Interhemispheric differences of electroencephalography signal characteristics in different sleep stages.

OBJECTIVE: The current electroencephalography (EEG) measurement setup is complex, laborious to set up, and uncomfortable for patients. We hypothesize that differences in EEG signal characteristics for sleep staging between the left and right hemispheres are negligible; therefore, there is potential to simplify the current measurement setup. We aimed to investigate the technical hemispheric differences in EEG signal characteristics along with electrooculography (EOG) signals during different sleep stages. METHODS: Type II portable polysomnography (PSG) recordings of 50 patients were studied. Amplitudes and power spectral densities (PSDs) of the EEG and EOG signals were compared between the left (C3-M2, F3-M2, O1-M2, and E1-M2) and the right (C4-M1, F4-M1, O2-M1, and E2-M2) hemispheres. Regression analysis was performed to investigate the potential influence of sleep stages on the hemispheric differences in PSDs. Wilcoxon signed-rank tests were also employed to calculate the effect size of hemispheres across different frequency bands and sleep stages. RESULTS: The results showed statistically significant differences in signal characteristics between hemispheres, but the absolute differences were minor. The median hemispheric differences in amplitudes were smaller than 3 µv with large interquartile ranges during all sleep stages. The absolute and relative PSD characteristics were highly similar between hemispheres in different sleep stages. Additionally, there were negligible differences in the effect size between hemispheres across all sleep stages. CONCLUSIONS: Technical signal differences between hemispheres were minor across all sleep stages, indicating that both hemispheres contain similar information needed for sleep staging. A reduced measurement setup could be suitable for sleep staging without the loss of relevant information.

[Development of Wireless Wearable Sleep Monitoring System Based on EEG Signal].

A wireless wearable sleep monitoring system based on EEG signals is developed. The collected EEG signals are wirelessly sent to the PC or mobile phone Bluetooth APP for real-time display. The system is small in size, low in power consumption, and light in weight. It can be worn on the patient's forehead and is comfortable. It can be applied to home sleep monitoring scenarios and has good application value. The key performance indicators of the system are compared with the industry-related medical device measurement standards, and the measurement results are better than the special standards.

Performance Evaluation of a New Sport Watch in Sleep Tracking: A Comparison against Overnight Polysomnography in Young Adults.

Introduction: This study aimed to validate the ability of a prototype sport watch (Polar Electro Oy, FI) to recognize wake and sleep states in two trials with and without an interval training session (IT) 6 h prior to bedtime. Methods: Thirty-six participants completed this study. Participants performed a maximal aerobic test and three polysomnography (PSG) assessments. The first night served as a device familiarization night and to screen for sleep apnea. The second and third in-home PSG assessments were counterbalanced with/without IT. Accuracy and agreement in detecting sleep stages were calculated between PSG and the prototype. Results: Accuracy for the different sleep stages (REM, N1 and N2, N3, and awake) as a true positive for the nights without exercise was 84 ± 5%, 64 ± 6%, 81 ± 6%, and 91 ± 6%, respectively, and for the nights with exercise was 83 ± 7%, 63 ± 8%, 80 ± 7%, and 92 ± 6%, respectively. The agreement for the sleep night without exercise was 60.1 ± 8.1%, k = 0.39 ± 0.1, and with exercise was 59.2 ± 9.8%, k = 0.36 ± 0.1. No significant differences were observed between nights or between the sexes. Conclusion: The prototype showed better or similar accuracy and agreement to wrist-worn consumer products on the market for the detection of sleep stages with healthy adults. However, further investigations will need to be conducted with other populations.

Sickle Cell Disease Phenotypes and Obstructive Sleep Apnea; Are They Related?

