Metrics of sleep apnea severity: beyond the apnea-hypopnea index

Endotyping, phenotyping and personalised therapy in obstructive sleep apnoea: are we there yet?

Obstructive sleep apnoea (OSA) was traditionally thought to be mainly caused by obesity and upper airway crowding, and hence OSA management was not personalised according to particular characteristics, with most symptomatic patients receiving continuous positive airway pressure therapy. Recent advances in our understanding have identified additional potential and distinct causes of OSA (endotypes), and subgroups of patients (phenotypes) with increased risk of cardiovascular complications. In this review, we discuss the evidence to date as to whether there are distinct clinically useful endotypes and phenotypes of OSA, and the challenges to the field in moving towards delivering personalised therapy in OSA.

Advanced Proteomics and Cluster Analysis for Identifying Novel Obstructive Sleep Apnea Subtypes before and after Continuous Positive Airway Pressure Therapy

Rationale: Studies have shown elevated inflammatory biomarkers in obstructive sleep apnea (OSA), but data after continuous positive airway pressure (CPAP) treatment are inconsistent. Objectives: We used the Olink proteomics panel to identify unique OSA clusters on the basis of inflammatory protein expression and assess the impact of CPAP therapy. Methods: Adults with newly diagnosed OSA had blood drawn at baseline and three to four months after CPAP. Samples were analyzed using the Olink proteomics platform, which measures 92 prespecified inflammatory proteins using proximity extension assay. Linear mixed-effects models were used to model changes in protein expression during the period of CPAP use, adjusting for batch, age, and sex. Unsupervised hierarchical clustering was performed to identify unique inflammatory OSA clusters on the basis of inflammatory biomarkers. Within-cluster impact of CPAP on inflammatory protein expression was assessed. Results: Among 46 patients, the mean age was 46 ± 12 years (22% women), mean body mass index was 31 ± 5 kg/m2, and mean respiratory disturbance index was 33 ± 17 events/hour. Unsupervised cluster and heatmap analysis revealed three unique proteomic clusters, with low (n = 21), intermediate (n = 19), and high (n = 6) inflammatory protein expression. After CPAP, there were significant within-cluster differences in protein expression. The low inflammatory cluster had a significant increase in protein expression (16%; P = 0.02), and the high inflammatory cluster had a significant decrease in protein expression (-20%; P = 0.003), more significant among those compliant with CPAP in the low (25%; P = 0.04) and high (-22%; P = 0.01) clusters. Conclusions: We identified three unique inflammatory clusters in patients with OSA using plasma proteomics, with a differential response to CPAP by cluster. Our results are hypothesis generating and require further investigation in larger longitudinal studies for enhanced cardiovascular risk profiling in OSA.

Enhancing OSA Assessment with Explainable AI. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-6. [PMID: 38083271 DOI: 10.1109/embc40787.2023.10341035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Explainable Artificial Intelligence (xAI) is a rapidly growing field that focuses on making deep learning models interpretable and understandable to human decision-makers. In this study, we introduce xAAEnet, a novel xAI model applied to the assessment of Obstructive Sleep Apnea (OSA) severity. OSA is a prevalent sleep disorder that can lead to numerous medical conditions and is currently assessed using the Apnea-Hypopnea Index (AHI). However, AHI has been criticized for its inability to accurately estimate the effect of OSAs on related medical conditions. To address this issue, we propose a human-centric xAI approach that emphasizes similarity between apneic events as a whole and reduces subjectivity in diagnosis by examining how the model makes its decisions. Our model was trained and tested on a dataset of 60 patients' Polysomnographic (PSG) recordings. Our results demonstrate that the proposed model, xAAEnet, outperforms models with traditional architectures such as convolutional regressor, autoencoder (AE), and variational autoencoder (VAE). This study highlights the potential of xAI in providing an objective OSA severity scoring method.Clinical relevance- This study provides an objective OSA severity scoring technique which could improve the management of apneic patients in clinical practice.

The role of oral appliance therapy in obstructive sleep apnoea

There is now widespread recognition within the world of sleep medicine of the increasing importance of dental sleep medicine and, in particular, the role of oral appliance therapy (OAT) in the management of adults with obstructive sleep apnoea (OSA). For the purpose of this review, the term OAT refers to a custom-made intra-oral appliance, which acts to posture the mandible in a forward and downward direction, away from its natural resting position. Whilst nasally applied continuous positive airway pressure remains the "gold standard" in nonsurgical OSA management, OAT remains the recognised alternative treatment.This review of OAT aims to provide an evidence-based update on our current understanding of their mode of action, exploring the potential anatomical and physiological impact of their use in preventing collapse of the upper airway; the current clinical practice guidelines, including the recently published National Institute of Clinical Excellence 2021 guidance, in conjunction with the American Academy of Sleep Medicine and American Academy of Dental Sleep Medicine; optimal design features, comparing the role of custom-made versus noncustom OAT devices and the importance of titration in achieving a dose-dependent effect; patient predictors, preference and adherence to OAT; its impact on a range of both patient- and clinician-centred health outcomes, with a comparison with CPAP; the limitations and side-effects of providing OAT; and, finally, a look at future considerations to help optimise the delivery and outcomes of OAT.

A Scoping Review on the Association between Night Eating Syndrome and Physical Health, Health-Related Quality of Life, Sleep and Weight Status in Adults

Night eating syndrome (NES) is characterised by recurrent episodes of night eating, evident through excessive food consumption after the evening meal or eating after awakening from sleep, often associated with significant distress and/or impairment in functioning. This scoping review was conducted according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews) guidelines. The search was conducted through the use of PubMed, Medline (OVID) and SCOPUS, to identify relevant articles published within the last 10 years. Search terms including "Night eating*" OR "NES" and Boolean phrases were used to refine the search. Additionally, the age of participants was restricted to 18 years and above, to ensure only adult participants were included. The abstracts of the remaining articles were used to screen for those that were relevant. From a total of 663 citations, 30 studies assessing night eating syndrome met the inclusion criteria to be included in the review. We found inconsistent associations of NES with higher body mass index (BMI), less physical activity, type 2 diabetes mellitus (T2DM) and poorer quality of sleep. These inconsistencies may have been due to the use of different measurement methods, lack of power from small sample sizes of NES in some studies and varying ages of participants, with associations being more likely to be found in higher-quality, representative populations than in university student samples. There were no associations of NES with T2DM in clinical populations and with hypertension, OSA and metabolic syndrome, but sample sizes were small. The impacts of NES on these medical conditions should be addressed in future, using well-sized and long-term studies involving representative populations of adults. In conclusion, NES likely has negative impacts on BMI, T2DM, physical activity, and sleep quality, which in turn may increase cardio-metabolic risk. However, further research is needed to elucidate the interaction between NES and its associated features.

