Sleep Apnea Heterogeneity, Phenotypes, and Cardiovascular Risk. Implications for Trial Design and Precision Sleep Medicine

Hypoxic burden to guide CPAP treatment allocation in patients with obstructive sleep apnoea: a post hoc study of the ISAACC trial

BACKGROUND

Hypoxic burden (HB) has emerged as a strong predictor of cardiovascular risk in obstructive sleep apnoea (OSA). We aimed to assess the potential of HB to predict the cardiovascular benefit of treating OSA with continuous positive airway pressure (CPAP).

METHODS

This was a post hoc analysis of the ISAACC trial (ClinicalTrials.gov: NCT01335087) including non-sleepy patients with acute coronary syndrome (ACS) diagnosed with OSA (apnoea-hypopnoea index ≥15 events·h-1) by respiratory polygraphy. Patients were randomised to CPAP or usual care and followed for a minimum of 1 year. HB was calculated as the total area under all automatically identified desaturations divided by total sleep time. Patients were categorised as having high or low baseline HB according to the median value (73.1%min·h-1). Multivariable Cox regression models were used to assess whether the effect of CPAP on the incidence of cardiovascular outcomes was dependent on the baseline HB level.

RESULTS

The population (362 patients assigned to CPAP and 365 patients assigned to usual care) was middle-aged (mean age 59.7 years), overweight/obese and mostly male (84.5%). A significant interaction was found between the treatment arm and the HB categories. In the high HB group, CPAP treatment was associated with a significant reduction in the incidence of cardiovascular events (HR 0.57, 95% CI 0.34-0.96). In the low HB group, CPAP-treated patients exhibited a trend toward a higher risk of cardiovascular outcomes than those receiving usual care (HR 1.33, 95% CI 0.79-2.25). The differential effect of the treatment depending on the baseline HB level followed a dose-response relationship.

CONCLUSION

In non-sleepy ACS patients with OSA, high HB levels were associated with a long-term protective effect of CPAP on cardiovascular prognosis.

Unveiling the sleep-cardiovascular connection: Novel perspectives and interventions-A narrative review

Introduction

Sleep is an important neurophysiological condition that is intricately linked to general health, laying the basis for both physiological and psychological well-being. A thorough examination of sleep disorders and cardiovascular health demonstrates their deep relationship, emphasizing the numerous diagnostic tools and treatment techniques available.

Aim

This study aims to examine the impact, mechanisms, diagnostic techniques, treatment strategies, implications, and healthcare interventions of the sleep-cardiovascular connection, to better understand the relationship between sleep disorders and cardiovascular health.

Methods

The paper reviews key studies conducted from 2015-till date, investigating the impact of sleep disorders on the cardiovascular system. It looked into data relating to cardiovascular outcomes based on the degree of sleep disorders, considered potential confounding factors, and addressed current research constraints.

Results

The findings highlight a strong link between sleep problems and poor cardiovascular outcomes. Emerging diagnostic tools, such as enhanced sleep-related technology and biomarkers, open up new avenues for determining the impact of sleep disturbances on cardiovascular health. In addition, the research discusses several treatment options, ranging from cognitive behavioral therapy to pharmaceutical therapies, and their potential benefits in addressing sleep-related cardiovascular risks.

Conclusion

The complex association between sleep disturbances and cardiovascular health emphasizes the need to recognize sleep as a critical component of overall well-being. Thus collaboration among medical disciplines, as well as individualized therapies, are critical to improving patient care. Moreover, Understanding and managing the consequences of sleep problems on cardiovascular health can lead to more effective interventions, better outcomes, and improved public health as research advances.

Challenges of Applying Automated Polysomnography Scoring at Scale

Automatic polysomnography analysis can be leveraged to shorten scoring times, reduce associated costs, and ultimately improve the overall diagnosis of sleep disorders. Multiple and diverse strategies have been attempted for implementation of this technology at scale in the routine workflow of sleep centers. The field, however, is complex and presents unsolved challenges in a number of areas. Recent developments in computer science and artificial intelligence are nevertheless closing the gap. Technological advances are also opening new pathways for expanding our current understanding of the domain and its analysis.

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.

