Severity of Desaturations Reflects OSA-Related Daytime Sleepiness Better Than AHI

Flow Limitation Is Associated with Excessive Daytime Sleepiness in Individuals without Moderate or Severe Obstructive Sleep Apnea

Rationale: Moderate-severe obstructive sleep apnea (OSA) (apnea-hypopnea index [AHI], >15 events/h) disturbs sleep through frequent bouts of apnea and is associated with daytime sleepiness. However, many individuals without moderate-severe OSA (i.e., AHI <15 events/h) also report sleepiness. Objectives: To test the hypothesis that sleepiness in the AHI <15 events/h group is a consequence of substantial flow limitation in the absence of overt reductions in airflow (i.e., apnea/hypopnea). Methods: A total of 1,886 participants from the MESA sleep cohort were analyzed for frequency of flow limitation from polysomnogram-recorded nasal airflow signal. Excessive daytime sleepiness (EDS) was defined by an Epworth Sleepiness Scale score ⩾11. Covariate-adjusted logistic regression assessed the association between EDS (binary dependent variable) and frequency of flow limitation (continuous) in individuals with an AHI <15 events/h. Results: A total of 772 individuals with an AHI <15 events/h were included in the primary analysis. Flow limitation was associated with EDS (odds ratio, 2.04; 95% confidence interval, 1.17-3.54; per 2-standard deviation increase in flow limitation frequency) after adjusting for age, sex, body mass index, race/ethnicity, and sleep duration. This effect size did not appreciably change after also adjusting for AHI. Conclusions: In individuals with an AHI <15 events/h, increasing flow limitation frequency by 2 standard deviations is associated with a twofold increase in the risk of EDS. Future studies should investigate addressing flow limitation in low-AHI individuals as a potential mechanism for ameliorating sleepiness.

Real-world data on polysomnography- and patient-reported outcomes in hypoglossal nerve stimulation and auto-titrating positive airway pressure therapy for obstructive sleep apnea

BACKGROUND

Few data are available comparing first-line positive airway pressure (PAP) therapy of obstructive sleep apnea (OSA), especially auto-adjusting PAP (aPAP), with second-line hypoglossal nerve stimulation (HGNS) therapy. The aim of this study was to directly compare these therapeutic options by standard polysomnography (PSG)-related parameters and patient-reported outcomes in comparable groups.

METHODS

20 patients (aged 57.30 ± 8.56 years; 6 female) were included in the HGNS and 35 patients (aged 56.83 ± 9.20 years; 9 female) were included in the aPAP group. In both groups participants had to fit the current guideline criteria for HGNS treatment. Groups were compared by analysis of covariance (ANCOVA) using inverse propensity score weighting.

RESULTS

Propensity scores did not differ between groups. Pre-therapeutic AHI (HGNS: 40.22 ± 12.78/h; aPAP: 39.23 ± 12.33/h) and ODI (HGNS: 37.9 ± 14.7/h, aPAP: 34.58 ± 14.74/h) were comparable between the groups. After 413.6 ± 116.66 days (HGNS) and 162.09 ± 140.58 days (aPAP) of treatment AHI (HGNS: 30.22 ± 17.65/h, aPAP group: 4.71 ± 3.42/h; p < 0.001) was significantly higher in the HGNS group compared to the aPAP group. However, epworth sleepiness scale (ESS) was post-interventionally significantly lower in the HGNS group compared to the aPAP group (pretherapeutic: HGNS: 13.32 ± 5.81 points, aPAP: 9.09 ± 4.71 points; posttherapeutic: HGNS: 7.17 ± 5.06 points; aPAP: 8.38 ± 5.41 points; p < 0.01).

CONCLUSION

These are novel real-world data. More research on the key parameters regarding titration of the HGNS neurostimulation parameter tuning and on the impact of factors influencing HGNS adherence is needed.

A new perspective on OSAS cases with the Baveno classification

OBJECTIVE/BACKGROUND

Since the apnea-hypopnea index (AHI), which is used in the diagnosis and grading of OSAS, does not adequately reflect the clinical perspective of the disease, the Baveno classification of OSA was developed, which allows multicomponent evaluation of OSAS patients. The aim of our study was to evaluate the application of the Baveno classification in clinical practice.

PATIENTS/METHODS

A prospective study was performed on patients diagnosed with OSAS between January 2021 and June 2022. Patients were divided into 4 groups according to Baveno classification (Groups A-D) and three groups as mild, moderate, and severe OSAS according to AHI.

RESULTS

A total of 378 patients (70% male, mean age 48.68 ± 11.81 years) were included in the study. The patients had mild (n: 75; 20%), moderate (n: 88; 23%), and severe (n: 215; 57%) OSAS. According to Baveno classification, patients were included in Groups A (n: 90; 24%), B (n: 105 (28%), C (n: 65; 17%), and D (n: 118; 31%). The mean AHIs of the Baveno groups were similar (p = 0.116). Oxygen desaturation index (ODI) was higher in Groups B and D compared to Group A. The duration of T90 desaturation was longer in Groups C and D compared to Groups A and B (p < 0.05).

CONCLUSIONS

The Baveno classification divided our OSAS cases into equivalent groups. One out of every four patients with mild OSAS was in Group D. This data was noteworthy in that the Baveno classification allows for the identification of symptomatic and comorbid patients with mild OSAS according to AHI and for the application of more effective treatments to these patients. Patients with comorbidities experienced oxygen desaturation for a longer period of time at night, and oxygenation deteriorated in patients with prominent symptoms. Baveno classification was found to be a more reasonable and easily applicable approach in clinical practice.

Using Apnea-Hypopnea Duration per Hour to Predict Hypoxemia Among Patients with Obstructive Sleep Apnea

Purpose

To explore the role of the mean apnea-hypopnea duration (MAD) and apnea-hypopnea duration per hour (HAD) in hypoxemia and evaluate whether they can effectively predict the occurrence of hypoxemia among adults with OSA.

Patients and Methods

A total of 144 participants underwent basic information gathering and polysomnography (PSG). Logistic regression models were conducted to evaluate the best index in terms of hypoxemia. To construct the prediction model for hypoxemia, we randomly divided the participants into the training set (70%) and the validation set (30%).

Results

The participants with hypoxemia tend to have higher levels of obesity, diabetes, AHI, MAD, and HAD compared with non-hypoxemia. The most relevant indicator of blood oxygen concentration is HAD (r = 0.73) among HAD, MAD, and apnea-hypopnea index (AHI). The fitness of HAD on hypoxemia showed the best. In the stage of establishing the prediction model, the area under the curve (AUC) values of both the training set and the validation set are 0.95. The increased HAD would elevate the risk of hypoxemia [odds ratio (OR): 1.30, 95% confidence interval (CI): 1.13-1.49].

Conclusion

The potential role of HAD in predicting hypoxemia underscores the significance of leveraging comprehensive measures of respiratory disturbances during sleep to enhance the clinical management and prognostication of individuals with sleep-related breathing disorders.

Nocturnal oxygen resaturation parameters are associated with cardiorespiratory comorbidities

BACKGROUND

There are strong associations between oxygen desaturations and cardiovascular outcomes. Additionally, oxygen resaturation rates are linked to excessive daytime sleepiness independent of oxygen desaturation severity. No studies have yet looked at the independent effects of comorbidities or medications on resaturation parameters.

METHODS

The Sleep Heart Health Study data was utilised to derive oxygen saturation parameters from 5804 participants. Participants with a history of comorbidities or medication usage were compared against healthy participants with no comorbidity/medication history.

RESULTS

4293 participants (50.4% female, median age 64 years) were included in the analysis. Females recorded significantly faster resaturation rates (mean 0.61%/s) than males (mean 0.57%/s, p < 0.001), regardless of comorbidities. After adjusting for demographics, sleep parameters, and desaturation parameters, resaturation rate was reduced with hypertension (-0.09 (95% CI -0.16, -0.03)), myocardial infarction (-0.13 (95% CI -0.21, -0.04)) and heart failure (-0.19 (95% CI -0.33, -0.05)), or when using anti-hypertensives (-0.10 (95% CI -0.17, -0.03)), mental health medications (-0.18 (95% CI -0.27, -0.08)) or anticoagulants (-0.41 (95% CI -0.56, -0.26)). Desaturation to Resaturation ratio for duration was decreased with mental health (-0.21 (95% CI -0.34, -0.08)) or diabetic medications (-0.24 (95% CI -0.41, -0.07)), and desaturation to resaturation ratio for area decreased with heart failure (-0.25 (95% CI -0.42, -0.08)).