OBJECTIVE: This study aims to compare the polysomnographic features between Arab-Indian and Benin phenotypes of sickle cell disease (SCD). MATERIALS AND METHODS: This prospective cross-sectional study was conducted in the Children's Hospital at King Fahad MedicalCity, in Riyadhwhere childrenwere recruited fromthe pediatric hematology clinic and pediatric sleepmedicine. All families were approached and patients who met the inclusion criteria and agreed to participate were included in the study. RESULTS: Eighty four children (37 of whom were females) with SCD were included in the study. Their median (interquartile) age was 9 (6.65, 11) years and their body mass index z score was -1.45 (-2.195, -1.45). The evidence of obstructive sleep apnea (OSA) was more prominent in the Benin phenotype (66.7%) in comparison to those of the Arab-Indian (35.2%) phenotype ( p = 0.006). Additionally, 56.7% of Benin had moderate to severe OSA whereas Arab-Indian had 18% with a ( p = 0.0003). Controlling for other factors, the odds ratio (confidence interval) of having OSA in Benin phenotype was 4.68 (1.42-15.38) times higher as compared to Arab-Indian phenotype. CONCLUSION: The risk of having OSA as well as the severity of OSA is higher in Benin phenotype as compared to Arab-Indian phenotype which indicates the presence of potential OSA risk factors other than the SCD itself.

Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review.

Background: Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and labor-intensive; requires various equipment and technical expertise; and is impractical for long-term or in-home use. Consumer wrist-worn wearables are able to monitor sleep parameters and thus could be used as an alternative for PSG. Consequently, wearables gained immense popularity over the past few years, but their accuracy has been a major concern. Objective: A systematic review of the literature was conducted to appraise the performance of 3 recent-generation wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) in determining sleep parameters and sleep stages. Methods: Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, a comprehensive search was conducted using the PubMed, Web of Science, Google Scholar, Scopus, and Embase databases. Eligible publications were those that (1) involved the validity of sleep data of any marketed model of the candidate wearables and (2) used PSG or an ambulatory electroencephalogram monitor as a reference sleep monitoring device. Exclusion criteria were as follows: (1) incorporated a sleep diary or survey method as a reference, (2) review paper, (3) children as participants, and (4) duplicate publication of the same data and findings. Results: The search yielded 504 candidate articles. After eliminating duplicates and applying the eligibility criteria, 8 articles were included. WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (-1.4 min), light sleep (-9.6 min), and deep sleep (-9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min). Fitbit Charge 4 and Garmin Vivosmart 4 both showed moderate accuracy in assessing sleep stages and total sleep time compared to PSG. Fitbit Charge 4 showed the least disagreement for REM sleep (4.0 min) relative to PSG. Additionally, Fitbit Charge 4 showed higher sensitivities to deep sleep (75%) and REM sleep (86.5%) compared to Garmin Vivosmart 4 and WHOOP. Conclusions: The findings of this systematic literature review indicate that the devices with higher relative agreement and sensitivities to multistate sleep (ie, Fitbit Charge 4 and WHOOP) seem appropriate for deriving suitable estimates of sleep parameters. However, analyses regarding the multistate categorization of sleep indicate that all devices can benefit from further improvement in the assessment of specific sleep stages. Although providers are continuously developing new versions and variants of wearables, the scientific research on these wearables remains considerably limited. This scarcity in literature not only reduces our ability to draw definitive conclusions but also highlights the need for more targeted research in this domain. Additionally, future research endeavors should strive for standardized protocols including larger sample sizes to enhance the comparability and power of the results across studies.

[Techniques for quantifying endotypes of obstructive sleep apnea].

Obstructive sleep apnea (OSA) is the frequent occurrence of apnea and/or hypopnea during sleep, leading to intermittent hypoxia, hypercapnia, and disruption of sleep architecture, further resulting in multisystem damage. The pathophysiological mechanisms include abnormal anatomical structure, low arousal threshold, high loop gain, and poor muscle reactivity, etc. As there are individual differences in the underlying mechanisms of OSA (i.e. endotypes), the effectiveness of treatment and prognosis may also vary according to these characteristics. Understanding the endotype of OSA is critical to understanding which patients are most likely to benefit from non-invasive ventilation therapy. Quantification of endotypes is central to the precision treatment of OSA and may provide the basis for accurate clinical treatment of OSA based on endotypes.

Night-to-night variability of objective sleep outcomes in youth Middle Eastern football players.

