Low Prognostic Value of Novel Nocturnal Metrics in Patients With OSA and High Cardiovascular Event Risk: Post Hoc Analyses of the SAVE Study

Nocturnal hypoxemic burden and micro- and macrovascular disease in patients with type 2 diabetes

BACKGROUND

Micro- and macrovascular diseases are common in patients with type 2 diabetes mellitus (T2D) and may be partly caused by nocturnal hypoxemia. The study aimed to characterize the composition of nocturnal hypoxemic burden and to assess its association with micro- and macrovascular disease in patients with T2D.

METHODS

This cross-sectional analysis includes overnight oximetry from 1247 patients with T2D enrolled in the DIACORE (DIAbetes COhoRtE) study. Night-time spent below a peripheral oxygen saturation of 90% (T90) as well as T90 associated with non-specific drifts in oxygen saturation (T90non - specific), T90 associated with acute oxygen desaturation (T90desaturation) and desaturation depths were assessed. Binary logistic regression analyses adjusted for known risk factors (age, sex, smoking status, waist-hip ratio, duration of T2D, HbA1c, pulse pressure, low-density lipoprotein, use of statins, and use of renin-angiotensin-aldosterone system inhibitors) were used to assess the associations of such parameters of hypoxemic burden with chronic kidney disease (CKD) as a manifestation of microvascular disease and a composite of cardiovascular diseases (CVD) reflecting macrovascular disease.

RESULTS

Patients with long T90 were significantly more often affected by CKD and CVD than patients with a lower hypoxemic burden (CKD 38% vs. 28%, p < 0.001; CVD 30% vs. 21%, p < 0.001). Continuous T90desaturation and desaturation depth were associated with CKD (adjusted OR 1.01 per unit, 95% CI [1.00; 1.01], p = 0.008 and OR 1.30, 95% CI [1.06; 1.61], p = 0.013, respectively) independently of other known risk factors for CKD. For CVD there was a thresholdeffect, and only severly and very severly increased T90non-specific was associated with CVD ([Q3;Q4] versus [Q1;Q2], adjusted OR 1.51, 95% CI [1.12; 2.05], p = 0.008) independently of other known risk factors for CVD.

CONCLUSION

While hypoxemic burden due to oxygen desaturations and the magnitude of desaturation depth were significantly associated with CKD, only severe hypoxemic burden due to non-specific drifts was associated with CVD. Specific types of hypoxemic burden may be related to micro- and macrovascular disease.

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.

Association between hypoxic burden and common cardiometabolic diseases in patients with severe obstructive sleep apnea

PURPOSE

To determine the possible associations between total sleep time spent with arterial oxygen saturation < 90% (T90) and comorbid cardiometabolic diseases (CMDs) in patients with severe obstructive sleep apnea (OSA).

METHODS

A retrospective review of the chart was conducted in patients with severe OSA diagnosed by in-lab polysomnography (PSG) between January 2018 and December 2019 at Siriraj Hospital. The patients were divided into two groups: hypoxic (T90 ≥ 10%) and nonhypoxic (T90 < 10%). The association between common CMDs including hypertension (HT), type 2 diabetes mellitus (T2DM), and impaired fasting glucose (IFG) was investigated and compared between the two groups.

RESULTS

Data were collected from 450 patients with severe OSA, 289 males/161 females with a mean age of 53.5 ± 14.2 years and an apnea-hypopnea index (AHI) of 49.6 events/h. Among these, 114 patients (25.3%) were defined as the hypoxic group (T90 ≥ 10%). When compared between the hypoxic and nonhypoxic groups, the patients in the hypoxic group were significantly younger and more obese, and had a higher proportion of male patients. The majority of patients (80%) had at least one CMD; however, the most common comorbidities significantly associated with hypoxic OSA (T90 ≥ 10%) were HT and IFG.

CONCLUSION

Hypoxic burden is significantly associated with an increased prevalence of HT and IFG in patients with severe OSA. T90 may be potentially useful for predicting CMDs in these patients. However, prospective studies are still required.

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.

Transvenous phrenic nerve stimulation for the treatment of central sleep apnea reduces episodic hypoxemic burden

STUDY OBJECTIVES

To determine the effect of transvenous phrenic nerve stimulation (TPNS) on the composition of the nocturnal hypoxemic burden in patients with CSA.