Utilizing Envelope Analysis of a Nasal Pressure Signal for Sleep Apnea Severity Estimation

Obstructive sleep apnea (OSA) severity assessment is based on manually scored respiratory events and their arbitrary definitions. Thus, we present an alternative method to objectively evaluate OSA severity independently of the manual scorings and scoring rules. A retrospective envelope analysis was conducted on 847 suspected OSA patients. Four parameters were calculated from the difference between the nasal pressure signal's upper and lower envelopes: average (AV), median (MD), standard deviation (SD), and coefficient of variation (CoV). We computed the parameters from the entirety of the recorded signals to perform binary classifications of patients using three different apnea-hypopnea index (AHI) thresholds (5-15-30). Additionally, the calculations were undertaken in 30-second epochs to estimate the ability of the parameters to detect manually scored respiratory events. Classification performances were assessed with areas under the curves (AUCs). As a result, the SD (AUCs ≥ 0.86) and CoV (AUCs ≥ 0.82) were the best classifiers for all AHI thresholds. Furthermore, non-OSA and severe OSA patients were separated well with SD (AUC = 0.97) and CoV (AUC = 0.95). Respiratory events within the epochs were identified moderately with MD (AUC = 0.76) and CoV (AUC = 0.82). In conclusion, envelope analysis is a promising alternative method by which to assess OSA severity without relying on manual scoring or the scoring rules of respiratory events.

More extensive white matter disruptions present in untreated obstructive sleep apnea than we thought: A large sample diffusion imaging study

Obstructive sleep apnea (OSA) may lead to white mater (WM) disruptions and cognitive deficits. However, no studies have investigated the full extent of the brain WM, and its associations with cognitive deficits in OSA remain unclear. We thus applied diffusion tensor imaging (DTI) tractography with multi-fiber models and used atlas-based bundle-specific approach to investigate the WM abnormalities for various tracts of the cerebral cortex, thalamus, brainstem, and cerebellum in patients with untreated OSA. We enrolled 100 OSA patients and 63 healthy controls. Fractional anisotropy (FA) and mean diffusivity (MD) values mapped on 33 regions of interest including WM tracts of cortex, thalamus, brainstem, and cerebellum were obtained from tractography-based reconstructions. We compared FA/MD values between groups and correlated FA/MD with clinical data in the OSA group after controlling for age and body mass index. OSA patients showed significantly lower FA values in multiple WM fibers including corpus callosum, inferior fronto-occipital fasciculus, middle/superior longitudinal fasciculi, thalamic radiations, and uncinate (FDR <0.05). Higher FA values were found in medial lemniscus of patients compared to controls (FDR <0.05). Lower FA values of rostrum of corpus callosum correlated with lower visual memory performance in OSA group (p < .005). Our quantitative DTI analysis demonstrated that untreated OSA could negatively impact the integrity of pathways more broadly, including brainstem structures such as medial lemniscus, in comparison to previous findings. Fiber tract abnormalities of the rostral corpus callosum were associated with impaired visual memory in untreated OSA may provide insights into the related pathomechanism.

Prognostic Implications of OSA in Acute Coronary Syndrome by Obesity Status

BACKGROUND

A close relationship exists between OSA and obesity. The impact of obesity on the prognostic significance of OSA in patients with acute coronary syndrome (ACS) remains unclear.

RESEARCH QUESTION

Do the effects of OSA on subsequent cardiovascular events in patients with ACS vary with obesity status?

STUDY DESIGN AND METHODS

This is a prospective cohort study. Patients 18 to 85 years of age and hospitalized for ACS were consecutively enrolled and underwent portable sleep monitoring after clinical stabilization. OSA was defined as an apnea hypopnea index ≥ 15 events/h. The primary end point was major adverse cardiovascular and cerebrovascular event (MACCE), including cardiovascular death, hospitalization for ACS, stroke, ischemia-driven revascularization, or hospitalization for heart failure.

RESULTS

Among 1,920 patients enrolled (84.5% men; mean age ± SD, 56.4 ± 10.5 years), 1,013 (52.8%) had OSA, and 718 (37.4%) were obese (BMI ≥ 28 kg/m²). During 2.9 years (1.5, 3.6) follow up, the incidence of MACCE was significantly higher in patients with obesity than in patients without obesity (hazard ratio [HR], 1.29; 95% CI, 1.06-1.58; P = .013). Although the prevalence of OSA was lower in patients without obesity than in those with obesity (43.9% vs 67.5%, P < .001), OSA independently predicted the incidence of MACCE only in patients without obesity (adjusted HR, 1.34; 95% CI, 1.03-1.75; P = .03), but not in patients with obesity (adjusted HR, 1.10; 95% CI, 0.78-1.55; P = .58). No significant interaction between obesity and OSA was noted (P for interaction = .35). The incremental risk associated with OSA in patients without obesity might be explained by more hospitalization for ACS and ischemia-driven revascularization.

