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Benedikt Holm,1 Michal Borsky,1 Erna S Arnardottir,2,3 Marta Serwatko,2 Jacky Mallett,1 Anna Sigridur Islind,1 María Óskarsdóttir1 1Reykjavik University, School of Technology, Department of Computer Science, Reykjavik, Iceland; 2Reykjavik University, School of Technology, Sleep Institute, Reykjavik, Iceland; 3Landspitali, The National University Hospital of Iceland, Reykjavik, IcelandCorrespondence: Benedikt Holm, Email benedikthth@ru.isIntroduction: The field of automatic respiratory analysis focuses mainly on breath detection on signals such as audio recordings, or nasal flow measurement, which suffer from issues with background noise and other disturbances. Here we introduce a novel algorithm designed to isolate individual respiratory cycles on a thoracic respiratory inductance plethysmography signal using the non-invasive signal of the respiratory inductance plethysmography belts.Purpose: The algorithm locates breaths using signal processing and statistical methods on the thoracic respiratory inductance plethysmography belt and enables the analysis of sleep data on an individual breath level.Patients and Methods: The algorithm was evaluated against a cohort of 31 participants, both healthy and diagnosed with obstructive sleep apnea. The dataset consisted of 13 female and 18 male participants between the ages of 20 and 69. The algorithm was evaluated on 7.3 hours of hand-annotated data from the cohort, or 8782 individual breaths in total. The algorithm was specifically evaluated on a dataset containing many sleep-disordered breathing events to confirm that it did not suffer in terms of accuracy when detecting breaths in the presence of sleep-disordered breathing. The algorithm was also evaluated across many participants, and we found that its accuracy was consistent across people. Source code for the algorithm was made public via an open-source Python library.Results: The proposed algorithm achieved an estimated 94% accuracy when detecting breaths in respiratory signals while producing false positives that amount to only 5% of the total number of detections. The accuracy was not affected by the presence of respiratory related events, such as obstructive apneas or snoring.Conclusion: This work presents an automatic respiratory cycle algorithm suitable for use as an analytical tool for research based on individual breaths in sleep recordings that include respiratory inductance plethysmography.Keywords: respiratory analysis, breath detection algorithm, sleep analysis, breath segmentation, respiratory cycle isolation

Obstructive sleep apnea diagnosis is based on the manual scoring of respiratory events. The agreement in the manual scoring of the respiratory events lacks an in-depth investigation as most of the previous studies reported only the apnea-hypopnea index or overall agreement, and not temporal, second-by-second or event subtype agreement. We hypothesized the temporal and subtype agreement to be low because the event duration or subtypes are not generally considered in current clinical practice. The data comprised 50 polysomnography recordings scored by 10 experts. The respiratory event agreement between the scorers was calculated using kappa statistics in a second-by-second manner. Obstructive sleep apnea severity categories (no obstructive sleep apnea/mild/moderate/severe) were compared between scorers. The Fleiss' kappa value for binary (event/no event) respiratory event scorings was 0.32. When calculated separately within N1, N2, N3 and R, the Fleiss' kappa values were 0.12, 0.23, 0.22 and 0.23, respectively. Binary analysis conducted separately for the event subtypes showed the highest Fleiss' kappa for hypopneas to be 0.26. In 34% of the participants, the obstructive sleep apnea severity category was the same regardless of the scorer, whereas in the rest of the participants the category changed depending on the scorer. Our findings indicate that the agreement of manual scoring of respiratory events depends on the event type and sleep stage. The manual scoring has discrepancies, and these differences affect the obstructive sleep apnea diagnosis. This is an alarming finding, as ultimately these differences in the scorings affect treatment decisions., (© 2024 The Author(s). Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Introduction: The apnea-hypopnea index (AHI) is the current diagnostic parameter for diagnosing and estimating the severity of obstructive sleep apnea (OSA). It is, however, poorly associated with the main clinical symptom of OSA, excessive daytime sleepiness, and with the often-seen cognitive decline among OSA patients. To better evaluate OSA severity, novel hypoxic load parameters have been introduced that consider the duration and depth of oxygen saturation drops associated with apneas or hypopneas. The aim of this paper was to compare novel hypoxic load parameters and traditional OSA parameters to verbal memory and executive function in OSA patients., Method: A total of 207 adults completed a one-night polysomnography at sleep laboratory and two neuropsychological assessments, the Rey Auditory Verbal Learning Test and Stroop test., Results: Simple linear regression analyses were used to evaluate independent associations between each OSA parameter and cognitive performance. Associations were found between immediate recall and arousal index, hypoxia <90 %, average SpO 2 during sleep, and DesSev100+RevSev100. Total recall was associated with all OSA parameters, and no associations were found with the Stroop test. Subsequently, sex, age, and education were included as covariates in multiple linear regression analyses for each OSA parameter and cognitive performance. The main findings of the study were that average SpO 2 during sleep was a significant predictor of total recall (p < .007, β = -.188) with the regression model explaining 21.2 % of performance variation. Average SpO 2 during sleep was also a significant predictor of immediate recall (p < .022, β = -.171) with the regression model explaining 11.4 % of performance variation. Neither traditional OSA parameters nor novel hypoxic load parameters predicted cognitive performance after adjustment for sex, age, and education., Conclusion: The findings validate that the AHI is not an effective indicator of cognitive performance in OSA and suggest that average oxygen saturation during sleep may be the strongest PSG predictor of cognitive decline seen in OSA. The results also underline the importance of considering age when choosing neurocognitive tests, the importance of including more than one test for each cognitive domain as most tests are not pure measures of a single cognitive factor, and the importance of including tests that cover all cognitive domains as OSA is likely to have diffuse cognitive effects., Competing Interests: Declaration of competing interest KTH: no conflict of interest. HH: no conflict of interest. TK: no conflict of interest. SN: no conflict of interest. TD: no conflict of interest. IHN: no conflict of interest. TL: no conflict of interest. ESA: honoraria from Nox Medical, Philips, ResMed, Jazz Pharmaceuticals, Linde Healthcare, Alcoa – Fjardaral, WinkSleep, ApniMed and Vistor. She is also a member of the Philips Sleep Medicine & Innovation Medical Advisory Board. MKJ: no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

State-of-the-art automatic sleep staging methods have demonstrated comparable reliability and superior time efficiency to manual sleep staging. However, fully automatic black-box solutions are difficult to adapt into clinical workflow due to the lack of transparency in decision-making processes. Transparency would be crucial for interaction between automatic methods and the work of sleep experts, i.e., in human-in-the-loop applications. To address these challenges, we propose an automatic sleep staging model (aSAGA) that effectively utilises both electroencephalography and electro-oculography channels while incorporating transparency of uncertainty in the decision-making process. We validated the model through extensive retrospective testing using a range of datasets, including open-access, clinical, and research-driven sources. Our channel-wise ensemble model, trained on both electroencephalography and electro-oculography signals, demonstrated robustness and the ability to generalise across various types of sleep recordings, including novel self-applied home polysomnography. Additionally, we compared model uncertainty with human uncertainty in sleep staging and studied various uncertainty mapping metrics to identify ambiguous regions, or "grey areas", that may require manual re-evaluation. The validation of this grey area concept revealed its potential to enhance sleep staging accuracy and to highlight regions in the recordings where sleep experts may struggle to reach a consensus. In conclusion, this study provides a technical basis and understanding of automatic sleep staging uncertainty. Our approach has the potential to improve the integration of automatic sleep staging into clinical practice; however, further studies are needed to test the model prospectively in real-world clinical settings and human-in-the-loop scoring applications., (© 2024 The Author(s). Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