METHODS

We analysed oximetry data from baseline and follow-up overnight polysomnograms (PSG) in 134 CSA patients with implanted TPNS randomised (1:1) to neurostimulation (treatment group; TPNS on) or no stimulation (control group; TPNS off) from the remedē System Pivotal Trial. The hypoxemic burden was quantified using a battery of metrics, including the oxygen desaturation index (ODI), the relative sleep time spent below 90% SpO2 (T90) due to acute episodic desaturations (T90_desat) and due to non-specific and non-cyclic drifts of SpO2 (T90_non-specific). Mean change from baseline is provided.

RESULTS

TPNS titrated to reduce respiratory events significantly reduced the ODI in the treatment group by -15.85 h^-1 ± 1.99 compared to the control group, which increased 1.32 h^-1 ± 1.85 (p 〈0001) and shortened the relative T90 duration by -3.81 percentage points ± 1.23 vs. 0.49 percentage points ± 1.14 increase (p = 0.012). This shortening of T90 was primarily accomplished by reducing the brief cyclic desaturations (T90_desaturation: -4.32 percentage points ± 0.98 vs. 0.52 percentage points ± 0.91, p = 0.0004) while notable non-specific drifts in SpO₂ remained unchanged (T90_non-specific: 0.18 percentage points ± 0.62 vs. -0.13 percentage points ± 0.57, p = 0.72).

CONCLUSIONS

TPNS appears to significantly reduce the nocturnal hypoxemic burden due to sleep-disordered breathing, but a considerable nocturnal hypoxemic burden from other sources remains. Further investigations are warranted to identify the best strategy to reduce the nocturnal hypoxemic burden beyond preventing respiratory events.

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.

Sleep Arousal-Related Ventricular Repolarization Lability Is Associated With Cardiovascular Mortality in Older Community-Dwelling Men

BACKGROUND

Sleep is fragmented by brief arousals, and excessive arousal burden has been linked to increased cardiovascular (CV) risk, but mechanisms are poorly understood.

RESEARCH QUESTION

Do arousals trigger cardiac ventricular repolarization lability that may predispose people to long-term cardiovascular mortality?

STUDY DESIGN AND METHODS

This study analyzed 407,541 arousals in the overnight polysomnograms of 2,558 older men in the Osteoporotic Fractures in Men sleep study. QT and RR intervals were measured beat-to-beat starting 15 s prior to arousal onset until 15 s past onset. Ventricular repolarization lability was quantified by using the QT variability index (QTVi).

RESULTS

During 10.1 ± 2.5 years of follow-up, 1,000 men died of any cause, including 348 CV deaths. During arousals, QT and RR variability increased on average by 5 and 55 ms, respectively, resulting in a paradoxical transient decrease in QTVi from 0.07 ± 1.68 to -1.00 ± 1.68. Multivariable Cox proportional hazards analysis adjusted for age, BMI, cardiovascular and respiratory risk factors, sleep-disordered breathing and arousal, diabetes, and Parkinson disease indicated that excessive QTVi during arousal was independently associated with all-cause and CV mortality (all-cause hazard ratio, 1.20 [95% CI, 1.04-1.38; P = .012]; CV hazard ratio, 1.29 [95% CI, 1.01 -1.65; P = .043]).

INTERPRETATION

Arousals affect ventricular repolarization. A disproportionate increase in QT variability during arousal is associated with an increased all-cause and CV mortality and may reflect ventricular repolarization maladaptation to the arousal stimulus. Whether arousal-related QTVi can be used for more tailored risk stratification warrants further study, including evaluating whether arousal suppression attenuates ventricular repolarization lability and reduces subsequent mortality.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT00070681; URL: www.

CLINICALTRIALS

gov.

Cardiovascular outcomes in obstructive sleep apnoea and implications of clinical phenotyping on effect of CPAP treatment

BACKGROUND

There is a growing awareness of the heterogeneity of obstructive sleep apnoea (OSA). Clinical trials of CPAP treatment on cardiovascular protection have been mostly negative. We aimed to assess the association between polysomnographic parameters and incident major adverse cardiovascular events (MACEs), and to investigate if the CPAP effect could be better delineated among clinical subgroups.

METHODS

This sleep cohort study was conducted using a clinical database and territory-wide electronic health administration data in Hong Kong. Cox regressions were used to calculate HRs. Latent class analysis was used to cluster patients with OSA according to clinical and polysomnographic features.