Pulse Wave Amplitude Drops Index: A Biomarker of Cardiovascular Risk in Obstructive Sleep Apnea

Rationale: It is currently unclear which patients with obstructive sleep apnea (OSA) are at increased cardiovascular risk. Objective: To investigate the value of pulse wave amplitude drops (PWADs), reflecting sympathetic activations and vasoreactivity, as a biomarker of cardiovascular risk in OSA. Methods: PWADs were derived from pulse oximetry-based photoplethysmography signals in three prospective cohorts: HypnoLaus (N = 1,941), the Pays-de-la-Loire Sleep Cohort (PLSC; N = 6,367), and "Impact of Sleep Apnea syndrome in the evolution of Acute Coronary syndrome. Effect of intervention with CPAP" (ISAACC) (N = 692). The PWAD index was the number of PWADs (>30%) per hour during sleep. All participants were divided into subgroups according to the presence or absence of OSA (defined as ⩾15 or more events per hour or <15/h, respectively, on the apnea-hypopnea index) and the median PWAD index. Primary outcome was the incidence of composite cardiovascular events. Measurements and Main Results: Using Cox models adjusted for cardiovascular risk factors (hazard ratio; HR [95% confidence interval]), patients with a low PWAD index and OSA had a higher incidence of cardiovascular events compared with the high-PWAD and OSA group and those without OSA in the HypnoLaus cohort (HR, 2.16 [1.07-4.34], P = 0.031; and 2.35 [1.12-4.93], P = 0.024) and in the PLSC (1.36 [1.13-1.63], P = 0.001; and 1.44 [1.06-1.94], P = 0.019), respectively. In the ISAACC cohort, the low-PWAD and OSA untreated group had a higher cardiovascular event recurrence rate than that of the no-OSA group (2.03 [1.08-3.81], P = 0.028). In the PLSC and HypnoLaus cohorts, every increase of 10 events per hour in the continuous PWAD index was negatively associated with incident cardiovascular events exclusively in patients with OSA (HR, 0.85 [0.73-0.99], P = 0.031; and HR, 0.91 [0.86-0.96], P < 0.001, respectively). This association was not significant in the no-OSA group and the ISAACC cohort. Conclusions: In patients with OSA, a low PWAD index reflecting poor autonomic and vascular reactivity was independently associated with a higher cardiovascular risk.

Documentation of polysomnographic and home sleep apnea test interpretations: room for improvement?

STUDY OBJECTIVES

Obstructive sleep apnea (OSA), a heterogeneous disorder with many different presentations, is diagnosed with sleep studies. In standard clinical practice, test data are reviewed and scored, and interpretations are documented. Little standardization exists regarding what should be included in interpretations. We aimed to determine how consistently the documented interpretation included references to study quality parameters and accepted disease phenotypes.

METHODS

This study was performed at a single academic center in January 2021. From the literature, we formulated a list of test and titration quality criteria and OSA phenotypes that should be reflected in study interpretations, including total recording time, total sleep time, positionality, and supine rapid eye movement (REM) sleep during titration. We retrospectively reviewed the documentation of sleep studies to determine how often these factors were reflected in interpretation reports or clinical notes.

RESULTS

Of 134 patients in the study, 81 were diagnosed with OSA. A finding of inadequate total recording time during polysomnography or total sleep time on home sleep apnea testing was most often not documented. Positionality of OSA was not documented in 33% of applicable studies. The absence of supine REM sleep during positive airway pressure titration was not mentioned in 15% of interpretations.

CONCLUSIONS

The documentation of quality concerns and clinically important OSA phenotypes in interpretations was inconsistent. Documentation of meaningful test quality information and sleep apnea phenotypes might be improved with report standardization or by developing enhanced data displays.

CITATION

Herberts MB, Morgenthaler TI. Documentation of polysomnographic and home sleep apnea test interpretations: room for improvement? J Clin Sleep Med. 2023;19(6):1043-1049.

Not-So-Sweet Dreams: Plasma and IgG N-Glycome in the Severe Form of the Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a prevalent disease associated with increased risk for cardiovascular and metabolic diseases and shortened lifespan. The aim of this study was to explore the possibility of using N-glycome as a biomarker for the severe form of OSA. Seventy subjects who underwent a whole-night polysomnography/polygraphy and had apnea-hypopnea index (AHI) over 30 were compared to 23 controls (AHI under 5). Plasma samples were used to extract 39 glycan peaks using ultra-high-performance liquid chromatography (UPLC) and 27 IgG peaks using capillary gel electrophoresis (CGE). We also measured glycan age, a molecular proxy for biological aging. Three plasma and one IgG peaks were significant in a multivariate model controlling for the effects of age, sex, and body mass index. These included decreased GP24 (disialylated triantennary glycans as major structure) and GP28 (trigalactosylated, triantennary, disialylated, and trisialylated glycans), and increased GP32 (trisialylated triantennary glycan). Only one IgG glycan peak was significantly increased (P26), which contains biantennary digalactosylated glycans with core fucose. Patients with severe OSA exhibited accelerated biological aging, with a median of 6.9 years more than their chronological age (p < 0.001). Plasma N-glycome can be used as a biomarker for severe OSA.

Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review

Worldwide, population aging and unhealthy lifestyles have increased the incidence of high-risk health conditions such as cardiovascular diseases, sleep apnea, and other conditions. Recently, to facilitate early identification and diagnosis, efforts have been made in the research and development of new wearable devices to make them smaller, more comfortable, more accurate, and increasingly compatible with artificial intelligence technologies. These efforts can pave the way to the longer and continuous health monitoring of different biosignals, including the real-time detection of diseases, thus providing more timely and accurate predictions of health events that can drastically improve the healthcare management of patients. Most recent reviews focus on a specific category of disease, the use of artificial intelligence in 12-lead electrocardiograms, or on wearable technology. However, we present recent advances in the use of electrocardiogram signals acquired with wearable devices or from publicly available databases and the analysis of such signals with artificial intelligence methods to detect and predict diseases. As expected, most of the available research focuses on heart diseases, sleep apnea, and other emerging areas, such as mental stress. From a methodological point of view, although traditional statistical methods and machine learning are still widely used, we observe an increasing use of more advanced deep learning methods, specifically architectures that can handle the complexity of biosignal data. These deep learning methods typically include convolutional and recurrent neural networks. Moreover, when proposing new artificial intelligence methods, we observe that the prevalent choice is to use publicly available databases rather than collecting new data.

