The different clinical faces of obstructive sleep apnoea: a cluster analysis

The PAP-RES algorithm: Defining who, why and how to use positive airway pressure therapy for OSA

Obstructive sleep apnea (OSA) is a common condition that is increasing in prevalence worldwide. Untreated OSA has a negative impact on health-related quality of life and is an independent risk factor for cardiovascular diseases. Despite available data suggesting that cardiovascular risk might differ according to clinical phenotypes and comorbidities, current approaches to OSA treatment usually take a "one size fits all" approach. Identification of cardiovascular vulnerability biomarkers and clinical phenotypes associated with response to positive airway pressure (PAP) therapy could help to redefine the standard treatment paradigm. The new PAP-RES (PAP-RESponsive) algorithm is based on the identification of OSA phenotypes that are likely to impact therapeutic goals and modalities. The paradigm shift is to propose a simplified approach that defines therapeutic goals based on OSA phenotype: from a predominantly "symptomatic phenotype" (individuals with high symptom burden that negatively impacts on daily life and/or accident risk or clinically significant insomnia) to a "vulnerable cardiovascular phenotype" (individuals with comorbidities [serious cardiovascular or respiratory disease or obesity] that have a negative impact on cardiovascular prognosis or a biomarker of hypoxic burden and/or autonomic nervous system dysfunction). Each phenotype requires a different PAP therapy care pathway based on differing health issues and treatment objectives.

Identification of quality-of-life clusters by the Quebec sleep questionnaire in sleep apnea patients

Patients with obstructive sleep apnea (OSA) may present different symptoms. The clinical importance of symptom clustering is supported by the difference in the incidence of cardiovascular diseases between hypersomnolent and non-hypersomnolent sleep apnea patients. The objective of this study was to determine if quality-of-life clusters could be identified from the Quebec Sleep Questionnaire (QSQ) in OSA patients. Latent class analysis was used to identify clusters in a multivariate analysis of dichotomic variables (presence or absence of symptoms) for each item the QSQ obtained from 147 patients who fulfilled the questionnaire during its validation and subsequent trials (75.5% males, age: 53 ± 11 years, body mass index (BMI): 30.4 ± 4.7 kg/m2, apnea/hypopnea index (AHI): 31.3 ± 14.8/h). Three clusters were identified. Quality of life was preserved in patients of cluster 1 (20.4% of patients). Patients of cluster 2 (32.6% of patients) had a moderately impaired quality of life, mainly due to daytime somnolence and poor sleep quality. Patients with impaired quality of life (cluster 3, 46.9% of patients) had an important impact in every domain of the QSQ with the highest sleepiness and daytime symptom impairments. Gender, BMI, and AHI did not differ between the three clusters. In conclusion, different quality-of-life clusters can be identified from the QSQ in sleep apnea patients. These clusters are similar to those reported previously. Further studies are needed to validate these clusters in larger and independent cohorts, to evaluate how they respond to OSA treatment, and their relationship with incident outcomes.

Differences in Polysomnographic and Craniofacial Characteristics of Catathrenia Phenotypes: A Cluster Analysis

Purpose

Catathrenia is a rare sleeping disorder characterized by repetitive nocturnal groaning during prolonged expirations. Patients with catathrenia had heterogeneous polysomnographic, comorbidity, craniofacial characteristics, and responses to treatment. Identifying phenotypes of catathrenia might benefit the exploration of etiology and personalized therapy.

Patients and Methods

Sixty-six patients diagnosed with catathrenia by full-night audio/video polysomnography seeking treatment with mandibular advancement devices (MAD) or continuous positive airway pressure (CPAP) were included in the cohort. Polysomnographic characteristics including sleep architecture, respiratory, groaning, and arousal events were analyzed. Three-dimensional (3D) and 2D craniofacial hard tissue and upper airway structures were evaluated with cone-beam computed tomography and lateral cephalometry. Phenotypes of catathrenia were identified by K-mean cluster analysis, and inter-group comparisons were assessed.

Results

Two distinct clusters of catathrenia were identified: cluster 1 (n=17) was characterized to have more males (71%), a longer average duration of groaning events (18.5±4.8 and 12.8±5.7s, p=0.005), and broader upper airway (volume 41,386±10,543 and 26,661±6700 mm3, p<0.001); cluster 2 (n=49) was characterized to have more females (73%), higher respiratory disturbance index (RDI) (median 1.0 [0.3, 2.0] and 5.2 [1.2, 13.3]/h, p=0.009), more respiratory effort-related arousals (RERA)(1 [1, 109] and 32 [13, 57)], p=0.005), smaller upper airway (cross-sectional area of velopharynx 512±87 and 339±84 mm2, p<0.001) and better response to treatment (41.2% and 82.6%, p=0.004).

Conclusion

Two distinct phenotypes were identified in patients with catathrenia, primary catathrenia, and catathrenia associated with upper airway obstruction, suggesting respiratory events and upper airway structures might be related to the etiology of catathrenia, with implications for its treatment.

Validation of the Sleepiz One + as a radar-based sensor for contactless diagnosis of sleep apnea

PURPOSE

The cardiorespiratory polysomnography (PSG) is an expensive and limited resource. The Sleepiz One + is a novel radar-based contactless monitoring device that can be used e.g. for longitudinal detection of nocturnal respiratory events. The present study aimed to compare the performance of the Sleepiz One + device to the PSG regarding the accuracy of apnea-hypopnea index (AHI).

METHODS

From January to December 2021, a total of 141 adult volunteers who were either suspected of having sleep apnea or who were healthy sleepers took part in a sleep study. This examination served to validate the Sleepiz One + device in the presence and absence of additional SpO2 information. The AHI determined by the Sleepiz One + monitor was estimated automatically and compared with the AHI derived from manual PSG scoring.

RESULTS

The correlation between the Sleepiz-AHI and the PSG-AHI with and without additional SpO2 measurement was rp = 0.94 and rp = 0,87, respectively. In general, the Bland-Altman plots showed good agreement between the two methods of AHI measurement, though their deviations became larger with increasing sleep-disordered breathing. Sensitivity and specificity for recordings without additional SpO2 was 85% and 88%, respectively. Adding a SpO2 sensor increased the sensitivity to 88% and the specificity to 98%.

CONCLUSION

The Sleepiz One + device is a valid diagnostic tool for patients with moderate to severe OSA. It can also be easily used in the home environment and is therefore beneficial for e.g. immobile and infectious patients. TRIAL REGISTRATION NUMBER AND DATE OF REGISTRATION FOR PROSPECTIVELY REGISTERED TRIALS: This study was registered on clinicaltrials.gov (NCT04670848) on 2020-12-09.

Characterisation of Symptom and Polysomnographic Profiles Associated with Cardiovascular Risk in a Sleep Clinic Population with Obstructive Sleep Apnoea

Aim

Recent data have identified specific symptom and polysomnographic profiles associated with cardiovascular disease (CVD) in patients with obstructive sleep apnoea (OSA). Our aim was to determine whether these profiles were present at diagnosis of OSA in patients with established CVD and in those with high cardiovascular risk. Participants in the Sydney Sleep Biobank (SSB) database, aged 30-74 years, self-reported presence of CVD (coronary artery disease, cerebrovascular disease, or heart failure). In those without established CVD, the Framingham Risk Score (FRS) estimated 10-year absolute CVD risk, categorised as "low" (<6%), "intermediate" (6-20%), or "high" (>20%). Groups were compared on symptom and polysomnographic variables.

Results

629 patients (68% male; mean age 54.3 years, SD 11.6; mean BMI 32.3 kg/m2, SD 8.2) were included. CVD was reported in 12.2%. A further 14.3% had a low risk FRS, 38.8% had an intermediate risk FRS, and 34.7% had a high risk FRS. Groups differed with respect to age, sex and BMI. OSA severity increased with established CVD and increasing FRS. The symptom of waking too early was more prevalent in the higher FRS groups (p=0.004). CVD and FRS groups differed on multiple polysomnographic variables; however, none of these differences remained significant after adjusting for age, sex, and BMI.

Conclusion

Higher CVD risk was associated with waking too early in patients with OSA. Polysomnographic variations between groups were explained by demographic differences. Further work is required to explore the influence of OSA phenotypic characteristics on susceptibility to CVD.