OBJECTIVE: To describe components of night-to-night variation in objective measures of sleep. METHODS: We conducted a secondary data analysis of consecutive and chronologically ordered actigraphy-based measurements for time in bed (min), time asleep (min), and wake-after-sleep onset (min). This investigation examined 575 individual night-based measures available for a sub-sample of fifty-two, male youth Middle Eastern football players tracked over a 14-day surveillance period (chronological age range: 12.1 to 16 years). Distinct multivariable-adjusted generalized additive models included each objective sleep outcome measure as dependent variable and disaggregated components of variation for night measurement-by-sleep period interaction, week part (weekday or weekend), and study participant random effects from within-subject night-to-night sleep variation. RESULTS: The within-subject standard deviation (SD) of ±98 min (95% confidence interval [CI], 92 to 104 min) for time in bed, ±87 min (95%CI, 82 to 93 min) for time asleep, and ±23 min (95%CI, 22 to 25 min) for wake-after-sleep-onset overwhelmed other sources of variability and accounted for ∼44% to 53% of the overall night-to-night variation. The night measurement-by-fragmented sleep period interaction SD was ±83 min (95%CI, 44 to 156 min) for time in bed, ±67 min (95%CI, 34 to 131 min) for time asleep, and ±15 min (95%CI, 7 to 32 min) for wake-after-sleep-onset that accounted for ∼22% to 32% of each sleep outcome measure overall variability. CONCLUSIONS: Substantial random night-to-night within-subject variability poses additional challenges for strategies aiming to mitigate problems of insufficient and inconsistent sleep that are detrimental to school learning and youth athlete development processes.

Validation of actigraphy sleep metrics in children aged 8 to 16 years: considerations for device type, placement and algorithms.

BACKGROUND: Actigraphy is often used to measure sleep in pediatric populations, despite little confirmatory evidence of the accuracy of existing sleep/wake algorithms. The aim of this study was to determine the performance of 11 sleep algorithms in relation to overnight polysomnography in children and adolescents. METHODS: One hundred thirty-seven participants aged 8-16 years wore two Actigraph wGT3X-BT (wrist, waist) and three Axivity AX3 (wrist, back, thigh) accelerometers over 24-h. Gold standard measures of sleep were obtained using polysomnography (PSG; Embletta MPRPG, ST + Proxy and TX Proxy) in the home environment, overnight. Epoch by epoch comparisons of the Sadeh (two algorithms), Cole-Kripke (three algorithms), Tudor-Locke (four algorithms), Count-Scaled (CS), and HDCZA algorithms were undertaken. Mean differences from PSG values were calculated for various sleep outcomes. RESULTS: Overall, sensitivities were high (mean ± SD: 91.8%, ± 5.6%) and specificities moderate (63.8% ± 13.8%), with the HDCZA algorithm performing the best overall in terms of specificity (87.5% ± 1.3%) and accuracy (86.4% ± 0.9%). Sleep outcome measures were more accurately measured by devices worn at the wrist than the hip, thigh or lower back, with the exception of sleep efficiency where the reverse was true. The CS algorithm provided consistently accurate measures of sleep onset: the mean (95%CI) difference at the wrist with Axivity was 2 min (-6; -14,) and the offset was 10 min (5, -19). Several algorithms provided accurate measures of sleep quantity at the wrist, showing differences with PSG of just 1-18 min a night for sleep period time and 5-22 min for total sleep time. Accuracy was generally higher for sleep efficiency than for frequency of night wakings or wake after sleep onset. The CS algorithm was more accurate at assessing sleep period time, with narrower 95% limits of agreement compared to the HDCZA (CS:-165 to 172 min; HDCZA: -212 to 250 min). CONCLUSION: Although the performance of existing count-based sleep algorithms varies markedly, wrist-worn devices provide more accurate measures of most sleep measures compared to other sites. Overall, the HDZCA algorithm showed the greatest accuracy, although the most appropriate algorithm depends on the sleep measure of focus.

Alpha anteriorization and theta posteriorization during deep sleep.

Brain states (wake, sleep, general anesthesia, etc.) are profoundly associated with the spatiotemporal dynamics of brain oscillations. Previous studies showed that the EEG alpha power shifted from the occipital cortex to the frontal cortex (alpha anteriorization) after being induced into a state of general anesthesia via propofol. The sleep research literature suggests that slow waves and sleep spindles are generated locally and propagated gradually to different brain regions. Since sleep and general anesthesia are conceptualized under the same framework of consciousness, the present study examines whether alpha anteriorization similarly occurs during sleep and how the EEG power in other frequency bands changes during different sleep stages. The results from the analysis of three polysomnography datasets of 234 participants show consistent alpha anteriorization during the sleep stages N2 and N3, beta anteriorization during stage REM, and theta posteriorization during stages N2 and N3. Although it is known that the neural circuits responsible for sleep are not exactly the same for general anesthesia, the findings of alpha anteriorization in this study suggest that, at macro level, the circuits for alpha oscillations are organized in the similar cortical areas. The spatial shifts of EEG power in different frequency bands during sleep may offer meaningful neurophysiological markers for the level of consciousness.

