Sleep-stage dependence and co-existence of cardio-respiratory coordination and phase synchronization.

Interactions between the cardiac and respiratory systems play a pivotal role in physiological functioning. Nonetheless, the intricacies of cardio-respiratory couplings, such as cardio-respiratory phase synchronization (CRPS) and cardio-respiratory coordination (CRC), remain elusive, and an automated algorithm for CRC detection is lacking. This paper introduces an automated CRC detection algorithm, which allowed us to conduct a comprehensive comparison of CRPS and CRC during sleep for the first time using an extensive database. We found that CRPS is more sensitive to sleep-stage transitions, and intriguingly, there is a negative correlation between the degree of CRPS and CRC when fluctuations in breathing frequency are high. This comparative analysis holds promise in assisting researchers in gaining deeper insights into the mechanics of and distinctions between these two physiological phenomena. Additionally, the automated algorithms we devised have the potential to offer valuable insights into the clinical applications of CRC and CRPS.

Enhanced conductive body heat loss during sleep increases slow-wave sleep and calms the heart.

Substantial evidence suggests that the circadian decline of core body temperature (CBT) triggers the initiation of human sleep, with CBT continuing to decrease during sleep. Although the connection between habitual sleep and CBT patterns is established, the impact of external body cooling on sleep remains poorly understood. The main aim of the present study is to show whether a decline in body temperatures during sleep can be related to an increase in slow wave sleep (N3). This three-center study on 72 individuals of varying age, sex, and BMI used an identical type of a high-heat capacity mattress as a reproducible, non-disturbing way of body cooling, accompanied by measurements of CBT and proximal back skin temperatures, heart rate and sleep (polysomnography). The main findings were an increase in nocturnal sleep stage N3 (7.5 ± 21.6 min/7.5 h, mean ± SD; p = 0.0038) and a decrease in heart rate (- 2.36 ± 1.08 bpm, mean ± SD; p < 0.0001); sleep stage REM did not change (p = 0.3564). Subjects with a greater degree of body cooling exhibited a significant increase in nocturnal N3 and a decrease in REM sleep, mainly in the second part of the night. In addition, these subjects showed a phase advance in the NREM-REM sleep cycle distribution of N3 and REM. Both effects were significantly associated with increased conductive inner heat transfer, indicated by an increased CBT- proximal back skin temperature -gradient, rather than with changes in CBT itself. Our findings reveal a previously far disregarded mechanism in sleep research that has potential therapeutic implications: Conductive body cooling during sleep is a reliable method for promoting N3 and reducing heart rate.

Obstructive sleep apnea heterogeneity and autonomic function: a role for heart rate variability in therapy selection and efficacy monitoring.

Obstructive sleep apnea is a highly prevalent sleep-related breathing disorder, resulting in a disturbed breathing pattern, changes in blood gases, abnormal autonomic regulation, metabolic fluctuation, poor neurocognitive performance, and increased cardiovascular risk. With broad inter-individual differences recognised in risk factors, clinical symptoms, gene expression, physiological characteristics, and health outcomes, various obstructive sleep apnea subtypes have been identified. Therapeutic efficacy and its impact on outcomes, particularly for cardiovascular consequences, may also vary depending on these features in obstructive sleep apnea. A number of interventions such as positive airway pressure therapies, oral appliance, surgical treatment, and pharmaceutical options are available in clinical practice. Selecting an effective obstructive sleep apnea treatment and therapy is a challenging medical decision due to obstructive sleep apnea heterogeneity and numerous treatment modalities. Thus, an objective marker for clinical evaluation is warranted to estimate the treatment response in patients with obstructive sleep apnea. Currently, while the Apnea-Hypopnea Index is used for severity assessment of obstructive sleep apnea and still considered a major guide to diagnosis and managements of obstructive sleep apnea, the Apnea-Hypopnea Index is not a robust marker of symptoms, function, or outcome improvement. Abnormal cardiac autonomic modulation can provide additional insight to better understand obstructive sleep apnea phenotyping. Heart rate variability is a reliable neurocardiac tool to assess altered autonomic function and can also provide cardiovascular information in obstructive sleep apnea. Beyond the Apnea-Hypopnea Index, this review aims to discuss the role of heart rate variability as an indicator and predictor of therapeutic efficacy to different modalities in order to optimise tailored treatment for obstructive sleep apnea.

