Association of novel measures of sleep disturbances with blood pressure: the Multi-Ethnic Study of Atherosclerosis

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Hypoxic Burden Based on Automatically Identified Desaturations Is Associated with Adverse Health Outcomes

Rationale: Recent studies have shown that sleep apnea-specific intermittent hypoxemia quantified by the hypoxic burden (HB) predicted cardiovascular disease (CVD)-related mortality in community-based and clinical cohorts. Calculation of HB is based on manual scoring of hypopneas and apneas, which is time-consuming and prone to interscorer variability. Objective: To validate a novel method to quantify the HB that is based on automatically scored desaturations. Methods: The sample included 5,655 middle-aged or older adults from the Sleep Heart Health Study (52.8% women; age, 63.2 ± 11.3 yr). The original HB method was based on a subject-specific search window obtained from an ensemble average of oxygen saturation signals (as measured by pulse oximetry) and synchronized with respect to the termination of scored respiratory events. In this study, however, the search window was obtained from ensemble average of oxygen saturation signals that synchronized with respect to the minimum of all automatically identified desaturations (⩾2% and other thresholds, including 3% and 4%, in sensitivity analyses). The time interval between the two maxima around the minimum saturation was defined as the search window. The oximetry-derived HB (HBOxi) was defined as the total area under all desaturation curves (restricted by the search window) divided by the total sleep time. Logistic and Cox regression models assessed the adjusted odds ratio (aOR)/hazard ratio of excessive daytime sleepiness (EDS), hypertension (HTN), and CVD mortality per 1-standard deviation increase in HBOxi after adjusting for several covariates and confounders. Results: The Spearman's rank correlation between HB (median [interquartile range], 34.4 [18.4-59.8] % min/h) and HBOxi (median [interquartile range], 34.5 [21.6-53.8] % min/h) was 0.81 (P < 0.001). Similar to HB, HBOxi was significantly associated with EDS (aOR [95% confidence interval (CI)], 1.17 [1.09-1.26] per standard deviation), HTN (aOR [95% CI], 1.13 [1.05-1.21]), and CVD mortality (adjusted hazard ratio [95% CI], 1.15 [1.01-1.30]) in fully adjusted models. Conclusions: The HBOxi was highly correlated with the HB based on manually scored apneas and hypopneas and was associated with EDS, HTN, and CVD mortality with similar effect sizes as previously reported. This method could be incorporated into wearable technology that accurately records oxygen saturation signals.

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.

Sleep Apnea Physiological Burdens and Cardiovascular Morbidity and Mortality

Rationale: Obstructive sleep apnea is characterized by frequent reductions in ventilation, leading to oxygen desaturations and/or arousals. Objectives: In this study, association of hypoxic burden with incident cardiovascular disease (CVD) was examined and compared with that of "ventilatory burden" and "arousal burden." Finally, we assessed the extent to which the ventilatory burden, visceral obesity, and lung function explain variations in hypoxic burden. Methods: Hypoxic, ventilatory, and arousal burdens were measured from baseline polysomnograms in the Multi-Ethnic Study of Atherosclerosis (MESA) and the Osteoporotic Fractures in Men (MrOS) studies. Ventilatory burden was defined as event-specific area under ventilation signal (mean normalized, area under the mean), and arousal burden was defined as the normalized cumulative duration of all arousals. The adjusted hazard ratios for incident CVD and mortality were calculated. Exploratory analyses quantified contributions to hypoxic burden of ventilatory burden, baseline oxygen saturation as measured by pulse oximetry, visceral obesity, and spirometry parameters. Measurements and Main Results: Hypoxic and ventilatory burdens were significantly associated with incident CVD (adjusted hazard ratio [95% confidence interval] per 1 SD increase in hypoxic burden: MESA, 1.45 [1.14, 1.84]; MrOS, 1.13 [1.02, 1.26]; ventilatory burden: MESA, 1.38 [1.11, 1.72]; MrOS, 1.12 [1.01, 1.25]), whereas arousal burden was not. Similar associations with mortality were also observed. Finally, 78% of variation in hypoxic burden was explained by ventilatory burden, whereas other factors explained only <2% of variation. Conclusions: Hypoxic and ventilatory burden predicted CVD morbidity and mortality in two population-based studies. Hypoxic burden is minimally affected by measures of adiposity and captures the risk attributable to ventilatory burden of obstructive sleep apnea rather than a tendency to desaturate.