Follow-up assessment of sleep-related symptoms in patients after treatment for cancer: responses to continuous positive airway pressure treatment for co-morbid obstructive sleep apnoea

PURPOSE

To assess changes in sleep-related symptoms in patients with breast cancer, endometrial cancer and melanoma previously examined for sleep-related symptoms and the presence of PSG (polysomnography)-determined OSA, ≥ 3 years post-treatment; and to evaluate how CPAP treatment affects sleep-related symptoms in patients previously diagnosed with OSA.

METHODS

Patients initially recruited from breast cancer, endometrial cancer, and melanoma follow-up clinics at Westmead Hospital (Sydney, Australia) participated in this questionnaire-based study. Demographic and change in cancer status data were collected at follow-up. Patients completed the Pittsburgh Sleep Quality Index [poor sleep quality, PSQITOTAL ≥ 5au], Insomnia Severity Index, Epworth Sleepiness Scale and Functional Outcomes of Sleep Questionnaire; with ΔPSQITOTAL ≥ 3au indicating a clinically meaningful change in sleep quality over follow-up. PSG-determined OSA was confirmed using the apnoea-hypopnoea index. CPAP compliance was determined via self-report (CPAP compliant, CPAP; not compliant, non-CPAP). Logistic regression models determined if changes in cancer status, AHI, cancer subgroup or CPAP treatment was predictive of ΔPSQITOTAL ≥ 3 au and p < 0.05 indicated statistical significance.

RESULTS

The 60 patients recruited had breast cancer (n = 22), endometrial cancer (n = 15), and melanoma (n = 23). Cancer subgroups were similarly aged, and all had median follow-up PSQITOTAL scores ≥ 5au; breast cancer patients scoring the highest (p < 0.05). The CPAP group had significantly reduced PSQITOTAL scores (p = 0.02) at follow-up, unlike the non-CPAP group. Cancer subgroups had similar median ISITOTAL, ESSTOTAL and FOSQ-10TOTAL scores at follow-up, regardless of CPAP treatment. There were no significant predictors of ΔPSQITOTAL ≥ 3 au at follow-up.

CONCLUSION

Sleep-related symptoms persist in patients with cancer ≥ 3 years after treatment, although these symptoms improve with CPAP. Future studies should evaluate how CPAP affects survival outcomes in cancer patients with comorbid OSA.

Polysomnographic characteristics of excessive daytime sleepiness phenotypes in obstructive sleep apnea: results from the international sleep apnea global interdisciplinary consortium

STUDY OBJECTIVES

Excessive daytime sleepiness (EDS) is a major symptom of obstructive sleep apnea (OSA). Traditional polysomnographic (PSG) measures only partially explain EDS in OSA. This study analyzed traditional and novel PSG characteristics of two different measures of EDS among patients with OSA.

METHODS

Sleepiness was assessed using the Epworth Sleepiness Scale (>10 points defined as "risk of dozing") and a measure of general sleepiness (feeling sleepy ≥ 3 times/week defined as "feeling sleepy"). Four sleepiness phenotypes were identified: "non-sleepy," "risk of dozing only," "feeling sleepy only," and "both at risk of dozing and feeling sleepy."

RESULTS

Altogether, 2083 patients with OSA (69% male) with an apnea-hypopnea index (AHI) ≥ 5 events/hour were studied; 46% were "non-sleepy," 26% at "risk of dozing only," 7% were "feeling sleepy only," and 21% reported both. The two phenotypes at "risk of dozing" had higher AHI, more severe hypoxemia (as measured by oxygen desaturation index, minimum and average oxygen saturation [SpO2], time spent < 90% SpO2, and hypoxic impacts) and they spent less time awake, had shorter sleep latency, and higher heart rate response to arousals than "non-sleepy" and "feeling sleepy only" phenotypes. While statistically significant, effect sizes were small. Sleep stages, frequency of arousals, wake after sleep onset and limb movement did not differ between sleepiness phenotypes after adjusting for confounders.

CONCLUSIONS

In a large international group of patients with OSA, PSG characteristics were weakly associated with EDS. The physiological measures differed among individuals characterized as "risk of dozing" or "non-sleepy," while "feeling sleepy only" did not differ from "non-sleepy" individuals.

Clinical and Polysomnographic Characteristics of Adult Patients with Suspected Obstructive Sleep Apnea from Different Sleep Clinics at a Single Tertiary Center

INTRODUCTION

The characteristics of patients across different sleep clinics may vary because they selectively visit specific specialists on the basis of their primary symptoms. This study aimed to compare the clinical and polysomnography (PSG) features of patients with suspected obstructive sleep apnea (OSA) at three sleep specialty clinics (otolaryngology [ENT], neurology [NR], and psychiatry [PSY]).

METHODS

We retrospectively analyzed the medical records and PSG reports of adult patients who underwent full-night PSG between January 2022 and June 2023 at a tertiary medical center. The demographic, questionnaire, and PSG variables were compared.

RESULTS

Of the 407 patients, 83.0% exhibited sleep-disordered breathing (apnea-hypopnea index ≥ 5) with varying severity among the specialty pathways. Patients in the ENT group (n = 231) were the youngest and had the shortest sleep latency and most severe OSA markers with the highest positive airway pressure (PAP) acceptance, while those in the NR group (n = 79) had similar OSA-related PSG parameters to those in the ENT group but were older and had more OSA-related comorbidities, although their PAP acceptance was relatively low. The PSY group (n = 97) included a significant proportion of patients with normal or mild OSA, a female majority, high levels of depression, and subjective sleep distress.

CONCLUSION

Our results highlight the multidisciplinary aspects of sleep medicine and diverse patients, and specialist needs for diagnosing sleep disorders and PAP acceptance. Exploring the potential differences in prognosis and treatment responses across various sleep specialty clinics would facilitate the development of personalized strategies.

ERS International Congress 2023: highlights from the Sleep Disordered Breathing Assembly

The topic of sleep-related breathing disorders is always evolving, and during the European Respiratory Society (ERS) International Congress 2023 in Milan, Italy, the latest research and clinical topics in respiratory medicine were presented. The most interesting issues included new diagnostic tools, such as cardiovascular parameters and artificial intelligence, pathophysiological traits of sleep disordered breathing from routine polysomnography or polygraphy signals, and new biomarkers and the diagnostic approach in patients with excessive daytime sleepiness. This article summarises the most relevant studies and topics presented at the ERS International Congress 2023. Each section has been written by early career members of ERS Assembly 4.

Is the time below 90% of SpO2 during sleep (T90%) a metric of good health? A longitudinal analysis of two cohorts

BACKGROUND

Novel wireless-based technologies can easily record pulse oximetry at home. One of the main parameters that are recorded in sleep studies is the time under 90% of SpO2 (T90%) and the oxygen desaturation index 3% (ODI-3%). We assessed the association of T90% and/or ODI-3% in two different scenarios (a community-based study and a clinical setting) with all-cause mortality (primary outcome).

METHODS

We included all individuals from the Sleep Heart Health Study (SHHS, community-based cohort) and Santiago Obstructive Sleep Apnea (SantOSA, clinical cohort) with complete data at baseline and follow-up. Two measures of hypoxemia (T90% and ODI-3%) were our primary exposures. The adjusted hazard ratios (HRs) per standard deviation (pSD) between T90% and incident all-cause mortality (primary outcome) were determined by adjusted Cox regression models. In the secondary analysis, to assess whether T90% varies across clinical factors, anthropometrics, abdominal obesity, metabolic rate, and SpO2, we conducted linear regression models. Incremental changes in R2 were conducted to test the hypothesis.

RESULTS

A total of 4323 (56% male, median 64 years old, follow-up: 12 years, 23% events) and 1345 (77% male, median 55 years old, follow-up: 6 years, 11.6% events) patients were included in SHHS and SantOSA, respectively. Every 1 SD increase in T90% was associated with an adjusted HR of 1.18 [95% CI: 1.10-1.26] (p value < 0.001) in SHHS and HR 1.34 [95% CI: 1.04-1.71] (p value = 0.021) for all-cause mortality in SantOSA. Conversely, ODI-3% was not associated with worse outcomes. R2 explains 62% of the variability in T90%. The main contributors were baseline-mean change in SpO2, baseline SpO2, respiratory events, and age.

CONCLUSION

The findings suggest that T90% may be an important marker of wellness in clinical and community-based scenarios. Although this nonspecific metric varies across the populations, ventilatory changes during sleep rather than other physiological or comorbidity variables explain their variability.