Oxygen resaturation rate is significantly associated with objectively assessed excessive daytime sleepiness in suspected obstructive sleep apnoea patients

INTRODUCTION

Commonly utilised metrics such as the apnoea-hypopnoea index show limited correlation to excessive daytime sleepiness (EDS). Oxygen desaturation parameters show better predictive power, however oxygen resaturation parameters have not yet been investigated. Oxygen resaturation may represent increased cardiovascular fitness and thus we hypothesized that a higher resaturation rate would be protective against EDS.

METHODS

Oxygen saturation parameters were computed via ABOSA software for adult patients referred for polysomnography and multiple sleep latency test in Israel Loewenstein hospital 2001-2011. EDS was defined as a mean sleep latency (MSL) below 8 min.

RESULTS

1629 patients (75% male, 53% obese, median age of 54 years) were included for analysis. The average desaturation event nadir was 90.4% and resaturation rate 0.59%/second. Median MSL was 9.6 min, and 606 patients met criteria for EDS. Patients who were younger, female, and with larger desaturations had significantly higher resaturation rates (p < 0.001). In multivariate models, adjusted for age, sex, body mass index, and average desaturation depth, resaturation rate showed a significant negative correlation with MSL (z-score standardised beta, -1 (95%CI -0.49, -1.52)), and significantly increased odds ratio (OR) of EDS (OR, 1.28 (95%CI 1.07, 1.53)). The beta associated with resaturation rate was larger, though non-significantly, than that of desaturation depth (difference 0.36 (95% CI -1.34, 0.62), p = 0.470).

CONCLUSION

Oxygen resaturation parameters show significant associations with objectively assessed EDS independent of desaturation parameters. Thus, resaturation and desaturation parameters may reflect differing underlying mechanistic pathways and both be considered novel and appropriate markers for assessing sleep-disordered breathing and associated outcomes.

Continuous positive airway pressure treatment of obstructive sleep apnea and hypertensive complications in high-risk pregnancy

PURPOSE

To evaluate whether or not continuous positive airway pressure (CPAP) treatment in pregnancies complicated by obstructive sleep apnea (OSA) is associated with a decrease in hypertensive disorders of pregnancy.

METHODS

This was a retrospective cohort study of perinatal outcomes in women who underwent objective OSA testing and treatment as part of routine clinical care during pregnancy. Where diagnostic criteria for OSA were reached (respiratory event index (REI) ≥ 5 events per hour), patients were offered CPAP therapy. Obstetrical outcomes were compared between the control group (no OSA), the group with untreated OSA (OSA diagnosed, not CPAP compliant), and the group with treated OSA (OSA diagnosed and CPAP compliant), with CPAP compliance defined as CPAP use ≥ 4 h, 70% of the time or greater. A composite hypertension outcome combined diagnoses of gestational hypertension (gHTN) and preeclampsia (PreE) of any severity.

RESULTS

The study comprised outcomes from 177 completed pregnancies. Our cohort was characterized by obesity, with average body mass indices > 35 kg/m2, and average maternal age > 30 years old. CPAP was initiated at an average gestational age of 23 weeks (12.1-35.3 weeks), and average CPAP use was 5.9 h (4-8.5 h). The composite hypertension outcome occurred in 43% of those without OSA (N = 77), 64% of those with untreated OSA (N = 77), and 57% of those with treated OSA, compliant with CPAP (N = 23) (p = 0.034).

CONCLUSION

Real-world data in this small study suggest that CPAP therapy may modulate the increased risk of hypertensive complications in pregnancies complicated by OSA.

Mattress-Based Non-Influencing Sleep Apnea Monitoring System

A mattress-type non-influencing sleep apnea monitoring system was designed to detect sleep apnea-hypopnea syndrome (SAHS). The pressure signals generated during sleep on the mattress were collected, and ballistocardiogram (BCG) and respiratory signals were extracted from the original signals. In the experiment, wavelet transform (WT) was used to reduce noise and decompose and reconstruct the signal to eliminate the influence of interference noise, which can directly and accurately separate the BCG signal and respiratory signal. In feature extraction, based on the five features commonly used in SAHS, an innovative respiratory waveform similarity feature was proposed in this work for the first time. In the SAHS detection, the binomial logistic regression was used to determine the sleep apnea symptoms in the signal segment. Simulation and experimental results showed that the device, algorithm, and system designed in this work were effective methods to detect, diagnose, and assist the diagnosis of SAHS.

Atrial Fibrillation in Obstructive Sleep Apnea Patients: Mechanisms, Risk Factors, and Management Strategies

Obstructive sleep apnea (OSA) is identified by apnea or hypopnea of the upper respiratory tract, which is associated with decreased oxygen saturation or awakening from sleep. A severe and prevalent association with OSA is atrial fibrillation (AF). This review article outlined numerous studies to understand the pathogenic pathways linked with developing OSA-associated AF and the therapeutic and preventive options available to reduce AF. The article looked for multiple risk factors common to OSA and AF. In addition, it has reviewed several therapeutic modalities such as continuous positive air pressure (CPAP), weight loss, upper airway stimulation (UAS), and other novel treatment options to find their efficiency in decreasing the outcome of AF in OSA patients. Since OSA often goes undiagnosed, this article emphasizes the importance of early screening in patients with AF and other comorbid conditions such as obesity, advanced age, diabetes, hypertension, and many more. The article focuses on the importance of preventive approaches that can be easily implemented, such as behavioral modifications.

Is obstructive sleep apnea a circadian rhythm disorder?