Associations of Slow-Wave Sleep With Prevalent and Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis

CONTEXT

N3 sleep (i.e., slow-wave sleep), a marker of deep restorative sleep, is implicated in hormonal and blood pressure regulation and may impact cardiometabolic health.

OBJECTIVE

We conducted cross-sectional and prospective analyses to test whether a higher proportion and longer duration of N3 sleep are associated with reduced type 2 diabetes risk.

METHODS

A subsample of participants from the Multi-Ethnic Study of Atherosclerosis completed 1-night polysomnography at Exam 5 (2010-2013) and were prospectively followed until Exam 6 (2016-2018). We used modified Poisson regression to examine the cross-sectional associations of N3 proportion and duration with prevalent diabetes and Cox proportional hazards models to estimate risk of diabetes according to N3 measures.

RESULTS

In cross-sectional analyses (n = 2026, mean age: 69 years), diabetes prevalence was 28% (n = 572). Compared with the first quartile (Q1) of the N3 proportion (<2.0%), participants in Q4 (≥15.4%) were 29% (95% CI 0.58, 0.87) less likely to have prevalent diabetes (P trend = .0016). The association attenuated after adjustment for demographics, lifestyles, and sleep-related factors (P trend = .3322). In prospective analyses of 1251 participants and 129 incident cases over 6346 person-years of follow-up, a curvilinear relationship was observed between N3 proportion and incident diabetes risk. In the fully adjusted model, the hazard ratio (95% CI) of developing diabetes vs Q1 was 0.47 (0.26, 0.87) for Q2, 0.34 (0.15, 0.77) for Q3, and 0.32 (0.10, 0.97) for Q4 (P nonlinearity = .0213). The results were similar for N3 duration.

CONCLUSION

Higher N3 proportion and longer N3 duration were prospectively associated with lower type 2 diabetes risk in a nonlinear fashion among older American adults.

Obstructive sleep apnoea heterogeneity and cardiovascular disease

Obstructive sleep apnoea (OSA), characterized by recurrent periods of upper airway obstruction and intermittent hypoxaemia, is prevalent in patients with cardiovascular disease (CVD), and is therefore important to consider in the prevention and management of CVD. Observational studies indicate that OSA is a risk factor for incident hypertension, poorly controlled blood pressure, stroke, myocardial infarction, heart failure, cardiac arrhythmias, sudden cardiac death and all-cause death. However, clinical trials have not provided consistent evidence that treatment with continuous positive airway pressure (CPAP) improves cardiovascular outcomes. These overall null findings might be explained by limitations in trial design and low levels of adherence to CPAP. Studies have also been limited by the failure to consider OSA as a heterogeneous disorder that consists of multiple subtypes resulting from variable contributions from anatomical, physiological, inflammatory and obesity-related risk factors, and resulting in different physiological disturbances. Novel markers of sleep apnoea-associated hypoxic burden and cardiac autonomic response have emerged as predictors of OSA-related susceptibility to adverse health outcomes and treatment response. In this Review, we summarize our understanding of the shared risk factors and causal links between OSA and CVD and emerging knowledge on the heterogeneity of OSA. We discuss the varied mechanistic pathways that result in CVD that also vary across subgroups of OSA, as well as the potential role of new biomarkers for CVD risk stratification.

Relevance of cortical arousals for risk stratification in sleep apnea: a 3 cohort analysis

STUDY OBJECTIVES

There is uncertainty on best approaches for defining apnea-hypopnea events. To clarify the contributions of desaturation vs arousal to defining hypopneas, we examined the associations of events with desaturation (≥ 3%) but not arousal (apnea-hypopnea index [AHI]≥3%Only) vs events with arousals but no desaturation (AHIArOnly) with obstructive sleep apnea-related comorbidities and incident cardiovascular disease across multiple cohorts.