Simultaneous 24-h ambulatory blood pressure measurement on both arms: a consideration for improving hypertension management.

OBJECTIVE: Arterial hypertension is one of the common treatment goals in today's medicine. 24-h ambulatory blood pressure measurement (ABPM) performed by oscillometric cuff-based devices is considered as the gold standard in hypertension diagnostics. This study aims at examining the measurement accuracy of a widely used, ABPM device. METHODS: Fifty-two young and healthy participants underwent simultaneous 24-h ABPM on the left and the right upper arm using two Boso/A&D TM-2430 oscillometric cuff-based devices. Pressure curves of the cuffs, as well as hydrostatic pressure difference between the cuffs were recorded. RESULTS: The mean differences between both simultaneous measurements were 1.16 mmHg with limits of agreement of 36.23 mmHg for SBP and 1.32 mmHg with limits of agreement of 32.65 mmHg for DBP. Excluding measurements where the pressure curves were disturbed and correcting for hydrostatic pressure difference between the cuffs, reduced the measurement error. However, limits of agreement remained around 20 mmHg. There were large differences in hypertension grading and dipping pattern classification between simultaneous measurements on the left and right arm. CONCLUSION: The cuff-based ABPM device reveals notable measurement uncertainties, influencing hypertension grading, dipping pattern classification and blood pressure variability. These effects are attributed in part to disturbances during cuff deflation and hydrostatic influences. Nonetheless, ABPM has shown its clinical values in several studies, while this study underscores its still unlocked potential to improve hypertension management.

Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea.

Purpose We aim to evaluate the diagnostic performance of the SleepImage Ring device in identifying obstructive sleep apnea (OSA) across different severity in comparison to standard polysomnography (PSG). Methods Thirty-nine patients (mean age, 56.8 ± 15.0 years; 29 [74.3%] males) were measured with the SleepImage Ring and PSG study simultaneously in order to evaluate the diagnostic performance of the SleepImage device for diagnosing OSA. Variables such as sensitivity, specificity, positive and negative likelihood ratio, positive and negative predictive value, and accuracy were calculated with PSG-AHI thresholds of 5, 15, and 30 events/h. Receiver operating characteristic curves were also built according to the above PSG-AHI thresholds. In addition, we analyzed the correlation and agreement between the apnea-hypopnea index (AHI) obtained from the two measurement devices. Results There was a strong correlation (r = 0.89, P < 0.001 and high agreement in AHI between the SleepImage Ring and standard PSG. Also, the SleepImage Ring showed reliable diagnostic capability, with areas under the receiver operating characteristic curve of 1.00 (95% CI, 0.91, 1.00), 0.90 (95% CI, 0.77, 0.97), and 0.98 (95% CI, 0.88, 1.000) for corresponding PSG-AHI of 5, 15 and 30 events/h, respectively. Conclusion The SleepImage Ring could be a clinically reliable and cheaper alternative to the gold standard PSG when aiming to diagnose OSA in adults. Supplementary Information: The online version contains supplementary material available at 10.1007/s13534-023-00304-9.

Automatic sleep-stage classification of heart rate and actigraphy data using deep and transfer learning approaches.

Manual sleep-stage scoring based on full-night polysomnography data recorded in a sleep lab has been the gold standard of clinical sleep medicine. This costly and time-consuming approach is unfit for long-term studies as well as assessment of sleep on a population level. With the vast amount of physiological data becoming available from wrist-worn devices, deep learning techniques provide an opportunity for fast and reliable automatic sleep-stage classification tasks. However, training a deep neural network requires large annotated sleep databases, which are not available for long-term epidemiological studies. In this paper, we introduce an end-to-end temporal convolutional neural network able to automatically score sleep stages from raw heartbeat RR interval (RRI) and wrist actigraphy data. Moreover, a transfer learning approach enables the training of the network on a large public database (Sleep Heart Health Study, SHHS) and its subsequent application to a much smaller database recorded by a wristband device. The transfer learning significantly shortens training time and improves sleep-scoring accuracy from 68.9% to 73.8% and inter-rater reliability (Cohen's kappa) from 0.51 to 0.59. We also found that for the SHHS database, automatic sleep-scoring accuracy using deep learning shows a logarithmic relationship with the training size. Although deep learning approaches for automatic sleep scoring are not yet comparable to the inter-rater reliability among sleep technicians, performance is expected to significantly improve in the near future when more large public databases become available. We anticipate those deep learning techniques, when combined with our transfer learning approach, will leverage automatic sleep scoring of physiological data from wearable devices and enable the investigation of sleep in large cohort studies.

