Multicentre sleep-stage scoring agreement in the Sleep Revolution project.

Determining sleep stages accurately is an important part of the diagnostic process for numerous sleep disorders. However, as the sleep stage scoring is done manually following visual scoring rules there can be considerable variation in the sleep staging between different scorers. Thus, this study aimed to comprehensively evaluate the inter-rater agreement in sleep staging. A total of 50 polysomnography recordings were manually scored by 10 independent scorers from seven different sleep centres. We used the 10 scorings to calculate a majority score by taking the sleep stage that was the most scored stage for each epoch. The overall agreement for sleep staging was κ = 0.71 and the mean agreement with the majority score was 0.86. The scorers were in perfect agreement in 48% of all scored epochs. The agreement was highest in rapid eye movement sleep (κ = 0.86) and lowest in N1 sleep (κ = 0.41). The agreement with the majority scoring varied between the scorers from 81% to 91%, with large variations between the scorers in sleep stage-specific agreements. Scorers from the same sleep centres had the highest pairwise agreements at κ = 0.79, κ = 0.85, and κ = 0.78, while the lowest pairwise agreement between the scorers was κ = 0.58. We also found a moderate negative correlation between sleep staging agreement and the apnea-hypopnea index, as well as the rate of sleep stage transitions. In conclusion, although the overall agreement was high, several areas of low agreement were also found, mainly between non-rapid eye movement stages.

Influence of head flexion and rotation on obstructive sleep apnea severity during supine sleep.

Head posture influences the collapsibility of the passive upper airway during anaesthesia. However, little is known about the impact of head posture during sleep. The objective of this study was to develop and validate an instrument to measure head posture during supine sleep and to apply this instrument to investigate the influence of head posture on obstructive sleep apnea (OSA) severity. A customized instrument to quantify head flexion and rotation during supine sleep was developed and validated in a benchtop experiment. Twenty-eight participants with suspected OSA were successfully studied using diagnostic polysomnography with the addition of the customized instrument. Head posture in supine sleep was discretized into four categories by two variables: head flexed or not (flexion >15°); and head rotated or not (rotation >45°). Sleep time in each posture and the posture-specific apnea-hypopnea index (AHI) were quantified. Linear mixed-effect modelling was applied to determine the influence of flexion and rotation on supine OSA severity. Twenty-four participants had ≥15 min of supine sleep in at least one head-posture category. Only one participant had ≥15 min of supine sleep time with the head extended. Head flexion was associated with a 12.9 events/h increase in the AHI (95% CI: 3.7-22.1, p = .007). Head rotation was associated with an 11.0 events/h decrease in the AHI (95% CI: 0.3-21.6, p = .04). Despite substantial interparticipant variability, head flexion worsened OSA severity, and head rotation improved OSA severity. Interventions to promote rotation and restrict flexion may have therapeutic benefit in selected patients.

Breath-holding as a novel approach to risk stratification in COVID-19.

BACKGROUND: Despite considerable progress, it remains unclear why some patients admitted for COVID-19 develop adverse outcomes while others recover spontaneously. Clues may lie with the predisposition to hypoxemia or unexpected absence of dyspnea ('silent hypoxemia') in some patients who later develop respiratory failure. Using a recently-validated breath-holding technique, we sought to test the hypothesis that gas exchange and ventilatory control deficits observed at admission are associated with subsequent adverse COVID-19 outcomes (composite primary outcome: non-invasive ventilatory support, intensive care admission, or death). METHODS: Patients with COVID-19 (N = 50) performed breath-holds to obtain measurements reflecting the predisposition to oxygen desaturation (mean desaturation after 20-s) and reduced chemosensitivity to hypoxic-hypercapnia (including maximal breath-hold duration). Associations with the primary composite outcome were modeled adjusting for baseline oxygen saturation, obesity, sex, age, and prior cardiovascular disease. Healthy controls (N = 23) provided a normative comparison. RESULTS: The adverse composite outcome (observed in N = 11/50) was associated with breath-holding measures at admission (likelihood ratio test, p = 0.020); specifically, greater mean desaturation (12-fold greater odds of adverse composite outcome with 4% compared with 2% desaturation, p = 0.002) and greater maximal breath-holding duration (2.7-fold greater odds per 10-s increase, p = 0.036). COVID-19 patients who did not develop the adverse composite outcome had similar mean desaturation to healthy controls. CONCLUSIONS: Breath-holding offers a novel method to identify patients with high risk of respiratory failure in COVID-19. Greater breath-hold induced desaturation (gas exchange deficit) and greater breath-holding tolerance (ventilatory control deficit) may be independent harbingers of progression to severe disease.