METHODS

In the Sleep Heart Health Study (n = 5,473), the Multi-Ethnic Study of Atherosclerosis (n = 1,904), and the Osteoporotic Fractures in Men Study (n = 2,685), we examined the independent associations of AHI≥3%Only and AHIArOnly with hypertension, diabetes, and daytime sleepiness, and incident cardiovascular disease.

RESULTS

After adjusting for covariates and AHI based on events with electroencephalogram arousal (regardless of desaturation), AHI≥3%Only was associated with hypertension in Sleep Heart Health Study (odds ratio: 1.12; 95% confidence interval: 1.04,1.21), per 1 standard deviation increase). Similar associations were observed in the Multi-Ethnic Study of Atherosclerosis and Osteoporotic Fractures in Men Study, as well as for associations with diabetes (odds ratio: 1.30; 1.09,1.54, and 1.25; 1.07,1.47, respectively), sleepiness (odds ratio: 1.19; 1.00,1.41; and 1.17; 1.01-1.35), and incident cardiovascular disease (hazard ratio: 1.37; 1.05,1.77 and 1.14; 1.00,1.29). In contrast, after adjusting for events with desaturation (regardless of arousal), AHIArOnly was unassociated with these outcomes. In Sleep Heart Health Study, greater baseline obstructive sleep apnea severity was associated with a reduction in arousal frequency over 5 years (P < .0001).

CONCLUSIONS

In middle-aged and older individuals, addition of events with arousals does not improve the strength of associations with comorbidities or incident cardiovascular disease. Research is needed to understand generalizability to younger individuals and the mechanistic role of arousals in obstructive sleep apnea.

CITATION

Azarbarzin A, Sands SA, Han S, et al. Relevance of cortical arousals for risk stratification in sleep apnea: a 3 cohort analysis. J Clin Sleep Med. 2023;19(8):1475-1484.

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

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

Is the Gut Microbiome Implicated in the Excess Risk of Hypertension Associated with Obstructive Sleep Apnea? A Contemporary Review

Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder and an established risk factor for cardiovascular diseases, including hypertension. The pathogenesis of elevated blood pressure (BP) in OSA is multifactorial, including sympathetic overdrive, vascular aberrations, oxidative stress, inflammation, and metabolic dysregulation. Among the mechanisms potentially involved in OSA-induced hypertension, the role of the gut microbiome is gaining increasing attention. Perturbations in the diversity, composition, and function of the gut microbiota have been causally linked to numerous disorders, and robust evidence has identified gut dysbiosis as a determinant of BP elevation in various populations. In this brief review, we summarize the current body of literature on the implications of altered gut microbiota for hypertension risk in OSA. Data from both preclinical models of OSA and patient populations are presented, and potential mechanistic pathways are highlighted, along with therapeutic considerations. Available evidence suggests that gut dysbiosis may promote the development of hypertension in OSA and may thus be a target for interventions aimed at attenuating the adverse consequences of OSA in relation to cardiovascular risk.

Hour-to-hour variability of respiratory sleep indices and ambulatory blood pressure

STUDY OBJECTIVES

Respiratory sleep indices are traditionally reported on the basis of the average total sleep time. The relationship between the hour-to-hour variability of these parameters and blood pressure (BP) has not been reported.

METHODS

We evaluated the associations of the hour-to-hour variability of the apnea-hypopnea index (AHI), oxygen desaturation index (ODI), and lowest oxygen saturation with the 24-h ambulatory BP in patients with hypertension and newly diagnosed obstructive sleep apnea. A total of 147 patients underwent polysomnography, based on which obstructive sleep apnea was diagnosed in 106 patients; these patients underwent 24-h ambulatory BP monitoring within the next 30 days. Each polysomnogram was divided into hourly reports to calculate the variability of the respiratory sleep indices. Variability independent of the mean was considered the primary measure of variability.

