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.

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.

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.

Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect.

PURPOSE OF REVIEW: Diagnosis of sleep apnoea was performed in sleep laboratories with polysomnography. This requires a room with supervision and presence of technologists and trained sleep experts. Today, clinical guidelines in most countries recommend home sleep apnoea testing with simple systems using six signals only. If criteria for signal quality, recording conditions, and patient selection are considered, then this is a reliable test with high accuracy. RECENT FINDINGS: Recently diagnostic tools for sleep apnoea diagnosis become even more simple: smartwatches and wearables with smart apps claim to diagnose sleep apnoea when these devices are tracking sleep and sleep quality as part of new consumer health checking. Alternative and new devices range from excellent diagnostic tools with high accuracy and full validation studies down to very low-quality tools which only result in random diagnostic reports. Due to the high prevalence of sleep apnoea, even a random diagnosis may match a real disorder sometimes. SUMMARY: Until now, there are no metrics established how to evaluate these alternative algorithms and simple devices. Proposals for evaluating smartwatches, smartphones, single-use sensors, and new algorithms are presented. New assessments may help to overcome current limitations in sleep apnoea severity metrics. VIDEO ABSTRACT: http://links.lww.com/COPM/A28.

Deep Recurrent Neural Networks for Automatic Detection of Sleep Apnea from Single Channel Respiration Signals.

Sleep apnea is a common sleep disorder that causes repeated breathing interruption during sleep. The performance of automated apnea detection methods based on respiratory signals depend on the signals considered and feature extraction methods. Moreover, feature engineering techniques are highly dependent on the experts' experience and their prior knowledge about different physiological signals and conditions of the subjects. To overcome these problems, a novel deep recurrent neural network (RNN) framework is developed for automated feature extraction and detection of apnea events from single respiratory channel inputs. Long short-term memory (LSTM) and bidirectional long short-term memory (BiLSTM) are investigated to develop the proposed deep RNN model. The proposed framework is evaluated over three respiration signals: Oronasal thermal airflow (FlowTh), nasal pressure (NPRE), and abdominal respiratory inductance plethysmography (ABD). To demonstrate our results, we use polysomnography (PSG) data of 17 patients with obstructive, central, and mixed apnea events. Our results indicate the effectiveness of the proposed framework in automatic extraction for temporal features and automated detection of apneic events over the different respiratory signals considered in this study. Using a deep BiLSTM-based detection model, the NPRE signal achieved the highest overall detection results with true positive rate (sensitivity) = 90.3%, true negative rate (specificity) = 83.7%, and area under receiver operator characteristic curve = 92.4%. The present results contribute a new deep learning approach for automated detection of sleep apnea events from single channel respiration signals that can potentially serve as a helpful and alternative tool for the traditional PSG method.

Prevalence and association analysis of obstructive sleep apnea with gender and age differences - Results of SHIP-Trend.

Identification of obstructive sleep apnea and risk factors is important for reduction in symptoms and cardiovascular risk, and for improvement of quality of life. The population-based Study of Health in Pomerania investigated risk factors and clinical diseases in a general population of northeast Germany. Additional polysomnography was applied to measure sleep and respiration with the objective of assessing prevalence and risk factors of obstructive sleep apnea in a German cohort. One-thousand, two-hundred and eight people between 20 and 81 years old (54% men, median age 54 years) underwent overnight polysomnography. The estimated obstructive sleep apnea prevalence was 46% (59% men, 33% women) for an apnea-hypopnea index ≥5%, and 21% (30% men, 13% women) for an apnea-hypopnea index ≥ 15. The estimated obstructive sleep apnea syndrome prevalence (apnea-hypopnea index ≥5; Epworth Sleepiness Scale >10) was 6%. The prevalence of obstructive sleep apnea continuously increased with age for men and women with, however, later onset for women. Gender, age, body mass index, waist-to-hip ratio, snoring, alcohol consumption (for women only) and self-reported cardiovascular diseases were significantly positively associated with obstructive sleep apnea, whereas daytime sleepiness was not. Diabetes, hypertension and metabolic syndrome were positively associated with severe obstructive sleep apnea. The associations became non-significant after adjustment for body mass. Women exhibited stronger associations than men. The prevalence of obstructive sleep apnea was high, with almost half the population presenting some kind of obstructive sleep apnea. The continuous increase of obstructive sleep apnea with age challenges the current theory that mortality due to obstructive sleep apnea and cardiovascular co-morbidities affect obstructive sleep apnea prevalence at an advanced age. Also, gender differences regarding obstructive sleep apnea and associations are significant for recognizing obstructive sleep apnea mechanisms and therapy responsiveness.