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

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

Loop Gain as a Predictor of Blood Pressure Response in Patients Treated for Obstructive Sleep Apnea: Secondary Analysis of a Clinical Trial

Rationale: Randomized trials have shown inconsistent cardiovascular benefits from obstructive sleep apnea (OSA) therapy. Intermittent hypoxemia can increase both sympathetic nerve activity and loop gain ("ventilatory instability"), which may thus herald cardiovascular treatment benefit. Objectives: To test the hypothesis that loop gain predicts changes in 24-hour mean blood pressure (MBP) in response to OSA therapy and compare its predictive value against that of other novel biomarkers. Methods: The HeartBEAT (Heart Biomarker Evaluation in Apnea Treatment) trial assessed the effect of 12 weeks of continuous positive airway pressure (CPAP) versus oxygen versus control on 24-hour MBP. We measured loop gain and hypoxic burden from sleep tests and identified subjects with a sleepy phenotype using cluster analysis. Associations between biomarkers and 24-h MBP were assessed in the CPAP/oxygen arms using linear regression models adjusting for various covariates. Secondary outcomes and predictors were analyzed similarly. Results: We included 93 and 94 participants in the CPAP and oxygen arms, respectively. Overall, changes in 24-hour MBP were small, but interindividual variability was substantial (mean [standard deviation], -2 [8] and 1 [8] mm Hg in the CPAP and oxygen arms, respectively). Higher loop gain was significantly associated with greater reductions in 24-hour MBP independent of covariates in the CPAP arm (-1.5 to -1.9 mm Hg per 1-standard-deviation increase in loop gain; P ⩽ 0.03) but not in the oxygen arm. Other biomarkers were not associated with improved cardiovascular outcomes. Conclusions: To our knowledge, this is the first study suggesting that loop gain predicts blood pressure response to CPAP therapy. Eventually, loop gain estimates may facilitate patient selection for research and clinical practice. Clinical trial registered with www.clinicaltrials.gov (NCT01086800).

Heterogeneity of obstructive sleep apnea phenotypes after ischemic stroke: Outcome variation by cluster analysis

INTRODUCTION

Obstructive sleep apnea (OSA) is common but under-recognized after stroke. The aim of this study was to determine whether post-stroke phenotypic OSA subtypes are associated with stroke outcome in a population-based observational cohort.

METHODS

Ischemic stroke patients (n = 804) diagnosed with OSA (respiratory event index ≥10) soon after ischemic stroke were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) project. Functional, cognitive, and quality of life outcomes were assessed at 90 days post-stroke and long-term stroke recurrence was ascertained. Latent profile analysis was performed based on demographic and clinical features, pre-stroke sleep characteristics, OSA severity, and vascular risk factors. Regression models were used to assess the association between phenotypic clusters and outcomes.

RESULTS

Four distinct phenotypic clusters provided the best fit. Cluster 1 was characterized by more severe stroke; cluster 2 by severe OSA and higher prevalence of medical comorbidities; cluster 3 by mild stroke and mild OSA; and cluster 4 by moderate OSA and mild stroke. Compared to cluster 3 and after adjustment for baseline stroke severity, cluster 1 and cluster 2 had worse 90-day functional outcome and cluster 1 also had worse quality of life. No difference in cognitive outcome or stroke recurrence rate was noted by cluster.

CONCLUSION

Post-stroke OSA is a heterogeneous disorder with different clinical phenotypes associated with stroke outcomes, including both daily function and quality of life. The unique presentations of OSA after stroke may have important implications for stroke prognosis and personalized treatment strategies.

Review and perspective on sleep-disordered breathing research and translation to clinics

Sleep-disordered breathing, ranging from habitual snoring to severe obstructive sleep apnea, is a prevalent public health issue. Despite rising interest in sleep and awareness of sleep disorders, sleep research and diagnostic practices still rely on outdated metrics and laborious methods reducing the diagnostic capacity and preventing timely diagnosis and treatment. Consequently, a significant portion of individuals affected by sleep-disordered breathing remain undiagnosed or are misdiagnosed. Taking advantage of state-of-the-art scientific, technological, and computational advances could be an effective way to optimize the diagnostic and treatment pathways. We discuss state-of-the-art multidisciplinary research, review the shortcomings in the current practices of SDB diagnosis and management in adult populations, and provide possible future directions. We critically review the opportunities for modern data analysis methods and machine learning to combine multimodal information, provide a perspective on the pitfalls of big data analysis, and discuss approaches for developing analysis strategies that overcome current limitations. We argue that large-scale and multidisciplinary collaborative efforts based on clinical, scientific, and technical knowledge and rigorous clinical validation and implementation of the outcomes in practice are needed to move the research of sleep-disordered breathing forward, thus increasing the quality of diagnostics and treatment.

Obstructive sleep apnea heterogeneity and autonomic function: a role for heart rate variability in therapy selection and efficacy monitoring

Obstructive sleep apnea is a highly prevalent sleep-related breathing disorder, resulting in a disturbed breathing pattern, changes in blood gases, abnormal autonomic regulation, metabolic fluctuation, poor neurocognitive performance, and increased cardiovascular risk. With broad inter-individual differences recognised in risk factors, clinical symptoms, gene expression, physiological characteristics, and health outcomes, various obstructive sleep apnea subtypes have been identified. Therapeutic efficacy and its impact on outcomes, particularly for cardiovascular consequences, may also vary depending on these features in obstructive sleep apnea. A number of interventions such as positive airway pressure therapies, oral appliance, surgical treatment, and pharmaceutical options are available in clinical practice. Selecting an effective obstructive sleep apnea treatment and therapy is a challenging medical decision due to obstructive sleep apnea heterogeneity and numerous treatment modalities. Thus, an objective marker for clinical evaluation is warranted to estimate the treatment response in patients with obstructive sleep apnea. Currently, while the Apnea-Hypopnea Index is used for severity assessment of obstructive sleep apnea and still considered a major guide to diagnosis and managements of obstructive sleep apnea, the Apnea-Hypopnea Index is not a robust marker of symptoms, function, or outcome improvement. Abnormal cardiac autonomic modulation can provide additional insight to better understand obstructive sleep apnea phenotyping. Heart rate variability is a reliable neurocardiac tool to assess altered autonomic function and can also provide cardiovascular information in obstructive sleep apnea. Beyond the Apnea-Hypopnea Index, this review aims to discuss the role of heart rate variability as an indicator and predictor of therapeutic efficacy to different modalities in order to optimise tailored treatment for obstructive sleep apnea.

Cluster Analysis of World Trade Center Related Lower Airway Diseases

ABSTRACT

Introduction: Cluster analysis can classify without a priori assumptions the heterogeneous chronic lower airway diseases found in former workers at the World Trade Center (WTC) disaster site. Methods: We selected the first available chest computed tomography scan with quantitative computed tomography measurements on 311 former WTC workers with complete clinical, and spirometric data from their closest surveillance visit. We performed a nonhierarchical iterative algorithm K-prototype cluster analysis, using gap measure. Results: A five-cluster solution was most satisfactory. Cluster 5 had the healthiest individuals. In cluster 4, smoking was most prevalent and intense but there was scant evidence of respiratory disease. Cluster 3 had symptomatic subjects with reduced forced vital capacity impairment (low FVC). Clusters 1 and 2 had less dyspneic subjects, but more functional and quantitative computed tomography evidence of chronic obstructive pulmonary disease (COPD) in cluster 1, or low FVC in cluster 2. Clusters 1 and 4 had the highest proportion of rapid first-second forced expiratory volume decliners. Conclusions: Cluster analysis confirms low FVC and COPD/pre-COPD as distinctive chronic lower airway disease phenotypes on long-term surveillance of the WTC workers.