Effects of mindfulness meditation and Acceptance and commitment therapy in patients with obstructive sleep apnea with residual excessive sleepiness: A randomized controlled pilot study.

OBJECTIVE: Assessing the effects of Mindfulness-Based Stress Reduction (MBSR) on symptoms of OSA, especially on the primary outcome, excessive daytime sleepiness (EDS). METHODS: Parallel randomized controlled trial. 16 OSA patients with residual EDS (rEDS) were randomized and assigned to either a standardized 8-week MBSR program or a time-matched program on Acceptance and Commitment Therapy (ACT). Both programs were conducted online. Participants answered questionnaires online at baseline (pre), post-intervention (post), three months after the intervention (follow-up) and were blinded to whether their group was the treatment or active control group but not to group allocation (partial blinding). Three participants dropped out early. Most analyses are based on the remaining 13 patients. RESULTS: There was a significant difference between the MBSR (n = 7) and ACT group (n = 6) in changes of EDS between pre and post (Cohen's d = 1.24, CI [0.01, 2.42]) and a significant reduction of EDS for patients in the ACT group at post (Cohen's d = 1.18 and [0.08, 2.22]). This EDS reduction averaging 2.17 points on the Epworth Sleepiness Scale reached the prespecified bar for clinical significance of two points on that scale. Insomnia symptoms, a secondary outcome, reduced significantly following ACT (Cohen's d = 1.43 [0.23, 2.58]). In MBSR, both participants and the MBSR-trainer judged movement-based exercises to be most efficacious. CONCLUSION: ACT shows potential as adjunctive therapy for OSA with rEDS, although further studies are needed. It seems promising to develop therapeutic approaches for OSA with rEDS using ACT, especially if they are tailored to the needs specific to this patient group. TRIAL REGISTRATION: https://www.drks.de; Identifier: DRKS00026812.

Effects of sleep fragmentation and partial sleep restriction on heart rate variability during night.

We developed a cross-over study design with two interventions in randomized order to compare the effects of sleep fragmentation and partial sleep restriction on cardiac autonomic tone. Twenty male subjects (40.6 ± 7.5 years old) underwent overnight polysomnography during 2 weeks, each week containing one undisturbed baseline night, one intervention night (either sleep restriction with 5 h of sleep or sleep fragmentation with awakening every hour) and two undisturbed recovery nights. Parameters of heart rate variability (HRV) were used to assess cardiac autonomic modulation during the nights. Sleep restriction showed significant higher heart rate (p = 0.018) and lower HRV-pNN50 (p = 0.012) during sleep stage N1 and lower HRV-SDNN (p = 0.009) during wakefulness compared to the respective baseline. For HR and SDNN there were recovery effects. There was no significant difference comparing fragmentation night and its baseline. Comparing both intervention nights, sleep restriction had lower HRV high frequency (HF) components in stage N1 (p = 0.018) and stage N2 (p = 0.012), lower HRV low frequency (LF) (p = 0.007) regarding the entire night and lower SDNN (p = 0.033) during WASO during sleep. Sleep restriction increases sympathetic tone and decreases vagal tone during night causing increased autonomic stress, while fragmented sleep does not affect cardiac autonomic parameters in our sample.

Home Sleep Testing of Sleep Apnea.

Measurement methods with graded complexity for use in the lab as well as for home sleep testing (HST) are available for the diagnosis of sleep apnea, and there are different classification systems in existence. Simplified HST measurements, which record fewer parameters than traditional four- to six-channel devices, can indicate sleep apnea and can be used as screening tool in high-prevalence patient groups. Peripheral arterial tonometry (PAT) is a technique which can be suitable for the diagnosis of sleep apnea in certain cases. Different measurement methods are used, which has an influence on the significance of the results. New minimal-contact and non-contact technologies of recording and analysis of surrogate parameters are under development. If they are validated by clinical studies, it will be possible to detect sleep apnea in need of treatment more effectively. In addition, this could become a solution to monitor the effectiveness of such treatment.