INTERPRETATION

For patients with ACS, OSA was independently associated with an increased risk of subsequent events, particularly among patients without obesity. These findings highlight the importance of identifying OSA in nonobese patients with ACS.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT03362385; URL: www.

CLINICALTRIALS

gov.

Proteomic profiling for prediction of recurrent cardiovascular event in patients with acute coronary syndrome and obstructive sleep apnea: A post-hoc analysis from the ISAACC study

BACKGROUND

Obstructive sleep apnea (OSA) is associated with a recurrent cardiovascular event (CVE) risk in patients with a first acute coronary syndrome (ACS). However, the pathological pathways by which OSA promotes this deleterious role are unknown. We aim to explore the proteomic profile associated with OSA that promote the recurrent CVE risk in severe OSA patients with ACS without previous cardiovascular diseases.

METHODS

This post-hoc analysis from the ISAACC study (NCT01335087) included 86 patients admitted for ACS. Patients underwent respiratory polygraphy for the first 24-72 h to OSA diagnosis. We analyzed of 276 cardiovascular and inflammatory related proteins in baseline fasting plasma samples using proximity expression assay technology (Olink®, Sweden). Protein levels were compared between severe OSA patients with/without recurrent CVEs during follow-up. Random forest was conducted to select relevant proteins and generate a predictive model of recurrent CVE.

RESULTS

We included 86 patients (median age: 61 years, median BMI: 29.4 kg/m² and 86 % males) admitted for ACS with severe OSA (56 without recurrent CVE/30 with recurrent CVE). The plasma levels of 38 proteins were differentially expressed between groups. Additionally, 12 proteins had a significant association with respiratory polygraphy parameters. Three proteins discriminate with an AUC of 0.81 (95 % CI of 0.71-0.9) between severe OSA patients with and without recurrent CVE. These proteins were implicated in cell proliferation, communication and apoptosis, and regulation/response to the inflammatory and immune systems.

CONCLUSION

In ACS patients with severe OSA, a proteomic profile was associated with recurrent CVEs. This proteomic profile was correlated with specific OSA parameters from respiratory polygraphy. Proteomic profiling may provide an new direction for patient risk stratification and clinical management.

Altered intrinsic brain functional network dynamics in moderate-to-severe obstructive sleep apnea

OBJECTIVES

Obstructive sleep apnea (OSA) can affect temporal fluctuations in brain activity during rest. Dynamic functional connectivity (dFC) captures the fluctuations in FC during the resting state. This study aimed to investigate differences in dFC between moderate-to-severe OSA patients and healthy controls using resting-state functional magnetic resonance imaging (fMRI) and sliding-window analysis.

METHODS

Thirty-seven consecutive patients with moderate-to-severe OSA and 16 age- and sex-matched controls underwent resting-state fMRI in the morning following overnight polysomnography. The dynamics of aberrant FC between the groups and the correlation between the dynamics and clinical variables were evaluated.

RESULTS

dFC analysis revealed two distinct connectivity states: hypoconnected (State I) and hyperconnected (State II). In OSA patients, State I occurred 34% more often than in the controls and the occurrence of State II was proportionally reduced. The time in State I positively correlated with the Pittsburg Sleep Quality Index score in the OSA patients.

CONCLUSIONS

This study showed dFC alterations in moderate-to-severe OSA patients, which may serve as a novel physiological biomarker for OSA.

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.

Continuous positive airway pressure and adverse cardiovascular events in obstructive sleep apnea: are participants of randomized trials representative of sleep clinic patients?

STUDY OBJECTIVES

Randomized controlled trials (RCTs) have shown no reduction in adverse cardiovascular (CV) events in patients randomized to continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea (OSA). This study examined whether randomized study populations were representative of OSA patients attending a sleep clinic.

METHODS

Sleep clinic patients were 3,965 consecutive adults diagnosed with OSA by in-laboratory polysomnography from 2006 to 2010 at a tertiary hospital sleep clinic. Characteristics of these patients were compared with participants of five recent RCTs examining the effect of CPAP on adverse CV events in OSA. The percentage of patients with severe (apnea-hypopnea index, [AHI] ≥ 30 events/h) or any OSA (AHI ≥ 5 events/h) who met the eligibility criteria of each RCT was determined, and those criteria that excluded the most patients identified.