Insomnia and sleep-disordered breathing in FKRP-related limb-girdle muscular dystrophy R9. The Norwegian LGMDR9 cohort study (2020)

Limb-girdle muscular dystrophy R9 (LGMDR9) is a progressive and disabling genetic muscle disease. Sleep is relevant in the patient care as it impacts on health, functioning, and well-being. LGMDR9 may potentially affect sleep by physical or emotional symptoms, myalgia, or sleep-disordered breathing (SDB) through cardiorespiratory involvement. The objective was to investigate the occurrence of insomnia and unrecognized or untreated SDB in LGMDR9, associated factors, and relationships with fatigue and health-related quality of life (HRQoL). All 90 adults in a Norwegian LGMDR9 cohort received questionnaires on sleep, fatigue, and HRQoL. Forty-nine of them underwent clinical assessments and 26 without mask-based therapy for respiration disorders additionally underwent polysomnography (PSG) and capnometry. Among 77 questionnaire respondents, 31% received mask-based therapy. The prevalence of insomnia was 32% of both those with and without such therapy but was significantly increased in fatigued respondents (54% vs 21%). Insomnia levels correlated inversely with mental HRQoL. Among 26 PSG candidates, an apnea-hypopnea index (AHI) ≥ 5/h was observed in 16/26 subjects (≥ 15/h in 8/26) with median 6.8 obstructive apneas and 0.2 central apneas per hour of sleep. The AHI was related to advancing age and an ejection fraction < 50%. Sleep-related hypoventilation was detected in one subject. Fatigue severity did not correlate with motor function or nocturnal metrics of respiration or sleep but with Maximal Inspiratory Pressure (r = - 0.46). The results indicate that insomnia and SDB are underrecognized comorbidities in LGMDR9 and associated with HRQoL impairment and heart failure, respectively. We propose an increased attention to insomnia and SDB in the interdisciplinary care of LGMDR9. Insomnia and pulmonary function should be examined in fatigued patients.

Identification of obstructive sleep apnea in children with obesity: A cluster analysis approach

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous disorder with a prevalence of 25%-60% in children with obesity. There is a lack of diagnostic tools to identify those at high risk for OSA.

METHOD

Children with obesity, aged 8-19 years old, were enrolled into an ongoing multicenter, prospective cohort study related to OSA. We performed k-means cluster analysis to identify clinical variables which could help identify obesity related OSA.

RESULTS

In this study, 118 participants were included in the analysis; 40.7% were diagnosed with OSA, 46.6% were female and the mean (SD) body mass index (BMI) and age were 39.7 (9.6) Kg/m², and 14.4 (2.6) years, respectively. The mean (SD) obstructive apnea-hypopnea index (OAHI) was 11.0 (21.1) events/h. We identified two distinct clusters based on three clustering variables (age, BMI z-score, and neck-height ratio [NHR]). The prevalence of OSA in clusters 1 and 2, were 22.4% and 58.3% (p = 0.001), respectively. Children in cluster 2, in comparison to cluster 1, had higher BMI z-score (4.7 (1.1) versus 3.2 (0.7), p < 0.001), higher NHR (0.3 (0.02) versus 0.2 (0.01), p < 0.001) and were older (15.0 (2.2) versus 13.7 (2.9) years, p = 0.09), respectively. However, there were no significant differences in sex and OSA symptoms between the clusters. The results from hierarchical clustering were similar to k-means analysis suggesting that the resulting OSA clusters were stable to different analysis approaches.

INTERPRETATION

BMI, NHR, and age are easily obtained in a clinical setting and can be utilized to identify children at high risk for OSA.

Long-term health outcomes for patients with obstructive sleep apnea: placing the Agency for Healthcare Research and Quality report in context-a multisociety commentary

This multisociety commentary critically examines the Agency for Healthcare Research and Quality (AHRQ) final report and systematic review on long-term health outcomes in obstructive sleep apnea. The AHRQ report was commissioned by the Centers for Medicare & Medicaid Services and particularly focused on the long-term patient-centered outcomes of continuous positive airway pressure, the variability of sleep-disordered breathing metrics, and the validity of these metrics as surrogate outcomes. This commentary raises concerns regarding the AHRQ report conclusions and their potential implications for policy decisions. A major concern expressed in this commentary is that the AHRQ report inadequately acknowledges the benefits of continuous positive airway pressure for several established, long-term clinically important outcomes including excessive sleepiness, motor vehicle accidents, and blood pressure. While acknowledging the limited evidence for the long-term benefits of continuous positive airway pressure treatment, especially cardiovascular outcomes, as summarized by the AHRQ report, this commentary reviews the limitations of recent randomized controlled trials and nonrandomized controlled studies and the challenges of conducting future randomized controlled trials. A research agenda to address these challenges is proposed including study designs that may include both high quality randomized controlled trials and nonrandomized controlled studies. This commentary concludes by highlighting implications for the safety and quality of life for the millions of people living with obstructive sleep apnea if the AHRQ report alone was used by payers to limit coverage for the treatment of obstructive sleep apnea while not considering the totality of available evidence.

CITATION

Patil SP, Billings ME, Bourjeily G, et al. Long-term health outcomes for patients with obstructive sleep apnea: placing the Agency for Healthcare Research and Quality report in context-a multisociety commentary. J Clin Sleep Med. 2024;20(1):135-149.

Obstructive sleep apnea severity and prevalent atrial fibrillation in a sleep clinic cohort with versus without excessive daytime sleepiness

BACKGROUND

Obstructive sleep apnea (OSA) is associated with atrial fibrillation (AF) in cardiac cohorts. Less is known regarding the magnitude of this association in a sleep clinic cohort with vs. without excessive daytime sleepiness (EDS).

OBJECTIVES

To explore the association of OSA severity with AF in a sleep clinic cohort stratified by EDS.

PATIENTS AND METHODS

All consecutive adults (n = 3814) admitted to the Skaraborg Hospital, Sweden between Jan 2005 and December 2011 were registered in a local database, and the follow-up ended in December 2018. OSA was defined as an apnea-hypopnea index (AHI) ≥5 events/h. Mild OSA was defined as AHI ≥5 & AHI<15 events/h; moderate OSA as AHI ≥15 & AHI<30 events/h; and severe OSA as AHI ≥30 events/h. EDS was defined as an Epworth Sleepiness Scale score ≥11. We conducted cross-sectional analyzes of the prevalent AF across the OSA severity categories and logistic regression analyzes stratified by EDS.

RESULTS

In all, 202 patients (5.3%) had AF at baseline, 1.6% in no-OSA, 3.9% in mild OSA, 5.2% in moderate OSA, and 7.6% in severe OSA, respectively (p < 0.001). The stratified analyzes revealed that patients with severe OSA without EDS had an increased risk for prevalent AF (OR 2.54, 95% CI 1.05-6.16; p = 0.039) independent of the confounding factors.

CONCLUSIONS

There was an independent dose-response relationship between OSA and prevalent AF among the non-sleepy phenotype in this sleep clinic cohort. Since adherence to OSA treatment is challenging in the absence of EDS, these patients may have increased risk for adverse cardiovascular outcomes.

Anaerobic pathogens associated with OSA may contribute to pathophysiology via amino-acid depletion

BACKGROUND

The human microbiome is linked to multiple metabolic disorders such as obesity and diabetes. Obstructive sleep apnoea (OSA) is a common sleep disorder with several metabolic risk factors. We investigated the associations between the gut microbiome composition and function, and measures of OSA severity in participants from a prospective community-based cohort study: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

METHODS

Bacterial-Wide Association Analysis (BWAS) of gut microbiome measured via metagenomics with OSA measures was performed adjusting for clinical, lifestyle and co-morbidities. This was followed by functional analysis of the OSA-enriched bacteria. We utilized additional metabolomic and transcriptomic associations to suggest possible mechanisms explaining the microbiome effects on OSA.

FINDINGS

Several uncommon anaerobic human pathogens were associated with OSA severity. These belong to the Lachnospira, Actinomyces, Kingella and Eubacterium genera. Functional analysis revealed enrichment in 49 processes including many anaerobic-related ones. Severe OSA was associated with the depletion of the amino acids glycine and glutamine in the blood, yet neither diet nor gene expression revealed any changes in the production or consumption of these amino acids.

INTERPRETATION

We show anaerobic bacterial communities to be a novel component of OSA pathophysiology. These are established in the oxygen-poor environments characteristic of OSA. We hypothesize that these bacteria deplete certain amino acids required for normal human homeostasis and muscle tone, contributing to OSA phenotypes. Future work should test this hypothesis as well as consider diagnostics via anaerobic bacteria detection and possible interventions via antibiotics and amino-acid supplementation.

FUNDING

Described in methods.