[Bidirectional aspects of SARS-CoV-2 and sleep disorders]. / Bidirektionale Aspekte von SARS-CoV-2 und Schlafstörungen.

This review highlights the relationship among sleep duration, sleep quality, the immune system, and SARS-CoV­2 infection. Short and/or poor sleep may have an impact on the development as well as the course of an infection. Similarly, SARS-CoV­2 infection as well as pandemic-related circumstances may negatively affect sleep. In particular, sleep quality decreases. The pandemic thus has the potential to initiate, exacerbate, and/or maintain sleep disorders. These findings are relevant because only sufficient and restful sleep can strengthen and have a protective effect on the immune system with respect to infection and its course. Therefore, the pandemic poses another challenge for sleep medicine, and at the same time offers an opportunity to communicate the importance of sleep for health and disease course.

Long- and short-term fluctuations compared for several organ systems across sleep stages.

Some details of cardiovascular and cardio-respiratory regulation and their changes during different sleep stages remain still unknown. In this paper we compared the fluctuations of heart rate, pulse rate, respiration frequency, and pulse transit times as well as EEG alpha-band power on time scales from 6 to 200 s during different sleep stages in order to better understand regulatory pathways. The five considered time series were derived from ECG, photoplethysmogram, nasal air flow, and central electrode EEG measurements from full-night polysomnography recordings of 246 subjects with suspected sleep disorders. We applied detrended fluctuation analysis, distinguishing between short-term (6-16 s) and long-term (50-200 s) correlations, i.e., scaling behavior characterized by the fluctuation exponents α 1 and α 2 related with parasympathetic and sympathetic control, respectively. While heart rate (and pulse rate) are characterized by sex and age-dependent short-term correlations, their long-term correlations exhibit the well-known sleep stage dependence: weak long-term correlations during non-REM sleep and pronounced long-term correlations during REM sleep and wakefulness. In contrast, pulse transit times, which are believed to be mainly affected by blood pressure and arterial stiffness, do not show differences between short-term and long-term exponents. This is in constrast to previous results for blood pressure time series, where α 1 was much larger than α 2, and therefore questions a very close relation between pulse transit times and blood pressure values. Nevertheless, very similar sleep-stage dependent differences are observed for the long-term fluctuation exponent α 2 in all considered signals including EEG alpha-band power. In conclusion, we found that the observed fluctuation exponents are very robust and hardly modified by body mass index, alcohol consumption, smoking, or sleep disorders. The long-term fluctuations of all observed systems seem to be modulated by patterns following sleep stages generated in the brain and thus regulated in a similar manner, while short-term regulations differ between the organ systems. Deviations from the reported dependence in any of the signals should be indicative of problems in the function of the particular organ system or its control mechanisms.

Estimation of Sleep Stages Analyzing Respiratory and Movement Signals.

The scoring of sleep stages is an essential part of sleep studies. The main objective of this research is to provide an algorithm for the automatic classification of sleep stages using signals that may be obtained in a non-obtrusive way. After reviewing the relevant research, the authors selected a multinomial logistic regression as the basis for their approach. Several parameters were derived from movement and breathing signals, and their combinations were investigated to develop an accurate and stable algorithm. The algorithm was implemented to produce successful results: the accuracy of the recognition of Wake/NREM/REM stages is equal to 73%, with Cohen's kappa of 0.44 for the analyzed 19324 sleep epochs of 30 seconds each. This approach has the advantage of using the only movement and breathing signals, which can be recorded with less effort than heart or brainwave signals, and requiring only four derived parameters for the calculations. Therefore, the new system is a significant improvement for non-obtrusive sleep stage identification compared to existing approaches.

Reconstruction of Pulse Wave and Respiration From Wrist Accelerometer During Sleep.