RESULTS

Compared to RCT participants, sleep clinic OSA patients were younger, sleepier, more likely to be female and less likely to have established CV disease. The percentage of patients with severe or any OSA who met the RCT eligibility criteria ranged from 1.2% to 20.9% and 0.8% to 21.9%, respectively. The eligibility criteria that excluded most patients were preexisting CV disease, symptoms of excessive sleepiness, nocturnal hypoxemia and co-morbidities.

CONCLUSIONS

A minority of sleep clinic patients diagnosed with OSA meet the eligibility criteria of RCTs of CPAP on adverse CV events in OSA. OSA populations in these RCTs differ considerably from typical sleep clinic OSA patients. This suggests that the findings of such OSA treatment-related RCTs are not generalizable to sleep clinic OSA patients.Randomized Intervention with Continuous Positive Airway Pressure in CAD and OSA (RICCADSA) trial, https://clinicaltrials.gov/ct2/show/NCT00519597, ClinicalTrials.gov number, NCT00519597.Usefulness of Nasal Continuous Positive Airway Pressure (CPAP) Treatment in Patients with a First Ever Stroke and Sleep Apnea Syndrome, https://clinicaltrials.gov/ct2/show/NCT00202501, ClinicalTrials.gov number, NCT00202501.Effect of Continuous Positive Airway Pressure (CPAP) on Hypertension and Cardiovascular Morbidity-Mortality in Patients with Sleep Apnea and no Daytime Sleepiness, https://clinicaltrials.gov/ct2/show/NCT00127348, ClinicalTrials.gov number, NCT00127348.Continuous Positive Airway Pressure (CPAP) in Patients with Acute Coronary Syndrome and Obstructive Sleep Apnea (OSA) (ISAACC), https://clinicaltrials.gov/ct2/show/NCT01335087, ClinicalTrials.gov number, NCT01335087.

Why could sleep medicine never do without polysomnography?

Given the clinical, methodological, conceptual and modelling challenges within the field of sleep medicine, polysomnography (PSG) has emerged as a central diagnostic tool over time. It has been highly beneficial to clinical practice over the years, thanks to the scientific data that it provides. More recently, sleep medicine has sought answers in precision medicine, broadening its quest for biomarkers that take into account environmental factors, big data, and nosological refinement. However, despite these innovative developments that are relatively independent of PSG, sleep medicine remains intimately associated with the latter. The aim of this paper was to show the central role of PSG for sleep medicine. Indeed, PSG is central to sleep medicine, not only due to the empirical data it provides but also because it represents an obligatory passage point (OPP) within the discipline. It crystallizes debate, pulls disparate types of data together, and facilitates a common language for the different specialties involved in sleep medicine, thereby lending legitimacy and credibility to the specialty. Thus, the role of polysomnography as an OPP in the field of sleep medicine reinforces the discipline, especially because critics (e.g., of the Apnea Hypopnea Index) cannot easily find fault with it.

Plasma profiling reveals a blood-based metabolic fingerprint of obstructive sleep apnea

INTRODUCTION

Obstructive sleep apnea (OSA) is a chronic, heterogeneous and multicomponent disorder with associated cardiovascular and metabolic alterations. Despite being the most common sleep-disordered breathing, it remains a significantly undiagnosed condition.

OBJECTIVE

We examined the plasma metabolome and lipidome of patients with suspected OSA, aiming to identify potential diagnosis biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease. Additionally, we evaluated the impact of continuous positive airway pressure (CPAP) treatment on the circulating metabolomic and lipidomic profile.

MATERIAL AND METHODS

Observational-prospective-longitudinal study including 206 consecutive subjects referred to the sleep unit. OSA was defined as an apnea-hypopnoea index ≥ 15 events/h after polysomnography (PSG). Patients treated with CPAP were followed-up for 6 months. Untargeted plasma metabolomic and lipidomic profiling was performed using liquid chromatography coulpled to massspectrometry.

RESULTS

A plasma profile composed of 33 metabolites (mainly glycerophospholipids and bile acids) was identified in OSA vs. non-OSA patients. This profile correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses disclosed a 4-metabolites-signature that provided an accuracy (95% CI) of 0.98 (0.95-0.99) for OSA detection. CPAP treatment was associated with changes in 5 plasma metabolites previously altered by OSA.

