Influence of Marital Status and Employment Status on Long-Term Adherence with Continuous Positive Airway Pressure in Sleep Apnea Patients

) of consecutive OSAHS patients in whom CPAP had been prescribed for at least 90 days, we studied the impact on long-term treatment adherence of socioeconomic factors, patients and disease characteristics prior to CPAP initiation. living alone; p = 0.01). Age, gender, Epworth sleepiness scale, depressive syndrome, associated cardiovascular morbidities, educational attainment and occupation category did not influence CPAP adherence.Marital status and employment status are independent factors of CPAP adherence in addition to BMI and disease severity. Patients living alone and/or working patients are at greater risk of non-adherence, whereas adherence is higher in married and retired patients. These findings suggest that the social context of daily life should be taken into account in risk screening for CPAP non-adherence. Future interventional studies targeting at-risk patients should be designed to address social motivating factors and work-related barriers to CPAP adherence

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Depressive Symptoms Before and After Long-term CPAP Therapy in Patients With Sleep Apnea

International audienceBACKGROUND:The outcome of depressive symptoms under CPAP therapy for OSA-hypopnea syndrome (OSAHS) has been poorly evaluated. In this multicenter, prospective cohort study, we evaluated the prevalence and correlates of persistent depressive symptoms after long-term CPAP therapy for OSAHS.METHODS:This study included 300 patients with OSAHS and depressive symptoms (13-item, self-rated Pichot depression scale [QD2A] ≥ 7) at diagnosis. The primary dependent variable was persistent depressive symptoms after ≥ 1 year of CPAP therapy. Multivariate regression analyses were performed to determine variables independently associated with the persistence of depressive symptoms.RESULTS:After an average of 529 days (range, 365-1,569 days) of CPAP therapy, the mean (SD) QD2A score decreased from 9.2 (2.0) to 5.4 (4.0) (P &amp;lt; .0001), but 125 patients (41.7%) presented persistent depressive symptoms. The persistence of depressive symptoms was independently associated with persistent excessive daytime sleepiness (EDS) (OR, 2.72; 95% CI, 1.33-5.61), comorbid cardiovascular disease (OR, 1.76; 95% CI, 1.02-3.00), and female sex (OR, 1.53; 95% CI, 1.09-2.13). A positive linear trend was observed for the adjusted OR of persistent depressive symptoms with decreasing CPAP effect on the Epworth sleepiness scale (P &amp;lt; .0001).CONCLUSIONS:CPAP therapy does not resolve depressive symptoms in many patients with OSAHS. Persistent depressive symptoms are strongly associated with EDS. Active monitoring of depressive symptoms is needed in patients with OSAHS who are treated with CPAP. Interventional trials are required to evaluate the impact of antidepressants, cognitive behavioral therapy, or both on comorbid depression in patients with OSAHS.</p

Cardiovascular risk and mortality prediction in patients suspected of sleep apnea: a model based on an artificial intelligence system

International audienceObjective. Cardiovascular disease (CVD) is one of the leading causes of death worldwide. There are many CVD risk estimators but very few take into account sleep features. Moreover, they are rarely tested on patients investigated for obstructive sleep apnea (OSA). However, numerous studies have demonstrated that OSA index or sleep features are associated with CVD and mortality. The aim of this study is to propose a new simple CVD and mortality risk estimator for use in routine sleep testing.Approach. Data from a large multicenter cohort of CVD-free patients investigated for OSA were linked to the French Health System to identify new-onset CVD. Clinical features were collected and sleep features were extracted from sleep recordings. A machine-learning model based on trees, AdaBoost, was applied to estimate the CVD and mortality risk score.Main results. After a median [inter-quartile range] follow-up of 6.0 [3.5-8.5] years, 685 of 5234 patients had received a diagnosis of CVD or had died. Following a selection of features, from the original 30 features, 9 were selected, including five clinical and four sleep oximetry features. The final model included age, gender, hypertension, diabetes, systolic blood pressure, oxygen saturation and pulse rate variability (PRV) features. An area under the receiver operating characteristic curve (AUC) of 0.78 was reached.Significance. AdaBoost, an interpretable machine-learning model, was applied to predict 6 year CVD and mortality in patients investigated for clinical suspicion of OSA. A mixed set of simple clinical features, nocturnal hypoxemia and PRV features derived from single channel pulse oximetry were used

Adherence to positive airway pressure in non-sleepy patients with obstructive sleep apnoea.