OBJECTIVE: Nocturnal recordings of heart rate and respiratory rate usually require several separate sensors or electrodes attached to different body parts - a disadvantage for at-home screening tests and for large cohort studies. In this paper, we demonstrate that a state-of-the-art accelerometer placed at subjects' wrists can be used to derive reliable signal reconstructions of heartbeat (pulse wave intervals) and respiration during sleep. METHODS: Based on 226 full-night recordings, we evaluate the performance of our signal reconstruction methodology with respect to polysomnography. We use a phase synchronization analysis metrics that considers individual heartbeats or breaths. RESULTS: The quantitative comparison reveals that pulse-wave signal reconstructions are generally better than respiratory signal reconstructions. The best quality is achieved during deep sleep, followed by light sleep N2 and REM sleep. In addition, a suggested internal evaluation of multiple derived reconstructions can be used to identify time periods with highly reliable signals, particularly for pulse waves. Furthermore, we find that pulse-wave reconstructions are hardly affected by apnea and hypopnea events. CONCLUSION: During sleep, pulse wave and respiration signals can simultaneously be reconstructed from the same accelerometer recording at the wrist without the need for additional sensors. Reliability can be increased by internal evaluation if the reconstructed signals are not needed for the whole sleep duration. SIGNIFICANCE: The presented methodology can help to determine sleep characteristics and improve diagnostics and treatment of sleep disorders in the subjects' normal sleep environment.

Enhancing Current Cardiorespiratory-based Approaches of Sleep Stage Classification by Temporal Feature Stacking.

This paper presents a generic method to enhance performance and incorporate temporal information for cardiorespiratory-based sleep stage classification with a limited feature set and limited data. The classification algorithm relies on random forests and a feature set extracted from long-time home monitoring for sleep analysis. Employing temporal feature stacking, the system could be significantly improved in terms of Cohen's κ and accuracy. The detection performance could be improved for three classes of sleep stages (Wake, REM, Non-REM sleep), four classes (Wake, Non-REM-Light sleep, Non-REM Deep sleep, REM sleep), and five classes (Wake, N1, N2, N3/4, REM sleep) from a κ of 0.44 to 0.58, 0.33 to 0.51, and 0.28 to 0.44 respectively by stacking features before and after the epoch to be classified. Further analysis was done for the optimal length and combination method for this stacking approach. Overall, three methods and a variable duration between 30 s and 30 min have been analyzed. Overnight recordings of 36 healthy subjects from the Interdisciplinary Center for Sleep Medicine at Charité-Universitätsmedizin Berlin and Leave-One-Out-Cross-Validation on a patient-level have been used to validate the method.Clinical relevance- The method can be employed generically to feature sets for (small scale) datasets to improve classification performance for classification problems with temporal relations with random forest classifiers.

Sleep Apnea & Chronic Obstructive Pulmonary Disease: Overlap Syndrome Dynamics in Patients from an Epidemiological Study.

Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. Chronic obstructive pulmonary disease (COPD) is a disorder which induces a persistent inflammation of the lungs. This condition produces hypoventilation, affecting the blood oxygenation, and leads to an increased risk of developing lung cancer and heart disease. In this study, we evaluated how COPD affects the severity and characteristics of OSA in a multivariate demographic database including polysomnographic signals. Results showed SpO2 subtle variations, such as more non-recovered desaturations and increased time below a 90% SpO2 level, which, in the long term, could worsen the risk to suffer cardiovascular and cerebrovascular diseases.Clinical Relevance- COPD increases the OSA risk due to hypoventilation and altered SpO2 behavior.

The Effect of Night Duty of Pharmacists on Sleepiness and Concentration at Daytime.

BACKGROUND: The changing responsibilities of pharmacists contribute to a lack of qualified pharmacists to fill vacant positions, particularly in rural areas. Consequently, pharmacy managers cover various duties, including an increasing number of nights being on duty that can impair daytime concentration and performance. The objective of the study was to assess the effect of night duties on daytime sleepiness, sleep quality, and concentration abilities of pharmacists. METHODS: 22 pharmacists, both sexes, aged 27 to 60 years, were recruited and their sleep time, sleep efficiency, and mobility (actigraphy) were assessed during a night on duty and a control night using an actimetry. Daytime sleepiness and concentration were assessed using standardized questionnaires (ESS, KSS, d2-R). RESULTS: Significant differences were observed between the night shift and control nights with respect to sleep time, sleep efficiency, and mobility. Daytime sleepiness was significantly increased after night shifts (ESS: 11.64 vs. 2.09; KSS: 6.77 vs. 2.41 after a night shift and control night, respectively; p < 0.001) and concentration diminished compared to control nights (d2-R KL: 220.95 vs. 260.36 after a night shift and control night, respectively; p < 0.001). CONCLUSIONS: The results provide evidence that night duties lead to high daytime sleepiness in pharmacists, which in turn may negatively affect their ability to concentrate and their error rate. Existing regulations on emergency pharmacy services should be reconsidered regarding the safety of the pharmaceutical supply.

