National strategy on the integration of sleep and circadian rhythms into public health research and policies: Report from the Canadian Sleep and Circadian Network

Scientists in sleep and circadian rhythms, public health experts, healthcare providers, partners, and stakeholders convened in 2020 for a 2-day meeting organized by the Canadian Sleep and Circadian Network to develop a national strategy for the integration of sleep and circadian rhythms into public health and policies in Canada. The objective of this paper is to present the national strategy that emerged from this meeting of 60 participants from across Canada. The meeting focused on 4 key target priorities: (1) atypical working schedules, (2) sleep and circadian rhythms of children and adolescents, (3) insomnia, and (4) impact of sleep apnea on health. Following constructive discussions over 2 days, it was decided that the following 4 strategic objectives should be prioritized to accelerate the integration of sleep and circadian rhythms into public health policies in Canada: (1) Increase public health sleep and circadian rhythm research, (2) Increase public health education and knowledge mobilization on sleep, (3) Inform and support public health sleep interventions and policies, and (4) Promote sleep health training. The participants recommended that research and public health efforts should address the needs along the continuum of sleep health. The committee noted that strategies and interventions could differ across contexts, settings, sectors, and jurisdictions. The national strategy also identified high-priority research questions in public health and recommended mechanisms to build research capacity, providing a path forward for the integration of sleep and circadian rhythms into public health research and policies.

An interim oral appliance as a screening tool during drug-induced sleep endoscopy to predict treatment success with a mandibular advancement device for obstructive sleep apnea

Purpose

Previous studies have shown a wide range of efficacy (29 to 71%) of a mandibular advancement device (MAD) in the treatment of obstructive sleep apnea (OSA). Currently, the ability to preselect suitable patients for MAD therapy based on individual characteristics related to upper airway collapsibility is limited. We investigated if the use of non-custom interim MAD during drug-induced sleep endoscopy (DISE) could be a valuable screening tool to predict MAD treatment outcome.

Methods

In a single-center prospective study including a consecutive series of patients with OSA, we compared DISE outcomes with a MAD in situ with polysomnography results after 3 months of using the same MAD that was used during DISE.

Results

Of 41 patients who completed the study, the median apnea–hypopnea index (AHI) was 16.0 events/h [IQR 7.4–23.4]. Respiratory outcomes on polysomnography, including apnea index (AI), total AHI, AHI in supine position, and oxygen desaturation index, all significantly improved after 3 months of MAD treatment. With complete improvement of the upper airway obstruction with the MAD in situ during DISE in supine position, patients were 6.3 times more likely to be a responder to MAD treatment compared to patients with a persisting complete obstruction, although not statistically significant (OR 6.3; 95%CI 0.9–42.7; p = 0.060).

Conclusion

The potential predictive value with regard to MAD therapy outcomes of the use of an interim MAD during DISE would be an important finding, since the prediction of MAD therapy outcome is of great clinical and scientific interest. A study with a larger cohort should be performed to further investigate our findings.

Dynamic models of obstructive sleep apnea provide robust prediction of respiratory event timing and a statistical framework for phenotype exploration

Obstructive sleep apnea (OSA), in which breathing is reduced or ceased during sleep, affects at least 10% of the population and is associated with numerous comorbidities. Current clinical diagnostic approaches characterize severity and treatment eligibility using the average respiratory event rate over total sleep time (apnea-hypopnea index). This approach, however, does not characterize the time-varying and dynamic properties of respiratory events that can change as a function of body position, sleep stage, and previous respiratory event activity. Here, we develop a statistical model framework based on point process theory that characterizes the relative influences of all these factors on the moment-to-moment rate of event occurrence. Our results provide new insights into the temporal dynamics of respiratory events, suggesting that most adults have a characteristic event pattern that involves a period of normal breathing followed by a period of increased probability of respiratory event occurrence, while significant differences in event patterns are observed among gender, age, and race/ethnicity groups. Statistical goodness-of-fit analysis suggests consistent and substantial improvements in our ability to capture the timing of individual respiratory events using our modeling framework. Overall, we demonstrate a more statistically robust approach to characterizing sleep disordered breathing that can also serve as a basis for identifying future patient-specific respiratory phenotypes, providing an improved pathway towards developing individualized treatments.