RESULTS

The median number of hourly polysomnogram reports was 7 (range, 4-8). The hour-to-hour variability of both AHI and ODI, but not of the lowest oxygen saturation, was correlated with the 24-h pulse pressure, 24-h systolic BP, and awake systolic BP (p < 0.05 for all). The fully adjusted linear regression analysis indicated that the hour-to-hour variability of AHI and ODI remained associated with the 24-h pulse pressure (AHI: β coefficient, 0.264 [95% CI = 0.033-0.495], p = 0.026; ODI: β coefficient, 0.450 [95% CI = 0.174-0.726], p = 0.002).

CONCLUSIONS

The hour-to-hour variability of AHI and ODI is independently associated with the 24-h pulse pressure. Further investigations are warranted to evaluate the clinical relevance of this new-found association.

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CITATION

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

Role of precision medicine in obstructive sleep apnoea

Obstructive sleep apnoea is a substantial clinical and public health problem because it contributes to harmful effects on quality of life, daytime symptoms, road traffic incidents, and cardiometabolic disease. Increasingly, obstructive sleep apnoea is recognised as a heterogeneous disease, and patients have varied susceptibility to long term complications and different responses to treatment. This narrative review summarises the current knowledge of precision medicine in obstructive sleep apnoea, particularly the role of symptom clusters, polysomnogram phenotypes, physiological endotypes, and circulating biomarkers in defining subtypes. In the near future, the prognostic accuracy of these measures in predicting long term complications in obstructive sleep apnoea will likely be improved, together with better matching of treatments to disease subtypes.

New Metrics from Polysomnography: Precision Medicine for OSA Interventions

Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.

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.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

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.

A novel EEG marker predicts perceived sleepiness and poor sleep quality

STUDY OBJECTIVES

To determine if a novel EEG-derived continuous index of sleep depth/alertness, the odds ratio product (ORP), predicts self-reported daytime sleepiness and poor sleep quality in two large population-based cohorts.

METHODS

ORP values which range from 0 (deep sleep) to 2.5 (fully alert) were calculated in 3s intervals during awake periods (ORPwake) and NREM sleep (ORPNREM) determined from home sleep studies in the HypnoLaus (N = 2162: 1106 females, 1056 males) and men androgen inflammation lifestyle environment and stress (MAILES) cohorts (N = 754 males). Logistic regression was used to examine associations between ORPwake, ORPNREM, and traditional polysomnography measures (as comparators) with excessive sleepiness (Epworth sleepiness scale >10) and poor sleep quality (Pittsburgh sleep quality index >5) and insomnia symptoms.

RESULTS

High ORPwake was associated with a ~30% increase in poor sleep quality in both HypnoLaus (odds ratio, OR, and 95% CI) 1.28 (1.09, 1.51), and MAILES 1.36 (1.10, 1.68). High ORPwake was also associated with a ~28% decrease in excessive daytime sleepiness in the MAILES dataset. ORPNREM was associated with a ~30% increase in poor sleep quality in HypnoLaus but not in MAILES. No consistent associations across cohorts were detected using traditional polysomnography markers.

CONCLUSIONS

ORP, a novel EEG-derived metric, measured during wake periods predicts poor sleep quality in two independent cohorts. Consistent with insomnia symptomatology of poor perceived sleep in the absence of excessive daytime sleepiness, ORPwake may provide valuable objective mechanistic insight into physiological hyperarousal.

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.

Circulating levels of cell adhesion molecules and risk of cardiovascular events in obstructive sleep apnea

Background

Obstructive sleep apnea (OSA) patients are at increased risk of cardiovascular disease (CVD). Cell adhesion molecules (CAM) are increased in OSA and CAM are also implicated in the development of CVD.

Research question

Do CAM (ICAM-1, VCAM-1 and E-selectin) have prognostic value in identifying risk of cardiovascular events in OSA?