The Different Facets of Heart Rate Variability in Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA), a heterogeneous and multifactorial sleep related breathing disorder with high prevalence, is a recognized risk factor for cardiovascular morbidity and mortality. Autonomic dysfunction leads to adverse cardiovascular outcomes in diverse pathways. Heart rate is a complex physiological process involving neurovisceral networks and relative regulatory mechanisms such as thermoregulation, renin-angiotensin-aldosterone mechanisms, and metabolic mechanisms. Heart rate variability (HRV) is considered as a reliable and non-invasive measure of autonomic modulation response and adaptation to endogenous and exogenous stimuli. HRV measures may add a new dimension to help understand the interplay between cardiac and nervous system involvement in OSA. The aim of this review is to introduce the various applications of HRV in different aspects of OSA to examine the impaired neuro-cardiac modulation. More specifically, the topics covered include: HRV time windows, sleep staging, arousal, sleepiness, hypoxia, mental illness, and mortality and morbidity. All of these aspects show pathways in the clinical implementation of HRV to screen, diagnose, classify, and predict patients as a reasonable and more convenient alternative to current measures.

New Trends and New Technologies in Sleep Medicine: Expanding Accessibility.

New trends in sleep medicine make use of the increased computational power of digital transformation. A current trend toward fewer sensors on the body of the sleeper and to more data processing from derived signals is observed. Telemedicine technologies are used for data transmission and for better patient management in terms of diagnosis and in terms of treatment of chronic conditions.

Surrogate based continuous noninvasive blood pressure measurement.

Arterial blood pressure is one of the most often measured vital parameters in clinical practice. State-of-the-art noninvasive ABP measurement technologies have noticeable limitations and are mainly based on uncomfortable techniques of complete or partial arterial occlusion by cuffs. Most commonplace devices provide only intermittent measurements, and continuous systems are bulky and difficult to apply correctly for nonprofessionals. Continuous cuffless ABP measurements are still an unmet clinical need and a topic of ongoing research, with only few commercially available devices. This paper discusses surrogate-based noninvasive blood pressure measurement techniques. It covers measurement methods of continuously and noninvasively inferring BP from surrogate signals without applying external pressures, except for reference or initialization purposes. The BP is estimated by processing signal features, so called surrogates, which are modulated by variations of BP. Discussed techniques include well-known approaches such as pulse transit time and pulse arrival time techniques, pulse wave analysis or combinations thereof. Despite a long research history, these methods have not found widespread use in clinical and ambulatory practice, in part due to technical limitations and the lack of a standardized regulatory framework. This work summarizes findings from an invited workshop of experts in the fields covering clinical expertise, engineering aspects, commercialization and standardization issues. The goal is to provide an application driven outlook, starting with clinical needs, and extending to technical actuality. It provides an outline of recommended research directions and includes a detailed overview of clinical use case scenarios for these technologies, opportunities, and limitations.

Health outcomes of continuous positive airway pressure versus mandibular advancement device for the treatment of severe obstructive sleep apnea: an individual participant data meta-analysis.

STUDY OBJECTIVES: The impact of therapy with continuous positive airway pressure (CPAP) and mandibular advancement device (MAD) has not been directly compared in patients with severe obstructive sleep apnea (OSA). The purpose of this individual participant data meta-analysis was to compare the treatment effects of CPAP and titratable MAD on sleepiness, quality of life, sleep-disordered breathing severity, and sleep structure in patients with severe OSA. METHODS: Randomized controlled trials (RCTs) that included severe OSA patients were identified in order to compare the impact of the two treatments. Individual data from severe OSA patients were extracted from the databases and pooled for analysis. RESULTS: Of the seven studies identified, three crossover RCT and one parallel-group RCT corresponding to 151 patients and 249 observations (125 in the CPAP treatment arm and 124 in the MAD treatment arm) were included in the analysis. Titratable MAD had a similar impact to CPAP on major patient-centered outcomes (sleepiness and quality of life). CPAP was more effective in reducing AHI and ODI. However, the two treatments had a similar impact on sleep structure with an increase of N3 and REM sleep. Finally, treatment adherence and preference were largely in favor of MAD. CONCLUSION: This meta-analysis suggests that MAD represents an effective alternative treatment in severe OSA patients intolerant to CPAP or who prefer alternate therapy.