RESULTS

Of 1860 eligible Chinese subjects who underwent polysomnography (2006-2013), 1544 (83%) had OSA. Over median follow-up of 8.3 years, 278 (14.9%) experienced MACEs. Apnoea-hypopnoea index (AHI) did not predict MACEs (HR: 0.95; 95% CI 0.76 to 1.17), whereas sleep time with oxygen saturation <90% (TST90) (HR: 1.41; 95% CI 1.10 to 1.81) was an independent predictor of MACEs, as were wake and nocturnal heart rate. In moderate-severe OSA (n=1108) who were indicated for CPAP treatment, regular CPAP was not associated with reduction of incident MACEs. Further cluster analysis identified a subgroup (n=333) who was younger, more obese, had more severe OSA (higher AHI and TST90) and more cardiovascular risks, in whom regular CPAP was associated with a lower risk of MACEs (HR:0.49, 95% CI 0.25 to 0.95).

CONCLUSIONS

OSA-related TST90 and mean heart rate, but not AHI, were robust predictors of MACEs. A clinical phenotype subgroup who demonstrated beneficial effect of CPAP treatment was identified.

Sleep characterization with smart wearable devices: a call for standardization and consensus recommendations

The general public increasingly adopts smart wearable devices to quantify sleep characteristics and dedicated devices for sleep assessment. The rapid evolution of technology has outpaced the ability to implement validation approaches and demonstrate relevant clinical applicability. There are untapped opportunities to validate and refine consumer devices in partnership with scientists in academic institutions, patients, and the private sector to allow effective integration into clinical management pathways and facilitate trust in adoption once reliability and validity have been demonstrated. We call for the formation of a working group involving stakeholders from academia, clinical care and industry to develop clear professional recommendations to facilitate appropriate and optimized clinical utilization of such technologies.

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.

Associations of sleep apnea risk and oxygen desaturation indices with cerebral small vessel disease burden in patients with stroke

Background

Obstructive sleep apnea (OSA) is associated with cerebral small vessel disease (CSVD). Nonetheless, whether OSA-risk determined by a simple screening questionnaire or indices quantifying nocturnal hypoxemia other than the conventional apnea–hypopnea index (AHI) by the home sleep apnea test (HSAT) associated with CSVD burden remains uncertain.

Methods

From 2018 to 2021, we recruited patients with transient ischemic attack (TIA)/minor stroke from the Queen Mary Hospital Acute Stroke Unit and TIA/Stroke Outpatient Clinics. Logistic regression models were applied to determine the association of baseline OSA-risk (on STOP-BANG questionnaire) or HSAT-derived indices quantifying nocturnal hypoxemia with global burden/individual markers of CSVD on MRI. Indices included oxygen desaturation (≥3%) index (ODI), minimum oxygen saturation (SpO₂), percentage of total sleep time with an oxygen saturation <90% (CT90%), and desaturation duration (≥3%, DesDur).

Results

In 283 patients with TIA/minor stroke (mean age 65 years, 64% men), OSA-risk was significantly associated with total CSVD score (multivariate-adjusted odds ratio: 1.23, 95% confidence interval 1.01–1.51), presence of lacunes [1.39 (1.09–1.79)] and burden of basal ganglia PVSs [1.32 (1.06–1.67)]. In 85/283 patients who completed HSAT, neither AHI, minimum SpO₂ nor CT90% was associated with CSVD burden. Nonetheless, ODI and DesDur remained significantly associated with total CSVD score after covariate adjustment: ODI [1.04 (1.01–1.07)] and DesDur [1.04 (1.01–1.08)].

Conclusion

In patients with TIA/minor stroke, high OSA-risk was associated with a greater CSVD burden. Oxygen desaturation indices (ODI and DesDur) rather than AHI were independently associated with global CSVD burden, indicating that longer and more severe desaturations may contribute to the pathogenesis of CSVD.

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Mediation effect of hypoxia in the relationship between obstructive sleep apnea and cardiovascular death risk

PURPOSE

This study aimed to explore the role of hypoxia in the relationship between obstructive sleep apnea (OSA) and cardiovascular disease (CVD) death risk based on data from the Sleep Heart Health Study (SHHS).