We investigated arousal scoring agreement within full-night polysomnography in a multi-centre setting. Ten expert scorers from seven centres annotated 50 polysomnograms using the American Academy of Sleep Medicine guidelines. The agreement between arousal indexes (ArIs) was investigated using intraclass correlation coefficients (ICCs). Moreover, kappa statistics were used to evaluate the second-by-second agreement in whole recordings and in different sleep stages. Finally, arousal clusters, that is, periods with overlapping arousals by multiple scorers, were extracted. The overall similarity of the ArIs was fair (ICC = 0.41), varying from poor to excellent between the scorer pairs (ICC = 0.04-0.88). The ArI similarity was better in respiratory (ICC = 0.65) compared with spontaneous (ICC = 0.23) arousals. The overall second-by-second agreement was fair (Fleiss' kappa = 0.40), varying from poor to substantial depending on the scorer pair (Cohen's kappa = 0.07-0.68). Fleiss' kappa increased from light to deep sleep (0.45, 0.45, and 0.53 for stages N1, N2, and N3, respectively), was moderate in the rapid eye movement stage (0.48), and the lowest in the wake stage (0.25). Over a half of the arousal clusters were scored by one or two scorers, and less than a third by at least five scorers. In conclusion, the scoring agreement varied depending on the arousal type, sleep stage, and scorer pair, but was overall relatively low. The most uncertain areas were related to spontaneous arousals and arousals scored in the wake stage. These results indicate that manual arousal scoring is generally not reliable, and that changes are needed in the assessment of sleep fragmentation for clinical and research purposes., (© 2023 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

In-laboratory polysomnography, the gold-standard for diagnosing sleep disorders, is resource-demanding and not conducive to multiple night evaluations. Ambulatory polysomnography, especially when self-applied, could be a viable alternative. This study aimed to assess the feasibility and reliability of self-applied polysomnography over three consecutive nights in untrained participants, assessing: technical success rate; comparing sleep diagnostic variables from single and multiple nights; and evaluating participants' subjective experience. Data were collected from 78 participants (55.1% females) invited to test a self-applicable polysomnography device for three consecutive nights at home. The technical success rate for valid sleep recordings was 82.5% out of 234 planned study nights, with 87.2% of participants obtaining at least two valid nights. Misclassification of obstructive sleep apnea severity was higher in participants with mild OSA (21.4%) compared with those with moderate-to-severe obstructive sleep apnea or no obstructive sleep apnea. Sleep efficiency and wake after sleep onset showed improvement from Night 1 to Night 3 (p < 0.001), and the mean polysomnography set-up time decreased significantly over this period. Participants reported moderate-to-high satisfaction with the device (System Usability Scale score 71.2 ± 12.4). The findings suggest that self-applied polysomnography is a feasible diagnostic method for untrained individuals at risk for sleep disorders, and that multiple night assessments can improve diagnostic precision for mild obstructive sleep apnea cases., (© 2024 The Author(s). Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Sleep recordings are increasingly being conducted in patients' homes where patients apply the sensors themselves according to instructions. However, certain sensor types such as cup electrodes used in conventional polysomnography are unfeasible for self-application. To overcome this, self-applied forehead montages with electroencephalography and electro-oculography sensors have been developed. We evaluated the technical feasibility of a self-applied electrode set from Nox Medical (Reykjavik, Iceland) through home sleep recordings of healthy and suspected sleep-disordered adults (n = 174) in the context of sleep staging. Subjects slept with a double setup of conventional type II polysomnography sensors and self-applied forehead sensors. We found that the self-applied electroencephalography and electro-oculography electrodes had acceptable impedance levels but were more prone to losing proper skin-electrode contact than the conventional cup electrodes. Moreover, the forehead electroencephalography signals recorded using the self-applied electrodes expressed lower amplitudes (difference 25.3%-43.9%, p < 0.001) and less absolute power (at 1-40 Hz, p < 0.001) than the polysomnography electroencephalography signals in all sleep stages. However, the signals recorded with the self-applied electroencephalography electrodes expressed more relative power (p < 0.001) at very low frequencies (0.3-1.0 Hz) in all sleep stages. The electro-oculography signals recorded with the self-applied electrodes expressed comparable characteristics with standard electro-oculography. In conclusion, the results support the technical feasibility of the self-applied electroencephalography and electro-oculography for sleep staging in home sleep recordings, after adjustment for amplitude differences, especially for scoring Stage N3 sleep., (© 2023 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Oxygen saturation (SpO 2 )-based parameters are more strongly linked to impaired daytime vigilance than the conventional diagnostic metrics in patients with obstructive sleep apnea (OSA). However, whether the association between SpO 2 -based parameters and impaired daytime