Obstructive sleep apnea is the most common sleep-related breathing disorder worldwide and remains underdiagnosed. Its multiple associated comorbidities contribute to a decreased quality of life and work performance as well as an increased risk of death. Standard treatment seems to have limited effects on cardiovascular and metabolic aspects of the disease, emphasising the need for early diagnosis and additional therapeutic approaches. Recent evidence suggests that the dysregulation of circadian rhythms, processes with endogenous rhythmicity that are adjusted to the environment through various cues, is involved in the pathogenesis of comorbidities. In patients with obstructive sleep apnea, altered circadian gene expression patterns have been demonstrated. Obstructive respiratory events may promote circadian dysregulation through the effects of sleep disturbance and intermittent hypoxia, with subsequent inflammation and disruption of neural and hormonal homeostasis. In this review, current knowledge on obstructive sleep apnea, circadian rhythm regulation, and circadian rhythm sleep disorders is summarised. Studies that connect obstructive sleep apnea to circadian rhythm abnormalities are critically evaluated. Furthermore, pathogenetic mechanisms that may underlie this association, most notably hypoxia signalling, are presented. A bidirectional relationship between obstructive sleep apnea and circadian rhythm dysregulation is proposed. Approaching obstructive sleep apnea as a circadian rhythm disorder may prove beneficial for the development of new, personalised diagnostic, therapeutic and prognostic tools. However, further studies are needed before the clinical approach to obstructive sleep apnea includes targeting the circadian system.

Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea

BACKGROUND

Mechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort is one of the main features of OSA and is associated with sympathetic overactivity, leading to increased vascular wall stiffness and remodelling. This study investigated associations between a new measure of respiratory effort (percentage of total sleep time spent with increased respiratory effort based on measurement of mandibular jaw movements (MJM): REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA.

METHODS

A machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices and MJM-derived parameters (including REMOV). The model was evaluated in a training subset and a test subset.

RESULTS

The analysis included 1127 patients: 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on 18 input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75 and specificity 0.83). Using the Shapley additive explanation method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index and neck circumference) and time with oxygen saturation <90%, ahead of standard PSG metrics (including the apnoea-hypopnoea index and oxygen desaturation index).

CONCLUSION

The proportion of sleep time spent with increased respiratory effort automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA.

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.

The role of artificial intelligence in the treatment of obstructive sleep apnea

BACKGROUND

The first-line and most common treatment for obstructive sleep apnea is nasal continuous positive airway pressure, which serves as a pneumatic splint to stabilize the upper airway and is effective when used with appropriate adherence. Continuous positive airway pressure compliance rates remain significantly low despite machine improvements and compliance intervention. Other treatment options include oral appliances, myofunctional therapy, and surgery. The aim of this project is to elucidate the role of artificial intelligence within improving the treatment of obstructive sleep apnea.

METHODS

Related publications between 1999 and 2022 were reviewed from PubMed and Embase databases utilizing search terms "artificial intelligence," "machine learning," "obstructive sleep apnea," and "treatment." Both authors independently screened the results by title/abstract then by full text review. 126 non-duplicate articles were screened, 38 articles were included after title and abstract screen and 30 articles were included after full text review. The inclusion criteria are outline in the PICO framework and involved studies focused on artificial intelligence application in guiding and evaluating obstructive sleep apnea treatment. Non-English articles were excluded.

RESULTS

The role of artificial intelligence in the treatment of OSA was categorized into the following sections: Predicting treatment outcomes of various treatment options, Improving/Evaluating treatment, and Personalizing treatment with improving understanding of underlying mechanisms of OSA.

CONCLUSIONS

Artificial intelligence has the capacity to improve the treatment of OSA through predicting outcomes of treatment options, evaluating the treatment the patient is currently utilizing and increasing understanding of the mechanisms that contribute to OSA disease process and physiology. Implementing AI in guiding treatment decisions allows patients to connect with treatment methods that would be most effective on an individual basis.

Effects of the combination of novel eye mask sleep position therapy device and oral appliance on positional OSA: A multi-arm, parallel-group randomized controlled trial

OBJECTIVES

We explored whether a new combination of eye mask sleep position therapy (SPT) and oral appliance therapy (OAT) was more effective at treating positional obstructive sleep apnea (POSA) than was the use of either device alone.

METHODS

In this randomized controlled trial, 60 POSA subjects diagnosed by standard polysomnography (PSG) were divided into three groups (ratio 1:1:1): SPT, OAT, and SPT combined with OAT (SOT). Participants underwent hospital-based follow-ups during months 1 and 6 after beginning treatment. The primary outcome was the decline in the apnea hypopnea index (AHI) at month 6. The secondary outcomes were changes in oxygen-derived parameters and the curative effect at month 6.

RESULTS

After 6 months of treatment, PSG showed that SPT, OAT, and SOT all improved the AHI and oxygen-derived parameters. The AHI decline was significantly better in the SOT group than in the OAT or SPT group (71.58% [50.56-84.84%] for SOT, 44.42% [21.23-67.52%] for OAT, and 33.24% [19.03-54.62%] for SPT at 6 months) (P = 0.018 and P < 0.001 for the comparisons of SOT with OAT and SOT with SPT, respectively). In terms of oxygen-derived parameters, only the sleep apnea-specific hypoxic burden (SASHB) improved more in the SOT group (76.89% [57.43-85.91%]) than in the other groups (44.73% [32.38-72.69%] for OAT and 41.82% [15.40-65.24%] for SPT, P = 0.002 and P < 0.001 for the comparisons of SOT with OAT and SOT with SPT, respectively). The efficacies of SPT, OAT, and SOT were 36.84%, 50%, and 80% at 6 months; the SOT group evidenced the highest value (rate ratio [95% confidence interval] 1.78 (1.05-3.03), P = 0.048 and 2.17 (1.16-4.07), P = 0.010, for the comparisons of SOT with OAT and SOT with SPT, respectively).

CONCLUSION

The combination of SPT and OAT was better than either treatment alone and may represent a good option for the treatment of POSA.

TRIAL REGISTRATION

Chinese Clinical Trial Registry; URL: http://www.chictr.org.cn/showproj.aspx?proj=42,852; No. ChiCTR1900025584.

Perioperative management of obstructive sleep apnea in lower extremity orthopedic procedures: A review of evidence to inform the development of a clinical pathway

Obstructive sleep apnea (OSA) is unrecognized in as high as 80% of patients before surgery. When untreated, OSA increases a surgical patient's propensity for airway collapse and sleep deprivation lending to a higher risk for emergent re-intubation, prolonged recovery time, escalation of care, hospital readmission, and longer length of stay. We have reviewed the evidence regarding diagnostic performance of OSA screening methods and the impact of perioperative management strategies on postoperative complications among patients with diagnosed or suspected OSA who are undergoing orthopedic surgery. We then integrated the data and recommendations from professional society guidelines to develop an evidence-based clinical care pathway to optimize the perioperative management of this surgical population. Successful management of patients with diagnosed or suspected OSA encompass five facets of care: screening, education, airway management, medications, and monitoring. This narrative review revealed two gaps in the evidence to inform management of patients undergoing orthopedic surgery 1) during the perioperative setting to include evidence-based interventions that reduce postoperative complications and 2) after discharge to an unmonitored environment. The clinical care pathway as well as perspectives for future research are discussed.

Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review

STUDY OBJECTIVES

Polysomnograms (PSGs) collect a plethora of physiologic signals across the night. However, few of these PSG data are incorporated into standard reports, and hence, ultimately, under-utilized in clinical decision making. Recently, there has been substantial interest regarding novel alternative PSG metrics that may help to predict obstructive sleep apnea (OSA)-related outcomes better than standard PSG metrics such as the apnea-hypopnea index. We systematically review the recent literature for studies that examined the use of alternative PSG metrics in the context of OSA and their association with health outcomes.

METHODS

We systematically searched EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews for studies published between 2000 and 2022 for those that reported alternative metrics derived from PSG in adults and related them to OSA-related outcomes.

RESULTS

Of the 186 initial studies identified by the original search, data from 31 studies were ultimately included in the final analysis. Numerous metrics were identified that were significantly related to a broad range of outcomes. We categorized the outcomes into 2 main subgroups: (1) cardiovascular/metabolic outcomes and mortality and (2) cognitive function- and vigilance-related outcomes. Four general categories of alternative metrics were identified based on signals analyzed: autonomic/hemodynamic metrics, electroencephalographic metrics, oximetric metrics, and respiratory event-related metrics.

CONCLUSIONS

We have summarized the current landscape of literature for alternative PSG metrics relating to risk prediction in OSA. Although promising, further prospective observational studies are needed to verify findings from other cohorts, and to assess the clinical utility of these metrics.

CITATION

Hajipour M, Baumann B, Azarbarzin A, et al. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med. 2023;19(2):225-242.

Gasotransmitter modulation of hypoglossal motoneuron activity

Obstructive sleep apnea (OSA) is characterized by sporadic collapse of the upper airway leading to periodic disruptions in breathing. Upper airway patency is governed by genioglossal nerve activity that originates from the hypoglossal motor nucleus. Mice with targeted deletion of the gene Hmox2, encoding the carbon monoxide (CO) producing enzyme, heme oxygenase-2 (HO-2), exhibit OSA, yet the contribution of central HO-2 dysregulation to the phenomenon is unknown. Using the rhythmic brainstem slice preparation that contains the preBötzinger complex (preBötC) and the hypoglossal nucleus, we tested the hypothesis that central HO-2 dysregulation weakens hypoglossal motoneuron output. Disrupting HO-2 activity increased the occurrence of subnetwork activity from the preBötC, which was associated with an increased irregularity of rhythmogenesis. These phenomena were also associated with the intermittent inability of the preBötC rhythm to drive output from the hypoglossal nucleus (i.e. transmission failures), and a reduction in the input-output relationship between the preBötC and the motor nucleus. HO-2 dysregulation reduced excitatory synaptic currents and intrinsic excitability in inspiratory hypoglossal neurons. Inhibiting activity of the CO-regulated H2S producing enzyme, cystathionine-γ-lyase (CSE), reduced transmission failures in HO-2 null brainstem slices, which also normalized excitatory synaptic currents and intrinsic excitability of hypoglossal motoneurons. These findings demonstrate a hitherto uncharacterized modulation of hypoglossal activity through mutual interaction of HO-2/CO and CSE/H2S, and support the potential importance of centrally derived gasotransmitter activity in regulating upper airway control.

Shorter respiratory event duration is related to prevalence of type 2 diabetes

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea-hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.

METHODS

Patients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.

RESULTS

A total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92-0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91-0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12-1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.

CONCLUSION

The average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.

T cell receptor repertoire as a novel indicator for identification and immune surveillance of patients with severe obstructive sleep apnea

Background

Obstructive sleep apnea (OSA) is the most prevalent sleep disturbance that affects approximately 936 million people worldwide and leads to extensively increased incidence of cardiovascular disease, metabolic syndrome, neurological disorders, and traffic accidents. Severe OSA patients suffer a significantly higher risk of complications and worse comorbidity outcomes. Notwithstanding, with inadequate access to contact diagnosis based on polysomnography (PSG), numerous patients with severe sleep apnea have not been diagnosed, especially during the pandemic. Moreover, how the T cell immunity is impaired in OSA remains largely unknown.

Methods

We primarily investigated the T cell receptor (TCR) repertoires of 50 patients with severe OSA, 23 patients with mild-to-moderate OSA, 23 patients without OSA, and 157 healthy individuals, from their peripheral blood. Firstly, we compared the clinical characteristics, blood cell counts, the ratio of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), and CD4+/CD8+T cell count between groups. Then, we compared the diversity, clonotypes, unique VJ alleles in patients with different disease severity. Furthermore, by identifying a series of disease-associated amino acid sequences, we employed a repeated hold-out machine learning strategy to explore the optimal algorithm for calculating the TCR repertoire characteristic Index (OSA-TCI). We further confirmed its relation with clinical features by linear regression analysis. Moreover, in followup of severe OSA patients who accepted adherent non-invasive ventilation, we assessed the changes of TCR repertoires, OSA-TCI, ESS, NLR, PLR, and CD4+/CD8+T after therapy.

Results

We found an unexpected increase in diversity and clonotypes in the TCR repertoire of OSA patients. Furthermore, we successfully developed a novel indicator termed OSA-TCI to summarize the unique repertoire alteration, which provided 90% of sensitivity and 87% of specificity in distinguishing severe OSA. In rationalization, OSA-TCI was found correlated to AHI, BMI, hemoglobin, N1, N2 percentage of sleep, snoring, smoking and lowest oxygen saturation, but only independently related to AHI (R = 0.603) and smoking (R = 0.22). Finally, we observed OSA-TCI in the eight severe patients decreased significantly after home noninvasive ventilation for three months during follow-up, consistently in line with the TCR repertoire improvement. In contrast, NLR, PLR, and the ratio of CD4+/CD8+T cell count were found useless to diagnose and therapeutic surveillance of severe OSA.

Conclusions

Our study is the first to unveil the TCR repertoire alteration in OSA, indicates possible insidious autoimmune mechanisms underlying OSA, and suggests that TCR repertoires serve as a convenient peripheral blood biomarker for OSA assessment without long-time contact and facility/instrument occupation. It may shed light on future diagnostic, immunological, pathophysiological, and prognostic research on OSA.

