Sleep Apnea-Specific Hypoxic Burden, Symptom Subtypes, and Risk of Cardiovascular Events and All-Cause Mortality.

Rationale: Data from population-based cohorts suggest that symptom subtypes and obstructive sleep apnea (OSA)-specific hypoxic burden (HB) could help to better identify patients with OSA at high cardiovascular (CV) risk. Objectives: We aimed to evaluate whether those new markers are associated with the risk of major adverse CV events (MACE) in clinical setting. Methods: Data from the Pays de la Loire cohort were linked to health administrative data to identify the occurrence of MACE (a composite outcome including all-cause mortality, acute myocardial infarction, stroke, and unplanned coronary revascularization) in patients with newly diagnosed OSA and no overt CV disease. Latent class analysis was used to identify subtypes based on eight clinically relevant variables. HB was defined as the total area under the respiratory event-related desaturation curve. Cox proportional hazards models were used to evaluate the association of symptom subtypes and HB with MACE. Measurements and Main Results: Four symptom subtypes were identified (minimally symptomatic [22.0%], disturbed sleep [17.5%], excessively sleepy [49.8%], and moderately sleepy [10.6%]). After a median follow-up of 78 months (interquartile range, 52-109), 592 (11.05%) of 5,358 patients experienced MACE. In a fully adjusted model, HB and overall nocturnal hypoxemia assessed by sleep time with oxygen saturation <90% were the only predictors of MACE (hazard ratio, 1.21; 95% confidence interval, 1.07-1.38; and hazard ratio, 1.34; 95% confidence interval, 1.16-1.55, respectively). The association appeared stronger toward younger patients and women. Conclusion: In clinical setting, patients with OSA who demonstrate elevated OSA-specific HB are at higher risk of a CV event and all-cause mortality. Symptom subtypes were not associated with MACE after adjustment for confounders.

Positive Airway Pressure Adherence, Mortality, and Cardiovascular Events in Patients with Sleep Apnea.

Rationale: Randomized controlled trials showed no effect of positive airway pressure (PAP) therapy for obstructive sleep apnea (OSA) on cardiovascular (CV) risk. However, patient selection and low PAP adherence preclude the generalization of their data to clinical samples. Objectives: To evaluate the association between hours of PAP use, mortality, and CV morbidity in real-life conditions. Methods: Data from the Pays de la Loire Cohort were linked to health administrative data to identify incident major adverse cardiovascular events (MACEs; a composite outcome of mortality, stroke, and cardiac diseases) in patients with OSA who were prescribed PAP. Cox proportional hazards analyses were conducted to evaluate the association between MACEs and quartiles of average daily PAP use over the study period. Measurements and Main Results: After a median follow-up of 6.6 years, 961 of 5,138 patients experienced MACEs. Considering nonadherent patients (0-4 h/night) as the reference group, adjusted hazard ratios (95% confidence intervals) for MACEs were 0.87 (0.73-1.04) for the 4-6 h/night group, 0.75 (0.62-0.92) for the 6-7 h/night group, and 0.78 (0.65-0.93) for the ⩾7 h/night group (P = 0.0130). Sensitivity analyses using causal inference approaches confirmed the association of PAP use with MACEs. The association was stronger in male patients (P value for interaction = 0.0004), patients without overt CV disease at diagnosis (P < 0.0001), and those belonging to the excessively sleepy symptom subtype (P = 0.060). Conclusions: These real-life clinical data demonstrate a dose-response relationship between PAP adherence and incident MACEs in OSA. Patient support programs may help improve PAP adherence and CV outcomes in patients with OSA.

Tracheal Sound Analysis.

Tracheal sound sensors provide multiple respiratory signals that are valuable for studying upper airway characteristics. This chapter reviews the original work and ongoing research on tracheal sound analysis in relation to upper airway obstruction during sleep. Past and current research suggest that being associated with other sleep study recording sensors and advanced signal processing techniques, tracheal sound analysis can extensively contribute to the diagnosis and assessment of sleep-disordered breathing.

A CPAP data-based algorithm for automatic early prediction of therapy adherence.