CONCLUSIONS

This analysis of the circulating metabolome and lipidome reveals a molecular fingerprint of OSA, which was modulated after effective CPAP treatment. Our results suggest blood-based biomarker candidates with potential application in the personalized management of OSA and suggest the activation of adaptive mechanisms in response to OSA-derived hypoxia.

Rapid eye movement predominant obstructive sleep apnoea: prognostic relevance and clinical approach

PURPOSE OF REVIEW

Rapid eye movement (REM) obstructive sleep apnoea (OSA) is a stage-specific OSA, in which obstructive events occur primarily during REM sleep. This review discusses REM-OSA definitions, its cardiometabolic correlates, associated comorbidities and treatment, and addresses diagnostic ambiguities and therapeutic pitfalls.

RECENT FINDINGS

Current evidence indicates that REM-OSA is prevalent among younger age groups and women and is independently associated with cardiometabolic complications, particularly hypertension, metabolic complications such as insulin resistance and metabolic syndrome. However, currently, there is no consensus on the accepted diagnostic criteria for REM-OSA. Available data suggest that adherence to positive airway pressure (PAP) therapy in patients with REM-OSA is suboptimal. Moreover, the currently accepted criteria for good adherence to PAP therapy of 4 h/night, 70% of the days may not be suitable for REM-OSA, as it will not cover most of the REM sleep periods. In addition, further research is needed to assess the impact of REM-OSA treatment on cardiometabolic outcomes.

SUMMARY

Patients with REM-OSA are at an increased risk of cardiometabolic complications. A high index of suspicion is needed to diagnose this disorder, and close follow-up is required to enhance adherence to therapy.

Cardiovascular risk and mortality prediction in patients suspected of sleep apnea: a model based on an artificial intelligence system

Objective. Cardiovascular disease (CVD) is one of the leading causes of death worldwide. There are many CVD risk estimators but very few take into account sleep features. Moreover, they are rarely tested on patients investigated for obstructive sleep apnea (OSA). However, numerous studies have demonstrated that OSA index or sleep features are associated with CVD and mortality. The aim of this study is to propose a new simple CVD and mortality risk estimator for use in routine sleep testing.Approach. Data from a large multicenter cohort of CVD-free patients investigated for OSA were linked to the French Health System to identify new-onset CVD. Clinical features were collected and sleep features were extracted from sleep recordings. A machine-learning model based on trees, AdaBoost, was applied to estimate the CVD and mortality risk score.Main results. After a median [inter-quartile range] follow-up of 6.0 [3.5-8.5] years, 685 of 5234 patients had received a diagnosis of CVD or had died. Following a selection of features, from the original 30 features, 9 were selected, including five clinical and four sleep oximetry features. The final model included age, gender, hypertension, diabetes, systolic blood pressure, oxygen saturation and pulse rate variability (PRV) features. An area under the receiver operating characteristic curve (AUC) of 0.78 was reached.Significance. AdaBoost, an interpretable machine-learning model, was applied to predict 6 year CVD and mortality in patients investigated for clinical suspicion of OSA. A mixed set of simple clinical features, nocturnal hypoxemia and PRV features derived from single channel pulse oximetry were used.

The Sleep Apnea-Specific Pulse-Rate Response Predicts Cardiovascular Morbidity and Mortality