CONCLUSIONS

Comorbidities and medications significantly affect nocturnal resaturation parameters, independent of desaturation parameters. However, the causal relationship remains unclear. Further research can enhance our knowledge and develop more precise and safer interventions for individuals affected by certain comorbidities.

Utility of the psychomotor vigilance task in screening for obstructive sleep apnoea

PURPOSE

The study aimed to assess the performance of the PVT in patients with suspected OSA, evaluate its role in population screening for OSA.

METHODS

The NoSAS, STOP-Bang, ESS scores and PVT tests were performed after suspected OSA patients' admission, followed by PSG. Then we compared the PVT results, calculated the sensitivity, specificity and ROC curve of PVT, and analyzed the accuracy of STOP-Bang and NoSAS questionnaire combined with PVT in predicting OSA.

RESULTS

A total of 308 patients were divided into four groups based on AHI: primary snoring (2.74 ± 1.4 events/h, n = 37); mild OSA (9.96 ± 3.25 events/h, n = 65); moderate OSA (22.41 ± 4.48 events/h, n = 76); and, severe OSA (59.42 ± 18.37 events/h, n = 130). There were significant differences in PVT lapses (p < 0.001) and reaction time (RT, p = 0.03) among the four groups. The PVT lapses and RT were positively correlated with AHI (p < 0.001) and ODI (p < 0.001), and negatively correlated with LSpO2 (p < 0.001). When diagnosing OSA (AHI ≥ 5 events/h), the AUCs of PVT, ESS, STOP-Bang, and NoSAS were 0.679, 0.579, 0.727, and 0.653, respectively; the AUCs of STOP-Bang and NoSAS combined with PVT increased. After combined PVT, the diagnostic specificity of STOP-Bang and NoSAS at nodes with AHI ≥ 5, ≥ 15 and ≥ 30 events/h increased to varying degrees.

CONCLUSION

Patients with OSA exhibited impairment in the PVT, and the combination of the PVT and STOP-Bang or NoSAS scores can improve the diagnostic efficacy and specificity for OSA.

Application study of apnea-hypopnea duration for assessing adult obstructive sleep apnea

BACKGROUND

Obstructive sleep apnea (OSA) is a common sleep disordered breathing disorder, which can cause serious damage to multiple human systems. Although polysomnography (PSG) is the current gold standard for diagnosis, it is complex and expensive. Therefore, it is of great significance to find a simple, economical and rapid primary screening and diagnosis method to replace PSG for the diagnosis of OSA.

OBJECTIVE

The purpose of this study is to propose a new method for the diagnosis and classification of OSA, which is used to automatically detect the duration of sleep apnea hypopnea events (AHE), so as to estimate the ratio(S) of the total duration of all-night AHE to the total sleep time only based on the sound signal of sleep respiration, and to identify OSA.

METHODS

We performed PSG tests on participants and extracted relevant sleep breathing sound signal data. This study is carried out in two stages. In the first stage, the relevant PSG report data of eligible subjects were recorded, the total duration of AHE in each subject's data was extracted, and the S value was calculated to evaluate the severity of OSA. In the second stage, only the sleep breath sound signal data of the same batch of subjects were used for automatic detection, and the S value in the sleep breath sound signal was extracted, and the S value was compared with the PSG diagnosis results to calculate the accuracy of the experimental method.

RESULTS

Among 225 subjects. Using PSG as the reference standard, the S value extracted from the PSG diagnostic data report can accurately diagnose OSA(accuracy rate 99.56%) and distinguish its severity (accuracy rate 95.11%). The accuracy of the S value detected in the sleep breathing sound signal in the diagnosis of severe OSA reached 100%.

CONCLUSION

The results show that the experimental parameter S value is feasible in OSA diagnosis and classification. OSA can be identified and evaluated only by sleep breathing sounds. This method helps to simplify the diagnostic grading of traditional OSA and lays a foundation for the subsequent development of simple diagnostic grading equipment.

BAFNet: Bottleneck Attention Based Fusion Network for Sleep Apnea Detection

Sleep apnea (SA) is a common sleep-related breathing disorder that tends to induce a series of complications, such as pediatric intracranial hypertension, psoriasis, and even sudden death. Therefore, early diagnosis and treatment can effectively prevent malignant complications SA incurs. Portable monitoring (PM) is a widely used tool for people to monitor their sleep conditions outside of hospitals. In this study, we focus on SA detection based on single-lead electrocardiogram (ECG) signals which are easily collected by PM. We propose a bottleneck attention based fusion network named BAFNet, which mainly includes five parts of RRI (R-R intervals) stream network, RPA (R-peak amplitudes) stream network, global query generation, feature fusion, and classifier. To learn the feature representation of RRI/RPA segments, fully convolutional networks (FCN) with cross-learning are proposed. Meanwhile, to control the information flow between RRI and RPA networks, a global query generation with bottleneck attention is proposed. To further improve the SA detection performance, a hard sample scheme with k-means clustering is employed. Experiment results show that BAFNet can achieve competitive results, which are superior to the state-of-the-art SA detection methods. It means that BAFNet has great potential to be applied in the home sleep apnea test (HSAT) for sleep condition monitoring.

Obstructive Sleep Apnea: The Effect of Bariatric Surgery After Five Years-A Prospective Multicenter Trial

BACKGROUND

The prevalence of obstructive sleep apnea (OSA) is high among the bariatric surgery candidates. Obesity is the most important individual risk factor for OSA. The aim of this study was to investigate the effect of a laparoscopic Roux-en-Y gastric bypass (LRYGB) on OSA 5 years after the surgery.

PATIENTS AND METHODS

In this prospective multicenter study, standard overnight cardiorespiratory recording was conducted to 150 patients at baseline prior to bariatric surgery. A total of 111 (73.3%) patients of those had OSA. Cardiorespiratory recordings at 5 years after surgery were available for 70 OSA patients. The changes in anthropometric and demographic measurements including age, weight, body mass index (BMI), and waist and neck circumference were evaluated. Also, a quality of life (QoL) questionnaire 15D administered in a baseline was controlled at 5-year follow-up visit.

RESULTS

At 5-year OSA was cured in 55% of patients, but moderate or severe OSA still persisted in 20% of patients after operation. Mean total AHI decreased from 27.8 events/h to 8.8 events/h (p < 0.001) at 5-year follow-up. A clinically significant difference in QoL was seen in mobility, breathing, sleeping, usual activities, discomfort and symptoms, vitality and sexual activity. The QoL total score improved more in OSA patient at 5-year follow-up.

CONCLUSIONS

LRYGB is an effective treatment of OSA in obese patients and the achieved beneficial outcomes are maintained at 5-year follow-up.

Excessive daytime sleepiness is associated with relative delta frequency power among patients with mild OSA

Background

Excessive daytime sleepiness (EDS) is a cause of low quality of life among obstructive sleep apnoea (OSA) patients. Current methods of assessing and predicting EDS are limited due to time constraints or differences in subjective experience and scoring. Electroencephalogram (EEG) power spectral densities (PSDs) have shown differences between OSA and non-OSA patients, and fatigued and non-fatigued patients. Therefore, polysomnographic EEG PSDs may be useful to assess the extent of EDS among patients with OSA.

Methods

Patients presenting to Israel Loewenstein hospital reporting daytime sleepiness who recorded mild OSA on polysomnography and undertook a multiple sleep latency test. Alpha, beta, and delta relative powers were assessed between patients categorized as non-sleepy (mean sleep latency (MSL) ≥10 min) and sleepy (MSL <10 min).

Results

139 patients (74% male) were included for analysis. 73 (53%) were categorized as sleepy (median MSL 6.5 min). There were no significant differences in demographics or polysomnographic parameters between sleepy and non-sleepy groups. In multivariate analysis, increasing relative delta frequency power was associated with increased odds of sleepiness (OR 1.025 (95% CI 1.024-1.026)), while relative alpha and beta powers were associated with decreased odds. The effect size of delta PSD on sleepiness was significantly greater than that of either alpha or beta frequencies.

Conclusion

Delta PSD during polysomnography is significantly associated with a greater degree of objective daytime sleepiness among patients with mild OSA. Further research is needed to corroborate our findings and identify the direction of potential causal correlation between delta PSD and EDS.