Association of sleep timing with all-cause and cardiovascular mortality: the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study.

STUDY OBJECTIVES: Previous studies have highlighted the importance of sleep patterns for human health. This study aimed to investigate the association of sleep timing with all-cause and cardiovascular disease mortality. METHODS: Participants were screened from two cohort studies: the Sleep Heart Health Study (SHHS; n = 4,824) and the Osteoporotic Fractures in Men Study (n = 2,658). Sleep timing, including bedtime and wake-up time, was obtained from sleep habit questionnaires at baseline. The sleep midpoint was defined as the halfway point between the bedtime and wake-up time. Restricted cubic splines and Cox proportional hazards regression analyses were used to examine the association between sleep timing and mortality. RESULTS: We observed a U-shaped association between bedtime and all-cause mortality in both the SHHS and Osteoporotic Fractures in Men Study groups. Specifically, bedtime at 11:00 pm and waking up at 7:00 am was the nadir for all-cause and cardiovascular disease mortality risks. Individuals with late bedtime (> 12:00 am) had an increased risk of all-cause mortality in SHHS (hazard ratio 1.53, 95% confidence interval 1.28-1.84) and Osteoporotic Fractures in Men Study (hazard ratio 1.27, 95% confidence interval 1.01-1.58). In the SHHS, late wake-up time (> 8:00 am) was associated with increased all-cause mortality (hazard ratio 1.39, 95% confidence interval 1.13-1.72). No significant association was found between wake-up time and cardiovascular disease mortality. Delaying sleep midpoint (> 4:00 am) was also significantly associated with all-cause mortality in the SHHS and Osteoporotic Fractures in Men Study. CONCLUSIONS: Sleep timing is associated with all-cause and cardiovascular disease mortality. Our findings highlight the importance of appropriate sleep timing in reducing mortality risk. CITATION: Ma M, Fan Y, Peng Y, et al. Association of sleep timing with all-cause and cardiovascular mortality: the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study. J Clin Sleep Med. 2024;20(4):545-553.

Effect of a nutraceutical combination on sleep quality among people with impaired sleep: a randomised, placebo-controlled trial.

In this randomised, placebo-controlled trial, adults with impaired sleep (Pittsburgh Sleep Quality Index ≥ 5) were randomly assigned using a minimization algorithm to receive a formulation containing L-theanine plus lemon balm, valerian, and saffron extracts, or placebo, during 6 weeks. Objective sleep quality parameters were measured using an actigraphy device. We enrolled and randomised 64 individuals, 31 from the active group and 27 from the placebo group completed the 6 week follow-up. Mean sleep efficiency remained unmodified in the active group, and increased by 3% in the placebo group, the between-group difference in the change was not statistically significant (p = 0.49). Total sleep time also improved more with placebo (13.0 vs. 1.33 min, p = 0.66). Time wake after sleep onset (WASO) decreased more in the active group (4.6% vs. 2.4%), but the difference was not significant (p = 0.33). Mean PSQI decreased by 3.11 points (32.3%) in the active group, and by 3.86 points (39.5%) in the placebo group (p = 0.41). SF-36 increased more with placebo (+ 18.3 in active, + 32.1 in placebo, p = 0.68). Salivary cortisol remained unchanged in both groups. No serious adverse events were reported. Among adults with impaired sleep, a nutraceutical combination did not improve objective or subjective sleep parameters more than a placebo infusion.

Effects of respiratory exercises in sleep bruxism and associated obstructive sleep apnea: a double-blind, placebo-controlled randomized clinical trial.