vigilance is modulated by sex, remains unknown. Hence, we investigated the interplay between sex and detailed SpO 2 -based metrics and their association with impaired vigilance in patients with OSA. The study population consisted of 855 (473 males, 382 females) patients with suspected OSA who underwent overnight polysomnography and psychomotor vigilance task (PVT). The population was grouped by sex and divided into quartiles (Q1-Q4) based on median reaction times (RTs) in the PVT. In addition to conventional diagnostic metrics, desaturation severity (DesSev), fall severity (FallSev), and recovery severity (RecovSev) were compared between the sexes and between the best (Q1) and worst (Q4) performing quartiles by using cumulative distribution functions (CDFs). Additionally, sex-specific covariate-adjusted linear regression models were used to investigate the connection between the parameters and RTs. The CDFs showed significantly higher hypoxic load in Q4 in males compared to females. In addition, the DesSev (β = 8.05, p < 0.01), FallSev (β = 6.48, p = 0.02), RecovSev (β = 9.13, p < 0.01), and Oxygen Desaturation Index (β = 12.29, p < 0.01) were associated with increased RTs only in males. Conversely, the Arousal Index (β = 10.75-11.04, p < 0.01) was associated with impaired vigilance in females. The severity of intermittent hypoxaemia was strongly associated with longer RTs in males whereas the Arousal Index had the strongest association in females. Thus, the impact of hypoxic load on impaired vigilance seems to be stronger in males than females., (© 2023 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Obesity is the primary risk factor for the development of obstructive sleep apnea, and physical inactivity plays an important role. However, most studies have either only evaluated physical activity subjectively or objectively in obstructive sleep apnea. The objectives of this study were: (i) to assess the relationship between obstructive sleep apnea severity (both apnea-hypopnea index and desaturation parameters) and both objectively and subjectively measured physical activity after adjustment for anthropometry and body composition parameters; and (ii) to assess the relationship between objective and subjective physical activity parameters and whether obstructive sleep apnea severity has a modulatory effect on this relationship. Fifty-four subjects (age 47.7 ± 15.0 years, 46% males) were categorized into groups according to obstructive sleep apnea severity: no obstructive sleep apnea; mild obstructive sleep apnea; and moderate-to-severe obstructive sleep apnea. All subjects were evaluated with subjective and objective physical activity, anthropometric and body composition measurements, and 3-night self-applied polysomnography. A one-way ANOVA was used to evaluate the differences between the three obstructive sleep apnea severity groups and multiple linear regression to predict obstructive sleep apnea severity. Differences in subjectively reported sitting time (p ≤ 0.004) were found between participants with moderate-to-severe obstructive sleep apnea, and those with either mild or no obstructive sleep apnea (p = 0.004). Age, body mass index and neck circumference explained 63.3% of the variance in the apnea-hypopnea index, and age, body mass index and visceral adiposity explained 67.8% of the variance in desaturation parameters. The results showed that the person's physical activity does not affect obstructive sleep apnea severity. A weak correlation was found between objective and subjective physical activity measures, which could be relevant for healthcare staff encouraging patients with obstructive sleep apnea to increase their physical activity., (© 2024 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Obstructive sleep apnea (OSA) is a common disease associated with a high prevalence of costly comorbidities and accidents that add to the disease's economic impact. Although more attention has been focused on OSA in recent years, no previous systematic reviews have synthesized findings from existing studies that provide estimates of the economic cost of OSA. This study aims to summarize the findings of existing studies that provide estimates of the cost of OSA. Two bibliographic databases, PubMed and Scopus, were used to identify articles on the costs of OSA. The systematic literature review identified 5,938 publications, of which 31 met the inclusion criteria. According to the results, adjusted for inflation and converted to euros, the annual cost per patient ranged from €236 (the incremental cost of OSA) for New Zealand to €28,267 for the United States. The total annual cost per patient in Europe ranged from €1,669 to €5,186. OSA causes a significant burden on society, and OSA-related costs increase many years before the diagnosis and remain elevated for a long time after the diagnosis. Despite some well-conducted studies, the cost estimates for OSA are uncertain and specific to the context in which the study