OBJECTIVE: Adherence is a critical issue in the treatment of obstructive sleep apnea with continuous positive airway pressure (CPAP). Approximately 40% of patients treated with CPAP are at risk of discontinuation or insufficient use (< 4 h/night). Assuming that the first few days on CPAP are critical for continued treatment, we tested the predictive value at day 14 (D14) of the Philips Adherence Profiler™ (AP) algorithm for adherence at 3 months (D90). METHOD: The AP™ algorithm uses CPAP machine data hosted in the database of EncoreAnywhere™. This retrospective study involved 457 patients (66% men, 60.0 ± 11.9 years; BMI = 31.2 ± 5.9 kg/m2; AHI = 37.8 ± 19.2; Epworth score = 10.0 ± 4.8) from the Pays de la Loire Sleep Cohort. At D90, 88% of the patients were adherent as defined by a mean daily CPAP use of ≥ 4 h. RESULTS: In a univariate analysis, the factors significantly associated with CPAP adherence at D90 were older age, lower BMI, CPAP adherence (≥ 4 h/night) at D14, and AP™ prediction at D14. In a multivariate analysis, only older age (OR 2.10 [1.29-3.41], p = 0.003) and the AP™ prediction at D14 (OR 16.99 [7.26-39.75], p < 0.0001) were significant predictors. CPAP adherence at D90 was not associated with device-derived residual events, nor with the levels of pressure or leakage except in the case of very significant leakage when it persisted for 90 days. CONCLUSION: Automatic telemonitoring algorithms are relevant tools for early prediction of CPAP therapy adherence and may make it possible to focus therapeutic follow-up efforts on patients who are at risk of non-adherence.

Cerebral Oxygenation During Respiratory Events in Children with Sleep-Disordered Breathing and Associated Disorders.

OBJECTIVES: To evaluate changes in cerebral oxygenation by means of near-infrared spectroscopy during respiratory events in children with sleep-disordered breathing (SDB) and associated disorders. STUDY DESIGN: Sixty-five children suspected of having SDB underwent a respiratory polygraphy with simultaneous recording of cerebral oxygenation indices. Respiratory events were analyzed by type of event, duration, variations of pulse oximetry (oxygen saturation [SpO2]), cerebral tissue oxygenation index (TOI), and heart rate. Data were categorized according to the severity of SDB and age. RESULTS: There were 540 obstructive and mixed apneas, 172 central apneas, and 393 obstructive hypopneas analyzed. The mean decreases in SpO2 and TOI were 4.1 ± 3.1% and 3.4 ± 2.8%, respectively. The mean TOI decrease was significantly smaller for obstructive hypopnea compared with apneas. The TOI decrease was significantly less in children with mild SDB as compared with those with moderate-to-severe SDB and in children >7 years as compared with those <7 years old. TOI decreases correlated significantly with SpO2 decreases, duration of event, and age, regardless of the type of event. In a multivariable regression model, predictive factors of TOI decreases were the type of respiratory event, SpO2 decrease, apnea-hypopnea index, and age. CONCLUSIONS: In children with SDB and associated disorders, cerebral oxygenation variations depend on the type of respiratory event, severity of SDB, and age.

Automatic identification of sleep and wakefulness using single-channel EEG and respiratory polygraphy signals for the diagnosis of obstructive sleep apnea.

Polysomnography (PSG) is necessary for the accurate estimation of total sleep time (TST) and the calculation of the apnea-hypopnea index (AHI). In type III home sleep apnea testing (HSAT), TST is overestimated because of the lack of electrophysiological sleep recordings. The aim of this study was to evaluate the accuracy and reliability of a novel automated sleep/wake scoring algorithm combining a single electroencephalogram (EEG) channel with actimetry and HSAT signals. The study included 160 patients investigated by PSG for suspected obstructive sleep apnea (OSA). Each PSG was recorded and scored manually using American Academy of Sleep Medicine (AASM) rules. The automatic sleep/wake-scoring algorithm was based on a single-channel EEG (FP2-A1) and the variability analysis of HSAT signals (airflow, snoring, actimetry, light and respiratory inductive plethysmography). Optimal detection thresholds were derived for each signal using a training set. Automatic and manual scorings were then compared epoch by epoch considering two states (sleep and wake). Cohen's kappa coefficient between the manual scoring and the proposed automatic algorithm was substantial, 0.74 ± 0.18, in separating wakefulness and sleep. The sensitivity, specificity and the positive and negative predictive values for the detection of wakefulness were 76.51% ± 21.67%, 95.48% ± 5.27%, 81.84% ± 15.42% and 93.85% ± 6.23% respectively. Compared with HSAT signals alone, AHI increased by 22.12% and 27 patients changed categories of OSA severity with the automatic sleep/wake-scoring algorithm. Automatic sleep/wake detection using a single-channel EEG combined with HSAT signals was a reliable method for TST estimation and improved AHI calculation compared with HSAT.

Apnea and hypopnea characterization using esophageal pressure, respiratory inductance plethysmography, and suprasternal pressure: a comparative study.