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.

Comparison of effects of OSA treatment by MAD and by CPAP on cardiac autonomic function during daytime.

PURPOSE: The present study compared the effects of mandibular advancement therapy (MAD) with continuous positive airway pressure therapy (CPAP) on daytime cardiac autonomic modulation in a wide range of obstructive sleep apnea (OSA) patients under controlled conditions in a randomized, two-period crossover trial. METHODS: Forty OSA patients underwent treatment with MAD and with CPAP for 12 weeks each. At baseline and after each treatment period, patients were assessed by polysomnography as well as by a daytime cardiac autonomic function test that measured heart rate variability (HRV), continuous blood pressure (BP), and baroreceptor sensitivity (BRS) under conditions of spontaneous breathing, with breathing at 6, 12, and 15/min. RESULTS: Both CPAP and MAD therapy substantially eliminated apneas and hypopneas. CPAP had a greater effect. During daytime with all four conditions of controlled breathing, three-minute mean values of continuous diastolic BP were significantly reduced for both MAD and CPAP therapy. At the same time, selective increases due to therapy with MAD were found for HRV high frequency (HF) values. No changes were observed for BRS in either therapy mode. CONCLUSIONS: These findings indicate that both MAD and CPAP result in similar beneficial changes in cardiac autonomic function during daytime, especially in blood pressure. CPAP is more effective than MAD in eliminating respiratory events.

The effect of room acoustics on the sleep quality of healthy sleepers.

INTRODUCTION: Noise is one of the factors that can seriously disturb sleep, and sound volume is an important factor in this context. One strategy involves avoiding exposure to sounds in the night, while entail the minimization of background noise in a bedroom. The goal of this study was to investigate the effect of systematic sound attenuation on nocturnal sleep by influencing sound volume and reverberation within the context of room acoustics. MATERIALS AND METHODS: On this basis, we designed a randomized, controlled crossover trial investigating 24 healthy sleepers (15 men and 9 women, aged 24.9 ± 4.1 years) with a body mass index (BMI) of 21.9 ± 1.6 kg/m2. Each participant slept for three consecutive nights at three different locations: (a) at our sleep lab, (b) at the participant's home, and (c) at an acoustically isolated room. In addition to conduct of polysomnography (PSG), subjective sleep quality and nocturnal noise level were measured at each location. We likewise measured room temperature and relative humidity. RESULTS: Under conditions of equal sleep efficiency, a significant increase in deep sleep, by 16-34 min, was determined in an acoustically isolated room in comparison to the two other sleep locations. Fewer arousal events and an increase in rapid eye movement (REM) latency became evident in an acoustically isolated environment. Sleep in a domestic environment was subjectively better than sleep under the two test conditions. DISCUSSION: For healthy sleepers, room acoustics influence the microstructure of sleep, without subjective morning benefit. Reduction of noise level and of reverberation leads to an increase in the amount of deep sleep and to reduction of nocturnal arousal events, which is especially important for poor sleepers.

Process and outcome for international reliability in sleep scoring.