PURPOSE: The aim of this study is to assess the effects of respiratory exercises (inspiratory and expiratory) in individuals with sleep bruxism (SB) and associated obstructive sleep apnea (OSA). METHODS: This is a double-blind, placebo-controlled randomized clinical trial including individuals with SB and associated respiratory events in OSA. Respiratory physical therapy was performed using inspiratory (Threshold® IMT), expiratory (Threshold® PEP) muscle training, and compared with a placebo group. A total of 30 daily respiratory cycles (inspiration and expiration) were performed five times a week for 12 weeks. Individuals were reassessed at two times, at baseline (T1) and after 12 weeks of training (T2) by means of the Pittsburgh Sleep Quality Index and Polysomnography. RESULTS: Awakening was significantly different (p ≤ 0.05) between the inspiratory group and placebo 12 weeks after respiratory physical therapy. The number of contractions of the masseter muscle differed between the inspiratory, expiratory, and placebo groups (p ≤ 0.05). CONCLUSION: Respiratory physical therapy for OSA improved awaking levels in 80 and 67% of the number of masseter muscle contractions, when compared to placebo. TRIAL REGISTRATION: Brazilian Registry of Clinical Trials (No. RBR-9F6JKM).

Changes of Serum Adiponectin Level in Patients with Obstructive Sleep Apnea Hypopnea Syndrome and Its Relationship with Sleep Monitoring Indexes.

Objective: To observe the changes of serum adiponectin (AP) levels in patients with obstructive sleep apnea hypopnea syndrome (OSAHS) and explore the correlation between serum AP and polysomnography (PSG) parameters in patients with OSAHS. Methods: The data of subjects who underwent PSG at the hospital between January 2021 and December 2022 were collected retrospectively and divided into simple snoring group (AHI < 5 times/h, n = 45), mild OSAHS group (5 ≤ AHI < 15 times/h, n = 63), moderate OSAHS group (15 ≤ AHI ≤ 30 times/h, n = 52), and severe OSAHS group (AHI > 30 times/h, n = 60). The general data, PSG indices, and serological indices of the subjects were collected and compared between groups. Pearson correlation analysis and partial correlation analysis were employed to examine the correlation between serum AP level and PSG parameters. Ordered logistic regression was employed to analyze the risk factors influencing the severity of OSAHS. The predictive capability of the serum AP level in determining the occurrence of OSAHS was assessed using ROC. The serum AP levels of subjects with different subtypes of PSG indicators were compared. Results: In the simple snoring group, mild OSAHS group, moderate OSAHS group, and severe OSAHS group, there were statistically significant differences in microarousal count, MAI, AHI, times of blood oxygen decreased by ≥ 3%, L-SaO2, and TS90% among the 4 groups (P < 0.05). The level of serum AP was positively correlated with L-SaO2 and negatively correlated with the proportion of REM, microarousal count, MAI, AHI, times of blood oxygen decreased by ≥ 3%, TS90%, and LP (P < 0.05). High AHI was a risk factor affecting the severity of OSAHS (95% CI: 1.446-4.170). The AUC of serum AP level in diagnosing OSAHS was 0.906 (95% CI: 0.8601-0.9521), and when the Youden Index was 0.678, the sensitivity was 88.9%, and the specificity was 78.9% (P < 0.0001). In the population with a high microarousal count, high AHI, and high times of blood oxygen decreased by ≥ 3% and high TS90%, the serum AP level was lower than that in the low-level population (P < 0.05). In the population with high L-SaO2, the serum AP level was higher than that in low-level population (P < 0.05). Conclusion: The level of serum AP decreased with the increase of the disease severity of patients with OSAHS and demonstrates a significant predictive capability for the occurrence of OSAHS. Monitoring the level of serum AP can effectively forecast the risk of OSAHS. Furthermore, alterations in serum AP levels are associated with both hypoxemia and a heightened frequency of arousal in patients with OSAHS.

Increasing obstructive sleep apnea risk is associated with albuminuria in Korean adults: cross-sectional analysis.