Longer duration electroencephalogram arousals have a better relationship with impaired vigilance and health status in obstructive sleep apnoea.

PURPOSE: Obstructive sleep apnoea (OSA) is a prevalent sleep disorder with significant health consequences. Sleep fragmentation is a feature of OSA and is often determined by the arousal index (ArI), a metric based on the electroencephalograph (EEG). The ArI has a weak correlation with neurocognitive outcomes in OSA patients. In this study, we examine whether changing from the current minimum EEG arousal duration of 3 s improves the association between sleep fragmentation and neurocognitive outcomes. METHODS: In a retrospective study, we selected OSA patients without any other comorbidities that are associated with neurocognitive impairment. The OSA patients were clustered into two groups based on their psychomotor vigilance task (PVT) performance to represent impaired and unimpaired neurocognition. RESULTS: While no differences were found in demographics or usual sleep study statistics, the impaired group had a greater number of EEG arousals greater than 5 s (P = 0.034), 7 s (P = 0.041), and 15 s (P = 0.036) in duration. There were no differences in the number of EEG arousals associated with sleep-disordered breathing events. These differences also corresponded with quality of life outcomes between the two groups. An ArI with a duration of 5 s or greater had the best combination of sensitivity (70.0%) and specificity (66.7%) compared with the usual 3 s duration (sensitivity and specificity of 70.0% and 53.3%, respectively). CONCLUSION: A re-examination of the EEG arousal scoring rules, and their duration, may help with allocation of health resources to OSA patients most in need.

A review of approaches for analysing obstructive sleep apnoea-related patterns in pulse oximetry data.

Overnight pulse oximetry allows the relatively non-invasive estimation of peripheral blood haemoglobin oxygen saturations (SpO2 ), and forms part of the typical polysomnogram (PSG) for investigation of obstructive sleep apnoea (OSA). While the raw SpO2 signal can provide detailed information about OSA-related pathophysiology, this information is typically summarized with simple statistics such as the oxygen desaturation index (ODI, number of desaturations per hour). As such, this study reviews the technical methods for quantifying OSA-related patterns in oximetry data. The technical methods described in literature can be broadly grouped into four categories: (i) Describing the detailed characteristics of desaturations events; (ii) Time series statistics; (iii) Analysis of power spectral distribution (i.e. frequency domain analysis); and (d) Non-linear analysis. These are described and illustrated with examples of oximetry traces. The utilization of these techniques is then described in two applications. First, the application of detailed oximetry analysis allows the accurate automated classification of PSG-defined OSA. Second, quantifications which better characterize the severity of desaturation events are better predictors of OSA-related epidemiological outcomes than standard clinical metrics. Finally, methodological considerations and further applications and opportunities are considered.

Intra-night variation in apnea-hypopnea index affects diagnostics and prognostics of obstructive sleep apnea.

BACKGROUND: Diagnostics of obstructive sleep apnea (OSA) is based on apnea-hypopnea index (AHI) determined as full-night average of occurred events. We investigate our hypothesis that intra-night variation in the frequency of obstructive events affects diagnostics and prognostics of OSA and should therefore be considered in clinical practice. METHODS: Polygraphic recordings of 1989 patients (mean follow-up 18.3 years) with suspected OSA were analyzed. Number and severity of individual obstructive events were calculated hourly for the first 6 h of sleep. OSA severity was determined based on the full-night AHI and AHI for the 2 h when the obstructive event frequency was highest (AHI2h). Hazard ratios for all-cause, cardiovascular, and non-cardiovascular mortalities were calculated for different OSA severity categories based on the full-night AHI and AHI2h. RESULTS: Frequency and duration of obstructive events varied hour-by-hour increasing towards morning. Using AHI2h led to a statistically significant rearrangement of patients between the OSA severity categories. The use of AHI2h for severity classification showed clearer relationship between the OSA severity and mortality than the full-night AHI. CONCLUSIONS: Currently, the intra-night variation in frequency and severity of obstructive events is completely ignored by conventional, full-night AHI and considering this information could improve the diagnostics of OSA.