Reaction time in psychomotor vigilance task is related to hypoxic load in males with sleep apnea

Oxygen saturation (SpO2 )-based parameters are more strongly linked to impaired daytime vigilance than the conventional diagnostic metrics in patients with obstructive sleep apnea (OSA). However, whether the association between SpO2 -based parameters and impaired daytime vigilance is modulated by sex, remains unknown. Hence, we investigated the interplay between sex and detailed SpO2 -based metrics and their association with impaired vigilance in patients with OSA. The study population consisted of 855 (473 males, 382 females) patients with suspected OSA who underwent overnight polysomnography and psychomotor vigilance task (PVT). The population was grouped by sex and divided into quartiles (Q1-Q4) based on median reaction times (RTs) in the PVT. In addition to conventional diagnostic metrics, desaturation severity (DesSev), fall severity (FallSev), and recovery severity (RecovSev) were compared between the sexes and between the best (Q1) and worst (Q4) performing quartiles by using cumulative distribution functions (CDFs). Additionally, sex-specific covariate-adjusted linear regression models were used to investigate the connection between the parameters and RTs. The CDFs showed significantly higher hypoxic load in Q4 in males compared to females. In addition, the DesSev (β = 8.05, p < 0.01), FallSev (β = 6.48, p = 0.02), RecovSev (β = 9.13, p < 0.01), and Oxygen Desaturation Index (β = 12.29, p < 0.01) were associated with increased RTs only in males. Conversely, the Arousal Index (β = 10.75-11.04, p < 0.01) was associated with impaired vigilance in females. The severity of intermittent hypoxaemia was strongly associated with longer RTs in males whereas the Arousal Index had the strongest association in females. Thus, the impact of hypoxic load on impaired vigilance seems to be stronger in males than females.

Effect of chronic intermittent hypoxia on ocular and intraoral mechanical allodynia mediated via the calcitonin gene-related peptide in a rat

STUDY OBJECTIVES

Obstructive sleep apnea, a significant hypoxic condition, may exacerbate several orofacial pain conditions. The study aims to define the involvement of calcitonin gene-related peptide (CGRP) in peripheral and central sensitization and in evoking orofacial mechanical allodynia under chronic intermittent hypoxia (CIH).

METHODS

Male rats were exposed to CIH. Orofacial mechanical allodynia was assessed using the eyeblink test and the two-bottle preference drinking test. The CGRP-immunoreactive neurons in the trigeminal ganglion (TG), CGRP-positive primary afferents projecting to laminae I-II of the trigeminal spinal subnucleus caudalis (Vc), and neural responses in the second-order neurons of the Vc were determined by immunohistochemistry. CGRP receptor antagonist was administrated in the TG.

RESULTS

CIH-induced ocular and intraoral mechanical allodynia. CGRP-immunoreactive neurons and activated satellite glial cells (SGCs) were significantly increased in the TG and the number of cFos-immunoreactive cells in laminae I-II of the Vc were significantly higher in CIH rats compared to normoxic rats. Local administration of the CGRP receptor antagonist in the TG of CIH rats attenuated orofacial mechanical allodynia; the number of CGRP-immunoreactive neurons and activated SGCs in the TG, and the density of CGRP-positive primary afferent terminals and the number of cFos-immunoreactive cells in laminae I-II of the Vc were significantly lower compared to vehicle-administrated CIH rats.

CONCLUSIONS

An increase in CGRP in the TG induced by CIH, as well as orofacial mechanical allodynia and central sensitization of second-order neurons in the Vc, supported the notion that CGRP plays a critical role in CIH-induced orofacial mechanical allodynia.

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 diagnosis and beyond using portable monitors

Obstructive sleep apnea (OSA) is a chronic sleep and breathing disorder with significant health complications, including cardiovascular disease and neurocognitive impairments. To ensure timely treatment, there is a need for a portable, accurate and rapid method of diagnosing OSA. This review examines the use of various physiological signals used in the detection of respiratory events and evaluates their effectiveness in portable monitors (PM) relative to gold standard polysomnography. The primary objective is to explore the relationship between these physiological parameters and OSA, their application in calculating the apnea hypopnea index (AHI), the standard metric for OSA diagnosis, and the derivation of non-AHI metrics that offer additional diagnostic value. It is found that increasing the number of parameters in PMs does not necessarily improve OSA detection. Several factors can cause performance variations among different PMs, even if they extract similar signals. The review also highlights the potential of PMs to be used beyond OSA diagnosis. These devices possess parameters that can be utilized to obtain endotypic and other non-AHI metrics, enabling improved characterization of the disorder and personalized treatment strategies. Advancements in PM technology, coupled with thorough evaluation and validation of these devices, have the potential to revolutionize OSA diagnosis, personalized treatment, and ultimately improve health outcomes for patients with OSA. By identifying the key factors influencing performance and exploring the application of PMs beyond OSA diagnosis, this review aims to contribute to the ongoing development and utilization of portable, efficient, and effective diagnostic tools for OSA.

Nurse practitioner-led, virtually delivered, motivational enhancement and device support intervention to improve CPAP adherence: A feasibility randomized control trial

BACKGROUND

Evidence indicates continuous positive airway pressure (CPAP) therapy improves several important patient-centered outcomes. However, adherence to this safe and effective intervention remains poor.

OBJECTIVES

Assess nine feasibility outcomes of a nurse practitioner-led, virtually delivered motivational enhancement and device support (MENDS) intervention to improve CPAP adherence in adults with Obstructive Sleep Apnea (OSA). Secondary aims compared the changes in CPAP adherence to patient-reported outcomes, patient activation, and perceived self-efficacy.

METHODS

This two-group feasibility randomized controlled trial included 29 patients newly diagnosed with OSA and prescribed CPAP therapy. The study was conducted from July 2020 through December 2021 at a midwestern sleep/pulmonary clinic. Participants were randomized to the MENDS intervention group (n=14) (30-45 minute interactive tele-discussions on weeks 2, 4, 6, and 8) or to the usual care (n=15) group. Feasibility, patient-reported outcomes, and behavioral constructs were measured at baseline and 12 weeks. CPAP adherence was measured weekly.

RESULTS

Feasibility of the MENDS sessions was demonstrated (56 sessions offered, 52 completed remotely without technical difficulties) with minimal participant attrition and no missing CPAP data. Generalized linear mixed models showed no statistically significant time-by-group interactions on adherence or patient-reported outcomes. Higher adherence and lower CPAP apnea-hypopnea index (AHI) scores were associated with declines in pre- to post-changes in fatigue and sleep disturbance. Lower CPAP AHI scores were associated with pre- to post-decreases in PROMIS Anxiety scores (r=.532, p=.005).

CONCLUSION

The virtual MENDS intervention was feasible. Higher CPAP adherence and lower AHI levels led to positive improvements in fatigue, sleep disturbance, and anxiety.

Respiratory event index underestimates severity of sleep apnea compared to apnea-hypopnea index

Polygraphy (PG) is often used to diagnose obstructive sleep apnea (OSA). However, it does not use electroencephalography, and therefore cannot estimate sleep time or score arousals and related hypopneas. Consequently, the PG-derived respiratory event index (REI) differs from the polysomnography (PSG)-derived apnea-hypopnea index (AHI). In this study, we comprehensively analyzed the differences between AHI and REI. Conventional AHI and REI were calculated based on total sleep time (TST) and total analyzed time (TAT), respectively, from two different PSG datasets (n = 1561). Moreover, TAT-based AHI (AHITAT) and TST-based REI (REITST) were calculated. These indices were compared keeping AHI as the gold standard. The REI, AHITAT, and REITST were significantly lower than AHI (p < 0.0001, p ≤ 0.002, and p ≤ 0.01, respectively). The total classification accuracy of OSA severity based on REI was 42.1% and 72.8% for two datasets. Based on AHITAT, the accuracies were 68.4% and 85.9%, and based on REITST, they were 65.9% and 88.5% compared to AHI. AHI was most correlated with REITST (r = 0.98 and r = 0.99 for the datasets) and least with REI (r = 0.92 and r = 0.97). Compared to AHI, REI had the largest mean absolute errors (13.9 and 6.7) and REITST the lowest (5.9 and 1.9). REI had the lowest sensitivities (42.1% and 72.8%) and specificities (80.7% and 90.9%) in both datasets. Based on these present results, REI underestimates AHI. Furthermore, these results indicate that arousal-related hypopneas are an important measure for accurately classifying OSA severity.

Obstructive sleep apnea and attention deficits: A systematic review of magnetic resonance imaging biomarkers and neuropsychological assessments

BACKGROUND AND OBJECTIVE

Obstructive sleep apnea (OSA) is a common sleep disorder that causes intermittent hypoxia and sleep fragmentation, leading to attention impairment and other cognitive deficits. Magnetic resonance imaging (MRI) is a powerful modality that can reveal the structural and functional brain alterations associated with attention impairment in OSA patients. The objective of this systematic review is to identify and synthesize the evidence on MRI biomarkers and neuropsychological assessments of attention deficits in OSA patients.