was conducted., Competing Interests: Declaration of competing interest The authors state that they have no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Progress in the field of insomnia since 2017 necessitated this update of the European Insomnia Guideline. Recommendations for the diagnostic procedure for insomnia and its comorbidities are: clinical interview (encompassing sleep and medical history); the use of sleep questionnaires and diaries (and physical examination and additional measures where indicated) (A). Actigraphy is not recommended for the routine evaluation of insomnia (C), but may be useful for differential-diagnostic purposes (A). Polysomnography should be used to evaluate other sleep disorders if suspected (i.e. periodic limb movement disorder, sleep-related breathing disorders, etc.), treatment-resistant insomnia (A) and for other indications (B). Cognitive-behavioural therapy for insomnia is recommended as the first-line treatment for chronic insomnia in adults of any age (including patients with comorbidities), either applied in-person or digitally (A). When cognitive-behavioural therapy for insomnia is not sufficiently effective, a pharmacological intervention can be offered (A). Benzodiazepines (A), benzodiazepine receptor agonists (A), daridorexant (A) and low-dose sedating antidepressants (B) can be used for the short-term treatment of insomnia (≤ 4 weeks). Longer-term treatment with these substances may be initiated in some cases, considering advantages and disadvantages (B). Orexin receptor antagonists can be used for periods of up to 3 months or longer in some cases (A). Prolonged-release melatonin can be used for up to 3 months in patients ≥ 55 years (B). Antihistaminergic drugs, antipsychotics, fast-release melatonin, ramelteon and phytotherapeutics are not recommended for insomnia treatment (A). Light therapy and exercise interventions may be useful as adjunct therapies to cognitive-behavioural therapy for insomnia (B)., (© 2023 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Sleep diaries are the gold standard for subjective assessment of sleep variables in clinical practice. Digitization of sleep diaries is needed, as paper versions are prone to human error, memory bias, and difficulties monitoring compliance., Methods: 45 healthy eligible participants (M age = 50.3 years, range 23-74, 56% female) were asked to use a sleep diary mobile app for 90 consecutive days. Univariate and bivariate analysis was used for group comparison and linear regression for analyzing reporting trends and compliance over time., Results: Overall compliance was high in the first two study months but tended to decrease over time ( p < 0.001). Morning and evening diary entries were highly correlated (r = 0.932, p < 0.001) and participants significantly answered on average 4.1 days (95% CI [1.7, 6.6]) more often in the morning (M = 60.2, sd = 22.1) than evening ((M = 56.1, sd = 22.2), p < 0.001)., Conclusion: Using a daily diary assessment in a longitudinal sleep study with a sleep diary delivered through a mobile application was feasible, and compliance in this study was satisfactory.

Obstructive sleep apnea (OSA)-related intermittent hypoxaemia is a potential risk factor for different OSA comorbidities, for example cardiovascular disease. However, conflicting results are found as to whether intermittent hypoxaemia is associated with impaired vigilance. Therefore, we aimed to investigate how desaturation characteristics differ between the non-impaired vigilance and impaired vigilance patient groups formed based on psychomotor vigilance task (PVT) performance and compared with traditional OSA severity parameters. The study population comprised 863 patients with suspected OSA who underwent a PVT test before polysomnography. The conventional OSA parameters, for example, the apnea-hypopnea index, oxygen desaturation index, and arousal index were computed. Furthermore, the median desaturation area, fall area, recovery area, and desaturation depth were computed with the pre-event baseline reference and with reference to the 100% oxygen saturation level. Patients were grouped into best- and worst-performing quartiles based on the number of lapses in PVT (Q1: PVT lapses <5 and Q4: PVT lapses >36). The association between parameters and impaired vigilance was evaluated by cumulative distribution functions (CDFs) and binomial logistic regression. Based on the CDFs, patients in Q4 had larger desaturation areas, recovery areas, and deeper desaturations when these were referenced to 100% saturation compared with Q1. The odds ratio (OR) of the median desaturation area (OR = 1.56), recovery area (OR = 1.71), and depth (OR = 1.65) were significantly elevated in Q4 in regression models. However, conventional OSA parameters were not significantly associated with impaired vigilance (ORs: 0.79-1.09). Considering desaturation parameters with a 100% SpO 2 reference in the diagnosis of OSA could provide additional information