Study design and methods

Patients with suspected OSA referred for a polysomnogram provided a fasting blood sample. Plasma levels of ICAM-1, VCAM-1 and E-selectin were determined by multiplex Luminex Assay (Milliporesigma ON, Canada). Cardiovascular events were determined by deterministic linkage to provincial health databases.

Results

418 patients were included in the analysis. Mostly male (68.2%), mean age of 50.7 yrs, median AHI 16.5 events/hour, and mean BMI of 31.7 kg/m². 36 cardiovascular events occurred in 8-yrs of follow up. Higher levels of ICAM-1 were associated with developing CVD (HR = 3.65 95% CI 1.40–9.53, 2^nd and 3rd tertiles vs. 1^st tertile), including in patients with OSA (HR = 3.1 95% CI 1.16–8.25). E-selectin was significantly associated with cardiovascular events in patients with moderate to severe OSA (HR = 3.31 95% CI 0.94–11.72, 2^nd and 3^rd tertiles vs. 1^st tertile) but not in patients without moderate to severe OSA (HR = 0.67 95% CI 0.19–2.38), p-value for interaction = 0.07.

Interpretation

In a suspected OSA cohort, patients with higher levels of ICAM-1 (>816 ng/ml) were significantly more likely to experience a cardiovascular event within 8 years after PSG. In moderate to severe OSA patients, a higher E-selectin (>36.4 ng/ml) was significantly associated with cardiovascular events.

Characteristics and Reproducibility of Novel Sleep EEG Biomarkers and their Variation with Sleep Apnea and Insomnia in a Large Community-Based Cohort

STUDY OBJECTIVES

New EEG features became available for use in polysomnography and have shown promise in early studies. They include a continuous index of sleep depth (Odds-Ratio-Product; ORP), agreement between right and left sleep depth (R/L coefficient), dynamics of sleep recovery following arousals (ORP-9), general EEG amplification (EEG Power), alpha intrusion and arousal intensity. This study was undertaken to establish ranges and reproducibility of these features in subjects with different demographics and clinical status.

METHODS

We utilized data from the two phases of the Sleep-Heart-Health-Study (SHHS1 and SHHS2). Polysomnograms of 5804 subjects from SHHS1 were scored to determine the above features. Feature values were segregated according to clinical status of Obstructive Sleep Apnea (OSA), insomnia, insomnia plus OSA, no clinical sleep disorder, and demographics (age, gender and race). Results from SHHS visit2 were compared with SHHS1 results.

RESULTS

All features varied widely among clinical groups and demographics. Relative to participants with no sleep disorder, wake ORP was higher in participants reporting insomnia symptoms and lower in those with OSA (p<0.0001 for both), reflecting opposite changes in sleep pressure, while NREM ORP was higher in both insomnia and OSA (p<0.0001), reflecting lighter sleep in both groups. There were significant associations with age, gender, and race. EEG Power, and REM ORP were highly reproducible across the two studies (ICC>0.75).

CONCLUSIONS

The reported results serve as bases for interpreting studies that utilize novel sleep EEG biomarkers and identify characteristic EEG changes that vary with age, gender and may help distinguish insomnia from OSA.

A composite sleep and pulmonary phenotype predicting hypertension

Background

Multiple aspects of sleep and Sleep Disordered Breathing (SDB) have been linked to hypertension. However, the standard measure of SDB, the Apnoea Hypopnea Index (AHI), has not identified patients likely to experience large improvements in blood pressure with SDB treatment.

Methods

To use machine learning to select sleep and pulmonary measures associated with hypertension development when considered jointly, we applied feature screening followed by Elastic Net penalized regression in association with incident hypertension using a wide array of polysomnography measures, and lung function, derived for the Sleep Heart Health Study (SHHS).