OBJECTIVES: To determine if recording of suprasternal pressure (SSP) can classify apneas and hypopneas as reliably as respiratory inductance plethysmography (RIP) belts and to compare the two methods to classification with esophageal pressure (Pes), the reference method for assessing respiratory effort. METHODS: In addition to polysomnographic recordings that included Pes, SSP was recorded. Recordings from 32 patients (25 males, mean age 66.7 ± 15.3 years, and mean BMI 30.1 ± 4.5 kg/m2) were used to compare the classification of detected apneas and hypopneas by three methods of respiratory effort evaluation (Pes, RIP belts, and SSP). Signals were analyzed randomly and independently from each other. All recordings were analyzed according to AASM guidelines. RESULTS: Using Pes as a reference for apnea characterization, the Cohen kappa (κ) was 0.93 for SSP and 0.87 for the RIP. The sensitivity/specificity of SSP was 97.0%/96.9% for obstructive, 93.9%/98.3% for central, and 94.9%/97.9% for mixed apneas. The sensitivity/specificity of the RIP was 97.4%/91.9% for obstructive, 87.5%/97.9% for central, and 85.6%/96.6% for mixed apneas. For hypopnea characterization using the Pes as a reference, κ was 0.92 for SSP and 0.86 for the RIP. The sensitivity/specificity of SSP was 99.7%/97.6% for obstructive and 97.6%/99.7% for central. The sensitivity/specificity of the RIP was 99.8%/81.1% for obstructive and 81.1%/99.8% for central. CONCLUSIONS: These results confirm the excellent agreement in the detection of respiratory effort between SSP, RIP belts, and Pes signals. Thus, we conclude that apnea and hypopnea characterization in adults with SSP is a reliable method.

Association between healthy behaviors and healthcare resource use with subsequent positive airway pressure therapy adherence in obstructive sleep apnoea.

BACKGROUND: The healthy adherer effect (HAE) has gained increasing attention as potential source of bias in observational studies examining the association of positive airway pressure (PAP) adherence with health outcomes in obstructive sleep apnea (OSA). RESEARCH QUESTION: Is adherence to PAP associated with healthy behaviors and healthcare resource use prior to device prescription? METHODS: Data from the IRSR Pays de la Loire Sleep Cohort were linked to health administrative data to identify proxies of heathy behaviors (HB) including adherence to cardiovascular (CV) drugs (medication possession ratio, [MPR]), cancer screening tests, influenza vaccination, alcohol and smoking consumption, and drowsiness-related road accidents during the two years preceding PAP onset in OSA patients. Multivariable regression analyses were conducted to evaluate the association of HB with subsequent PAP adherence. Healthcare resource use was evaluated according to subsequent PAP adherence. FINDINGS: We included 2,836 patients who had started PAP therapy between 2012 and 2018 (65% of whom were PAP adherent with mean daily use ≥4h/night). Being adherent to CV active drugs (MPR≥80%) and non-smoker were associated with a higher likelihood of PAP adherence (odds ratio, OR [95% confidence interval]: 1.43 [1.15; 1.77] and 1.37 [1.10; 1.71] respectively). Patients with no history of drowsiness-related road accidents were more likely to continue PAP (OR: 1.39 [1.04; 1.87]). PAP adherent patients used less healthcare resources 2 years before PAP initiation, than non-adherents (mean number of outpatient consultations: 19.0 vs 17.2, P=.003; hospitalization days: 5.7 vs 5.0, P=.04; emergency room visit: 30.7 vs 24.0% P=.0002). INTERPRETATION: Patients who adhere to PAP therapy of OSA were more health seeking and less healthcare users prior to device initiation than non-adherent patients. Until the HAE associated with PAP adherence is better understood, caution is warranted when interpreting the association of PAP adherence with CV health outcomes and healthcare resource use in non-randomized cohorts.

Pulse transit time as a measure of respiratory effort under noninvasive ventilation.

Among the respiratory events that may occur during nocturnal noninvasive ventilation (NIV), differentiating between central and obstructive events requires appropriate indicators of respiratory effort. The aim of the present study was to assess pulse transit time (PTT) as an indicator of respiratory effort under NIV in comparison with oesophageal pressure (P(oes)). During wakefulness, PTT was compared to P(oes) during spontaneous breathing and under NIV with or without induced leaks in 11 healthy individuals. In addition, the contribution of PTT versus P(oes) to differentiation of central from obstructive respiratory events occurring under NIV during sleep was evaluated in 10 patients with obesity hypoventilation syndrome (OHS). From spontaneous breathing to NIV without leaks, respiratory effort decreased significantly whereas, with increasing level of leaks, there was a significant increase in respiratory effort. Changes in PTT accurately reflected changes in P(oes). In OHS patients during nocturnal NIV, intraclass correlation coefficients between P(oes) and PTT were 0.970 for total number of events and 0.970 for percentage of central events. PTT accurately reflects the unloading of respiratory muscles induced by NIV and the increase in respiratory effort during leaks. PTT during sleep is also useful to differentiate central from obstructive respiratory events occurring under NIV.