Rationale: Randomized controlled trials have been unable to detect a cardiovascular benefit of continuous positive airway pressure in unselected patients with obstructive sleep apnea (OSA). We hypothesize that deleterious cardiovascular outcomes are concentrated in a subgroup of patients with a heightened pulse-rate response to apneas and hypopneas (ΔHR). Methods: We measured the ΔHR in the MESA (Multi-Ethnic Study of Atherosclerosis) (N = 1,395) and the SHHS (Sleep Heart Health Study) (N = 4,575). MESA data were used to determine the functional form of the association between the ΔHR and subclinical cardiovascular biomarkers, whereas primary analyses tested the association of the ΔHR with nonfatal or fatal cardiovascular disease (CVD) and all-cause mortality in longitudinal data from the SHHS. Measurements and Main Results: In the MESA, U-shaped relationships were observed between subclinical CVD biomarkers (coronary artery calcium, NT-proBNP [N-terminal prohormone BNP], and Framingham risk score) and the ΔHR; notably, a high ΔHR (upper quartile) was associated with elevated biomarker scores compared with a midrange ΔHR (25th-75th centiles). In the SHHS, individuals with a high ΔHR compared with a midrange ΔHR were at increased risk of nonfatal or fatal CVD and all-cause mortality (nonfatal adjusted hazard ratio [95% confidence interval (CI)], 1.60 [1.28-2.00]; fatal adjusted hazard ratio [95% CI], 1.68 [1.22-2.30]; all-cause adjusted hazard ratio [95% CI], 1.29 [1.07-1.55]). The risk associated with a high ΔHR was particularly high in those with a substantial hypoxic burden (nonfatal, 1.93 [1.36-2.73]; fatal, 3.50 [2.15-5.71]; all-cause, 1.84 [1.40-2.40]) and was exclusively observed in nonsleepy individuals. Conclusions: Individuals with OSA who demonstrate an elevated ΔHR are at increased risk of cardiovascular morbidity and mortality. This study identifies a prognostic biomarker for OSA that appears useful for risk stratification and patient selection for future clinical trials.

Effect of Upper Airway Stimulation in Patients with Obstructive Sleep Apnea (EFFECT): A Randomized Controlled Crossover Trial

Background: Several single-arm prospective studies have demonstrated the safety and effectiveness of upper airway stimulation (UAS) for obstructive sleep apnea. There is limited evidence from randomized, controlled trials of the therapy benefit in terms of OSA burden and its symptoms. Methods: We conducted a multicenter, double-blinded, randomized, sham-controlled, crossover trial to examine the effect of therapeutic stimulation (Stim) versus sham stimulation (Sham) on the apnea-hypopnea index (AHI) and the Epworth Sleepiness Scale (ESS). We also examined the Functional Outcomes of Sleep Questionnaire (FOSQ) on sleep architecture. We analyzed crossover outcome measures after two weeks using repeated measures models controlling for treatment order. Results: The study randomized 89 participants 1:1 to Stim (45) versus Sham (44). After one week, the AHI response rate was 76.7% with Stim and 29.5% with Sham, a difference of 47.2% (95% CI: 24.4 to 64.9, p < 0.001) between the two groups. Similarly, ESS was 7.5 ± 4.9 with Stim and 12.0 ± 4.3 with Sham, with a significant difference of 4.6 (95% CI: 3.1 to 6.1) between the two groups. The crossover phase showed no carryover effect. Among 86 participants who completed both phases, the treatment difference between Stim vs. Sham for AHI was −15.5 (95% CI −18.3 to −12.8), for ESS it was −3.3 (95% CI −4.4 to −2.2), and for FOSQ it was 2.1 (95% CI 1.4 to 2.8). UAS effectively treated both REM and NREM sleep disordered breathing. Conclusions: In comparison with sham stimulation, therapeutic UAS reduced OSA severity, sleepiness symptoms, and improved quality of life among participants with moderate-to-severe OSA.

Future Treatment of Sleep Disorders: Syndromic Approach Versus Management of Treatable Traits?

Sleep disorders are categorized in line with traditional taxonomy. This conventional approach allows adequate management of many patients. Failure of treatment, however, may be due to nonspecificity of symptoms, coincidental association between symptoms and pathophysiological endotype, as well as co-occurrence of different pathologic mechanisms affecting sleep. Complex phenotypes often do not respond well to standard therapeutic interventions. In these cases, the clinical workup should aim at identifying treatable traits that will likely improve under targeted therapy. The challenge for sleep medicine is to further develop this innovative approach that is driven by the principles of systems medicine.

Artificial intelligence in sleep medicine: an American Academy of Sleep Medicine position statement

None

Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during polysomnography (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level.

Effect of Continuous Positive Airway Pressure on Arrhythmia in Atrial Fibrillation and Sleep Apnea: A Randomized Controlled Trial

RATIONALE

Sleep apnea (SA) is highly prevalent in patients with atrial fibrillation (AF), and both conditions are associated with adverse cardiovascular outcomes.

OBJECTIVES

To determine the effect of continuous positive airway pressure (CPAP) on AF burden.

METHODS

This open-label, parallel-group, randomized, controlled trial included patients with paroxysmal AF and moderate-to-severe SA (apnea-hypopnea index ≥15). Eligible patients were randomized (1:1) to 5 months' treatment with CPAP plus usual care (CPAP, n=55) or usual care alone (control, n=54) by a computerised system. Outcome assessment was blinded. The planned primary outcome was the difference between CPAP treatment and control in change of AF burden (% of time in AF), as measured by implantable loop recorder.