METHODS

We searched the Scopus and PubMed databases for studies that used MRI to measure biomarkers related to attention alteration in OSA patients and reported qualitative and quantitative data on the association between MRI biomarkers and attention outcomes. We also included studies that found an association between neuropsychological assessments and MRI findings in OSA patients with attention deficits.

RESULTS

We included 19 studies that met our inclusion criteria and extracted the relevant data from each study. We categorized the studies into three groups based on the MRI modality and the cognitive domain they used: structural and diffusion tensor imaging MRI findings, functional, perfusion, and metabolic MRI findings, and neuropsychological assessment findings.

CONCLUSIONS

We found that OSA is associated with structural, functional, and metabolic brain alterations in multiple regions and networks that are involved in attention processing. Treatment with continuous positive airway pressure can partially reverse some of the brain changes and improve cognitive function in some domains and in some studies. This review suggests that MRI techniques and neuropsychological assessments can be useful tools for monitoring the progression and response to treatment of OSA patients.

A Review of Novel Oximetry Parameters for the Prediction of Cardiovascular Disease in Obstructive Sleep Apnoea

Obstructive sleep apnoea (OSA) is a sleep disorder with repetitive collapse of the upper airway during sleep, which leads to intermittent hypoxic events overnight, adverse neurocognitive, metabolic complications, and ultimately an increased risk of cardiovascular disease (CVD). The standard diagnostic parameter for OSA, apnoea-hypopnoea index (AHI), is inadequate to predict CVD morbidity and mortality, because it focuses only on the frequency of apnoea and hypopnoea events, and fails to reveal other physiological information for the prediction of CVD events. Novel parameters have been introduced to compensate for the deficiencies of AHI. However, the calculation methods and criteria for these parameters are unclear, hindering their use in cross-study analysis and studies. This review aims to discuss novel parameters for predicting CVD events from oximetry signals and to summarise the corresponding computational methods.

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

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

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

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

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.

National Knowledge-Driven Management of Obstructive Sleep Apnea-The Swedish Approach

INTRODUCTION

This paper describes the development of "Swedish Guidelines for OSA treatment" and the underlying managed care process. The Apnea Hypopnea Index (AHI) is traditionally used as a single parameter for obstructive sleep apnea (OSA) severity classification, although poorly associated with symptomatology and outcome. We instead implement a novel matrix for shared treatment decisions based on available evidence.

METHODS

A national expert group including medical and dental specialists, nurses, and patient representatives developed the knowledge-driven management model. A Delphi round was performed amongst experts from all Swedish regions (N = 24). Evidence reflecting treatment effects was extracted from systematic reviews, meta-analyses, and randomized clinical trials.

RESULTS

The treatment decision in the process includes a matrix with five categories from a "very weak"" to "very strong" indication to treat, and it includes factors with potential influence on outcome, including (A) OSA-related symptoms, (B) cardiometabolic comorbidities, (C) frequency of respiratory events, and (D) age. OSA-related symptoms indicate a strong incitement to treat, whereas the absence of symptoms, age above 65 years, and no or well-controlled comorbidities indicate a weak treatment indication, irrespective of AHI.

CONCLUSIONS

The novel treatment matrix is based on the effects of treatments rather than the actual frequency of respiratory events during sleep. A nationwide implementation of this matrix is ongoing, and the outcome is monitored in a prospective evaluation by means of the Swedish Sleep Apnea Registry (SESAR).

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.

Implication of a novel measure of obstructive sleep apnea severity for cardiovascular morbidity

OBJECTIVE

To evaluate the association between cardiovascular morbidity and obstructive sleep apnea (OSA) severity quantified using the sleep breathing impairment index (SBII), a novel measure that captures both respiratory events and event-associated hypoxia.

PATIENTS AND METHODS

This retrospective follow-up study included 737 participants with OSA who were diagnosed based on an apnea-hypopnea index of >5/h in polysomnography from January 1, 2012 to December 31, 2015. Data on baseline clinical characteristics and polysomnography parameters were collected. SBII was determined as the sum of products of respiratory events and event-related desaturation areas, and was categorized based on its quintiles. The outcomes were any hospital admission for cardiovascular diseases, including coronary heart disease, stroke, peripheral vascular disease, or heart failure after the diagnosis of OSA. Logistic regression models were constructed to estimate the potential association between SBII and cardiovascular morbidity after adjusting for confounders.

RESULTS

A total of 60 cardiovascular events were recorded. Compared with the first quintile of SBII, the odds ratio (95% confidence interval [CI]) of cardiovascular morbidity for the second, third, and fourth quintiles were 4.01 (95% CI, 1.22-13.24), 3.91 (95% CI, 1.05-14.53), and 7.57 (95% CI, 1.70-33.68) after adjusting for covariables, including anthropometric variables, medical conditions, and sleep parameters.

CONCLUSION

In patients with OSA, higher SBII was associated with an increased cardiovascular risk. These findings suggest that a more comprehensive measure, such as SBII incorporating the respiratory event and related hypoxia during sleep, may better capture the disease burden and reflect the OSA-associated adverse outcomes.

Hypoxic Burden in Obstructive Sleep Apnea: Present and Future

Conventional measures of obstructive sleep apnea (OSA) severity, such as the apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) are commonly used to quantify OSA severity and guide therapeutical decision-making processes. However, it is widely recognized that both AHI and ODI have important limitations and novel physiologically-informed metrics are needed to better capture the severity of OSA and characterize its physiological consequences, particularly the severity of recurrent nocturnal hypoxemia, ensuing the respiratory events. According to recent studies, the sleep apnea-specific "hypoxic burden (HB)", defined as the sum of individual areas under the oxygen desaturation curve, has shown some promise in identifying high risk individuals with OSA. In addition to the frequency of respiratory events, HB capture the depth and duration of OSA-related hypoxemia that may prove to be important disease characterizing features, not captured by the conventional "frequency-based" metrics, such as AHI and ODI. In this "perspective" paper the methods to quantify the HB, its characteristics, associations with health outcomes, and its limitations will be discussed.

Duration of respiratory events in obstructive sleep apnea: Factors influencing the duration of respiratory events

Several factors influence respiratory event duration during sleep. In general, women have shorter respiratory events compared to men as it appears that women have a more reactive upper airway contributing to the occurrence of short events. In addition, the increased amount of adipose tissue in the upper airways should make the reopening of the upper airways more difficult, leading to long respiratory events. Nevertheless, an increase in body mass index decreases the median duration of apneas, hypopneas, and desaturations in all OSA severity categories. Also, respiratory events are longer in older adults compared to younger ones, and the most likely mechanism explaining this phenomenon appears to be the increased circulatory delay associated with aging. Several studies have also shown that apnea events are longer in rapid eye movement sleep compared to non-rapid eye movement sleep. The main mechanism behind these differences appears to be the greater pharyngeal muscle relaxation during rapid eye movement sleep. Finally, sleeping position affects the duration of respiratory events; apneas and hypopneas are longer in the supine compared to lateral postures regardless of the severity of OSA. In the present report, we discuss the best-known factors influencing the duration of abnormal breathing events during sleep.

Obstructive sleep apnea‐related intermittent hypoxaemia is associated with impaired vigilance

Obstructive sleep apnea (OSA)-related intermittent hypoxaemia is a potential risk factor for different OSA comorbidities, for example cardiovascular disease. However, conflicting results are found as to whether intermittent hypoxaemia is associated with impaired vigilance. Therefore, we aimed to investigate how desaturation characteristics differ between the non-impaired vigilance and impaired vigilance patient groups formed based on psychomotor vigilance task (PVT) performance and compared with traditional OSA severity parameters. The study population comprised 863 patients with suspected OSA who underwent a PVT test before polysomnography. The conventional OSA parameters, for example, the apnea-hypopnea index, oxygen desaturation index, and arousal index were computed. Furthermore, the median desaturation area, fall area, recovery area, and desaturation depth were computed with the pre-event baseline reference and with reference to the 100% oxygen saturation level. Patients were grouped into best- and worst-performing quartiles based on the number of lapses in PVT (Q1: PVT lapses <5 and Q4: PVT lapses >36). The association between parameters and impaired vigilance was evaluated by cumulative distribution functions (CDFs) and binomial logistic regression. Based on the CDFs, patients in Q4 had larger desaturation areas, recovery areas, and deeper desaturations when these were referenced to 100% saturation compared with Q1. The odds ratio (OR) of the median desaturation area (OR = 1.56), recovery area (OR = 1.71), and depth (OR = 1.65) were significantly elevated in Q4 in regression models. However, conventional OSA parameters were not significantly associated with impaired vigilance (ORs: 0.79-1.09). Considering desaturation parameters with a 100% SpO₂ reference in the diagnosis of OSA could provide additional information on the severity of OSA and related daytime vigilance impairment.