METHODS

Multivariate logistic regression analysis was used to analyze the association between OSA, hypoxia, and CVD death risk. Causal mediation analysis was performed to assess the role of hypoxia. The severity of OSA was evaluated by the apnea-hypopnea index (AHI), and the hypoxia was quantified by the percentage of sleep time with less than 90% oxygen saturation (PCTST90).

RESULTS

Of these 5,145 participants, 989 had no OSA, 2,110 had mild OSA, and 2,046 had moderate-to-severe OSA. After adjusting all confounders, mild OSA [odds ratio (OR): 1.800; 95% confidence interval (CI), 1.192-2.802], moderate-to-severe OSA (OR: 1.745; 95%CI, 1.148-2.758), 0 < PCTST90 < 1 (OR: 1.668; 95%CI, 1.184-2.385), and PCTST90 ≥ 1 (OR: 1.649; 95%CI, 1.148-2.400) were associated with an increased death risk of CVD. Furthermore, participants with mild OSA (OR: 3.742; 95%CI, 3.183-4.398) and moderate-to-severe OSA (OR: 19.671; 95%CI, 16.303-23.734) had a higher risk of hypoxia than those without OSA. Causal mediation analysis indicated that the average direct effect (ADM) of moderate-to-severe OSA and average causal mediation effect (ACME) of hypoxia on CVD death risk were 0.024 (95%CI, 0.004-0.040) and 0.013 (95%CI, 0.005-0.020), respectively, and the average mediating effect ratio was 33.94%.

CONCLUSION

Hypoxia played a mediating role in the increased death risk of CVD caused by OSA, and the mediating effect of hypoxia did not account for a large proportion.

Independent Association Between Oxygen Desaturation Index and Cardiovascular Disease in Non-Sleepy Sleep-Disordered Breathing Subtype: A Chinese Community-Based Study

PURPOSE

Non-sleepy sleep-disordered breathing (SDB) is increasingly recognized as an important clinical subtype. The association between non-sleepy SDB and cardiovascular disease (CVD) is not well understood. Our objectives were to investigate the relationship between non-sleepy SDB and CVD and determine which nocturnal hypoxia parameter most strongly reflects this association in a large community population.

PATIENTS AND METHODS

Cross-sectional data from 3626 randomly-selected Chinese community-dwelling participants who underwent overnight type IV sleep monitoring were analyzed. Parameters of nocturnal hypoxemia were extracted from sleep monitoring devices, including mean nocturnal oxygen saturation, lowest oxygen saturation, oxygen desaturation index (ODI), and time with oxygen saturation <90%. An ODI ≥7.0 events/h was considered to signify SDB. An Epworth Sleepiness Scale score of 10 or less indicated no sleepiness.

RESULTS

The SDB rate was 30.7% (1114/3626), of which 96.5% (1075/1114) were considered the non-sleepy SDB subtype. ODI, typical nocturnal intermittent hypoxia indicator for SDB, was independently related to CVD, regardless of whether excessive daytime sleepiness was present. After adjusting for confounders, ODI most strongly reflected the association between non-sleepy SDB and CVD (OR:1.023; 95% CI:1.003-1.043). We observed a nonlinear association between ODI and the prevalence of CVD, where the likelihood of CVD increased with ODI≥10 events/h and a markedly increasing trend was observed with ODI ≥20 events/h (reference ODI = 7.0 events/h). Metabolic parameters, Pittsburgh Sleep Quality Index, and inflammatory marker did not mediate the association between ODI and CVD in the non-sleepy SDB subtype.

CONCLUSION

In the Chinese community-dwelling population, non-sleepy SDB was highly prevalent. ODI, an easily extracted indicator from a type IV sleep monitor, most strongly reflected the association between non-sleepy SDB and CVD.

New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences

Current approaches to quantify and diagnose sleep disorders and circadian rhythm disruption are imprecise, laborious, and often do not relate well to key clinical and health outcomes. Newer emerging approaches that aim to overcome the practical and technical constraints of current sleep metrics have considerable potential to better explain sleep disorder pathophysiology and thus to more precisely align diagnostic, treatment and management approaches to underlying pathology. These include more fine-grained and continuous EEG signal feature detection and novel oxygenation metrics to better encapsulate hypoxia duration, frequency, and magnitude readily possible via more advanced data acquisition and scoring algorithm approaches. Recent technological advances may also soon facilitate simple assessment of circadian rhythm physiology at home to enable sleep disorder diagnostics even for “non-circadian rhythm” sleep disorders, such as chronic insomnia and sleep apnea, which in many cases also include a circadian disruption component. Bringing these novel approaches into the clinic and the home settings should be a priority for the field. Modern sleep tracking technology can also further facilitate the transition of sleep diagnostics from the laboratory to the home, where environmental factors such as noise and light could usefully inform clinical decision-making. The “endpoint” of these new and emerging assessments will be better targeted therapies that directly address underlying sleep disorder pathophysiology via an individualized, precision medicine approach. This review outlines the current state-of-the-art in sleep and circadian monitoring and diagnostics and covers several new and emerging approaches to better define sleep disruption and its consequences.