Findings

At baseline, n=860 SHHS individuals with complete data were age 61 years, on average. Of these, 291 developed hypertension ~5 years later. A combination of pulmonary function and 18 sleep phenotypes predicted incident hypertension (OR=1.43, 95% confidence interval [1.14, 1.80] per 1 standard deviation (SD) of the phenotype), while the apnoea-hypopnea index (AHI) had low evidence of association with incident hypertension (OR =1.13, 95% confidence interval [0.97, 1.33] per 1 SD). In a generalization analysis in 923 individuals from the Multi-Ethnic Study of Atherosclerosis, aged 65 on average with 615 individuals with hypertension, the new phenotype was cross-sectionally associated with hypertension (OR=1.26, 95% CI [1.10, 1.45]).

Interpretation

A unique combination of sleep and pulmonary function measures better predicts hypertension compared to the AHI. The composite measure included indices capturing apnoea and hypopnea event durations, with shorter event lengths associated with increased risk of hypertension.

Funding

This research was supported by National Heart, Lung, and Blood Institute (NHLBI) contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169 and by National Center for Advancing Translational Sciences grants UL1-TR- 000040, UL1-TR-001079, and UL1-TR-001420. The MESA Sleep ancillary study was supported by NHLBI grant HL-56984. Pulmonary phenotyping in MESA was funded by NHLBI grants R01-HL077612 and R01-HL093081. This work was supported by NHLBI grant R35HL135818 to Susan Redline.

Proteomic biomarkers of sleep apnea

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is characterized by recurrent partial to complete upper airway obstructions during sleep, leading to repetitive arousals and oxygen desaturations. Although many OSA biomarkers have been reported individually, only a small subset have been validated through both cross-sectional and intervention studies. We sought to profile serum protein biomarkers in OSA in unbiased high throughput assay.

METHODS

A highly multiplexed aptamer array (SomaScan) was used to profile 1300 proteins in serum samples from 713 individuals in the Stanford Sleep Cohort, a patient-based registry. Outcome measures derived from overnight polysomnography included Obstructive Apnea Hypopnea Index (OAHI), Central Apnea Index (CAI), 2% Oxygen Desaturation index, mean and minimum oxygen saturation indices during sleep. Additionally, a separate intervention-based cohort of 16 individuals was used to assess proteomic profiles pre- and post-intervention with positive airway pressure.

RESULTS

OAHI was associated with 65 proteins, predominantly pathways of complement, coagulation, cytokine signaling, and hemostasis which were upregulated. CAI was associated with two proteins including Roundabout homolog 3 (ROBO3), a protein involved in bilateral synchronization of the pre-Bötzinger complex and cystatin F. Analysis of pre- and post intervention samples revealed IGFBP-3 protein to be increased while LEAP1 (Hepicidin) to be decreased with intervention. An OAHI machine learning classifier (OAHI >=15 vs OAHI<15) trained on SomaScan protein measures alone performed robustly, achieving 76% accuracy in a validation dataset.

CONCLUSIONS

Multiplex protein assays offer diagnostic potential and provide new insights into the biological basis of sleep disordered breathing.

Multiple, objectively measured sleep dimensions including hypoxic burden and chronic kidney disease: findings from the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Poor sleep may contribute to chronic kidney disease (CKD) through several pathways, including hypoxia-induced systemic and intraglomerular pressure, inflammation, oxidative stress and endothelial dysfunction. However, few studies have investigated the association between multiple objectively measured sleep dimensions and CKD.

METHODS

We investigated the cross-sectional association between sleep dimensions and CKD among 1895 Multi-Ethnic Study of Atherosclerosis Sleep Ancillary Study participants who completed in-home polysomnography, wrist actigraphy and a sleep questionnaire. Using Poisson regression models with robust variance, we estimated separate prevalence ratios (PR) and 95% CIs for moderate-to-severe CKD (glomerular filtration rate <60 mL/min/1.73 m² or albuminuria >30 mg/g) among participants according to multiple sleep dimensions, including very short (≤5 hours) sleep, Apnoea-Hypopnoea Index and sleep apnoea-specific hypoxic burden (SASHB) (total area under the respiratory event-related desaturation curve divided by total sleep duration, %min/hour)). Regression models were adjusted for sociodemographic characteristics, health behaviours and clinical characteristics.