MEASUREMENTS AND MAIN RESULTS

A total of 579 patients with paroxysmal AF had respiratory polygraphy, of whom 244 (42.1%) had moderate-to-severe SA. Of these, 158 (64.8%) participated in the CPAP run-in period, of whom 40 (25.3%) patients did not tolerate the treatment. One-hundred-eight patients were available for the primary analysis. The mean time in AF decreased from 5.6% at baseline to 4.1% during the last three months of CPAP intervention and from 5.0% to 4.3% in the control group. The adjusted between-group difference at follow-up was -0.63 (95% confidence interval: -2.55 to 1.30) percentage points; P=0.52. Seven serious adverse events (13%) occurred in the CPAP group, and two (4%) occurred in the control group.

CONCLUSIONS

In patients with paroxysmal AF and SA, treatment with CPAP did not result in a statistically significant reduction in the burden of AF. Clinical trial registration available at www.clinicaltrials.gov, ID: NCT02727192.

Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample

STUDY OBJECTIVES

Polysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to develop a clinically useful support vector machine (SVM)-based prediction model to identify patients with high probability of OSA for nonsleep specialist physician in clinical practice.

METHODS

The SVM model was developed using the features routinely collected at the clinical evaluation from 6,875 Chinese patients referred to sleep clinics for suspected OSA. Three apnea-hypopnea index (AHI) cutoffs, ≥5/h, ≥15/h, and ≥30/h were used to define the severity of OSA. The continuous and categorized features were selected separately and were further selected through stepwise forward feature selection. The modeling was achieved through fivefold cross-validation. The model discriminative ability was evaluated for the whole data set and four subgroups categorized with gender and age (<65 versus ≥65 years old [y/o]).

RESULTS

Two features were selected to predict AHI cutoff ≥5/h with six features selected for ≥15/h, and six features selected for ≥30/h, respectively, to reach Area under the Receiver Operating Characteristic (AUROC) 0.82, 0.80, and 0.78, respectively. The sensitivity was 74.14%, 75.18%, and 70.26%, while the specificity was 74.71%, 68.73%, and 70.30%, respectively. Compared to logistic regression, Berlin questionnaire, NoSAS Score, and Supersparse Linear Integer Model (SLIM) scoring system, the SVM model performs better with a more balanced sensitivity and specificity. The discriminative ability was best for male <65 y/o and modest for female ≥65 y/o.

CONCLUSION

Our model provides a simple and accurate modality for early identification of patients with OSA and may potentially help prioritize them for sleep study.

Functional outcomes of sleep predict cardiovascular intermediary outcomes and all-cause mortality in incident hemodialysis patients

STUDY OBJECTIVES

Patients with end-stage kidney disease (ESKD) commonly experience sleep disturbances. Sleep disturbance has been inconsistently associated with mortality risk in hemodialysis patients, but the burden of symptoms from sleep disturbances has emerged as a marker that may shed light on these discrepancies and guide treatment decisions. This study examines whether functional outcomes of sleep are associated with increased risk of intermediary CV outcomes or mortality among adults initiating hemodialysis.

METHODS

In 228 participants enrolled in the Predictors of Arrhythmic and Cardiovascular risk in ESRD (PACE) study, the Functional Outcomes of Sleep Questionnaire-10 (FOSQ-10), which assesses functional outcomes of daytime sleepiness, was administered within 6 months of enrollment. Intermediary CV outcomes included QTc [ms], heart rate variance [ms²], left ventricular mass index [g/m², LVMI], and left ventricular hypertrophy [LVH]. The association of FOSQ-10 score with all-cause mortality was examined using proportional hazards regression. Results: Mean age was 55 years, median BMI was 28 kg/m² (IQR 24,33), with 70% African Americans. Median FOSQ-10 score was 19.7 (IQR: 17.1,20.0). A 10% lower FOSQ-10 score was associated with increased mortality risk (HR 1.09, 95%CI 1.01-1.18). Lower FOSQ-10 scores were associated with longer QTc duration and lower heart rate variance, but not LVMI or LVH.

CONCLUSIONS

In adults initiating dialysis, sleep-related functional impairment is common and is associated with intermediary cardiovascular disease measures and increased mortality risk. Future studies should assess the impact of screening for sleep disturbances in ESKD patients to identify individuals at increased risk for cardiovascular complications and death.

Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes

BACKGROUND

Polysomnography (PSG) is the gold standard for diagnosis of sleep-disordered breathing (SDB). But it is impractical to perform PSG in all patients with diabetes. The objective was to develop a clinically easy-to-use prediction model to diagnosis SDB in patients with diabetes.

METHODS

A total of 440 patients with diabetes were recruited and underwent overnight PSG at West China Hospital. Prediction algorithms were based on oxygen desaturation index (ODI) and other variables, including sex, age, body mass index, Epworth score, mean oxygen saturation, and total sleep time. Two phase approach was employed to derivate and validate the models.

RESULTS

ODI was strongly correlated with apnea-hypopnea index (AHI) (rs = 0.941). In the derivation phase, the single cutoff model with ODI was selected, with area under the receiver operating characteristic curve (AUC) of 0.956 (95%CI 0.917-0.994), 0.962 (95%CI 0.943-0.981), and 0.976 (95%CI 0.956-0.996) for predicting AHI ≥5/h, ≥15/h, and ≥30/h, respectively. We identified the cutoff of ODI 5/h, 15/h, and 25/h, as having important predictive value for AHI ≥5/h, ≥15/h, and ≥30/h, respectively. In the validation phase, the AUC of ODI was 0.941 (95%CI 0.904-0.978), 0.969 (95%CI 0.969-0.991), and 0.949 (95%CI 0.915-0.983) for predicting AHI ≥5/h, ≥15/h, and ≥30/h, respectively. The sensitivity of ODI ≥5/h, ≥15/h, and ≥25/h was 92%, 90%, and 93%, respectively, while the specificity was 73%, 89%, and 85%, respectively.

CONCLUSIONS

ODI is a sensitive and specific tool to predict SDB in patients with diabetes.

MicroRNAs to guide medical decision-making in obstructive sleep apnea: A review

Obstructive sleep apnea (OSA) is a common and frequently underdiagnosed sleep disorder tightly associated with a wide range of morbidities and an elevated risk of the main causes of mortality. This condition represents a major public health concern due to its increasing worldwide prevalence and its serious pathological consequences. Current clinical guidelines support the importance of effective diagnosis and treatment of OSA and emphasize the unmet need for biomarkers to guide medical decision-making. In recent years, the noncoding transcriptome has emerged as a new opportunity for biomarker discovery. In this review, we provide a brief overview of the current understanding of noncoding RNAs, specifically microRNAs (miRNAs). Then, we carefully address the potential role of miRNAs as novel indicators for the management of both pediatric and adult OSA, highlighting their translational applicability, particularly for diagnosis and therapy allocation. Finally, we identify the gaps in the research state-of-art, discuss current methodological and conceptual limitations and propose future key steps and perspectives for the incorporation of miRNAs into routine clinical practice.

Excess brain age in the sleep electroencephalogram predicts reduced life expectancy

The brain age index (BAI) measures the difference between an individual's apparent "brain age" (BA; estimated by comparing EEG features during sleep from an individual with age norms), and their chronological age (CA); that is BAI = BA-CA. Here, we evaluate whether BAI predicts life expectancy. Brain age was quantified using a previously published machine learning algorithm for a cohort of participants ≥40 years old who underwent an overnight sleep electroencephalogram (EEG) as part of the Sleep Heart Health Study (n = 4877). Excess brain age (BAI >0) was associated with reduced life expectancy (adjusted hazard ratio: 1.12, [1.03, 1.21], p = 0.002). Life expectancy decreased by -0.81 [-1.44, -0.24] years per standard-deviation increase in BAI. Our findings show that BAI, a sleep EEG-based biomarker of the deviation of sleep microstructure from patterns normal for age, is an independent predictor of life expectancy.

Further Development of P4 Approach to Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a heterogeneous disorder. Cluster analysis has identified different physiologic subtypes with respect to symptoms. A difference exists in cardiovascular risk from OSA between the 7 subtypes identified. There are 3 basic subtypes replicated in multiple studies: (a) a group where insomnia is the main symptom; (b) an asymptomatic group; (c) a group with marked excessive sleepiness. The symptomatic benefit from treatment with nasal CPAP varies between these 3 subtypes. Data from the Sleep Heart Health Study reveal that the increased risk of cardiovascular disease from OSA occurs only in the excessively sleepy group.