on the severity of OSA and related daytime vigilance impairment., (© 2022 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Objective: Obstructive sleep apnea (OSA) is diagnosed using the apnea-hypopnea index (AHI), which is the average number of respiratory events per hour of sleep. Recently, machine learning algorithms for automatic AHI assessment have been developed, but many of them do not consider the individual sleep stages or events. In this study, we aimed to develop a deep learning model to simultaneously score both sleep stages and respiratory events. The hypothesis was that the scoring and subsequent AHI calculation could be performed utilizing pulse oximetry data only., Methods: Polysomnography recordings of 877 individuals with suspected OSA were used to train the deep learning models. The same architecture was trained with three different input signal combinations (model 1: photoplethysmogram (PPG) and oxygen saturation (SpO 2 ); model 2: PPG, SpO 2 , and nasal pressure; model 3: SpO 2 , nasal pressure, electroencephalogram (EEG), oronasal thermocouple, and respiratory belts)., Results: Model 1 reached comparative performance with models 2 and 3 for estimating the AHI (model 1 intraclass correlation coefficient (ICC) = 0.946; model 2 ICC = 0.931; model 3 ICC = 0.945), and REM-AHI (model 1 ICC = 0.912; model 2 ICC = 0.921; model 3 ICC = 0.883). The automatic sleep staging accuracies (wake/N1/N2/N3/REM) were 69%, 70%, and 79% with models 1, 2, and 3, respectively., Conclusion: AHI can be estimated using pulse oximetry-based automatic scoring. Explicit scoring of sleep stages and respiratory events allows visual validation of the automatic analysis, and provides information on OSA phenotypes., Significance: Automatic scoring of sleep stages and respiratory events with a simple pulse oximetry setup could allow cost-effective, large-scale screening of OSA.

Introduction: Visual sleep scoring has several shortcomings, including inter-scorer inconsistency, which may adversely affect diagnostic decision-making. Although automatic sleep staging in adults has been extensively studied, it is uncertain whether such sophisticated algorithms generalize well to different pediatric age groups due to distinctive EEG characteristics. The preadolescent age group (10-13-year-olds) is relatively understudied, and thus, we aimed to develop an automatic deep learning-based sleep stage classifier specifically targeting this cohort., Methods: A dataset ( n  = 115) containing polysomnographic recordings of Icelandic preadolescent children with sleep-disordered breathing (SDB) symptoms, and age and sex-matched controls was utilized. We developed a combined convolutional and long short-term memory neural network architecture relying on electroencephalography (F4-M1), electrooculography (E1-M2), and chin electromyography signals. Performance relative to human scoring was further evaluated by analyzing intra- and inter-rater agreements in a subset ( n  = 10) of data with repeat scoring from two manual scorers., Results: The deep learning-based model achieved an overall cross-validated accuracy of 84.1% (Cohen's kappa κ = 0.78). There was no meaningful performance difference between SDB-symptomatic ( n  = 53) and control subgroups ( n  = 52) [83.9% (κ = 0.78) vs. 84.2% (κ = 0.78)]. The inter-rater reliability between manual scorers was 84.6% (κ = 0.78), and the automatic method reached similar agreements with scorers, 83.4% (κ = 0.76) and 82.7% (κ = 0.75)., Conclusion: The developed algorithm achieved high classification accuracy and substantial agreements with two manual scorers; the performance metrics compared favorably with typical inter-rater reliability between manual scorers and performance reported in previous studies. These suggest that our algorithm may facilitate less labor-intensive and reliable automatic sleep scoring in preadolescent children., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Somaskandhan, Leppänen, Terrill, Sigurdardottir, Arnardottir, Ólafsdóttir, Serwatko, Sigurðardóttir, Clausen, Töyräs and Korkalainen.)

Hyperhidrosis is characterized by excessive sweating beyond thermoregulatory needs that affects patients' quality of life. It results from an excessive stimulation of eccrine sweat glands in the skin by the sympathetic nervous system. Hyperhidrosis may be primary or secondary to an underlying cause. Nocturnal hyperhidrosis is associated with different sleep disorders, such as obstructive sleep apnea, insomnia, restless legs syndrome/periodic limb movement during sleep and narcolepsy. The major cause of the hyperhidrosis is sympathetic overactivity and, in the case of narcolepsy type 1, orexin deficiency may also contribute. In this narrative review, we will provide an outline of the possible mechanisms underlying sudomotor dysfunction and the resulting nocturnal hyperhidrosis in these different sleep disorders and explore its clinical relevance., (© 2022 European Sleep Research Society.)