Obstructive sleep apnea: transition from pathophysiology to an integrative disease model

Obstructive sleep apnea (OSA) is characterised by recurring episodes of upper airway obstruction during sleep and the fundamental abnormality reflects the inability of the upper airway dilating muscles to withstand the negative forces generated within the upper airway during inspiration. Factors that result in narrowing of the oropharynx such as abnormal craniofacial anatomy, soft tissue accumulation in the neck, and rostral fluid shift in the recumbent position increase the collapsing forces within the airway. The counteracting forces of upper airway dilating muscles, especially the genioglossus, are negatively influenced by sleep onset, inadequacy of the genioglossus responsiveness, ventilatory instability, especially post arousal, and loop gain. OSA is frequently associated with comorbidities that include metabolic, cardiovascular, renal, pulmonary, and neuropsychiatric, and there is growing evidence of bidirectional relationships between OSA and comorbidity, especially for heart failure, metabolic syndrome, and stroke. A detailed understanding of the complex pathophysiology of OSA encourages the development of therapies targeted at pathophysiological endotypes and facilitates a move towards precision medicine as a potential alternative to continuous positive airway pressure therapy in selected patients.

Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation

Background

High loop gain (unstable ventilatory control) is an important—but difficult to measure—contributor to obstructive sleep apnea (OSA) pathogenesis, predicting OSA sequelae and/or treatment response. Our objective was to develop and validate a clinical prediction tool of loop gain.

Methods

A retrospective cohort of consecutive adults with OSA (apnea–hypopnea index, AHI > 5/hour) based on in-laboratory polysomnography 01/2017–12/2018 was randomly split into a training and test-set (3:1-ratio). Using a customized algorithm (“reference standard”) loop gain was quantified from raw polysomnography signals on a continuous scale and additionally dichotomized (high > 0.7). Candidate predictors included general patient characteristics and routine polysomnography data. The model was developed (training-set) using linear regression with backward selection (tenfold cross-validated mean square errors); the predicted loop gain of the final linear regression model was used to predict loop gain class. More complex, alternative models including lasso regression or random forests were considered but did not meet pre-specified superiority-criteria. Final model performance was validated on the test-set.

Results

The total cohort included 1055 patients (33% high loop gain). Based on the final model, higher AHI (beta = 0.0016; P < .001) and lower hypopnea-percentage (beta = −0.0019; P < .001) predicted higher loop gain values. The predicted loop gain showed moderate-to-high correlation with the reference loop gain (r = 0.48; 95% CI 0.38–0.57) and moderate discrimination of patients with high versus low loop gain (area under the curve = 0.73; 95% CI 0.67–0.80).

Conclusion

To our knowledge this is the first prediction model of loop gain based on readily-available clinical data, which may facilitate retrospective analyses of existing datasets, better patient selection for clinical trials and eventually clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01950-y.

A Real-Time Medical Ventilation on Heart Failure Analysis Based on Sleep Apnea Snore and Meta-Analysis

An issue with cardiac ventilation can result in death at any moment throughout a person's life. The apnea-hypopnea index (AHI) has historically been influenced by medical ventilation on heart failure; nevertheless, the sleep snore analysis is the best model to diagnose. The problems with ventilation are caused by problems with air pressure and blood circulation in the heart valves, where the pathological measures are continually detecting ventilation issues. Understanding the pathophysiology of OSA will have a direct impact on clinical treatment choices as well as the design of clinical studies. Treatments could be tailored to each patient's unique needs based on the fundamental reason to their OSA. Through the OSA treatment, patients could feel better, and understanding OSA symptoms and also outcomes will improve patient's health; as a result, the study reveals that most of the population are likely to benefit from specific OSA treatment approaches. For achieving the benefits of OSA treatment the classification accuracy is needed to be improved. So, in this research work, an LeNet-100 CNN-based deep learning technology is used to get information and apply the classification approaches. We obtained the heart failure dataset from the Kaggle website for conducting a meta-analysis. An accuracy of 93.25%, sensitivity of 97.29%, recall of 96.34%, and F measure of 95.34% had been attained. This approach outperforms the technology and is comparable to the present heart failure meta-analysis..