Sleep Apnea and Incident Unprovoked Venous Thromboembolism: Data from the Pays de la Loire Sleep Cohort.

BACKGROUND: Previous studies have reported inconsistent findings regarding the association between obstructive sleep apnea (OSA) and incident venous thromboembolism (VTE). More specifically, the association between OSA and unprovoked VTE was barely evaluated. We aimed to evaluate whether apnea hypopnea index (AHI) and nocturnal hypoxemia markers were associated with unprovoked VTE incidence in patients investigated for OSA. MATERIAL AND METHODS: Data from the Pays de la Loire Sleep Cohort were linked to the French health administrative data to identify incident unprovoked VTE in patients suspected for OSA and no previous VTE disease. Cox proportional hazards models were used to evaluate the association of unprovoked VTE incidence with AHI and nocturnal hypoxemia markers including the time spent under 90% of saturation (T90), oxygen desaturation index, and hypoxic burden (HB), a more specific marker of respiratory events related to hypoxia. The impact of continuous positive airway pressure (CPAP) was evaluated in the subgroup of patients who were proposed the treatment. RESULTS: After a median [interquartile range] follow-up of 6.3 [4.3-9.0] years, 104 of 7,355 patients developed unprovoked VTE, for an incidence rate of 10.8 per 1,000 patient-years. In a univariate analysis, T90 and HB predicted incident VTE. In the fully adjusted model, T90 was the only independent predictor (hazard ratio: 1.06; 95% confidence interval: [1.01-1.02]; p = 0.02). The CPAP treatment has no significant impact on VTE incidence. CONCLUSION: Patients with more severe nocturnal hypoxia are more likely to have incident unprovoked VTE.

Overnight pulse rate variability and risk of major neurocognitive disorder in older patients with obstructive sleep apnea.

BACKGROUND: Increasing evidence links obstructive sleep apnea (OSA) to cognitive decline. Autonomic dysfunction assessed by heart rate variability is a promising early biomarker of cognitive impairment in populations without major neurocognitive disorder (MND). We aimed to determine whether nocturnal pulse rate variability (PRV) extracted from oximetry signal and OSA severity could predict MND onset among older OSA patients. METHODS: This study relied on data collected within the multicenter longitudinal Pays de la Loire Sleep Cohort, linked to health administrative data to identify new-onset MND. We included patients ≥60 years with newly diagnosed OSA, and no history of MND or atrial fibrillation. Cox proportional-hazards models were used to evaluate the association of MND with indices of PRV and OSA severity generated from sleep recordings. RESULTS: After a median follow-up of 6.8 [4.7-9.4] years, 70 of 3283 patients (2.1%) had been diagnosed with MND. In multivariable Cox models, MND incidence was associated with age (p < 0.0001), depression (p = 0.013), and PRV assessed by the root mean square of the successive normal-to-normal (NN) beat interval differences (RMSSD; p = 0.008) and standard deviation of NN beat intervals (SDNN; p = 0.02). Patients with the highest quartile of RMSSD had a 2.3-fold [95%CI 1.11-4.92] higher risk of being diagnosed with MND. Indices of OSA and nocturnal hypoxia severity were not associated with MND. CONCLUSIONS: Within a large clinic-based cohort of older patients with OSA, we found an association between oximetry-based indices of PRV and the onset of MND. Nocturnal oximetry-derived PRV indices could allow the early identification of OSA patients at higher risk of MND.

High prevalence of obstructive sleep apnea in pregnant women with class III obesity: a prospective cohort study.