Reliable, automated, and user-friendly solutions for the identification of sleep stages in home environment are needed in various clinical and scientific research settings. Previously we have shown that signals recorded with an easily applicable textile electrode headband (FocusBand, T 2 Green Pty Ltd) contain characteristics similar to the standard electrooculography (EOG, E1-M2). We hypothesize that the electroencephalographic (EEG) signals recorded using the textile electrode headband are similar enough with standard EOG in order to develop an automatic neural network-based sleep staging method that generalizes from diagnostic polysomnographic (PSG) data to ambulatory sleep recordings of textile electrode-based forehead EEG. Standard EOG signals together with manually annotated sleep stages from clinical PSG dataset (n = 876) were used to train, validate, and test a fully convolutional neural network (CNN). Furthermore, ambulatory sleep recordings including a standard set of gel-based electrodes and the textile electrode headband were conducted for 10 healthy volunteers at their homes to test the generalizability of the model. In the test set (n = 88) of the clinical dataset, the model's accuracy for 5-stage sleep stage classification was 80% (κ = 0.73) using only the single-channel EOG. The model generalized well for the headband-data, reaching 82% (κ = 0.75) overall sleep staging accuracy. In comparison, accuracy of the model was 87% (κ = 0.82) in home recordings using the standard EOG. In conclusion, the CNN model shows potential on automatic sleep staging of healthy individuals using a reusable electrode headband in a home environment.

Study Objectives: Sleep stability can be studied by evaluating the cyclic alternating pattern (CAP) in electroencephalogram (EEG) signals. The present study presents a novel approach for assessing sleep stability, developing an index based on the CAP A-phase characteristics to display a sleep stability profile for a whole night's sleep., Methods: Two ensemble classifiers were developed to automatically score the signals, one for "A-phase" and the other for "non-rapid eye movement" estimation. Both were based on three one-dimension convolutional neural networks. Six different inputs were produced from the EEG signal to feed the ensembles' classifiers. A proposed heuristic-oriented search algorithm individually tuned the classifiers' structures. The outputs of the two ensembles were combined to estimate the A-phase index (API). The models can also assess the A-phase subtypes, their API, and the CAP cycles and rate., Results: Four dataset variations were considered, examining healthy and sleep-disordered subjects. The A-phase average estimation's accuracy, sensitivity, and specificity range was 82%-87%, 72%-80%, and 82%-88%, respectively. A similar performance was attained for the A-phase subtype's assessments, with an accuracy range of 82%-88%. Furthermore, in the examined dataset's variations, the API metric's average error varied from 0.15 to 0.25 (with a median range of 0.11-0.24). These results were attained without manually removing wake or rapid eye movement periods, leading to a methodology suitable to produce a fully automatic CAP scoring algorithm., Conclusions: Metrics based on API can be understood as a new view for CAP analysis, where the goal is to produce and examine a sleep stability profile., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Novel diagnostic markers for obstructive sleep apnea beyond the apnea-hypopnea index (AHI) have been introduced. There are no studies on their association with markers of subclinical myocardial injury. We assessed the association between novel desaturation parameters and elevated cardiac troponin I and T. Participants with polysomnography (498) from the Akershus Sleep Apnea study were divided into normal and elevated biomarker groups based on sex-specific concentration thresholds (cardiac troponin I: ≥4 ng/L for women, ≥6 ng/L for men; and cardiac troponin T: ≥7 ng/L for women, ≥8 ng/L for men). Severity of obstructive sleep apnea was evaluated with the AHI, oxygen desaturation index, total sleep time with oxygen saturation below 90% (T90), lowest oxygen saturation (Min SpO 2 %), and novel oxygen desaturation parameters: desaturation duration and desaturation severity. How the AHI and novel desaturation parameters predicted elevated cardiac troponin I and cardiac troponin T levels was assessed by the area under the curve (AUC). Based on multivariable-adjusted linear regression, the AHI (β = 0.004, p = 0.012), desaturation duration (β = 0.007, p = 0.004), and desaturation severity (β = 0.147, p = 0.002) were