Disturbed Sleep is Not Good for the Heart: A Narrative Review

Sleep-related breathing disorders, including obstructive sleep apnea (OSA) and central sleep apnea (CSA), have a major impact on cardiovascular function. It has shown an association with hypertension, coronary artery disease, cardiac arrhythmias, sudden cardiac death, and congestive heart failure (CHF). This review focuses on highlighting the relationship between sleep apnea and CHF. We discuss the underlying pathophysiology, which involves the mechanical, neurohormonal, and inflammatory mechanisms; in addition, the similarities and differentiating clinical features of OSA in patients with CHF and without CHF. We have also discussed several treatment strategies, including weight loss, continuous positive airway pressure (CPAP), supplemental oxygen therapy, theophylline, acetazolamide, mandibular advancement device, and hypoglossal nerve stimulation (HGNS). We conclude that since there are several overlapping clinical features in patients with OSA with Heart Failure (HF) and without HF, early detection and treatment are crucial to decrease the risk of HF, coronary artery disease, and stroke.

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.

Anatomical determinants of upper airway collapsibility in obstructive sleep apnea: A systematic review and meta-analysis

Upper airway (UA) collapsibility is one of the key factors that determine the severity of obstructive sleep apnea (OSA). Interventions for OSA are aimed at reducing UA collapsibility, but selecting the optimal alternative intervention for patients who fail CPAP is challenging because currently no validated method predicts how anatomical changes affect UA collapsibility. The gold standard objective measure of UA collapsibility is the pharyngeal critical pressure (P_crit). A systematic literature review and meta-analysis were performed to identify the anatomical factors with the strongest correlation with P_crit. A search using the PRISMA methodology was performed on PubMed for English language scientific papers that correlated P_crit to anatomic variables and OSA severity as measured by the apnea-hypopnea index (AHI). A total of 29 papers that matched eligibility criteria were included in the quantitative synthesis. The meta-analysis suggested that AHI has only a moderate correlation with P_crit (estimated Pearson correlation coefficient r = 0.46). The meta-analysis identified four key anatomical variables associated with UA collapsibility, namely hyoid position (r = 0.53), tongue volume (r = 0.51), pharyngeal length (r = 0.50), and waist circumference (r = 0.49). In the future, biomechanical models that quantify the relative importance of these anatomical factors in determining UA collapsibility may help identify the optimal intervention for each patient. Many anatomical and structural factors such as airspace cross-sectional areas, epiglottic collapse, and palatal prolapse have inadequate data and require further research.

Do brachycephaly and nose size predict the severity of obstructive sleep apnea (OSA)? A sample-based geometric morphometric analysis of craniofacial variation in relation to OSA syndrome and the role of confounding factors

Obstructive sleep apnea is a common disorder that leads to sleep fragmentation and is potentially bidirectionally related to a variety of comorbidities, including an increased risk of heart failure and stroke. It is often considered a consequence of anatomical abnormalities, especially in the head and neck, but its pathophysiology is likely to be multifactorial in origin. With geometric morphometrics, and a large sample of adults from the Study for Health in Pomerania, we explore the association of craniofacial morphology to the apnea-hypopnea index used as an estimate of obstructive sleep apnea severity. We show that craniofacial size and asymmetry, an aspect of morphological variation seldom analysed in obstructive sleep apnea research, are both uncorrelated to apnea-hypopnea index. In contrast, as in previous analyses, we find evidence that brachycephaly and larger nasal proportions might be associated to obstructive sleep apnea severity. However, this correlational signal is weak and completely disappears when age-related shape variation is statistically controlled for. Our findings suggest that previous work might need to be re-evaluated, and urge researchers to take into account the role of confounders to avoid potentially spurious findings in association studies.

Incorporating neck circumference or neck-to-height ratio into the GOAL questionnaire to better detect and describe obstructive sleep apnea with application to clinical decisions

Objective

Although neck circumference (NC) and neck-to-height ratio (NHR) have been recognized as effective predictors of the clinical diagnosis of adult obstructive sleep apnea (OSA), they have not been included in the widely used GOAL questionnaire. Not coincidentally, the NHR has not been adequately considered in the development and validation of the STOP-Bang questionnaire, No-Apnea score and the NoSAS score. The motivation for the study was (1) to combine the GOAL questionnaire with the NC and NHR, respectively, to evaluate its predictive performance and (2) to compare it with the STOP-Bang questionnaire, the No-Apnea score, the NOSAS score, and the GOAL questionnaire.

Materials and methods

This retrospectively allocated cross-sectional study was conducted from November 2017 to March 2022 in adults who underwent nocturnal polysomnography (PSG) or home sleep apnea testing (HSAT). In this paper, the GOAL questionnaire was combined with the NC and NHR, respectively, using logistic regression. The performance of the six screening tools was assessed by discriminatory ability [area under the curve (AUC) obtained from receiver operating characteristic (ROC) curves] and a 2 × 2 league table [including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR−)] and compared under AHI ≥5/h, AHI ≥15/h, and AHI ≥30/h conditions.

Results

A total of 288 patients were enrolled in the study. For all severity OSA levels, the sensitivity of GOAL+NC ranged from 70.12 to 70.80%, and specificity ranged from 86.49 to 76.16%. The sensitivity of GOAL+NHR ranged from 73.31 to 81.75%, while specificity ranged from 83.78 to 70.86%. As for area under the curve (AUC) value under ROC curve, when AHI ≥5/h, compared with GOAL (0.806), No-Apnea (0.823), NoSAS (0.817), and GOAL+NC (0.815), GOAL+NHR (0.831) obtained the highest AUC value, but lower than STOP-Bang (0.837).

Conclusion

The predictive power of incorporating NC or NHR into the GOAL questionnaire was significantly better than that of the GOAL itself. Furthermore, GOAL+NHR was superior to GOAL+NC in predicting OSA severity and better than the No-Apnea score and the NoSAS score.