The hypoxic burden of sleep apnoea predicts cardiovascular disease-related mortality: the Osteoporotic Fractures in Men Study and the Sleep Heart Health Study.

AIMS: Apnoea-hypopnoea index (AHI), the universal clinical metric of sleep apnoea severity, poorly predicts the adverse outcomes of sleep apnoea, potentially because the AHI, a frequency measure, does not adequately capture disease burden. Therefore, we sought to evaluate whether quantifying the severity of sleep apnoea by the 'hypoxic burden' would predict mortality among adults aged 40 and older. METHODS AND RESULTS: The samples were derived from two cohort studies: The Outcomes of Sleep Disorders in Older Men (MrOS), which included 2743 men, age 76.3 ± 5.5 years; and the Sleep Heart Health Study (SHHS), which included 5111 middle-aged and older adults (52.8% women), age: 63.7 ± 10.9 years. The outcomes were all-cause and Cardiovascular disease (CVD)-related mortality. The hypoxic burden was determined by measuring the respiratory event-associated area under the desaturation curve from pre-event baseline. Cox models were used to calculate the adjusted hazard ratios for hypoxic burden. Unlike the AHI, the hypoxic burden strongly predicted CVD mortality and all-cause mortality (only in MrOS). Individuals in the MrOS study with hypoxic burden in the highest two quintiles had hazard ratios of 1.81 [95% confidence interval (CI) 1.25-2.62] and 2.73 (95% CI 1.71-4.36), respectively. Similarly, the group in the SHHS with hypoxic burden in the highest quintile had a hazard ratio of 1.96 (95% CI 1.11-3.43). CONCLUSION: The 'hypoxic burden', an easily derived signal from overnight sleep study, predicts CVD mortality across populations. The findings suggest that not only the frequency but the depth and duration of sleep related upper airway obstructions, are important disease characterizing features.

Quantifying the magnitude of pharyngeal obstruction during sleep using airflow shape.

RATIONALE AND OBJECTIVES: Non-invasive quantification of the severity of pharyngeal airflow obstruction would enable recognition of obstructive versus central manifestation of sleep apnoea, and identification of symptomatic individuals with severe airflow obstruction despite a low apnoea-hypopnoea index (AHI). Here we provide a novel method that uses simple airflow-versus-time ("shape") features from individual breaths on an overnight sleep study to automatically and non-invasively quantify the severity of airflow obstruction without oesophageal catheterisation. METHODS: 41 individuals with suspected/diagnosed obstructive sleep apnoea (AHI range 0-91 events·h-1) underwent overnight polysomnography with gold-standard measures of airflow (oronasal pneumotach: "flow") and ventilatory drive (calibrated intraoesophageal diaphragm electromyogram: "drive"). Obstruction severity was defined as a continuous variable (flow:drive ratio). Multivariable regression used airflow shape features (inspiratory/expiratory timing, flatness, scooping, fluttering) to estimate flow:drive ratio in 136 264 breaths (performance based on leave-one-patient-out cross-validation). Analysis was repeated using simultaneous nasal pressure recordings in a subset (n=17). RESULTS: Gold-standard obstruction severity (flow:drive ratio) varied widely across individuals independently of AHI. A multivariable model (25 features) estimated obstruction severity breath-by-breath (R2=0.58 versus gold-standard, p<0.00001; mean absolute error 22%) and the median obstruction severity across individual patients (R2=0.69, p<0.00001; error 10%). Similar performance was achieved using nasal pressure. CONCLUSIONS: The severity of pharyngeal obstruction can be quantified non-invasively using readily available airflow shape information. Our work overcomes a major hurdle necessary for the recognition and phenotyping of patients with obstructive sleep disordered breathing.