Redefining Comorbid Insomnia and Sleep Apnea: The Association of Sleep Breathing Impairment and Insomnia with Incident Diabetes

Rationale: Obstructive sleep apnea (OSA) is a prevalent sleep disorder that is frequently comorbid with insomnia and often accompanied by metabolic diseases such as type 2 diabetes. Although the apnea-hypopnea index (AHI) is currently the diagnostic criterion for gauging the severity of OSA, the AHI has not consistently predicted incident diabetes. Objectives: To test whether a combined insomnia-OSA (COMISA) phenotype based on comorbid insomnia and sleep breathing impairment index (COMISA-SBII) predicts incident diabetes and to compare the association with an AHI definition of COMISA (COMISA-AHI) in the MrOS (Osteoporotic Fractures in Men) study. Methods: The study samples came from participants in the MrOS sleep study without diabetes at their baseline examination. The SBII was derived as the product of the duration of each respiratory event (apnea and hypopnea) and the accompanying desaturation area from baseline unattended polysomnography. A subgroup of individuals classified as having comorbid insomnia (difficulties falling asleep, waking up in the middle of the night and/or early morning awakenings >15 times per month, and daytime impairments) and sleep breathing impairment (greater than 50th percentile of SBII) were identified at baseline. The primary outcome was incident diabetes during the follow-up visits. Cox proportional models were built to assess the adjusted hazard ratios of COMISA-AHI and COMISA-SBII. Prediction model performances of incident diabetes were compared across different models. Results: A total of 2,365 men (mean age, 76 yr) without diabetes at baseline were included. During a median follow-up of 10.0 years, diabetes developed in 181. After adjusting for demographic characteristics, comorbidities, and behavioral risk factors, participants with COMISA-SBII had a higher risk of incident diabetes (hazard ratio, 1.82; 95% confidence interval, 1.15-2.89) than those without sleep disorders (those with an SBII ⩽13.17 and no insomnia). The result remained significant in the risk competing model. Compared with COMISA-AHI, the addition of COMISA-SBII to a crude model with established risk factors significantly improved the predictive value of incident diabetes. Conclusions: COMISA-SBII, but not COMISA-AHI, predicted incident diabetes after accounting for multiple covariates in a cohort of older men. A comorbid insomnia phenotype based on SBII plus insomnia symptoms may be an important clinical subtype.

Anatomical phenotype of obstructive sleep apnea patients based on cluster analysis

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

A nationwide study on the prevalence and contributing factors of obstructive sleep apnea in Iran

Reliable obstructive sleep apnea (OSA) prevalence information in Iran is lacking due to inconsistent local study results. To estimate OSA prevalence and identify clinical phenotypes, we conducted a nationally representative study using multi-stage random cluster sampling. We recruited 3198 individuals and extrapolated the results to the entire Iranian population using complex sample survey analyses. We identified 3 clinical phenotypes as "sleepy," "insomnia," and "restless legs syndrome (RLS)." The prevalence of OSA was 28.7% (95%CI: 26.8-30.6). The prevalence of "sleepy," "insomnia," and "RLS" phenotypes were 82.3%, 77.8%, and 36.5% in women, and 64.8%, 67.5%, and 17.9% in men, respectively. "Sleepy" and "insomnia" phenotypes overlapped the most. Age (OR: 1.9), male sex (OR: 3.8), BMI (OR: 1.13), neck circumference (OR: 1.3), RLS (OR: 2.0), and insomnia (OR: 2.3) were significant OSA predictors (p-values: 0.001). In men, "sleepy" phenotype was associated with youth and unmarried status but not in women. The "insomnia" phenotype was associated with shorter sleep duration in women; cardiovascular diseases (CVD), urban residency, and shorter sleep duration in men. "RLS" phenotype was associated with shorter sleep duration and CVD in women and older age, lower educational level, CVD, and hypertension in men. The findings point to the need for funding of OSA screening in Iran, for a different assessment of men and women, and for future sleep research to consider overlapping phenotypes.

Polysomnographic Phenotypes of Obstructive Sleep Apnea in a Real-Life Cohort: A Pathophysiological Approach

INTRODUCTION

Obstructive sleep apnea (OSA) is heterogeneous and complex, but its severity is still based on the apnea-hypoapnea index (AHI). The present study explores using cluster analysis (CA), the additional information provided from routine polysomnography (PSG) to optimize OSA categorization.

METHODS

Cross-sectional study of OSA subjects diagnosed by PSG in a tertiary hospital sleep unit during 2016-2020. PSG, demographical, clinical variables, and comorbidities were recorded. Phenotypes were constructed from PSG variables using CA. Results are shown as median (interquartile range).

RESULTS

981 subjects were studied: 41% females, age 56 years (45-66), overall AHI 23events/h (13-42) and body mass index (BMI) 30kg/m2 (27-34). Three PSG clusters were identified: Cluster 1: "Supine and obstructive apnea predominance" (433 patients, 44%). Cluster 2: "Central, REM and shorter-hypopnea predominance" (374 patients, 38%). Cluster 3: "Severe hypoxemic burden and higher wake after sleep onset" (174 patients, 18%). Based on classical OSA severity classification, subjects are distributed among the PSG clusters as severe OSA patients (AHI≥30events/h): 46% in cluster 1, 17% in cluster 2 and 36% in cluster 3; moderate OSA (15≤AHI<30events/h): 57% in cluster 1, 34% in cluster 2 and 9% in cluster 3; mild OSA (5≤AHI<15events/h): 28% in cluster 1, 68% in cluster 2 and 4% in cluster 3.

CONCLUSIONS

The CA identifies three specific PSG phenotypes that do not completely agree with classical OSA severity classification. This emphasized that using a simplistic AHI approach, the OSA severity is assessed by an incorrect or incomplete analysis of the heterogeneity of the disorder.

Clinical phenotypes of obstructive sleep apnea: a cluster analysis based on sleep perception and sleep quality

PURPOSE

To determine obstructive sleep apnea (OSA) phenotypes using cluster analysis including variables of sleep perception and sleep quality and to further explore factors correlated with poor sleep quality in different clusters.

METHODS

This retrospective study included patients with OSA undergoing polysomnography (PSG) between December 2020 and April 2022. Two-step cluster analysis was performed to detect distinct clusters using sleep perception variables including discrepancy in total sleep time (TST), sleep onset latency (SOL), and wakefulness after sleep onset (WASO); objective TST, SOL, and WASO; and sleep quality. One-way analysis of variance or chi-squared tests were used to compare clinical and PSG characteristics between clusters. Binary logistic regression analyses were used to explore factors correlated with poor sleep quality.

RESULTS

A total of 1118 patients were included (81.6% men) with mean age ± SD 43.3 ± 13.1 years, Epworth sleepiness score, 5.7 ± 4.4, and insomnia severity index 3.0 ± 2.4. Five distinct OSA clusters were identified: cluster 1 (n = 254), underestimated TST; cluster 2 (n = 158), overestimated TST; cluster 3 (n = 169), overestimated SOL; cluster 4 (n = 155), normal sleep discrepancy and poor sleep quality; and cluster 5 (n = 382), normal sleep discrepancy and good sleep quality. Patients in cluster 2 were older, more commonly had hypertension, and had the lowest apnea-hypopnea index and oxygen desaturation index. Age and sleep efficiency were correlated with poor sleep quality in clusters 1, 2, and 5, and also AHI in cluster 2.

CONCLUSION

Subgroups of patients with OSA have different patterns of sleep perception and quality that may help us to further understand the characteristics of sleep perception in OSA and provide clues for personalized treatment.

Screening practices for obstructive sleep apnea in healthy community people: a Chinese community-based study

Background

Owing to the lack of clear guidelines, the significance of obstructive sleep apnea (OSA) screening in healthy community people is unclear. This study aimed to screen for OSA in a healthy community population and provide a basis for its screening.

Methods

Permanent residents from five communities in the coastal and mountainous areas of south China were selected. The screening process included demographic and sleep questionnaire surveys, and an OSA screening. To compare the prevalence and risk factors of OSA in different areas, a type IV wearable intelligent sleep monitor (WISM) was used for screening.

Results

A total of 3,650 participants completed all studies, with a mean age of 53.81±12.71 years. In addition, 4,318 participants completed the OSA screening within 30 days, and the objective screening speed was 200 people per day. The recovery rate of the screening equipment was 99.37% (4,291/4,318), the screening success rate was 89.63% (3,846/4,291), and the rejection rate was 2.7% (120/4,438). The prevalence of high-risk OSA screened using the Stop-Bang questionnaire was 42.8% (1,563/3,650) and that screened using the device was 30.7% (1,119/3,650). The prevalence of OSA screened using the Stop-Bang questionnaire was higher than that screened using the device (P<0.01). Further analysis of sleep quality and daytime sleepiness showed that 47.6% (1,736/3,650) of the community population had good sleep quality and 6.6% (240/3,650) had daytime sleepiness. Age, sex, body mass index (BMI), neck circumference, and hypertension were risk factors for OSA in the community population.

Conclusions

The use of objective type IV sleep detection equipment to screen a large sample population in the community in a short time is feasible. The prevalence of high-risk OSA screened using the Stop-Bang questionnaire was higher than that screened using the objective screening device.