Desaturation event scoring criteria affect the perceived severity of nocturnal hypoxic load

OBJECTIVES/BACKGROUND

Interest in using blood oxygen desaturations in the diagnostics of sleep apnea has risen in recent years. However, no standardized criteria for desaturation scoring exist which complicates the drawing of solid conclusions from literature.

PATIENTS/METHODS

We investigated how different desaturation scoring criteria affect the severity of nocturnal hypoxic load and the prediction of impaired daytime vigilance in 845 patients. Desaturations were scored based on three features: 1) minimum oxygen saturation drop during the event (2-20%, 1% interval), 2) minimum duration of the event (2-20s, 1s interval), and 3) maximum plateau duration within the event (5-60s, 5s interval), resulting in 4332 different scoring criteria. The hypoxic load was described with oxygen desaturation index (ODI), desaturation severity (DesSev), and desaturation duration (DesDur) parameters. Association between hypoxic load and impaired vigilance was investigated with covariate-adjusted area under curve (AUC) analyses by dividing patients into normal (≤5 lapses) and impaired (≥36 lapses) vigilance groups based on psychomotor vigilance task performance.

RESULTS

The severity of hypoxic load varied greatly between different scoring criteria. For example, median ODI ranged between 0.4 and 12.9 events/h, DesSev 0.01-0.23 %-point, and DesDur 0.3-9.6 %-point when the minimum transient drop criterion of 3% was used and other two features were altered. Overall, the minimum transient drop criterion had the largest effect on parameter values. All models with differently determined parameters predicted impaired vigilance moderately (AUC = 0.722-0.734).

CONCLUSIONS

Desaturation scoring criteria greatly affected the severity of hypoxic load. However, the difference in the prediction of impaired vigilance between different criteria was rather small.

Correlates of excessive daytime sleepiness in obstructive sleep apnea: Results from the nationwide SESAR cohort including 34,684 patients

Excessive daytime sleepiness (EDS) is a hallmark symptom in obstructive sleep apnea (OSA). It is commonly eliminated by obstructive sleep apnea therapy and constitutes a major treatment indication. This study aimed to identify determinants of excessive daytime sleepiness by the Epworth Sleepiness Scale (ESS) scores in the large, representative national obstructive sleep apnea patient cohort of the Swedish Sleep Apnea Registry (SESAR, www.sesar.se). Data from 34,684 patients with obstructive sleep apnea recruited at 23 sites (33% females, mean age 55.7 ± 13.7 years, BMI 30.2 ± 6.3 kg/m² , AHI 29.1 ± 22.3, and ODI 24.9 ± 21.4 events/h) had a mean ESS score in the mild to moderate excessive daytime sleepiness range (9.7 ± 4.9). The proportion of patients with excessive daytime sleepiness was 41.4% in men and 44.6% in women. Independent predictors of excessive daytime sleepiness included gender, age, and hypoxic markers (high ODI and low mean saturation). Univariate and multivariate analyses were used to identify significant predictors for the ESS score and for excessive daytime sleepiness (ESS ≥10) amongst anthropometric factors, sleep apnea frequency (apnea-hypopnea index (AHI)), markers of intermittent hypoxia (oxygen desaturation index (ODI), mean saturation (mSaO₂ )), as well as prevalent comorbidities. Depression was associated with higher ESS scores and hypertension/atrial fibrillation with lower scores. The oxygen desaturation index provided a stronger predictor of excessive daytime sleepiness than the apnea-hypopnea index. The severity of obstructive sleep apnea, captured as the apnea-hypopnea index, was only weakly associated with daytime sleepiness in this representative obstructive sleep apnea patient cohort. Age had different effects in men and women.The impact of obstructive sleep apnea in a wider patient related perspective needs to be determined after the inclusion of factors other than the apnea-hypopnea index.

Obstructive sleep apnea in young Asian adults with sleep-related complaints

This study aimed to investigate the proportion of young OSA adults with sleep-related complaints in a sleep center, affiliated with a tertiary medical center for over a decade. This study presents a chronicle change in the numbers of young adults receiving polysomnography (PSG) and young patients with OSA from 2000 to 2017. We further analyzed 371 young patients with OSA among 2378 patients receiving PSG in our sleep center from 2016 to 2017 to capture their characteristics. Young adults constituted a substantial and relatively steady portion of examinees of PSG (25.1% ± 2.8%) and confirmed OSA cases (19.8 ± 2.4%) even though the total numbers increased with the years. Young adults with OSA tend to be sleepier, have a greater body mass index, and have a higher percentage of cigarette smoking and alcohol consumption. They also complained more about snoring and daytime sleepiness. They had a higher apnea-hypopnea index on average and experienced more hypoxemia during their sleep, both in terms of duration and the extent of desaturation. Even though the prevalence of comorbidities increased with age, hypertension in young male adults carried higher risks for OSA. Young adults with OSA have constituted a relatively constant portion of all confirmed OSA cases across time. The young adults with OSA were heavier, more symptomatic, and with more severe severity.Clinical trial: The Institutional Review Board of Taipei Veterans General Hospital approved the study (VGHIRB No. 2018-10-002CC). The study is registered with ClinicalTrials.gov, number NCT03885440.

ABOSA - Freely available automatic blood oxygen saturation signal analysis software: Structure and validation

BACKGROUND AND OBJECTIVE

Many sleep recording software used in clinical settings have some tools to automatically analyze the blood oxygen saturation (SpO₂) signal by detecting desaturations. However, these tools are often inadequate for scientific research as they do not provide SpO₂ signal-based parameters which are superior in the estimation of sleep apnea severity and related medical consequences. In addition, these software require expensive licenses and they lack batch analysis tools. Thus, we developed the first freely available automatic blood oxygen saturation analysis software (ABOSA) that provides sophisticated SpO₂ signal-based parameters and enables batch analysis of large datasets.

METHODS

ABOSA was programmed with MATLAB. ABOSA automatically detects desaturation and recovery events from the SpO₂ signals (EDF files) and calculates numerous parameters, such as oxygen desaturation index (ODI) and desaturation severity (DesSev). The accuracy of the ABOSA software was evaluated by comparing its desaturation scorings to manual scorings in Kuopio (n = 1981) and Loewenstein (n = 930) sleep apnea patient datasets. Validation was performed in a second-by-second manner by calculating Matthew's correlation coefficients (MCC) and median differences in parameter values. Finally, the performance of the ABOSA software was compared to two commercial software, Noxturnal and Profusion, in 100 patient subpopulations. As Noxturnal or Profusion does not calculate novel desaturation parameters, these were calculated with custom-made functions.

RESULTS

The agreements between ABOSA and manual scorings were great in both Kuopio (MCC = 0.801) and Loewenstein (MCC = 0.898) datasets. However, ABOSA slightly overestimated the desaturation parameter values. The median differences in ODIs were 0.8 (Kuopio) and 0.0 (Loewenstein) events/h. Similarly, the median differences in DesSevs were 0.02 (Kuopio) and 0.01 (Loewenstein) percentage points. In a second-by-second analysis, ABOSA performed very similarly to Noxturnal and Profusion software in both Kuopio (MCC_ABOSA = 0.807, MCC_Noxturnal = 0.807, MCC_Profusion = 0.811) and Loewenstein (MCC_ABOSA = 0.904, MCC_Noxturnal = 0.911, MCC_Profusion = 0.871) datasets. Based on Noxturnal and Profusion scorings, the desaturation parameter values were similarly overestimated compared to ABOSA.

CONCLUSIONS

ABOSA is an accurate and freely available software that calculates both traditional clinical parameters and novel parameters, provides a detailed characterization of desaturation and recovery events, and enables batch analysis of large datasets. These are features that no other software currently provides making ABOSA uniquely suitable for scientific research use.