International audienceComplaints of excessive daytime sleepiness (EDS) are absent in many individuals with obstructive sleep apnoea (OSA). The influence of EDS prior to treatment on continuous positive airway pressure (CPAP) adherence has not been clearly determined [1, 2]. The aim of this prospective cohort study was to evaluate the adherence and perceived benefit during long-term CPAP therapy in a "real life" population of non-sleepy OSA patients.</p

Hypoxic burden and heart-rate variability predict stroke incidence in sleep apnoea

International audienceManuscript word count: 1,374 "take home" message: Indices of sleep apnoea-related hypoxic burden and heart rate variability derived from full-night polysomnography might be useful for identifying sleep apnoea patients at risk for stroke

Association of symptom subtypes and obstructive sleep apnoea-specific hypoxic burden with cardiovascular morbidity and all-cause mortality

International audienceBackground: 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.Aim: We aimed to evaluate whether OSA symptoms subtypes and HB derived from sleep recordings were associated with increased CV risk in clinical setting.Methods: Clinical data from a large multicenter cohort were linked to health administrative data to identify new-onset of CV events and death in patients with OSA and no overt CV disease. Latent class analysis was used to identify subtypes based on 8 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 a composite outcome of incident CV events or death from any cause.Results: Four symptom subtypes were identified (minimally symptomatic [22.0%], disturbed sleep [17.5%], excessively sleepy [49.8%], and moderately sleepy [10.6%]), similar to prior studies. After a median follow-up of 78 months, 592 (11.05%) of 5358 patients experienced our composite outcome. In a fully adjusted model, increasing age and HB, male gender, the presence of diabetes, hypertension and COPD were significant predictors of the composite outcome. AHI and symptom subtypes were not associated with CV risk after adjustments.Conclusion: In clinical setting, patients with OSA who demonstrate elevated OSA specific HB are at higher risk of CV event and all cause mortality. Symptom subtypes have no predictive value after adjustment for confounders

Association of Nocturnal Hypoxemia and Pulse Rate Variability with Incident Atrial Fibrillation in Patients Investigated for Obstructive Sleep Apnea

International audienceRationale: Nocturnal hypoxemia and sympathetic/parasympathetic imbalance might contribute to the occurrence or atrial fibrillation (AF) in patients with obstructive sleep apnea (OSA). During sleep recordings, pulse rate variability (PRV) derived from oximetry might provide an accurate estimation of heart rate variability, which reflects the autonomic cardiovascular control. Objectives: We aimed to evaluate whether indices of oxygen desaturation and PRV derived from nocturnal oximetry were associated with AF incidence in patients investigated for OSA. Methods: Data from a large multicenter cohort of AF-free patients investigated for OSA between May 15, 2007, and December 31, 2017, were linked to health administrative data to identify hospitalized and nonhospitalized patients with new-onset AF. Cox proportional hazards models were used to evaluate the association between AF incidence and oximetry-derived indices automatically generated from sleep recordings. Results: After a median (interquartile range) follow-up of 5.34 (3.3-8.0) years, 181 of 7,205 patients developed AF (130 were hospitalized for AF). After adjusting for confounders, including anthropomorphic data, alcohol intake, cardiac, metabolic and respiratory diseases, beta blocker/calcium channel blocker medications, type of sleep study, study site, and positive airway pressure adherence, AF risk was associated with increasing nocturnal hypoxemia (P trend = 0.004 for quartiles of percentage of recording time with oxygen saturation &lt;90%) and PRV (P trend &lt; 0.0001 for quartiles of root mean square of the successive normal-normal beat interval differences), and decreasing sympathetic/parasympathetic tone (P trend = 0.0006 for quartiles of low-frequency power/high-frequency power ratio). The highest risk of AF was observed in patients with the highest quartiles of both the percentage of recording time with oxygen saturation &lt;90% and the root mean square of the successive normal-normal beat interval differences compared with those with neither of these conditions (adjusted hazard ratio, 3.61; 95% confidence interval, 2.10-6.22). Similar associations were observed when the analyses were restricted to hospitalized AF. Conclusions: In patients investigated for OSA, nocturnal hypoxemia and PRV indices derived from single-channel pulse oximetry were independent predictors of AF incidence. Patients with both marked nocturnal hypoxemia and high PRV were at higher risk of AF. Oximetry may be used to identify patients with OSA at greatest risk of developing AF