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

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

Unmasking Heterogeneity of Sleep Apnea

Sleep apnea is heterogeneous in multiple dimensions. There are different physiological risk factors that may have clinical relevance. However, assessing them is challenging. An approach to ascertain them using a simple model of ventilatory control has been proposed. It is based, however, on untenable assumptions. There are limited validation data and reproducibility is not stellar. There are also different symptom subtypes. They have been found in multiple population-based and clinical cohorts worldwide. Symptomatic benefit from therapy is most marked in the excessively sleepy subtype. This group may also be the group at increased CV risk from obstructive sleep apnea.

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.

International Consensus Statement on Obstructive Sleep Apnea

BACKGROUND

Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).

METHODS

Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.

RESULTS

The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.

CONCLUSION

This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Cardiovascular Outcomes in Adults with Coronary Artery Disease and Obstructive Sleep Apnea with versus without Excessive Daytime Sleepiness in the RICCADSA Cinical Trial

Rationale: Recent randomized controlled trials did not show cardiovascular benefits of continuous positive airway pressure (CPAP) in adults with coronary artery disease (CAD) and obstructive sleep apnea (OSA) in intention-to-treat analyses. It has been argued that exclusion of patients with OSA with excessive daytime sleepiness (EDS), who may be most likely to benefit from CPAP treatment, may be a reason for the null results. Objectives: We addressed 1) the effect of concomitant EDS on adverse outcomes in patients with CAD and OSA; and 2) whether the cardiovascular benefit of CPAP adherence differs between individuals with versus without EDS. Methods: This was a secondary analysis of the RICCADSA (Randomized Intervention with CPAP in CAD and Obstructive Sleep Apnea) trial, conducted in Sweden between 2005 and 2013. Data were analyzed from 155 patients with CAD with OSA (apnea-hypopnea index ⩾ 15/h) and EDS (Epworth Sleepiness Scale score ⩾ 10), who were allocated to CPAP and 244 patients without EDS (ESS < 10), who were randomized to CPAP or no CPAP. Patients who were allocated to no CPAP or were nonadherent (CPAP usage < 4 h/night) were compared with adherent patients (CPAP usage ⩾ 4 h/night) at 1-year follow-up. Inverse probability of treatment weighting was applied to mimic randomization of EDS. The primary endpoint was the first event of repeat revascularization, myocardial infarction, stroke, or cardiovascular mortality. Results: The median follow-up was 52.2 months. The incidence of the primary endpoint did not differ significantly between the EDS versus no-EDS groups in the entire cohort. Within the adherent group, patients without EDS had a significantly decreased risk compared with patients with EDS (adjusted hazard ratio, 0.41; 95% confidence interval, 0.20-0.85; P = 0.02). Conclusions: Adverse cardiovascular outcomes did not differ by degrees of EDS for patients with CAD with OSA who were untreated or nonadherent to treatment. CPAP use, at least 4 h/night, was associated with reduced adverse outcomes in participants without EDS. Clinical trial registered with www.clinicaltrials.gov (NCT00519597).

Chronic pain is common and worsens daytime sleepiness, insomnia, and quality of life in veterans with obstructive sleep apnea

STUDY OBJECTIVES

Chronic noncancer pain (CP) commonly co-occurs with obstructive sleep apnea (OSA) and may contribute to greater symptom burden. The study aims were to (1) characterize CP among veterans with OSA and (2) examine differences in sleepiness (Epworth Sleepiness Scale), insomnia symptoms (Insomnia Severity Index), and quality of life (Short Form Health Survey-20) in veterans with OSA with or without pre-existing CP.

METHODS

An observational, cross-sectional, study of 111 veterans with newly diagnosed, untreated OSA was conducted. Descriptive statistics characterized the sample and comorbid CP outcomes. Regression analyses were performed to investigate associations between self-reported CP and sleep-related symptoms or quality of life while controlling for potential confounders.

RESULTS

CP was reported by 69.5% (95% confidence interval: 61.8%, 76.2%) of participants. Having CP was associated with increased Epworth Sleepiness Scale (12.7 ± 5.5 vs 10.2 ± 5.2; P = .021) and Insomnia Severity Index scores (18.1 ± 6.2 vs 13.7 ± 7.4; P = .002), and worse quality of life across all Short Form Health Survey-20 domains.

CONCLUSIONS

There is a high prevalence of CP among veterans with OSA and symptom burden is higher in patients with OSA and CP. Future investigations should address symptom response and burden to OSA treatment in comorbid OSA and CP to guide outcome expectancies and residual OSA symptom treatment plans.

CITATION

Saconi B, Kuna ST, Polomano RC, Compton PA, Keenan BT, Sawyer AM. Chronic pain is common and worsens daytime sleepiness, insomnia, and quality of life in veterans with obstructive sleep apnea. J Clin Sleep Med. 2023;19(6):1121-1132.

Examining the feasibility of adult quality-of-life measurement for obstructive sleep apnea in clinical settings: what is the path forward for sleep centers?

Quality of life (QoL) is one of the outcomes that can be measured as a component of the required standards for sleep facility accreditation by the American Academy of Sleep Medicine. Utilization of a psychometrically robust QoL instrument is recommended; however, clinicians face a challenge balancing psychometric properties with questionnaire completion and scoring characteristics. This article provides an overview of common QoL instruments as a reference for clinicians when selecting a QoL tool for use in the clinical setting for adult patients with obstructive sleep apnea.

CITATION

Colvin L, Collop N, Lorenz R, Morgenthaler T, Weaver TE. Examining the feasibility of adult quality-of-life measurement for obstructive sleep apnea in clinical settings: what is the path forward for sleep centers? J Clin Sleep Med. 2023;19(6):1145-1155.

Five-year Transitions of Symptom Subtypes in Untreated Obstructive Sleep Apnea

Objectives

It is unknown if symptom subtypes of obstructive sleep apnea (OSA) transition over time and what clinical factors may predict transitions.

Methods

Data from 2,643 participants of the Sleep Heart Health Study with complete baseline and 5-year follow-up visits were analyzed. Latent Class Analysis on 14 symptoms at baseline and follow up determined symptom subtypes. Individuals without OSA (AHI<5) were incorporated as a known class at each time point. Multinomial logistic regression assessed the effect of age, sex, body mass index (BMI) and AHI on specific class transitions.

Results

The sample consisted of 1,408 women (53.8%) and mean (SD) age 62.4 (10.5) years. We identified four OSA symptom subtypes at both baseline and follow-up visits: minimally symptomatic, disturbed sleep, moderately sleepy and excessively sleepy . Nearly half (44.2%) of the sample transitioned to a different subtype from baseline to follow-up visits; transitions to moderately sleepy were the most common (77% of all transitions). A five-year older age was associated with a 6% increase in odds to transit from excessively sleepy to moderately sleepy [OR (95% CI) = 1.06 (1.02, 1.12)]. Women had 2.35 times higher odds (95% CI: 1.27, 3.27) to transition from moderately sleepy to minimal symptoms . A 5-unit increase in BMI was associated with 2.29 greater odds (95% CI: 1.19, 4.38) to transition from minimal symptoms to excessively sleepy .

Interpretation

While over half of the sample did not transition their subtype over 5 years, among those who did, the likelihood of transitioning between subtypes was significantly associated with a higher baseline age, higher baseline BMI and with women, but was not predicted by AHI.

Clinical Trials

Sleep Heart Health Study (SHHS) Data Coordinating Center, (SHHS) https://clinicaltrials.gov/ct2/show/NCT00005275 , NCT00005275.

Statement of significance

There is very little research assessing symptom progression and its contributions to clinical heterogeneity in OSA. In a large sample with untreated OSA, we grouped common OSA symptoms into subtypes and assessed if age, sex, or BMI predicted transitions between the subtypes over 5 years. Approximately half the sample transitioned to a different symptom subtype and improvements in symptom subtype presentation were common. Women and older individuals were more likely to transition to less severe subtypes, while increased BMI predicted transition to more severe subtype. Determining whether common symptoms like disturbed sleep or excessive daytime sleepiness occur early in the course of the disease or as a result of untreated OSA over an extended period can improve clinical decisions concerning diagnosis and treatment.

Is insomnia severity a moderator of the associations between obstructive sleep apnea severity with mood and diabetes-related distress?

PURPOSE

This study examined insomnia severity as a moderator of the associations between obstructive sleep apnea (OSA) severity with impaired mood and diabetes-related distress in adults with OSA and type 2 diabetes (T2D).