Phenotyping Pharyngeal Pathophysiology using Polysomnography in Patients with Obstructive Sleep Apnea.

RATIONALE: Therapies for obstructive sleep apnea (OSA) could be administered on the basis of a patient's own phenotypic causes ("traits") if a clinically applicable approach were available. OBJECTIVES: Here we aimed to provide a means to quantify two key contributors to OSA-pharyngeal collapsibility and compensatory muscle responsiveness-that is applicable to diagnostic polysomnography. METHODS: Based on physiological definitions, pharyngeal collapsibility determines the ventilation at normal (eupneic) ventilatory drive during sleep, and pharyngeal compensation determines the rise in ventilation accompanying a rising ventilatory drive. Thus, measuring ventilation and ventilatory drive (e.g., during spontaneous cyclic events) should reveal a patient's phenotypic traits without specialized intervention. We demonstrate this concept in patients with OSA (N = 29), using a novel automated noninvasive method to estimate ventilatory drive (polysomnographic method) and using "gold standard" ventilatory drive (intraesophageal diaphragm EMG) for comparison. Specialized physiological measurements using continuous positive airway pressure manipulation were employed for further comparison. The validity of nasal pressure as a ventilation surrogate was also tested (N = 11). MEASUREMENTS AND MAIN RESULTS: Polysomnography-derived collapsibility and compensation estimates correlated favorably with those quantified using gold standard ventilatory drive (R = 0.83, P < 0.0001; and R = 0.76, P < 0.0001; respectively) and using continuous positive airway pressure manipulation (R = 0.67, P < 0.0001; and R = 0.64, P < 0.001; respectively). Polysomnographic estimates effectively stratified patients into high versus low subgroups (accuracy, 69-86% vs. ventilatory drive measures; P < 0.05). Traits were near-identical using nasal pressure versus pneumotach (N = 11, R ≥ 0.98, both traits; P < 0.001). CONCLUSIONS: Phenotypes of pharyngeal dysfunction in OSA are evident from spontaneous changes in ventilation and ventilatory drive during sleep, enabling noninvasive phenotyping in the clinic. Our approach may facilitate precision therapeutic interventions for OSA.

Identifying obstructive sleep apnoea patients responsive to supplemental oxygen therapy.

A possible precision-medicine approach to treating obstructive sleep apnoea (OSA) involves targeting ventilatory instability (elevated loop gain) using supplemental inspired oxygen in selected patients. Here we test whether elevated loop gain and three key endophenotypic traits (collapsibility, compensation and arousability), quantified using clinical polysomnography, can predict the effect of supplemental oxygen on OSA severity.36 patients (apnoea-hypopnoea index (AHI) >20 events·h-1) completed two overnight polysomnographic studies (single-blinded randomised-controlled crossover) on supplemental oxygen (40% inspired) versus sham (air). OSA traits were quantified from the air-night polysomnography. Responders were defined by a ≥50% reduction in AHI (supine non-rapid eye movement). Secondary outcomes included blood pressure and self-reported sleep quality.Nine of 36 patients (25%) responded to supplemental oxygen (ΔAHI=72±5%). Elevated loop gain was not a significant univariate predictor of responder/non-responder status (primary analysis). In post hoc analysis, a logistic regression model based on elevated loop gain and other traits (better collapsibility and compensation; cross-validated) had 83% accuracy (89% before cross-validation); predicted responders exhibited an improvement in OSA severity (ΔAHI 59±6% versus 12±7% in predicted non-responders, p=0.0001) plus lowered morning blood pressure and "better" self-reported sleep.Patients whose OSA responds to supplemental oxygen can be identified by measuring their endophenotypic traits using diagnostic polysomnography.

Dynamic loop gain increases upon adopting the supine body position during sleep in patients with obstructive sleep apnoea.