Hypoxic Burden in Obstructive Sleep Apnea: Present and Future

Conventional measures of obstructive sleep apnea (OSA) severity, such as the apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) are commonly used to quantify OSA severity and guide therapeutical decision-making processes. However, it is widely recognized that both AHI and ODI have important limitations and novel physiologically informed metrics are needed to better capture the severity of OSA and characterize its physiological consequences, particularly the severity of recurrent nocturnal hypoxemia, ensuing the respiratory events. According to recent studies, the sleep apnea-specific "Hypoxic Burden (HB)", defined as the sum of individual areas under the oxygen desaturation curve, has shown some promise in identifying high risk individuals with OSA. In addition to the frequency of respiratory events, HB capture the depth and duration of OSA-related hypoxemia that may prove to be important disease characterizing features, not captured by the conventional "frequency-based" metrics, such as AHI and ODI. In this "Perspective" paper the methods to quantify the HB, its characteristics, associations with health outcomes, and its limitations will be discussed.

Co-exposure to multiple air pollutants and sleep disordered breathing in patients with or without obstructive sleep apnea: A cross-sectional study

BACKGROUND

Air pollution may be a contributing risk factor for obstructive sleep apnea (OSA). However, the health effects of co-exposure to multiple air pollutants on OSA patients remain unclear.

OBJECTIVES

To assess the joint effect of multi-pollutant on sleep disordered breathing (SDB) parameters in patients with or without OSA and identify the dominant pollutants.

METHODS

A total of 2524 outpatients from April 2020 to May 2021 were recruited in this cross-sectional study. Ambient air pollutant data were obtained from the nearest central monitoring stations to participants' residential address. SDB parameters were measured by the ApneaLink devices, including apnea-hypopnea index (AHI), hypopnea index (HI), oxygen desaturation index (ODI), average oxygen saturation (SpO₂), percentage sleep time with <90% saturation (T90), and desaturation. Bayesian kernel machine regression (BKMR) was applied to evaluate the effects of multiple pollutants.

RESULTS

Significant associations were observed between air pollutants and SDB parameters (including increases in AHI, HI, ODI, and desaturation) among patients with OSA. Co-exposure to air pollutants was positively correlated with AHI, HI, and ODI. PM₁₀ and O₃ dominated the effects of pollutant mixtures on OSA, with the highest posterior inclusion probability (PIP) values of 0.592 and 0.640, respectively. Stratified analysis showed that, compared to male patients with OSA, stronger effects on the SDB parameters were observed in female patients. Stronger associations were also found in the warm season than those in the cold season.

CONCLUSION

Co-exposure to air pollutants was associated with SDB parameters among patients with OSA, PM₁₀ and O₃ might play the dominant roles.

Novel oxygen desaturation parameters are associated with cardiac troponin I: Data from the Akershus Sleep Apnea Project

Novel diagnostic markers for obstructive sleep apnea beyond the apnea-hypopnea index (AHI) have been introduced. There are no studies on their association with markers of subclinical myocardial injury. We assessed the association between novel desaturation parameters and elevated cardiac troponin I and T. Participants with polysomnography (498) from the Akershus Sleep Apnea study were divided into normal and elevated biomarker groups based on sex-specific concentration thresholds (cardiac troponin I: ≥4 ng/L for women, ≥6 ng/L for men; and cardiac troponin T: ≥7 ng/L for women, ≥8 ng/L for men). Severity of obstructive sleep apnea was evaluated with the AHI, oxygen desaturation index, total sleep time with oxygen saturation below 90% (T90), lowest oxygen saturation (Min SpO₂ %), and novel oxygen desaturation parameters: desaturation duration and desaturation severity. How the AHI and novel desaturation parameters predicted elevated cardiac troponin I and cardiac troponin T levels was assessed by the area under the curve (AUC). Based on multivariable-adjusted linear regression, the AHI (β = 0.004, p = 0.012), desaturation duration (β = 0.007, p = 0.004), and desaturation severity (β = 0.147, p = 0.002) were associated with cardiac troponin I levels but not cardiac troponin T. T90 was associated with cardiac troponin I (β = 0.006, p = 0.009) and cardiac troponin T (β = 0.005, p = 0.007). The AUC for the AHI 0.592 (standard error 0.043) was not significantly different from the AUC of T90 (SD 0.640, p = 0.08), desaturation duration 0.609 (SD 0.044, p = 0.42) or desaturation severity 0.616 (SD 0.043, p = 0.26) in predicting myocardial injury as assessed by cardiac troponin I. Oxygen desaturation parameters and the AHI were associated with cardiac troponin I levels but not cardiac troponin T levels. Novel oxygen desaturation parameters did not improve the prediction of subclinical myocardial injury compared to the AHI.

Diabetes and cardiovascular diseases are associated with the worsening of intermittent hypoxaemia

Intermittent hypoxaemia is a risk factor for numerous diseases. However, the reverse pathway remains unclear. Therefore, we investigated whether pre-existing hypertension, diabetes or cardiovascular diseases are associated with the worsening of intermittent hypoxaemia. Among the included 2,535 Sleep Heart Health Study participants, hypertension (n = 1,164), diabetes (n = 170) and cardiovascular diseases (n = 265) were frequently present at baseline. All participants had undergone two polysomnographic recordings approximately 5.2 years apart. Covariate-adjusted linear regression analyses were utilized to investigate the difference in the severity of intermittent hypoxaemia at baseline between each comorbidity group and the group of participants free from all comorbidities (n = 1,264). Similarly, we investigated whether the pre-existing comorbidities are associated with the progression of intermittent hypoxaemia. Significantly higher oxygen desaturation index (β = 1.77 [95% confidence interval: 0.41-3.13], p = 0.011), desaturation severity (β = 0.07 [95% confidence interval: 0.00-0.14], p = 0.048) and desaturation duration (β = 1.50 [95% confidence interval: 0.31-2.69], p = 0.013) were observed in participants with pre-existing cardiovascular diseases at baseline. Furthermore, the increase in oxygen desaturation index (β = 3.59 [95% confidence interval: 1.78-5.39], p < 0.001), desaturation severity (β = 0.08 [95% confidence interval: 0.02-0.14], p = 0.015) and desaturation duration (β = 2.60 [95% confidence interval: 1.22-3.98], p < 0.001) during the follow-up were higher among participants with diabetes. Similarly, the increase in oxygen desaturation index (β = 2.73 [95% confidence interval: 1.15-4.32], p = 0.001) and desaturation duration (β = 1.85 [95% confidence interval: 0.62-3.08], p = 0.003) were higher among participants with cardiovascular diseases. These results suggest that patients with pre-existing diabetes or cardiovascular diseases are at increased risk for an expedited worsening of intermittent hypoxaemia. As intermittent hypoxaemia is an essential feature of sleep apnea, these patients could benefit from the screening and follow-up monitoring of sleep apnea.

The Impact of Intermittent Hypoxemia on Left Atrial Remodeling in Patients with Obstructive Sleep Apnea Syndrome

Obstructive sleep apnea syndrome (OSAS) is a significant risk factor for left atrial (LA) remodeling. Intermittent hypoxemia occurs during the sleep cycle in patients with OSAS and plays a crucial role in cardiovascular pathologies such as stroke, arrhythmia, and coronary artery disease. However, there is very little information about the role of intermittent hypoxemia in LA remodeling in patients with OSAS. In total, 154 patients with sleep-related breathing disorders (SRBD) were prospectively recruited for this study. All enrolled SRBD patients underwent polysomnography and echocardiography. Significant OSAS was defined as an oxygen desaturation index (ODI) of ≥10 per hour. Intermittent hypoxia/reoxygenation (IHR) stimulation was used to test the effect of hypoxia on the viability, reactive oxygen species, apoptosis, and inflammation-associated cytokine expression in the HL-1 cell line. To investigate the effect of patients’ exosomes on HIF-1 and inflammation-associated cytokine expression, as well as the relationship between ODI and their expression, exosomes were purified from the plasma of 95 patients with SRBD and incubated in HL-1 cells. The LA size was larger in patients with significant OSAS than in those without. There was a significant association between ODI, lowest SpO2, mean SpO2, and LA size (all p < 0.05) but not between the apnea–hypopnea index and LA size. IHR condition caused increased LDH activity, reactive oxygen species (ROS) levels, and apoptosis in HL-1 cells and decreased cellular viability (all p < 0.05). The expression of HIF-1α, TNF-α, IL-6, and TGF-β increased in the IHR condition compared with the control (all p < 0.05). The expression of HIF-1α, IL-1β, and IL-6 increased in the HL-1 cells incubated with exosomes from those patients with significant OSAS than those without (all p < 0.05). There was a significantly positive correlation between ODI and the expression of HIF-1α, TNF-α, IL-1β, IL-6, and TGF-β; a significantly negative correlation between mean SpO2 and IL-6 and TGF-β; and a significantly negative correlation between the lowest SpO2 and HIF-1α (all p < 0.05). In conclusion, intermittent hypoxemia was strongly associated with LA remodeling, which might be through increased ROS levels, LDH activity, apoptosis, and the expression of HIF-1α and inflammation-associated cytokines.