METHODS

This secondary analysis used pooled baseline data from two randomized controlled trials that evaluated the efficacy of treatment of OSA or insomnia in adults with T2D. Participants for this analysis had OSA (Apnea Hypopnea Index [AHI] ≥ five events/hour obtained from an in-home sleep apnea testing device) and completed questionnaires on insomnia, mood, and diabetes-related distress. Hierarchical multiple linear regression and multivariate linear regression analyses were used controlling for demographic characteristics and restless leg syndrome.

RESULTS

Of 240 participants, mean age was 57.8 ± 10.17, 50% were female, and 35% were non-White. Participants had poorly controlled diabetes (Mean HbA1C = 7.93 ± 1.62), and moderate OSA (Mean AHI = 19.3 ± 16.2). Insomnia severity significantly moderated the association between OSA severity and mood (b = -0.048, p = .017). Although insomnia severity did not moderate the relationship between OSA severity and diabetes-related distress (b = -0.009, p = .458), insomnia severity was independently associated with greater diabetes-related distress (b = 1.133, p < .001).

CONCLUSIONS

In adults with T2D and OSA, as insomnia severity increased, increasing OSA severity was associated with lower level of mood disturbances. Insomnia independently increased the level of diabetes-related distress. These findings suggest that comorbid insomnia may be more impactful than OSA on increasing mood disturbances and diabetes-related distress in adults with T2D.

The independent role of nasal obstruction in resistant hypertension for uncontrolled hypertensive patients with obstructive sleep apnea

PURPOSE

To determine the independent predictive role of nasal obstruction in resistant hypertension (RH) in uncontrolled hypertensive patients with obstructive sleep apnea (OSA).

METHODS

This prospective cohort study comprised of 236 OSA patients with uncontrolled blood pressure (BP) using 1 or 2 classes of antihypertensive drugs visiting Sleep Medicine Center from April 2021 to March 2022. Information on demographic characteristics, comorbidities, BP control and classes of antihypertensive medication, sleep-related symptoms, Nasal Obstruction Symptom Evaluation (NOSE) Scale and sleep parameters was collected. RH incidence according to the BP control and classes of antihypertensive drugs data during the 5 month follow-up was collected.

RESULTS

After 5 month follow-up, 217 participants were included for final data analysis. Ninety-five subjects had nocturnal nasal obstruction with a higher proportion of RH (36.8% vs. 17.2%, p = 0.001) compared to those without nocturnal nasal obstruction. After adjustment for demographic characteristics, sleep-related symptoms and OSA severity, multinomial logistic regression models showed that nocturnal nasal obstruction (all ORs > 2.5, p < 0.05) or NOSE ≥ 8 (all ORs > 4.5, p < 0.05) was independently associated with a higher odds of RH. Nasal obstruction treatment improved NOSE score significantly, but did not reduce the incidence of RH significantly. Effective nasal obstruction treatment was associated with antihypertensive drugs reduction (OR 4.43; 95% CI 1.20-16.27).

CONCLUSIONS

Nasal obstruction is an independent predictor of RH in uncontrolled hypertensive patients with OSA. In addition to the treatment of OSA, assessment and treatment of nasal obstruction should be considered in the management of uncontrolled hypertensive patients with OSA.

Weekdays' sleeping condition and its influence on occurrence of general malaise in Japanese children aged 10 to 12 years

The present study aimed to elucidate weekdays' sleeping condition and its influence on occurrence of general malaise in children. A total of 761 Japanese children aged 10 to 12 years were surveyed regarding their weekdays' waking time and bedtime and general malaise using a self-administered questionnaire. As the result of hierarchical cluster analysis on the sleep condition, the participants were classified into three clusters. Sleep duration was significantly longer in cluster 1 (9.35 ± 0.52 h) than in clusters 2 (7.83 ± 0.77 h) and 3 (9.02 ± 0.30 h) and significantly longer in cluster 3 than in cluster 2. Waking time was significantly later in cluster 3 (7:01 ± 0:12) than in clusters 1 (6:22 ± 0:31) and 2 (6:24 ± 0:33, p < 0.001). Bedtime was significantly later in cluster 2 (22:34 ± 0:47) than in clusters 3 (21:59 ± 0:19) and 1 (21:01 ± 0:22) and significantly later in cluster 3 than in cluster 1. There were significantly more subjects in cluster 2 than in clusters 1 and 3 who responded "nearly every day" or "occasionally" to the five of seven questionnaires related to general malaise. The current results indicate that in Japanese children aged 10 to 12 years, (1) sleeping condition of weekdays are classified into three clusters with different mean values for each of sleep duration, bedtime, and waking time, and (2) the occurrence of general malaise may be enhanced in individuals whose sleep duration is less than 8 h.

Role of craniofacial phenotypes in the response to oral appliance therapy for obstructive sleep apnea

BACKGROUND

Mandibular advancement device (MAD) is a good alternative for patients with obstructive sleep apnea (OSA). However, the treatment response varies amongst individuals.

OBJECTIVE

This study aimed to explore the role of craniofacial features in the response to MADs to improve prognostication and patient selection.

METHODS

The retrospective trial contained 42 males aged 41.5 ± 9.0 years, and with an apnea-hypopnea index (AHI) of 21.5 ± 13.8 events/h. According to the mandibular plane angle, participants were divided into three groups: low angle (n = 13), average angle (n = 14) and high angle (n = 15). Under the monitoring of home sleep testing, adjustable MADs were used to titrate the mandible forward from 0 mm with an increment of 0.5 mm every day. The polysomnography outcomes, mandibular protrusion amounts, changes in upper airway MRI measurements and nasal resistance were compared amongst the three groups.

RESULTS

The normalisation rate (AHI <5 /h) was 92.3%, 57.1% and 46.7%, respectively, in the low-, average- and high-angle groups (p = .027). The effective protrusion where AHI was reduced by half was 20 (11.3 ~ 37.5) %, 31.3 (23.6 ~ 50) % and 50 (36.9 ~ 64.9) % of the maximal mandibular protrusion, in the low-, average- and high-angle groups (p = .004). Multivariate logistic regression revealed that increased gonion angle (OR = 0.878) and baseline AHI(OR = 0.868) can reduce the probability of normalisation.

CONCLUSION

The high mandibular plane angle might be an unfavourable factor to MAD treatment and more protrusion was needed to achieve a 50% reduction in AHI. Vertical craniofacial pattern (gonion angle) and baseline AHI constituted the model for predicting the effect of MADs.

Screening for obstructive sleep apnoea in post-treatment cancer patients

BACKGROUND AND AIMS

For cancer patients, comorbid obstructive sleep apnea (OSA) poses additional risk to their surgical/anaesthetic outcomes, quality of life, and survival. However, OSA screening is not well-established in oncology settings. We tested two screening tools (STOP-Bang questionnaire [SBQ] and the at-home monitoring device, ApneaLink™Air), for predicting polysomnography (PSG) confirmed OSA in post-treatment cancer patients.

METHODS

Breast (n = 56), endometrial (n = 37) and melanoma patients (n = 50) were recruited from follow-up clinics at Westmead Hospital (Sydney, Australia). All underwent overnight PSG, 137 completed SBQ, and 99 completed ApneaLink™Air. Positive (PPV) and negative (NPV) predictive values for PSG-determined moderate-to-severe OSA and severe OSA, were calculated using an SBQ threshold ≥3 au and ApneaLink™Air apnoea-hypopnea index thresholds of ≥10, ≥15 and ≥30 events/h.

RESULTS

Both SBQ and ApneaLink™Air had high NPVs (92.7% and 85.2%-95.6% respectively) for severe OSA, but NPVs were lower for moderate-to-severe OSA (69.1% and 59.1%-75.5%, respectively). PPV for both tools were relatively low (all <73%). Combining both tools did not improve screening performance.

CONCLUSIONS

These screening tools may help identify cancer patients without severe OSA, but both are limited in identifying those with moderate-to-severe or severe OSA. PSG remains optimal for adequately identifying and managing comorbid OSA in cancer patients.

Associations between self-reported sleep patterns and health, cognition and amyloid measures: results from the Wisconsin Registry for Alzheimer's Prevention

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.