BACKGROUND AND OBJECTIVE: Obstructive sleep apnoea (OSA) is typically worse in the supine versus lateral sleeping position. One potential factor driving this observation is a decrease in lung volume in the supine position which is expected by theory to increase a key OSA pathogenic factor: dynamic ventilatory control instability (i.e. loop gain). We aimed to quantify dynamic loop gain in OSA patients in the lateral and supine positions, and to explore the relationship between change in dynamic loop gain and change in lung volume with position. METHODS: Data from 20 patients enrolled in previous studies on the effect of body position on OSA pathogenesis were retrospectively analysed. Dynamic loop gain was calculated from routinely collected polysomnographic signals using a previously validated mathematical model. Lung volumes were measured in the awake state with a nitrogen washout technique. RESULTS: Dynamic loop gain was significantly higher in the supine than in the lateral position (0.77 ± 0.15 vs 0.68 ± 0.14, P = 0.012). Supine functional residual capacity (FRC) was significantly lower than lateral FRC (81.0 ± 15.4% vs 87.3 ± 18.4% of the seated FRC, P = 0.021). The reduced FRC we observed on moving to the supine position was predicted by theory to increase loop gain by 10.2 (0.6, 17.1)%, a value similar to the observed increase of 8.4 (-1.5, 31.0)%. CONCLUSION: Dynamic loop gain increased by a small but statistically significant amount when moving from the lateral to supine position and this may, in part, contribute to the worsening of OSA in the supine sleeping position.

The private life of echidnas: using accelerometry and GPS to examine field biomechanics and assess the ecological impact of a widespread, semi-fossorial monotreme.

The short-beaked echidna (Tachyglossus aculeatus) is a monotreme and therefore provides a unique combination of phylogenetic history, morphological differentiation and ecological specialisation for a mammal. The echidna has a unique appendicular skeleton, a highly specialised myrmecophagous lifestyle and a mode of locomotion that is neither typically mammalian nor reptilian, but has aspects of both lineages. We therefore were interested in the interactions of locomotor biomechanics, ecology and movements for wild, free-living short-beaked echidnas. To assess locomotion in its complex natural environment, we attached both GPS and accelerometer loggers to the back of echidnas in both spring and summer. We found that the locomotor biomechanics of echidnas is unique, with lower stride length and stride frequency than reported for similar-sized mammals. Speed modulation is primarily accomplished through changes in stride frequency, with a mean of 1.39 Hz and a maximum of 2.31 Hz. Daily activity period was linked to ambient air temperature, which restricted daytime activity during the hotter summer months. Echidnas had longer activity periods and longer digging bouts in spring compared with summer. In summer, echidnas had higher walking speeds than in spring, perhaps because of the shorter time suitable for activity. Echidnas spent, on average, 12% of their time digging, which indicates their potential to excavate up to 204 m3 of soil a year. This information highlights the important contribution towards ecosystem health, via bioturbation, of this widespread Australian monotreme.

Quantifying the ventilatory control contribution to sleep apnoea using polysomnography.

Elevated loop gain, consequent to hypersensitive ventilatory control, is a primary nonanatomical cause of obstructive sleep apnoea (OSA) but it is not possible to quantify this in the clinic. Here we provide a novel method to estimate loop gain in OSA patients using routine clinical polysomnography alone. We use the concept that spontaneous ventilatory fluctuations due to apnoeas/hypopnoeas (disturbance) result in opposing changes in ventilatory drive (response) as determined by loop gain (response/disturbance). Fitting a simple ventilatory control model (including chemical and arousal contributions to ventilatory drive) to the ventilatory pattern of OSA reveals the underlying loop gain. Following mathematical-model validation, we critically tested our method in patients with OSA by comparison with a standard (continuous positive airway pressure (CPAP) drop method), and by assessing its ability to detect the known reduction in loop gain with oxygen and acetazolamide. Our method quantified loop gain from baseline polysomnography (correlation versus CPAP-estimated loop gain: n=28; r=0.63, p<0.001), detected the known reduction in loop gain with oxygen (n=11; mean±sem change in loop gain (ΔLG) -0.23±0.08, p=0.02) and acetazolamide (n=11; ΔLG -0.20±0.06, p=0.005), and predicted the OSA response to loop gain-lowering therapy. We validated a means to quantify the ventilatory control contribution to OSA pathogenesis using clinical polysomnography, enabling identification of likely responders to therapies targeting ventilatory control.