Diagnostic performance of screening tools for the detection of obstructive sleep apnea in people living with HIV

STUDY OBJECTIVES

Many people living with HIV (PLWH) have undiagnosed obstructive sleep apnea (OSA), which may contribute to commonly reported fatigue and the high cardiovascular disease burden in this population. Our objective was to assess the utility of traditional OSA screening tools (STOP-BANG, Berlin Questionnaire (BQ), and Epworth Sleepiness Scale (ESS)) for detecting OSA in PLWH.

METHODS

Adult PLWH were recruited from sleep/HIV clinics and the community into a larger clinical trial which included completion of these questionnaires before in-laboratory polysomnography. Discriminatory performance of these screening tools was assessed using area under receiver operating characteristic curves (AUC). The reference standard for the primary analysis was OSA based on an AHI≥5/h using recommended "1A"-criteria (hypopnea with 3%-desaturation and/or arousal). Secondary analyses explored acceptable "1B"-criteria (hypopnea with 4%-desaturation) and/or higher AHI cut-offs (≥15/h).

RESULTS

120 PLWH were included (mean-age: 50±11 years; body mass index: 27±4 kg/m², 84% male) and OSA was diagnosed in 75% using 1A-criteria. In the primary analysis, the discriminatory performance of the three screening tools was low (AUCs 0.58 to 0.70) and similar across the tools (P≥0.14). In secondary analyses, STOP-BANG showed moderate-high discriminatory ability (AUCs 0.77-0.80) and performed significantly better (P≤0.008) than the BQ or ESS (AUCs 0.53-0.62).

CONCLUSIONS

OSA was highly prevalent in our cohort of PLWH. Although STOP-BANG could reasonably identify moderate-severe OSA, the tools were not reliable for mild disease. Specifically, the questionnaires perform poorly for PLWH with mild OSA manifesting with arousals, yet such people may be at risk of fatigue/sleepiness and impaired memory consolidation.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Title: Obstructive Sleep Apnea Endotypes and Impact on Phenotypes of People Living With HIV (PLWH/OSA); Identifier: NCT03575143; URL: https://clinicaltrials.gov/ct2/show/NCT03575143.

Multidimensional assessment and cluster analysis for OSA phenotyping

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is a heterogeneous disease with varying phenotype. A cluster analysis based on multidimensional disease characteristics, including symptom, anthropometry, polysomnography (PSG), and craniofacial morphology, in combination with auto-continuous positive airway pressure (CPAP) titration response and comorbidity profiles was performed within a well-characterized cohort of patients with OSA, with the aim to refine current phenotypic expressions of OSA with clinical implications.

METHODS

Two hundred and ninety-one subjects with a new diagnosis of moderate to severe OSA, referred for auto-CPAP titration to the sleep center were included for analysis. In-laboratory PSG and craniofacial computed tomography (CT) scanning was performed, followed by an auto-CPAP titration. The symptom of excessive daytime sleepiness (EDS) was assessed by Epworth sleepiness scale (ESS).

RESULTS

Three patient phenotypes, corresponding to the "normal weight, non-sleepy and moderate OSA", the "obese, non-sleepy and severe OSA" and "obese, sleepy, very severe OSA with craniofacial limitation" were identified. Among the PSG parameters, only N3% and mean pulse oxygen saturation (SPO₂) were found to be associated with ESS, and they only explain small fraction of the variation (R²=0.136). Neck circumference and craniofacial limitation were associated the more severe phenotype, which had higher prevalence of hypertension, metabolic syndrome, greater diurnal blood gas abnormalities and worse PAP titration response.

CONCLUSIONS

Three OSA phenotypes were identified according to multiple aspect of clinical features in patients with moderate to severe OSA, which differed in prevalence of hypertension, metabolic syndrome, diurnal blood gas parameters and CPAP titration response. Self-reported EDS was not related with the severity of sleep breathing disturbance, and craniofacial limitation was associated the more severe phenotype. These findings highlight the necessity of integrate multiple disease characters into phenotyping to achieve better understanding of the clinical pictures of OSA.