RESULTS

Of the 1895 participants, mean age was 68.2±9.1 years, 54% were women, 37% were white, 28% black, 24% Hispanic/Latino and 11% Asian. Several sleep metrics were associated with higher adjusted PR of moderate-to-severe CKD: very short versus recommended sleep duration (PR=1.40, 95% CI 1.06 to 1.83); SASHB (Box-Cox transformed SASHB: PR=1.06, 95% CI 1.02 to 1.12); and for participants in the highest quintile of SASHB plus sleep apnoea: PR=1.28, 95% CI 1.01 to 1.63.

CONCLUSIONS

Sleep apnoea associated hypoxia and very short sleep, likely representing independent biological mechanisms, were associated with a higher moderate-to-severe CKD prevalence, which highlights the potential role for novel interventions.

Understanding the pathophysiological mechanisms of cardiometabolic complications in obstructive sleep apnoea: towards personalised treatment approaches

In January 2019, a European Respiratory Society research seminar entitled "Targeting the detrimental effects of sleep disturbances and disorders" was held in Dublin, Ireland. It provided the opportunity to critically review the current evidence of pathophysiological responses of sleep disturbances, such as sleep deprivation, sleep fragmentation or circadian misalignment and of abnormalities in physiological gases such as oxygen and carbon dioxide, which occur frequently in respiratory conditions during sleep. A specific emphasis of the seminar was placed on the evaluation of the current state of knowledge of the pathophysiology of cardiovascular and metabolic diseases in obstructive sleep apnoea (OSA). Identification of the detailed mechanisms of these processes is of major importance to the field and this seminar offered an ideal platform to exchange knowledge, and to discuss pitfalls of current models and the design of future collaborative studies. In addition, we debated the limitations of current treatment strategies for cardiometabolic complications in OSA and discussed potentially valuable alternative approaches.

Comparing two measures of sleep depth/intensity

Study Objectives

To compare delta spectral power (delta) and odds ratio product (ORP) as measures of sleep depth during sleep restriction with placebo or a drug that increases delta.

Methods

This is a secondary analysis of data from a study of 41 healthy participants randomized to receive placebo or gaboxadol 15 mg during sleep restriction. Participants underwent in-laboratory sleep studies on two baseline, four sleep restriction (5-h), and two recovery nights. Relation between delta or ORP and sleep depth was operationally defined as the degree of association of each metric to the probability of arousal or awakening occurring during the next 30 s (arousability).

Results

ORP values in wake, N1, N2, N3, and REM were significantly different. Delta differed between both N2 and N3 and other sleep stages but not between wake and N1 or N1 and REM. Epoch-by-epoch and individual correlations between ORP and delta power were modest or insignificant. The relation between ORP and arousability was linear across the entire ORP range. Delta also changed with arousability but only when delta values were less than 300 μV2. Receiver-operating-characteristic analysis found the ability to predict imminent arousal to be significantly greater with ORP than with log delta power for all experimental conditions. Changes in ORP, but not log delta, across the night correlated with next-day physiologic sleep tendency.

Conclusions

Compared to delta power, ORP is more discriminating among sleep stages, more sensitive to sleep restriction, and more closely associated with arousability. This evidence supports ORP as a measure of sleep depth/intensity.

A Review of Current Tools Used for Evaluating the Severity of Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a common and heterogeneous disease characterized by episodic collapse within the upper airways, which leads to reduced ventilation and adverse consequences, including hypoxia, hypercapnia, sleep fragmentation, and long-term effects such as cardiovascular comorbidities. The clinical diagnosis of OSA and its severity classification are often determined based on the apnea-hypopnea index (AHI), defining the number of apneic and hypopnea events per hour of sleep. However, the limitations of the AHI to assess disease severity have necessitated the exploration of other metrics for additional information to reflect the complexity of OSA. Novel parameters such as the hypoxic burden have the potential to better capture the main features of OSA by maximizing the information available from the polysomnogram. These emerging measures have described multidimensional qualities of sleep-disordered breathing events and breathing irregularity and will ultimately result in better management of OSA.