STUDY OBJECTIVES: To determine the prevalence of obstructive sleep apnea (OSA) in a cohort of women with class III obesity, and a comparator lean group, in the second and third trimesters of pregnancy. Secondary objectives were to compare characteristics of women with obesity with and without OSA and to assess factors that were predictive of OSA. METHODS: We performed a prospective cohort study involving 33 women with class III obesity (mean body mass index 43.5 ± 3.9 kg/m2) and 39 lean women (body mass index 22.0 ± 1.7 kg/m2) with singleton pregnancies. Participants completed 2 level 3 sleep studies between 12-22 weeks and 32-38 weeks gestation. OSA was defined as a respiratory event index ≥ 5 events/h (≥ 3% desaturation criteria). Levels of interleukin-6, glucose, and C-peptide were quantified in maternal blood. Logistic regression analysis was performed to determine predictors of OSA. RESULTS: OSA was identified in 12 (37.5%) and 14 (50.0%) women with obesity and in 1 (2.6%) and 3 (9.1%) lean women in the second and third trimesters, respectively. Women with obesity with OSA were older than those with no OSA but otherwise had similar characteristics. In unadjusted analysis of women with obesity, increased age, body mass index, homeostatic model assessment of insulin resistance, and history of nonsmoking were associated with increased odds of OSA. In multivariable analysis, only increased age remained significantly associated with OSA. CONCLUSIONS: OSA is highly prevalent in pregnant women with class III obesity. Further research is required to establish effective management strategies for the growing number of women in this high-risk group. CITATION: Johns EC, Hill EA, Williams S, et al. High prevalence of obstructive sleep apnea in pregnant women with class III obesity: a prospective cohort study. J Clin Sleep Med. 2022;18(2):423-432.

Risk Factors for Sleepiness at the Wheel and Sleep-Related Car Accidents Among Patients with Obstructive Sleep Apnea: Data from the French Pays de la Loire Sleep Cohort.

PURPOSE: We aimed to determine the risk factors of sleepiness at the wheel among patients with obstructive sleep apnea (OSA) and to determine factors that were independently associated with reported sleep-related near-miss accidents or car accidents. PATIENTS AND METHODS: This retrospective study was conducted on 843 OSA patients from the French Pays de la Loire sleep cohort database. Each patient completed surveys including anthropometric data, medical history, professional status, and data on alcohol and tobacco use. Epworth sleepiness scale (ESS) and sleep quality questionnaires were administered. Regarding driving, data were collected on occurrence of sleepiness-related near-misses or car accidents, and on distance driven per year. The primary dependent variable of interest was reported sleepiness at the wheel. RESULTS: On multivariable regression analysis, reported sleepiness at the wheel (n=298) was independently associated with younger age (p=0.02), male gender (p=0.009), marked nocturnal hypoxemia (p=0.006), lower BMI (p=0.03), absence of cardiovascular disease (p=0.022), executives or high degree jobs (p=0.003) and reported difficulty-maintaining sleep (p=0.03). Only past experience of sleepiness at the wheel (OR 12.18, [6.38-23.25]) and an ESS ≥11 (OR 4.75 [2.73-8.27]) were independently associated with reported car accidents (n=30) or near-miss accidents (n=137). CONCLUSION: In patients newly diagnosed with OSA, the risk of car accident seems multifactorial, and its evaluation should include multiple parameters such as patient self-reported sleepiness at the wheel, occurrence of sleepiness-related accidents, anthropometry, professional status, and insomnia complaints. Thus, it is possible to evaluate this risk and advise patients as early as the first visit at the sleep medicine clinic without waiting for the results of the sleep study.

Diagnosis of sleep apnea without sensors on the patient's face.

STUDY OBJECTIVES: Thermistors, nasal cannulas, and respiratory inductance plethysmography (RIP) are the recommended reference sensors of the American Academy of Sleep Medicine (AASM) for the detection and characterization of apneas and hypopneas; however, these sensors are not well tolerated by patients and have poor scorability. We evaluated the performance of an alternative method using a combination of tracheal sounds (TSs) and RIP signals. METHODS: Consecutive recordings of 70 adult patients from the Pays de la Loire Sleep Cohort were manually scored in random order using the AASM standard signals and the combination TS and RIP signals, without respiratory sensors placed on the patient's face. The TS-RIP scoring used the TS and RIP-flow signals for detection of apneas and hypopneas, respectively, and the suprasternal pressure and RIP belt signals for the characterization of apneas. RESULTS: Sensitivity and specificity of the TS-RIP combination were 96.21% and 91.34% for apnea detection and 89.94% and 93.25% for detecting hypopneas, respectively, with a kappa coefficient of 0.87. For the characterization of apneas, sensitivity and specificity were 98.67% and 96.17% for obstructive apneas, 92.66% and 99.36% for mixed apneas, and 96.14% and 98.89% for central apneas, respectively, with a kappa coefficient of 0.94. The TS-RIP scoring revealed a high agreement for classifying obstructive sleep apnea into severity classes (none, mild, moderate, and severe obstructive sleep apnea) with a Cohen's kappa coefficient of 0.96. CONCLUSIONS: Compared with the AASM reference sensors, the TS-RIP combination allows reliable noninvasive detection and characterization of respiratory events with a high degree of sensitivity and specificity. TS-RIP combination could be used for diagnosis of obstructive sleep apnea in adults, either as an alternative to the AASM sensors or in combination with the recommended AASM sensors.