OBJECTIVES: The aim was to evaluate the inter-rater reliability in scoring sleep stages in two sleep labs in Berlin Germany and Beijing China. METHODS: The subjects consist of polysomnography (PSGs) from 15 subjects in a German sleep laboratory, with 7 mild to moderate sleep apnea hypopnea syndrome (SAHS) patients and 8 healthy controls, and PSGs from 15 narcolepsy patients in a Chinese sleep laboratory. Five experienced technologists including two Chinese and three Germans without common training scored the PSGs following the 2007 AASM manual except the EEG signals included only two EEG leads (C3/A2 and C4/A1). Differences in inter-scorer agreement were analyzed based on epoch-by-epoch comparison by means of Cohen's κ, and quantitative sleep parameters by means of intra-class correlation coefficients. RESULTS: Inter-laboratory epoch-by-epoch agreement comparison between scorers from the two countries yielded a moderate agreement with a mean κ value of 0.57 for controls, 0.58 for SAHS, and 0.54 for narcolepsy. When compared with controls, the inter-scoring agreement is higher for wake and N3 stage scoring in SAHS and N1 and N3 scoring in narcolepsy (p < 0.05). The only sleep stage with lower scoring agreement in both SAHS (κ 0.69 vs. 0.79, p = 0.034) and narcolepsy (0.66 vs 0.79, p = 0.022) was stage REM. Inter-laboratory comparisons showed that the most common combinations of deviating scorings were N1 and N2, N2 and N3, and N1 and wake. A 6.5 % deviating scoring rate of wake and REM and a 13.4 % deviating scoring rate of N1 and REM indicated that inter-laboratory scoring in narcolepsy was about twice as in SAHS and controls confused. This was further confirmed by agreement analysis of quantitative parameters using intra-class correlation coefficients ICC(2,1) indicating REM sleep scoring agreement was lower in narcolepsy than in controls (p < 0.05). CONCLUSION: Low REM stage scoring agreement exists for narcoleptics and SAHS, indicating the necessity to study sleep stage scoring agreement for a specific sleep disorder. Intensive training is needed for the scoring of sleep in international multiple center studies to improve the scoring agreement.

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.

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.

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.

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 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.

Auto bi-level pressure relief-PAP is as effective as CPAP in OSA patients--a pilot study.

PURPOSE: Continuous positive airway pressure (CPAP) is the therapy of choice for the treatment of obstructive sleep apnea (OSA). Not all patients can use CPAP therapy with adequate compliance. There is a need to develop more comfortable modes. Auto bi-level Pressure Relief-Positive Airway Pressure (ABPR-PAP) can be an alternative. We conducted a prospective double-blind, randomised trial to evaluate the efficacy and compliance of ABPR-PAP compared with CPAP in OSA patients. METHODS: We included 35 CPAP naive patients (age 53.3 ± 10.3 years, BMI 31.0 ± 5.0 kg/m(2), ESS 10.0 ± 4.2) diagnosed with moderate to severe OSA who underwent a successful CPAP titration. Patients were randomised into the CPAP or the ABPR-PAP treatment group. We used the same device (BIPAP® Auto, Philips Respironics) for CPAP or ABPR-PAP. Apnea-hypopnea index (AHI) was determined using polysomnography before (AHI 40.6 ± 18.3 per hour) and after treatment. RESULTS: Eighteen patients received CPAP and the remaining 17 received APBR-PAP. Groups were similar in terms of demographics and OSA severity. There were no serious adverse events during the trial. CPAP was fixed by a sleep expert and ABPR-PAP varied (range 5-15 cmH(2)O). AHI decreased in the CPAP group to 6.4 ± 5.7 per hour and in the ABPR-PAP group to 4.8 ± 3.6 per hour in the first night (N = 35). After 3 months, the AHI decreased in the CPAP group to 4.4 ± 5.3 per hour and in the ABPR-PAP group to 2.6 ± 3.8 per hour (N = 32). Differences between the groups were not statistically significant. There were no differences in compliance. CONCLUSIONS: ABPR-PAP is a promising new ventilation mode that enables effective treatment of OSA patients.

[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.

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.