Pulse Oximetry: The Working Principle, Signal Formation, and Applications

Pulse oximeters are routinely used in various medical-grade and consumer-grade applications. They can be used to estimate, for example, blood oxygen saturation, autonomic nervous system activity and cardiac function, blood pressure, sleep quality, and recovery through the recording of photoplethysmography signal. Medical-grade devices often record red and infra-red light-based photoplethysmography signals while smartwatches and other consumer-grade devices usually rely on a green light. At its simplest, a pulse oximeter can consist of one or two photodiodes and a photodetector attached, for example, a fingertip or earlobe. These sensors are used to record light absorption in a medium as a function of time. This time-varying absorption information is used to form a photoplethysmography signal. In this chapter, we discuss the working principles of pulse oximeters and the formation of the photoplethysmography signal. We will further discuss the advantages and disadvantages of pulse oximeters, which kind of applications exist in the medical field, and how pulse oximeters are utilized in daily health monitoring.

Effect of nocturnal hypoxemia on glycemic control among diabetic Saudi patients presenting with obstructive sleep apnea

BACKGROUND

Obstructive sleep apnea (OSA) is a prevalent disease that is associated with an increased incidence of type II diabetes mellitus (DM) if left untreated. We aimed to determine the association between glycosylated hemoglobin (HbA1c) levels and both nocturnal hypoxemia and apnea-hypopnea index (AHI) among a Saudi patients with OSA.

METHODS

A cross-sectional study that enrolled 103 adult patients diagnosed with DM and confirmed to have OSA by full night attended polysomnography between 2018 and 2021. Those who presented with acute illness, chronic obstructive pulmonary disease (COPD)/restrictive lung diseases causing sleep-related hypoxemia, or no available HbA1c level within 6 months before polysomnography were excluded from the study. Univariate and multivariate linear regression analyses between HbA1c levels and parameters of interest were tested.

RESULTS

Sixty-seven (65%) of the studied population had uncontrolled DM (HbA1c ≥7%). In univariate regression analysis, there was a significant positive association between HbA1c, and sleep time spent with an oxygen saturation below 90% (T90), female gender, and body mass index (BMI) (p<0.05) but not AHI, or associated comorbidities (p>0.05). In the multivariate analysis, HbA1c was positively associated with increasing T90 (p<0.05), and ODI (p<0.05), but not with AHI (p>0.05).

CONCLUSION

Nocturnal hypoxemia could be an important factor affecting glycemic control in patients with OSA suffering from DM irrespective of the severity of both diseases.

Implications of Obstructive Sleep-related Breathing Disorder in Dentistry: Focus on Snoring and Obstructive Sleep Apnea

Obstructive sleep-related breathing disorder (SRBD) is an umbrella term that encompasses various types of upper airway dysfunctions during sleep characterized by increased respiratory effort secondary to snoring and/or increased upper airway resistance and pharyngeal collapse. Obstructive sleep apnea (OSA) is a representative SRBD that involves a significant decrease in or cessation of airflow despite the presence of respiratory effort. While snoring is considered a normal condition, it can cause serious noise disturbance to sleep partners and is considered a predictor of OSA. Snoring and OSA are highly correlated with obesity. SRBDs can lead to cardiovascular disease, hypertension, decreased quality of life, decreased work efficiency, daytime sleepiness, decreased neurocognitive activity, and psychological impairments. In dentistry, research on sleep problems has focused on temporomandibular disorder (TMD)/orofacial pain. The relationship between OSA and TMD/orofacial pain has been reported, but it is not clear whether it is a simple correlation or a causal relationship. Therefore, we aimed to review the causes of SRBDs including snoring and OSA and to review and infer the relationship between these SRBDs and TMD/orofacial pain. The effects of snoring and OSA extend beyond sleep disturbances and are worthy of future research, especially with regard to TMD.

Oximetry Indices in the Management of Sleep Apnea: From Overnight Minimum Saturation to the Novel Hypoxemia Measures

Obstructive sleep apnea (OSA) is a multidimensional disease often underdiagnosed due to the complexity and unavailability of its standard diagnostic method: the polysomnography. Among the alternative abbreviated tests searching for a compromise between simplicity and accurateness, oximetry is probably the most popular. The blood oxygen saturation (SpO₂) signal is characterized by a near-constant profile in healthy subjects breathing normally, while marked drops (desaturations) are linked to respiratory events. Parameterization of the desaturations has led to a great number of indices of severity assessment commonly used to assist in OSA diagnosis. In this chapter, the main methodologies used to characterize the overnight oximetry profile are reviewed, from visual inspection and simple statistics to complex measures involving signal processing and pattern recognition techniques. We focus on the individual performance of each approach, but also on the complementarity among the great amount of indices existing in the state of the art, looking for the most relevant oximetric feature subset. Finally, a quick overview of SpO₂-based deep learning applications for OSA management is carried out, where the raw oximetry signal is analyzed without previous parameterization. Our research allows us to conclude that all the methodologies (conventional, time, frequency, nonlinear, and hypoxemia-based) demonstrate high ability to provide relevant oximetric indices, but only a reduced set provide non-redundant complementary information leading to a significant performance increase. Finally, although oximetry is a robust tool, greater standardization and prospective validation of the measures derived from complex signal processing techniques are still needed to homogenize interpretation and increase generalizability.

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.

Time Under 90% Oxygen Saturation and Systemic Hypertension in Patients with Obstructive Sleep Apnea Syndrome

PURPOSE

The diagnosis and severity of obstructive sleep apnea (OSA) are commonly based on the apnea hypopnea index (AHI). However, patients with similar severity AHIs may show widely varying comorbidities and risks for cardiovascular disease, which may be associated with different severities of nocturnal hypoxia. The percentage of cumulative time with oxygen saturation below 90% in total sleep time (T90) is receiving increasing attention in OSA research because it describes the duration and degree of hypoxia during the whole sleep. This study aimed to explore the distribution of T90 in OSA patients with similar severity and to evaluate the relationship between T90 and hypertension.

PATIENTS AND METHODS

A total of 775 patients with OSA were enrolled in this study, all participants were divided into groups according to the T90 value: light hypoxia (T90≤5%), mild hypoxia (T90 accounted for 5-10%), moderate hypoxia (T90 accounted for 10-25%), and severe hypoxia (T90>25%). Multivariate logistic regression analysis was performed to assess the association between T90 and hypertension.

RESULTS

Of the patients with mild OSA, 94.33% had light hypoxia, and 88.64% of moderate OSA patients had light hypoxia. The proportions of light, mild, moderate, and severe hypoxia among patients with severe OSA were 28.60%, 17.69%, 21.40%, and 32.31%, respectively. After adjustment for potential confounders, the risk of hypertension in patients with severe OSA increased according to the severity categories of T90. The odds ratio for T90 accounting for 10-25% relative to T90≤5% was 2.544 (95%confidence interval, 1.254-5.164; P=0.010) and as high as 2.692 (95%confidence interval, 1.403-5.166; P=0.003) in patients with T90>25%.

CONCLUSION

OSA patients with similar degree of AHI may have different T90 values, especially in severe OSA. A higher T90 was independently associated with the risk of hypertension after adjustment for traditional risk factors in patients with severe OSA. Our findings highlight the potential role for T90 in predicting hypertension in patients severe OSA.

Current and future strategies for diagnostic and management of obstructive sleep apnea

INTRODUCTION

Obstructive sleep apnea (OSA) is a common sleep disorder with multiple comorbidities including hypertension, diabetes, and cardiovascular disorders. Detected based on an overnight sleep study is called polysomnography (PSG); OSA still remains undiagnosed in majority of the population mainly attributed to lack of awareness. To overcome the limitations posed by PSG such as patient discomfort and overnight hospitalization, newer technologies are being explored. In addition, challenges associated with current management of OSA using continuous positive airway pressure (CPAP), etc. presents several pitfalls.

AREAS COVERED

Conventional and modern detection/management techniques including PSG, CPAP, smart wearable/pillows, bio-motion sensors, etc., have both pros and cons. To fulfill the limitations in OSA diagnostics, there is an imperative need for new technology for screening of symptomatic and more importantly asymptomatic OSA patients to reduce the risk of several associated life-threatening comorbidities. In this line, molecular marker-based diagnostics have shown great promises.