Increased Flow Limitation During Sleep Is Associated With Increased Psychomotor Vigilance Task Lapses in Individuals With Suspected OSA.

BACKGROUND: Impaired daytime vigilance is an important consequence of OSA, but several studies have reported no association between objective measurements of vigilance and the apnea-hypopnea index (AHI). Notably, the AHI does not quantify the degree of flow limitation, that is, the extent to which ventilation fails to meet intended ventilation (ventilatory drive). RESEARCH QUESTION: Is flow limitation during sleep associated with daytime vigilance in OSA? STUDY DESIGN AND METHODS: Nine hundred ninety-eight participants with suspected OSA completed a 10-min psychomotor vigilance task (PVT) before same-night in-laboratory polysomnography. Flow limitation frequency (percent of flow-limited breaths) during sleep was quantified using airflow shapes (eg, fluttering and scooping) from nasal pressure airflow. Multivariable regression assessed the association between flow limitation frequency and the number of lapses (response times > 500 ms, primary outcome), adjusting for age, sex, BMI, total sleep time, depression, and smoking status. RESULTS: Increased flow limitation frequency was associated with decreased vigilance: a 1-SD (35.3%) increase was associated with 2.1 additional PVT lapses (95% CI, 0.7-3.7; P = .003). This magnitude was similar to that for age, where a 1-SD increase (13.5 years) was associated with 1.9 additional lapses. Results were similar after adjusting for AHI, hypoxemia severity, and arousal severity. The AHI was not associated with PVT lapses (P = .20). In secondary exploratory analysis, flow limitation frequency was associated with mean response speed (P = .012), median response time (P = .029), fastest 10% response time (P = .041), slowest 10% response time (P = .018), and slowest 10% response speed (P = .005). INTERPRETATION: Increased flow limitation during sleep was associated with decreased daytime vigilance in individuals with suspected OSA, independent of the AHI. Flow limitation may complement standard clinical metrics in identifying individuals whose vigilance impairment most likely is explained by OSA.

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.

Sleep stage continuity is associated with objective daytime sleepiness in patients with suspected obstructive sleep apnea.

STUDY OBJECTIVES: Excessive daytime sleepiness (EDS) in patients with obstructive sleep apnea (OSA) is poorly explained by standard clinical sleep architecture metrics. We hypothesized that reduced sleep stage continuity mediates this connection independently from standard sleep architecture metrics. METHODS: 1,907 patients with suspected OSA with daytime sleepiness complaints underwent in-lab diagnostic polysomnography and next-day Multiple Sleep Latency Test (MSLT). Sleep architecture was evaluated with novel sleep-stage continuity quantifications (mean sleep stage duration and probability of remaining in each sleep stage), and conventional metrics (total N1, N2, N3 and REM times; and sleep onset latency). Multivariate analyses were utilized to identify variables associated with moderate EDS (5 ≤ mean daytime sleep latency (MSL) ≤ 10 minutes) and severe EDS (MSL < 5 minutes). RESULTS: Compared to those without EDS, participants with severe EDS had lower N3 sleep continuity (mean N3 period duration 10.4 vs 13.7 minutes, p<0.05), less N3 time (53.8 vs 76.5 minutes, p<0.05); greater total sleep time (374.0 vs 352.5 minutes, p<0.05) and greater N2 time (227.5 vs 186.8 minutes, p<0.05). After adjusting for standard sleep architecture metrics using multivariate logistic regression, decreased mean wake and N3 period duration, and the decreased probability of remaining in N2 and N3 sleep remained significantly associated with severe EDS, while the decreased probability of remaining in wake and N2 sleep were associated with moderate EDS. CONCLUSIONS: Patients with OSA with EDS experience lower sleep continuity, noticeable especially during N3 sleep and wake. Sleep-stage continuity quantifications assist in characterizing the sleep architecture and are associated with objective daytime sleepiness highlighting the need for more detailed evaluations of sleep quality.