Several studies have shown an association between albuminuria and obstructive sleep apnea (OSA). However, studies on the relationship between the STOP-BANG questionnaire that can screen for OSA and microalbuminuria are still insufficient. Therefore, this study attempted to clarify the relationship between microalbuminuria and OSA risk using the STOP-BANG questionnaire in Korean adults. A total of 7478 participants (3289 men and 4189 women) aged over 40 were enrolled in the Korean National Health and Nutrition Examination Survey from 2019 to 2020. STOP-BANG questionnaire to screen OSA was obtained from subjects. The urinary albumin/creatinine ratio (ACR) and proteinuria were measured via a single dipstick to evaluate renal function. The high OSA risk group had a higher mean ACR value than the low OSA risk group (36.8 ± 172.2 vs 17.7 ± 82.5; P < 0.001). The proportion of subjects with values of 30 ≤ ACR < 300 mg/g (11.9% vs 6.1%; P < 0.001) and ACR > 300 mg/g (2.1% vs 0.7%; P < 0.001) was significantly higher in high OSA risk group. Multivariate logistic regression results confirmed that microalbuminuria (OR 1.279, 95% confidence interval (CI) 1.068-1.532, P = 0.008) was significantly correlated with high OSA risk. In addition, significant correlation with high OSA risk was also found in macroalbuminuria (OR 1.684, 95% CI 1.073-2.530, P = 0.022) and proteinuria (OR 1.355, 95% CI 1.030-1.783, P = 0.030). We confirmed a significant correlation between high OSA risk and albuminuria/proteinuria in Korean adults. Therefore, renal function evaluation is required in high OSA risk patients, and OSA diagnosis through PSG test and treatment is necessary.

Effect of hypoglossal nerve stimulation on snoring: an evaluation using objective acoustic parameters.

STUDY OBJECTIVES: Hypoglossal nerve stimulation is an established therapy for sleep apnea syndrome. Whether or not this therapy on snoring and nighttime noise exposure is effective and how strong this effect may be has not been objectively investigated thus far and was the aim of this study. METHODS: In 15 participants (14 males; age: 30-72 years; mean: 51.7 years), polysomnography and acoustic measurements were performed before and after hypoglossal nerve stimulation. RESULTS: The therapy led to a significant improvement in sleep apnea (apnea-hypopnea index from 35.8 events/h to 11.2 events/h, P < .001). Acoustic parameters showed a highly significant reduction in the average sound pressure level (42.9 db[A] to 36.4 db[A], P < .001), averaged sound energy, A-weighted (LAeq; 33.1 db[A] to 28.7 db[A], P < .001), snoring index (1,068 to 506, P < .001), percentage snoring time (29.7-14.1%, P < .001), and psychoacoustic snore score, the latter being a measure of annoyance due to snoring (47.9 to 24.5, P < .001). CONCLUSIONS: This study was able to show for the first time by means of objective acoustic and psychoacoustic parameters that hypoglossal nerve stimulation can not only cause a significant improvement in sleep apnea but also has a positive effect on snoring and thus noise annoyance experienced by the bed partner. CLINICAL TRIAL REGISTRATION: Registry: German Clinical Trials Register; Name: Effect of Hypoglossal Nerve Stimulation on Snoring: An Evaluation Using Objective Acoustic Parameters; URL: https://drks.de/search/de/trial/DRKS00032354; Identifier: DRKS00032354. CITATION: Fischer R, Vielsmeier V, Kuehnel TS, et al. Effect of hypoglossal nerve stimulation on snoring: an evaluation using objective acoustic parameters. J Clin Sleep Med. 2024;20(3):363-370.

The predictive value of mandibular advancement maneuvers during drug-induced sleep endoscopy for treatment success of oral appliance treatment in obstructive sleep apnea: a prospective study.

STUDY OBJECTIVES: To prospectively validate drug-induced sleep endoscopy with mandibular advancement maneuvers as a prediction tool for treatment success of oral appliance treatment (OAT). METHODS: Seventy-seven patients diagnosed with moderate obstructive sleep apnea were included and underwent drug-induced sleep endoscopy. The upper airway collapse was assessed using the VOTE classification. Additionally, three mandibular advancement maneuvers were performed to predict treatment success of OAT. If the maneuver was negative, the level and degree and configuration of the persistent collapse was described according to the VOTE classification. All patients were treated with OAT and completed a follow-up sleep study with OAT in situ without regard to their anticipated response to treatment. RESULTS: Sixty-four patients completed 6-month follow up. A positive jaw thrust maneuver proved to be significantly associated with favorable OAT response, whereas the chin lift maneuver and the vertical chin lift maneuver were not. Additionally, a persistent lateral oropharyngeal collapse when performing any mandibular advancement maneuver was significantly associated with unfavorable OAT response. CONCLUSIONS: The current findings suggest that a jaw thrust maneuver should be preferred over the chin lift maneuver for predicting OAT response. Patients with a positive jaw thrust maneuver should be counseled toward favorable OAT response, whereas those with persistent lateral oropharyngeal collapse should be advised about the likelihood of unfavorable OAT response. A negative jaw thrust maneuver did not prove to be a significant predictor for unfavorable response to OAT. Consequently, uncertainties arise regarding the justification of performing drug-induced sleep endoscopy solely for predicting the efficacy of OAT. However, the results of the current study could be influenced by heterogeneity in the assessment of respiratory parameters, variability in the performance of the mandibular advancement maneuvers, and the instability of bolus technique sedation. CLINICAL TRIAL REGISTRATION: Registry: Netherlands Trial Register; Name: Drug-induced Sleep Endoscopy: a prediction tool for success rate of oral appliance treatment; Identifier: NL8425; URL: https://www.onderzoekmetmensen.nl/en/trial/20741. CITATION: Veugen CCAFM, Kant E, Kelder JC, Schipper A, Stokroos RJ, Copper MP. The predictive value of mandibular advancement maneuvers during drug-induced sleep endoscopy for treatment success of oral appliance treatment in obstructive sleep apnea: a prospective study. J Clin Sleep Med. 2024;20(3): 353-361.

pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis.

Objective.Photoplethysmography is a non-invasive optical technique that measures changes in blood volume within tissues. It is commonly and being increasingly used for a variety of research and clinical applications to assess vascular dynamics and physiological parameters. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and limited open tools exist for continuous photoplethysmogram (PPG) analysis. Consequently, the primary objective of this research was to identify, standardize, implement and validate key digital PPG biomarkers.Approach.This work describes the creation of a standard Python toolbox, denotedpyPPG, for long-term continuous PPG time-series analysis and demonstrates the detection and computation of a high number of fiducial points and digital biomarkers using a standard fingerbased transmission pulse oximeter.Main results.The improved PPG peak detector had an F1-score of 88.19% for the state-of-the-art benchmark when evaluated on 2054 adult polysomnography recordings totaling over 91 million reference beats. The algorithm outperformed the open-source original Matlab implementation by ∼5% when benchmarked on a subset of 100 randomly selected MESA recordings. More than 3000 fiducial points were manually annotated by two annotators in order to validate the fiducial points detector. The detector consistently demonstrated high performance, with a mean absolute error of less than 10 ms for all fiducial points.Significance.Based on these fiducial points,pyPPGengineered a set of 74 PPG biomarkers. Studying PPG time-series variability usingpyPPGcan enhance our understanding of the manifestations and etiology of diseases. This toolbox can also be used for biomarker engineering in training data-driven models.pyPPGis available onhttps://physiozoo.com/.

A population-based study exploring association of parasomnia symptoms with sleep onset delay among school-aged children.

OBJECTIVE: Parasomnia is potentially implicated in sleep pattern and sleep architecture, however, evidence is quite limited. This study aimed to investigate the association between parasomnia symptoms and sleep onset delay among children through a large epidemiological study. METHODS: Two rounds of cross-sectional studies were conducted among 21,704 children aged 3-11; one taking place in Shanghai and the other in Sanya, Hainan province. Children's sleep characteristics were evaluated using the Children's Sleep Habits Questionnaire (CSHQ). Propensity score matching was adopted to balance the difference of covariates, and the logistic regression models were implemented to examine the associations between parasomnia symptoms and sleep onset delay. RESULTS: A total of 38.2 % of children had sleep onset delay. Parasomnias, especially non rapid eye movement (NREM) and rapid eye movement (REM) parasomnia symptoms, were associated with an increased risk of sleep onset delay (Sleep Walking: OR = 1.55; Sleep Terror: OR = 1.34; Nightmare: OR = 1.37, all p˂0.001). The similar findings were observed in stratified analyses according to sleep duration, and the association was pronounced in sleep sufficiency group (Sleep Walking: OR = 1.62; Sleep Terror: OR = 1.35; Nightmare: OR = 1.35, all p˂0.001). Moreover, a dose-dependent pattern was observed, in which cumulative parasomnia symptoms were associated with increasing risk of sleep onset delay (2 symptoms: OR = 1.19; ≥3 symptoms: OR = 1.40; by comparison with ≤1 symptom). All these findings were also similarly observed in the propensity score matching sample. Moreover, the associations were generally established in both Shanghai and Sanya children. CONCLUSIONS: Parasomnia symptoms were associated with a higher risk of sleep onset delay independently of sleep duration among children. More studies are needed to enrich the current evidence, thus further clarifying the association and interaction among different sleep parameters.