EXPERT OPINION

A detailed overview is presented on the OSA management and diagnostic approaches and recent advances in the molecular screening methods. The potentials of biomarker-based detection and its limitations are also portrayed and a comparison between the standard, current modern approaches, and promising futuristic technologies for OSA diagnostics and management is set forth.ABBREVIATIONS AHI: Apnea hypopnea index; AI: artificial intelligence; CAM: Cell adhesion molecules; CPAP: Continuous Positive Airway Pressure; COVID-19: Coronavirus Disease 2019; CVD: Cardiovascular disease; ELISA: Enzyme linked immunosorbent assay; HSAT: Home sleep apnea testing; IR-UWB: Impulse radio-ultra wideband; MMA: maxillomandibular advancement; PSG: Polysomnography; OSA: Obstructive sleep apnea; SOD: Superoxide dismutase; QD: Quantum dot.

Sleep Measurements in Women

Sleep in women and men have been studied in several studies with higher prevalence of sleep complaints in women compared with men. Several factors can affect sleep and could be argued to contribute to sex and gender differences in general sleep. There are no differences in guidelines when measuring sleep in women but several sleep assessment tools have been validated or compared between sexes. Because there is still a lack of knowledge on sleep measurements in women, the present review aimed to produce an overview of the current knowledge of objective and subjective sleep measurements in women.

Towards Validating the Effectiveness of Obstructive Sleep Apnea Classification from Electronic Health Records Using Machine Learning

Obstructive sleep apnea (OSA) is a common, chronic, sleep-related breathing disorder characterized by partial or complete airway obstruction in sleep. The gold standard diagnosis method is polysomnography, which estimates disease severity through the Apnea-Hypopnea Index (AHI). However, this is expensive and not widely accessible to the public. For effective screening, this work implements machine learning algorithms for classification of OSA. The model is trained with routinely acquired clinical data of 1479 records from the Wisconsin Sleep Cohort dataset. Extracted features from the electronic health records include patient demographics, laboratory blood reports, physical measurements, habitual sleep history, comorbidities, and general health questionnaire scores. For distinguishing between OSA and non-OSA patients, feature selection methods reveal the primary important predictors as waist-to-height ratio, waist circumference, neck circumference, body-mass index, lipid accumulation product, excessive daytime sleepiness, daily snoring frequency and snoring volume. Optimal hyperparameters were selected using a hybrid tuning method consisting of Bayesian Optimization and Genetic Algorithms through a five-fold cross-validation strategy. Support vector machines achieved the highest evaluation scores with accuracy: 68.06%, sensitivity: 88.76%, specificity: 40.74%, F1-score: 75.96%, PPV: 66.36% and NPV: 73.33%. We conclude that routine clinical data can be useful in prioritization of patient referral for further sleep studies.

Gamma Power of Electroencephalogram Arousal is Modulated by Respiratory Event Type and Severity in Obstructive Sleep Apnea

OBJECTIVE

We aimed to investigate the differences in electroencephalogram (EEG) gamma power (30-40 Hz) of respiratory arousals between varying types and severities of respiratory events, and in different sleep stages.

METHODS

Power spectral densities of EEG signals from diagnostic Type I polysomnograms of 869 patients with clinically suspected obstructive sleep apnea were investigated. Arousals were compared between sleep stages, as well as between the type (obstructive apnea and hypopnea), and duration (10-20 s, 20-30 s, and >30 s) of the related respiratory event. Moreover, we investigated whether the presence of a ≥3% blood oxygen desaturation influenced the arousal gamma power.

RESULTS

Gamma power of respiratory arousals was the lowest in Stage R sleep and increased from Stage N1 towards Stage N3. Gamma power was higher when the arousals were caused by obstructive apneas compared to hypopneas. Moreover, arousal gamma power increased when the duration of the related apnea increased, whereas an increase in the hypopnea duration did not have a similar effect. Furthermore, respiratory events associated with desaturations increased the arousal gamma power more compared to respiratory events not associated with desaturations.

CONCLUSION

Gamma power of respiratory arousals increased in deeper sleep and as the severity of the related respiratory event increased in terms of degree of obstruction and presence of desaturation.

SIGNIFICANCE

As increased gamma power might indicate a greater shift towards wakefulness, the present findings demonstrate that the arousal intensity and the magnitude of sleep disruption may vary depending on the event type and severity.

Obstructive Sleep Apnea and Cardiac Arrhythmias: A Contemporary Review

Obstructive sleep apnea (OSA) is a highly prevalent disorder with a growing incidence worldwide that closely mirrors the global obesity epidemic. OSA is associated with enormous healthcare costs in addition to significant morbidity and mortality. Much of the morbidity and mortality related to OSA can be attributed to an increased burden of cardiovascular disease, including cardiac rhythm disorders. Awareness of the relationship between OSA and rhythm disorders is variable among physicians, a fact that can influence patient care, since the presence of OSA can influence the incidence, prevalence, and successful treatment of multiple rhythm disorders. Herein, we provide a review of this topic that is intentionally broad in scope, covering the relationship between OSA and rhythm disorders from epidemiology and pathophysiology to diagnosis and management, with a particular focus on the recognition of undiagnosed OSA in the general clinical population and the intimate relationship between OSA and atrial fibrillation.

How sleepy patients differ from non-sleepy patients in mild obstructive sleep apnea?

To aim is investigate whether demographic, polysomnographic or sleep behaviour data differ between non-sleepy, sleepy and very sleepy patients with mild obstructive sleep apnea. The study population consisted of 439 consecutive adult patients diagnosed with mild obstructive sleep apnea (5 ≤ apnea-hypopnea index < 15) after a complete polysomnographic evaluation. The patients were divided into three groups based on subjective sleepiness: very sleepy (Epworth Sleepiness Scale ≥ 16, n = 59); sleepy (10 < Epworth Sleepiness Scale < 16, n = 102); and non-sleepy (Epworth Sleepiness Scale ≤ 10, n = 278). Demographic, polysomnographic and sleep behaviour data were compared between the groups. There were no statistically significant differences in breathing abnormality indices and most of the demographic features between the groups. The number of arousals was significantly higher in the very sleepy group compared with the non-sleepy group (140.8 ± 105.2 versus 107.6 ± 72.2). Very sleepy patients reported feeling sleepy during the daytime more often (42.4% versus 31.7%) and sleeping significantly less during the week compared with non-sleepy patients. Also, a significantly higher proportion of sleepy (47.1%) and very sleepy patients (44.1%) reported taking naps during weekends compared with non-sleepy patients (35.6%). In a regression analysis, also total sleep time (β = 0.045), sleep efficiency (β = -0.160), apnea index (β = -0.397), apnea-hypopnea index in supine position (β = 0.044), periodic limb movement index (β = 0.196) and periodic limb movement-related arousal index (β = -0.210) affected subjective daytime sleepiness. The results suggest that excessive daytime sleepiness in patients with mild obstructive sleep apnea appears to be related to inadequate sleeping habits (i.e. insufficient sleep during working days) and decreased sleep quality rather than differences in breathing abnormalities.

Detailed Assessment of Sleep Architecture With Deep Learning and Shorter Epoch-to-Epoch Duration Reveals Sleep Fragmentation of Patients With Obstructive Sleep Apnea

Traditional sleep staging with non-overlapping 30-second epochs overlooks multiple sleep-wake transitions. We aimed to overcome this by analyzing the sleep architecture in more detail with deep learning methods and hypothesized that the traditional sleep staging underestimates the sleep fragmentation of obstructive sleep apnea (OSA) patients. To test this hypothesis, we applied deep learning-based sleep staging to identify sleep stages with the traditional approach and by using overlapping 30-second epochs with 15-, 5-, 1-, or 0.5-second epoch-to-epoch duration. A dataset of 446 patients referred for polysomnography due to OSA suspicion was used to assess differences in the sleep architecture between OSA severity groups. The amount of wakefulness increased while REM and N3 decreased in severe OSA with shorter epoch-to-epoch duration. In other OSA severity groups, the amount of wake and N1 decreased while N3 increased. With the traditional 30-second epoch-to-epoch duration, only small differences in sleep continuity were observed between the OSA severity groups. With 1-second epoch-to-epoch duration, the hazard ratio illustrating the risk of fragmented sleep was 1.14 (p = 0.39) for mild OSA, 1.59 (p < 0.01) for moderate OSA, and 4.13 (p < 0.01) for severe OSA. With shorter epoch-to-epoch durations, total sleep time and sleep efficiency increased in the non-OSA group and decreased in severe OSA. In conclusion, more detailed sleep analysis emphasizes the highly fragmented sleep architecture in severe OSA patients which can be underestimated with traditional sleep staging. The results highlight the need for a more detailed analysis of sleep architecture when assessing sleep disorders.