Circulating markers of oxidative stress and risk of incident cardiovascular events in obstructive sleep apnea

The identification of which patients with obstructive sleep apnea (OSA) are more likely to develop cardiovascular disease (CVD) remains a challenge. OSA causes oxidative stress (OS) which may contribute to CVD pathogenesis. Therefore, OS markers could be useful in risk-stratifying cardiovascular (CV) risk in OSA patients. The purpose of this pilot study was to assess whether three OS marker levels could be associated with incident CVD in suspected OSA patients. Morning plasma levels of 8-isoprostane, 8-hydroxy-2'-deoxyguanosine (8-OHdG) and superoxide dismutase (SOD) were measured in patients with suspected OSA referred for a polysomnogram (PSG). A composite outcome of CV events was defined by linkage with provincial administrative health databases. Cox proportional hazards models were used to assess the relationship between the levels of OS markers and events. 352 patients were included (mean age of 51.4 years, 68% male, median apnea hypopnea index of 16/h). Thirty-one first CV events occurred over an 8-year follow-up. In univariate or fully adjusted models, none of the OS markers were significantly associated with incident CV events (hazard ratio in adjusted models of: 1.25 (95% CI 0.56-2.80, p = 0.59), 1.15 (0.52-2.57, p = 0.73), 0.77 (0.37-1.61, p = 0.48), for 8-OHdG, 8-isoprostane and SOD; however, confidence intervals were wide. In this small preliminary study, oxidative stress markers were not significantly associated with risk of CV events. However, moderate associations between these markers and risk of CV events are possible and should be the focus of future larger studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00399-0.

CPAP for secondary cardiovascular prevention in obstructive sleep apnoea patients: not only one moon, but many stars

While continuous positive airway pressure (CPAP) therapy has a strong evidence base for the treatment of obstructive sleep apnoea (OSA), its impact on cardiovascular comorbidity remains unclear. This journal club reviews three recent randomised controlled trials aimed to evaluate the impact of CPAP therapy in secondary prevention of cerebrovascular and coronary heart disease (SAVE trial), comorbid coronary heart disease (RICCADSA trial) and in patients admitted with acute coronary syndrome (ISAACC trial). All three trials included patients with moderate-to-severe OSA and excluded patients with severe daytime sleepiness. When CPAP was compared with usual care, they all reported no difference in a similar primary composite end-point including death from cardiovascular disease, cardiac events, and strokes. These trials faced the same methodological challenges, including a low primary end-point incidence, the exclusion of sleepy patients, and a low CPAP adherence. Therefore, caution must be taken when broadening their results to the wider OSA population. Although randomised controlled trials provide a high level of evidence, they may not be sufficient to capture the diversity of OSA. Large-scale, real-world data may be able to provide a more rounded and generalisable picture of the effects of routine clinical use of CPAP on cardiovascular morbimortality.

Symptom subtypes and risk of incident cardiovascular and cerebrovascular disease in a clinic-based obstructive sleep apnea cohort

STUDY OBJECTIVES

Patients with obstructive sleep apnea (OSA) are at increased risk of cardiovascular and cerebrovascular disease, but predicting those at greatest risk is challenging. Using latent class analysis, patients with OSA can be placed into discrete symptom subtypes. The aim of this study was to determine whether symptom subtypes are associated with future cerebrovascular disease in patients with OSA in a clinic-based cohort.

METHODS

Patients with suspected OSA referred for a polysomnogram at an academic sleep center completed a comprehensive symptom survey. Patients with OSA (apnea-hypopnea index ≥ 5 events/h) were then placed into symptom subtypes based on responses to survey questions using latent class analysis. Cardiovascular events (stroke, myocardial infarction, unstable angina, bypass grafting, percutaneous coronary intervention, cardiac resynchronization therapy, defibrillation) occurring within 8 years of polysomnogram were identified by linkage to provincial health databases.

RESULTS

1,607 patients were studied, of whom 1,292 had OSA. One hundred forty first events occurred within 8 years of polysomnogram. Patients in the excessively sleepy with disturbed sleep subtype had a significantly increased rate of events compared to the minimally symptomatic subtype (hazard ratio = 2.25, 95% confidence interval: 1.02-4.94; P = .04). Two symptoms (restless legs and dozing off or sleeping while talking to someone) were significantly associated with future risk of cerebrovascular disease (hazard ratio = 1.68, 1.12-2.49 and 4.23, 1.61-11.16, respectively).

CONCLUSIONS

Patients with OSA in the clinic who are in the excessively sleepy with disturbed sleep subtype are significantly more likely to have a future cardiovascular event. This underscores the importance of understanding clinical heterogeneity and incorporating symptom subtype definitions into routine clinical care.

CITATION

Allen AJH, Jen R, Mazzotti DR, et al. Symptom subtypes and risk of incident cardiovascular and cerebrovascular disease in a clinic-based obstructive sleep apnea cohort. J Clin Sleep Med. 2022;18(9):2093-2102.

Turning Over a New Leaf-Pharmacologic Therapy in Obstructive Sleep Apnea

Despite extensive research, there is currently no approved drug for obstructive sleep apnea (OSA) treatment. OSA is a heterogeneous condition that involves multiple dominating pathophysiological traits. Drug development in this field needs to address both pathophysiological mechanisms and associated comorbid conditions in order to meet requirements for long-term therapy in OSA. Several drug candidates have been proposed and ongoing phase II trials that target various forms of sleep-disordered breathing have been initiated. The field is moving toward tailored therapeutic approaches in patients with OSA.

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.

Impact of Desaturation Patterns versus Apnea-Hypopnea Index in the Development of Cardiovascular Comorbidities in Obstructive Sleep Apnea Patients

Various phenotypes of obstructive sleep apnea (OSA) have been recently described and are poorly assessed by the commonly used polysomnographic indices, such as the apnea-hypopnea index and oxygen desaturation index. Nocturnal hypoxemia is the hallmark of OSA and new quantitative markers, as hypoxic burden or desaturation severity, have been shown to be associated with cardiovascular (CV) mortality. The purpose of this overview is to review the endophenotypical and clinical characteristics of OSA, the current metrics, and to analyze different measurements of hypoxemia in OSA to predict the cardiovascular impact (eg hypoxic burden). Potential interest of multidimensional models to classify OSA, such as BAVENO classification, is also discussed, with the goal of focusing on specific endophenotypes that are likely to develop CV comorbidities, in order to guide clinicians to more aggressive management of OSA in these individuals.

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.

Comparative associations of oximetry patterns in Obstructive Sleep Apnea with incident cardiovascular disease

STUDY OBJECTIVES

Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. The aim of this study was to compare associations of different oximetry patterns with incident CVD in men and women with OSA.

METHODS

Sleep Heart Health Study data were used for analysis. n = 2878 Participants (51.8% female; mean age 63.5 ± 10.5 years) with OSA (Apnea Hypopnea Index [AHI] ≥ 5 events/h) and no pre-existing CVD at baseline or within the first 2 years of follow-up were included. Four oximetry analysis approaches were applied: desaturation characteristics, time series analysis, power spectral density, and non-linear analysis. Thirty-one resulting oximetry patterns were compared to incident CVD using proportional hazards regression models adjusted for age, race, smoking, BMI, and sex.