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.

Nasal Pressure Derived Airflow Limitation and Ventilation Measurements are Resilient to Reduced Signal Quality.

Obstructive sleep apnea is a disorder characterized by partial or complete airway obstructions during sleep. Our previously published algorithms use the minimally invasive nasal pressure signal routinely collected during diagnostic polysomnography (PSG) to segment breaths and estimate airflow limitation (using flow:drive) and minute ventilation for each breath. The first aim of this study was to investigate the effect of airflow signal quality on these algorithms, which can be influenced by oronasal breathing and signal-to-noise ratio (SNR). It was hypothesized that these algorithms would make inaccurate estimates when the expiratory portion of breaths is attenuated to simulate oronasal breathing, and pink noise is added to the airflow signal to reduce SNR. At maximum SNR and 0% expiratory amplitude, the average error was 2.7% for flow:drive, -0.5% eupnea for ventilation, and 19.7 milliseconds for breath duration (n = 257,131 breaths). At 20 dB and 0% expiratory amplitude, the average error was -15.1% for flow:drive, 0.1% eupnea for ventilation, and 28.4 milliseconds for breath duration (n = 247,160 breaths). Unexpectedly, simulated oronasal breathing had a negligible effect on flow:drive, ventilation, and breath segmentation algorithms across all SNRs. Airflow SNR ≥ 20 dB had a negligible effect on ventilation and breath segmentation, whereas airflow SNR ≥ 30 dB had a negligible effect on flow:drive. The second aim of this study was to explore the possibility of correcting these algorithms to compensate for airflow signal asymmetry and low SNR. An offset based on estimated SNR applied to individual breath flow:drive estimates reduced the average error to ≤ 1.3% across all SNRs at patient and breath levels, thereby facilitating for flow:drive to be more accurately estimated from PSGs with low airflow SNR.Clinical Relevance- This study demonstrates that our airflow limitation, ventilation, and breath segmentation algorithms are robust to reduced airflow signal quality.

Pathophysiology Underlying Demographic and Obesity Determinants of Sleep Apnea Severity.

Rationale: Sleep apnea is the manifestation of key endotypic traits, including greater pharyngeal collapsibility, reduced dilator muscle compensation, and elevated chemoreflex loop gain. Objectives: We investigated how endotypic traits vary with obesity, age, sex, and race/ethnicity to influence sleep apnea disease severity (apnea-hypopnea index [AHI]). Methods: Endotypic traits were estimated from polysomnography in a diverse community-based cohort study (Multi-Ethnic Study of Atherosclerosis, N = 1,971; age range, 54-93 yr). Regression models assessed associations between each exposure (continuous variables per 2 standard deviations [SDs]) and endotypic traits (per SD) or AHI (events/h), independent of other exposures. Generalizability was assessed in two independent cohorts. Results: Greater AHI was associated with obesity (+19 events/h per 11 kg/m2 [2 SD]), male sex (+13 events/h vs. female), older age (+7 events/h per 20 yr), and Chinese ancestry (+5 events/h vs. White, obesity adjusted). Obesity-related increase in AHI was best explained by elevated collapsibility (+0.40 SD) and greater loop gain (+0.38 SD; percentage mediated, 26% [95% confidence interval (CI), 20-32%]). Male-related increase in AHI was explained by elevated collapsibility (+0.86 SD) and reduced compensation (-0.40 SD; percentage mediated, 57% [95% CI, 50-66%]). Age-related AHI increase was explained by elevated collapsibility (+0.37 SD) and greater loop gain (+0.15 SD; percentage mediated, 48% [95% CI, 34-63%]). Increased AHI with Chinese ancestry was explained by collapsibility (+0.57 SD; percentage mediated, 87% [95% CI, 57-100]). Black race was associated with reduced collapsibility (-0.30 SD) and elevated loop gain (+0.29 SD). Similar patterns were observed in the other cohorts. Conclusions: Different subgroups exhibit different underlying pathophysiological pathways to sleep apnea, highlighting the variability in mechanisms that could be targeted for intervention.