Potential Pathophysiological Pathways in the Complex Relationships between OSA and Cancer

Several epidemiological and clinical studies have suggested a relationship between obstructive sleep apnea (OSA) and a higher incidence or severity of cancer. This relationship appears to be dependent on a myriad of factors. These include non-modifiable factors, such as age and gender; and modifiable or preventable factors, such as specific comorbidities (especially obesity), the use of particular treatments, and, above all, the histological type or location of the cancer. Heterogeneity in the relationship between OSA and cancer is also related to the influences of intermittent hypoxemia (a hallmark feature of OSA), among others, on metabolism and the microenvironment of different types of tumoral cells. The hypoxia inducible transcription factor (HIF-1α), a molecule activated and expressed in situations of hypoxemia, seems to be key to enabling a variety of pathophysiological mechanisms that are becoming increasingly better recognized. These mechanisms appear to be operationally involved via alterations in different cellular functions (mainly involving the immune system) and molecular functions, and by inducing modifications in the microbiome. This, in turn, may individually or collectively increase the risk of cancer, which is then, further modulated by the genetic susceptibility of the individual. Here, we provide an updated and brief review of the different pathophysiological pathways that have been identified and could explain the relationship between OSA and cancer. We also identify future challenges that need to be overcome in this intriguing field of research.

Hyperhidrosis in sleep disorders - A narrative review of mechanisms and clinical significance

Hyperhidrosis is characterized by excessive sweating beyond thermoregulatory needs that affects patients' quality of life. It results from an excessive stimulation of eccrine sweat glands in the skin by the sympathetic nervous system. Hyperhidrosis may be primary or secondary to an underlying cause. Nocturnal hyperhidrosis is associated with different sleep disorders, such as obstructive sleep apnea, insomnia, restless legs syndrome/periodic limb movement during sleep and narcolepsy. The major cause of the hyperhidrosis is sympathetic overactivity and, in the case of narcolepsy type 1, orexin deficiency may also contribute. In this narrative review, we will provide an outline of the possible mechanisms underlying sudomotor dysfunction and the resulting nocturnal hyperhidrosis in these different sleep disorders and explore its clinical relevance.

Cluster analysis of clinical phenotypic heterogeneity in obstructive sleep apnea assessed using photoplethysmography

BACKGROUND

We evaluated heterogeneity in clinical phenotypes among patients with obstructive sleep apnea syndrome (OSAHS) using photoplethysmography (PPG) in cluster analysis.

METHODS

All enrolled patients underwent polysomnography (PSG) monitoring while wearing a PPG device. Pulse wave signals were recorded with a modified pulse oximetry probe in the PPG device. The pulse wave-derived cardiac risk composite parameter (CRI) and eight derived signal parameters were used to assess OSAHS phenotype. We defined a high cardiovascular risk OSAHS group (CRI ≥0.5) and low cardiovascular risk OSAHS group (CRI <0.5). K-means clustering was performed for analysis of clinical phenotype heterogeneity in OSAHS by combining the CRI and its derived signals.

RESULTS

The OSAHS group had high cardiovascular risk for sex, age, body mass index, systolic and diastolic blood pressure, apnea hypopnea index, and obstructive arousal index and higher risk of developing hypertension, diabetes, and cerebrovascular comorbidities. The low cardiovascular risk OSAHS group had higher blood oxygen levels. Three clinical phenotypes were identified in CRI clustering: 1) typical OSAHS with high risk of hypertension (characterized by middle age, obesity, hypertension with severe OSAHS); 2) older women and mild OSAHS; 3) older men and mild OSAHS. Three subtypes were obtained based on the eight cardiac risk-derived parameters: 1) hypoxia combined with decreased pulse wave amplitude variation; 2) decreased vascular pulse wave amplitude combined with decreased pulse frequency; 3) arrhythmia combined with hypoxia.

CONCLUSIONS

Establishing OSAHS clinical phenotypes with the CRI and derived parameters using PPG may help in establishing multi-dimensional assessment of cardiovascular risk in OSAHS.

Moving toward Equitable Care for Sleep Apnea in the United States: Positive Airway Pressure Adherence Thresholds: An Official American Thoracic Society Policy Statement

Background: Positive airway pressure (PAP) is a highly effective treatment for obstructive sleep apnea (OSA), but adherence limits its efficacy. In addition, coverage of PAP by CMS (Centers for Medicare & Medicaid Services) and other insurers in the United States depends on adherence. This leaves many beneficiaries without PAP, disproportionally impacting non-white and low socioeconomic position patients with OSA and exacerbating sleep health disparities. Methods: An inter-professional, multidisciplinary, international committee with various stakeholders was formed. Three working groups (the historical policy origins, impact of current policy, and international PAP coverage models) met and performed literature reviews and discussions. Using surveys and an iterative discussion-based consensus process, the policy statement recommendations were created. Results: In this position paper, we advocate for policy change to CMS PAP coverage requirements to reduce inequities and align with patient-centered goals. We specifically call for eradicating repeat polysomnography, eliminating the 4-hour rule, and focusing on patient-oriented outcomes such as improved sleepiness and sleep quality. Conclusions: Modifications to the current policies for PAP insurance coverage could improve health disparities.

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CITATION

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

Risk of resistant hypertension associated with insomnia in patients with obstructive sleep apnea

OBJECTIVES

Patients with obstructive sleep apnea (OSA) have a high prevalence of hypertension but vary in blood pressure (BP) control, which may be partially explained by comorbid insomnia. We investigated the association of insomnia symptoms with uncontrolled BP and resistant hypertension (RH) in OSA patients.

METHODS

Between 2018 and 2021, hypertensive patients with OSA were enrolled. Information on demographic characteristics, insomnia symptoms, class of antihypertensive medications, BP control and sleep study data were collected. Controlled BP was defined as systolic BP < 140 mm Hg and diastolic BP < 90 mm Hg (BP standard); uncontrolled BP as above BP standard with use of 1-2 classes of antihypertensive medication; and RH as above BP standard with the use of ≥3 classes of antihypertensive medication (including a diuretic). Multinomial logistic regression models were fit to determine the association between insomnia symptoms and uncontrolled BP or RH (versus controlled BP) after multivariable adjustment.

RESULTS

Among the analytic sample (n = 326), 64.1% of participants had uncontrolled BP and 15.6% had RH. OSA severity was associated with a higher odds of RH (OR, 2.92; 95% CI, 1.71-4.99). After adjustment for confounders including demographic characteristics, sedative hypnotics usage, sleepiness, OSA severity and quality of life, participants experiencing insomnia symptoms had a 3.0 times higher odds of RH. Insomnia was not associated with uncontrolled BP.

CONCLUSIONS

Experiencing insomnia was associated with increased odds of RH in OSA patients. These results suggest that comorbid insomnia may contribute to inadequate BP control in OSA patients.

Novel metabolic phenotypes for extrahepatic complication of nonalcoholic fatty liver disease

BACKGROUND AND AIMS

Phenotypic heterogeneity among patients with NAFLD is poorly understood. We aim to identify clinically important phenotypes within NAFLD patients and assess the long-term outcomes among different phenotypes.

METHODS

We analyzed the clinical data of 2311 participants from the Third National Health and Nutrition Examination Survey (NHANES III) and their linked mortality data through December 2019. NAFLD was diagnosed by ultrasonographic evidence of hepatic steatosis without other liver diseases and excess alcohol use. A 2-stage cluster analysis was applied to identify clinical phenotypes. We used Cox proportional hazard models to explore all-cause and cause-specific mortality between clusters.

RESULTS

We identified 3 NAFLD phenotypes. Cluster 1 was characterized by young female patients with better metabolic profiles and lower prevalence of comorbidities; Cluster 2 by obese females with significant insulin resistance, diabetes, inflammation, and advanced fibrosis and Cluster 3 by male patients with hypertension, atherogenic dyslipidemia, and liver and kidney damage. In a median follow-up of 26 years, 989 (42.8%) all-cause mortality occurred. Cluster 1 patients presented the best prognosis, whereas Cluster 2 and 3 had higher risks of all-cause (Cluster 2-adjusted HR: 1.48, 95% CI: 1.16-1.90; Cluster 3-adjusted HR: 1.29, 95% CI: 1.01-1.64) and cardiovascular (Cluster 2-adjusted HR: 2.01, 95% CI: 1.18-3.44; Cluster 3-adjusted HR: 1.75, 95% CI: 1.03-2.97) mortality.

CONCLUSIONS

Three phenotypically distinct and clinically meaningful NAFLD subgroups have been identified with different characteristics of metabolic profiles. This study reveals the substantial disease heterogeneity that exists among NAFLD patients and underscores the need for granular assessments to define phenotypes and improve clinical practice.