Reconstitution of Monocyte Subsets and PD-L1 Expression but Not T Cell PD-1 Expression in Obstructive Sleep Apnea Patients upon PAP Therapy

Obstructive sleep apnea (OSA) is characterized by nocturnal breathing intermissions resulting in oxidative stress and eventually, a low-grade systemic inflammation. The study aimed to investigate the impact of positive airway pressure (PAP) therapy on the inflammatory milieu as measured by monocyte and T cell phenotypic alterations. Participants were assessed for their OSA severity before PAP therapy and about six months later, including patient-reported outcome and therapy usage by telemetry readout. The distributions of the CD14/CD16-characterized monocyte subsets as well as the CD4/CD8-characterized effector T cell subsets with regard to their PD-1 and PD-L1 expression were analyzed by flow cytometry from blood samples. Data of 25 patients revealed a significant reconstitution of the monocyte subset distribution and a decrease in PD-L1 expression on pan-monocytes and CD8⁺ T cells without an association to initial AHI and overweight. The PD-1 expression was still increased on T cell subsets, especially on CD4⁺ TH17/22 cells. We conclude that PAP therapy might have a rapid effect on the monocyte phenotype and overall PD-L1 expression levels. However, T cell immune alterations especially on TH17/22 cells persist longer, indicating an ongoing disturbance of the adaptive immune system.

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

Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.

Validation of an Overnight Wireless High-Resolution Oximeter plus Cloud-Based Algorithm for the Diagnosis of Obstructive Sleep Apnea

OBJECTIVES

Obstructive sleep apnea (OSA) is a common but largely underdiagnosed condition. This study aimed to test the hypothesis that the oxygen desaturation index (ODI) obtained using a wireless high-resolution oximeter with a built-in accelerometer linked to a smartphone with automated cloud analysis, Overnight Digital Monitoring (ODM), is a reliable method for the diagnosis of OSA.

METHODS

Consecutive patients referred to the sleep laboratory with suspected OSA underwent in-laboratory polysomnography (PSG) and simultaneous ODM. The PSG apnea-hypopnea index (AHI) was analyzed using the criteria recommended and accepted by the American Academy of Sleep Medicine (AASM) for the definition of hypopnea: arousal or ≥3% O2 desaturation (PSG-AHI3%) and ≥4% O2 desaturation (PSG-AHI4%), respectively. The results of PSG and ODM were compared by drawing parallels between the PSG-AHI3% and PSG-AHI4% with ODM-ODI3% and ODM-ODI4%, respectively. Bland-Altman plots, intraclass correlation, receiver operating characteristics (ROC) and area under the curve (AUC) analyses were conducted for statistical evaluation. ClinicalTrial.gov: NCT03526133.

RESULTS

This study included 304 participants (men: 55%; age: 55±14 years; body mass index: 30.9±5.7 kg/m2; PSG-AHI3%: 35.3±30.1/h, ODM-ODI3%: 30.3±25.9/h). The variability in the AASM scoring bias (PSG-AHI3% vs PSG-AHI4%) was significantly higher than that for PSG-AHI3% vs ODM-ODI3% (3%) and PSG-AHI4% vs ODM-ODI4% (4%) (9.7, 5.0, and 2.9/h, respectively; p<0.001). The limits of agreement (2±SD, derived from the Bland-Altman plot) of AASM scoring variability were also within the same range for (PSG vs ODM) 3% and 4% variability: 18.9, 21.6, and 16.5/h, respectively. The intraclass correlation/AUC for AASM scoring variability and PSG vs ODM 3% or 4% variability were also within the same range (0.944/0.977 and 0.953/0.955 or 0.971/0.964, respectively).

CONCLUSION

Our results showed that ODM is a simple and accurate method for the diagnosis of OSA.