RESULTS

There were no associations between OSA oximetry patterns and incident CVD in the total sample or in men. In women, there were some associations between incident CVD and time series analysis (e.g. SpO2 distribution standard deviation, HR 0.81, 95% CI 0.68-0.96, p = 0.014) and power spectral density oximetry patterns (e.g. Full frequency band mean HR 0.75; 95% CI 0.59-0.95; p = 0.015).

CONCLUSIONS

Comprehensive comparison of baseline oximetry patterns in OSA found none were related to development of CVD. There were no standout individual oximetry patterns that appear to be candidates for CVD risk phenotyping in OSA, but some showed marginal relationships with CVD risk in women. Further work is required to understand whether OSA phenotypes can be used to predict susceptibility to cardiovascular disease.

A Systematic Review of Sleep-Wake Disorder Diagnostic Criteria Reliability Studies

The aim of this article is to provide a systematic review of reliability studies of the sleep-wake disorder diagnostic criteria of the international classifications used in sleep medicine. Electronic databases (ubMed (1946-2021) and Web of Science (-2021)) were searched up to December 2021 for studies computing the Cohen's kappa coefficient of diagnostic criteria for the main sleep-wake disorder categories described in the principal classifications. Cohen's kappa coefficients were extracted for each main sleep-wake disorder category, for each classification subtype, and for the different types of methods used to test the degree of agreement about a diagnosis. The database search identified 383 studies. Fifteen studies were analyzed in this systematic review. Insomnia disorder (10/15) and parasomnia disorder (7/15) diagnostic criteria were the most studied. The reliability of all sleep-wake disorders presented a Cohen's kappa with substantial agreement (Cohen's kappa mean = 0.66). The two main reliability methods identified were "test-retest reliability" (11/15), principally used for International Classification of Sleep Disorders (ICSD), and "joint interrater reliability" (4/15), principally used for Diagnostic and Statistical Manual of Mental Disorders (DSM) subtype diagnostic criteria, in particularl, the DSM-5. The implications in terms of the design of the methods used to test the degree of agreement about a diagnosis in sleep medicine are discussed.

A Novel Quantitative Arousal-Associated EEG-Metric to Predict Severity of Respiratory Distress in Obstructive Sleep Apnea Patients

Respiratory arousals (RA) on polysomnography (PSG) are an important predictor of obstructive sleep apnea (OSA) disease severity. Additionally, recent reports suggest that more global indices of desaturation such as the hypoxic burden, namely the area under the curve (AUC) of the oxygen saturation (SaO2) PSG trace may better depict the desaturation burden in OSA. Here we investigated possible associations between a new metric, namely the AUC of the respiratory arousal electroencephalographic (EEG) recording, and already established parameters as the apnea/hypopnea index (AHI), arousal index and hypoxic burden in patients with OSA. In this data-driven study, polysomnographic data from 102 patients with OSAS were assessed (32 female; 70 male; mean value of age: 52 years; mean value of Body-Mass-Index-BMI: 31 kg/m2). The marked arousals from the pooled EEG signal (C3 and C4) were smoothed and the AUC was estimated. We used a support vector regressor (SVR) analysis to predict AHI, arousal index and hypoxic burden as captured by the PSG. The SVR with the arousal-AUC metric could quite reliably predict the AHI with a high correlation coefficient (0,58 in the training set, 0,65 in the testing set and 0,64 overall), as well as the hypoxic burden (0,62 in the training set, 0,58 in the testing set and 0,59 overall) and the arousal index (0,58 in the training set, 0,67 in the testing set and 0,66 overall). This novel arousal-AUC metric may predict AHI, hypoxic burden and arousal index with a quite high correlation coefficient and therefore could be used as an additional quantitative surrogate marker in the description of obstructive sleep apnea disease severity.

Barriers of artificial intelligence implementation in the diagnosis of obstructive sleep apnea

Background

Obstructive sleep apnea is a common clinical condition and has a significant impact on the health of patients if untreated. The current diagnostic gold standard for obstructive sleep apnea is polysomnography, which is labor intensive, requires specialists to utilize, expensive, and has accessibility challenges. There are also challenges with awareness and identification of obstructive sleep apnea in the primary care setting. Artificial intelligence systems offer the opportunity for a new diagnostic approach that addresses the limitations of polysomnography and ultimately benefits patients by streamlining the diagnostic expedition.

Main body

The purpose of this project is to elucidate the barriers that exist in the implementation of artificial intelligence systems into the diagnostic context of obstructive sleep apnea. It is essential to understand these challenges in order to proactively create solutions and establish an efficient adoption of this new technology. The literature regarding the evolution of the diagnosis of obstructive sleep apnea, the role of artificial intelligence in the diagnosis, and the barriers in artificial intelligence implementation was reviewed and analyzed.

Conclusion

The barriers identified were categorized into different themes including technology, data, regulation, human resources, education, and culture. Many of these challenges are ubiquitous across artificial intelligence implementation in any medical diagnostic setting. Future research directions include developing solutions to the barriers presented in this project.

Graphical abstract

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.

Towards Sleep Study Automation: Detection Evaluation of Respiratory-Related Events

The diagnosis of sleep disordered breathing depends on the detection of several respiratory-related events: apneas, hypopneas, snores, or respiratory event-related arousals from sleep studies. While a number of automatic detection methods have been proposed, reproducibility of these methods has been an issue, in part due to the absence of a generally accepted protocol for evaluating their results. With sleep measurements this is usually treated as a classification problem and the accompanying issue of localization is not treated as similarly critical. To address these problems we present a detection evaluation protocol that is able to qualitatively assess the match between two annotations of respiratory-related events. This protocol relies on measuring the relative temporal overlap between two annotations in order to find an alignment that maximizes their F1-score at the sequence level. This protocol can be used in applications which require a precise estimate of the number of events, total event duration, and a joint estimate of event number and duration. We assess its application using a data set that contains over 10,000 manually annotated snore events from 9 subjects, and show that when using the American Academy of Sleep Medicine Manual standard, two sleep technologists can achieve an F1-score of 0.88 when identifying the presence of snore events. In addition, we drafted rules for marking snore boundaries and showed that one sleep technologist can achieve F1-score of 0.94 at the same tasks. Finally, we compared our protocol against the protocol that is used to evaluate sleep spindle detection and highlighted the differences.