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.

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.

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.

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.

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.

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.

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.

Positional obstructive sleep apnea within a large multicenter French cohort: prevalence, characteristics, and treatment outcomes.

STUDY OBJECTIVES: To assess, in a large cohort of patients with obstructive sleep apnea, the factors that are independently associated with positional obstructive sleep apnea (POSA) and exclusive POSA (e-POSA) and determine their prevalence. The secondary objective was to evaluate the outcome of positive airway pressure (PAP) therapy for patients with POSA and e-POSA. METHODS: This retrospective study included 6,437 patients with typical mild-to-severe OSA from the Pays de la Loire sleep cohort. Patients with POSA and e-POSA were compared to those with non-POSA for clinical and polysomnographic characteristics. In a subgroup of patients (n = 3,000) included in a PAP follow-up analysis, we determined whether POSA and e-POSA phenotypes were associated with treatment outcomes at 6 months. RESULTS: POSA and e-POSA had a prevalence of 53.5% and 20.1%, respectively, and were independently associated with time in supine position, male sex, younger age, lower apnea-hypopnea index and lower body mass index. After adjustment for confounding factors, patients with POSA and e-POSA had a significantly lower likelihood of treatment adherence (PAP daily use ≥ 4 h) at 6 months and were at higher risk of PAP treatment withdrawal compared to those with non-POSA. CONCLUSIONS: The prevalence and independent predictors of POSA and e-POSA were determined in this large clinical population. Patients with POSA and e-POSA have lower PAP therapy adherence, and this choice of treatment may not be optimal. Thus, there is a need to offer these patients an alternative therapy.

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.

Tracheal sounds for the scoring of sleep respiratory events in children.

STUDY OBJECTIVES: Oronasal thermistor and nasal cannula are recommended for the scoring of respiratory events (RE) but these sensors are poorly tolerated in children. The aim of the study was to evaluate tracheal sounds (TS) and suprasternal pressure (SSP) for the scoring of RE during sleep in children. METHODS: We compared the detection and characterization of RE by AASM-recommended sensors ("AASM" scoring), with the detection and characterization of RE by the combination of TS and SSP with respiratory inductance plethysmography-sum (TS-RIP scoring), and TS and SSP only (TS scoring). RESULTS: The recordings of 17 patients were analyzed. The TS, SSP, and RIP flow signals were present during 95%, 95%, and 99% of the validated recording time, respectively, as compared to 79% and 86% for nasal cannula and oronasal thermistor. A total of 1,456 RE were scored with the "AASM" scoring, 1,335 with the TS-RIP scoring, and 1,311 with the TS scoring. Sensitivity for apnea and hypopnea detection was 88% and 84% for the TS-RIP scoring, and 86% and 77% for the TS scoring. For apnea characterization, the TS-RIP scoring sensitivities and specificities were 97% and 100%, 76% and 98%, and 95% and 97%, for obstructive, mixed, and central apnea, respectively. For the TS scoring, they were 95% and 100%, 95% and 97%, and 91% and 97%, respectively. CONCLUSIONS: TS and SSP + RIP-sum has a good sensitivity and specificity for the detection and characterization of apnea and hypopnea in children. TS and SSP alone have good sensitivity and specificity for apnea detection and characterization but lower sensitivity for hypopnea detection.

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.

Comparison of Apnea Detection Using Oronasal Thermal Airflow Sensor, Nasal Pressure Transducer, Respiratory Inductance Plethysmography and Tracheal Sound Sensor.

STUDY OBJECTIVES: Evaluation of apnea detection using a tracheal sound (TS) sensor during sleep in patients with obstructive sleep apnea. METHODS: Polysomnographic recordings of 32 patients (25 male, mean age 66.7 ± 15.3 years, and mean body mass index 30.1 ± 4.5 kg/m2) were analyzed to compare the detection of apneas by four different methods of airflow signals: oronasal thermal airflow sensor (thermistor), nasal pressure transducer (NP), respiratory inductance plethysmography (RIPsum) and TS. The four used signals were scored randomly and independently from each other according to American Academy of Sleep Medicine rules. Results of apnea detection using NP, RIPsum and TS signals were compared to those obtained by thermistor as a reference signal. RESULTS: The number of apneas detected by the thermistor was 4,167. The number of apneas detected using the NP was 5,416 (+29.97%), using the RIPsum was 2,959 (-29.71%) and using the TS was 5,019 (+20.45%). The kappa statistics (95% confidence interval) were 0.72 (0.71 to 0.74) for TS, 0.69 (0.67 to 0.70) for NP, and 0.57 (0.55 to 0.59) for RIPsum. The sensitivity/specificity (%) with respect to the thermistor were 99.23/69.27, 64.07/93.06 and 96.06/76.07 for the NP, RIPsum and TS respectively. CONCLUSIONS: With the sensor placed properly on the suprasternal notch, tracheal sounds could help detecting apneas that are underscored by the RIPsum and identify apneas that may be overscored by the NP sensor due to mouth breathing. In the absence of thermistor, TS sensors can be used for apnea detection. CLINICAL TRIAL REGISTRATION: Registry: German Clinical Trials Register (DRKS), Title: Using the tracheal sound probe of the polygraph CID102 to detect and differentiate obstructive, central, and mixed sleep apneas in patients with sleep disordered breathing, Identifier: DRKS00012795, URL: https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00012795.