associated with cardiac troponin I levels but not cardiac troponin T. T90 was associated with cardiac troponin I (β = 0.006, p = 0.009) and cardiac troponin T (β = 0.005, p = 0.007). The AUC for the AHI 0.592 (standard error 0.043) was not significantly different from the AUC of T90 (SD 0.640, p = 0.08), desaturation duration 0.609 (SD 0.044, p = 0.42) or desaturation severity 0.616 (SD 0.043, p = 0.26) in predicting myocardial injury as assessed by cardiac troponin I. Oxygen desaturation parameters and the AHI were associated with cardiac troponin I levels but not cardiac troponin T levels. Novel oxygen desaturation parameters did not improve the prediction of subclinical myocardial injury compared to the AHI., (© 2022 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Obstructive sleep apnea is linked to severe health consequences such as hypertension, daytime sleepiness, and cardiovascular disease. Nearly a billion people are estimated to have obstructive sleep apnea with a substantial economic burden. However, the current diagnostic parameter of obstructive sleep apnea, the apnea-hypopnea index, correlates poorly with related comorbidities and symptoms. Obstructive sleep apnea severity is measured by counting respiratory events, while other physiologically relevant consequences are ignored. Furthermore, as the clinical methods for analysing polysomnographic signals are outdated, laborious, and expensive, most patients with obstructive sleep apnea remain undiagnosed. Therefore, more personalised diagnostic approaches are urgently needed. The Sleep Revolution, funded by the European Union's Horizon 2020 Research and Innovation Programme, aims to tackle these shortcomings by developing machine learning tools to better estimate obstructive sleep apnea severity and phenotypes. This allows for improved personalised treatment options, including increased patient participation. Also, implementing these tools will alleviate the costs and increase the availability of sleep studies by decreasing manual scoring labour. Finally, the project aims to design a digital platform that functions as a bridge between researchers, patients, and clinicians, with an electronic sleep diary, objective cognitive tests, and questionnaires in a mobile application. These ambitious goals will be achieved through extensive collaboration between 39 centres, including expertise from sleep medicine, computer science, and industry and by utilising tens of thousands of retrospectively and prospectively collected sleep recordings. With the commitment of the European Sleep Research Society and Assembly of National Sleep Societies, the Sleep Revolution has the unique possibility to create new standardised guidelines for sleep medicine., (© 2022 European Sleep Research Society.)

Study Objectives: The high prevalence of obstructive sleep apnea (OSA) in the general population makes diagnosing OSA a high priority. Typically, patients receive in-person instructions to hook up the home sleep apnea test devices. Using recorded video instructions would save health care personnel time and improve access to OSA diagnostics for patients in remote areas. The aim of this study was to compare the quality of home sleep apnea test recordings when using in-person and video hookup instructions in a randomized study., Methods: A total of 100 patients aged 18 to 70 years with suspected OSA were randomized to receive either in-person or video hookup instructions for the Nox T3 device (Nox Medical, Reykjavik, Iceland). The overall quality of the resulting sleep studies was analyzed by determining the number of technically invalid studies. The recording quality of 4 sensors (pulse oximeter, nasal cannula, thorax and abdominal respiratory inductance plethysmography belts) was assessed by checking for signal artifacts., Results: No significant difference was found between the 2 groups in any quality index. Only 1 (2%) and 2 (3.9%) sleep studies were technically invalid in the in-person and video instructions group, respectively. The average ± standard deviation recording quality of the 4 sensors combined was 94.8% ± 13.6% for the in-person and 96.0% ± 11.0% for the video instructions group., Conclusions: This study found no difference in home sleep apnea test recording quality between the 2 groups. Video hookup instructions are therefore viable and an important step toward a telemedicine-based way of diagnosing OSA., Citation: Horne AF, Olafsdottir KA, Arnardottir ES. In-person vs video hookup instructions: a comparison of home sleep apnea testing quality. J Clin Sleep Med . 2022;18(8):2069-2074., (© 2022 American Academy of Sleep Medicine.)

The diagnosis of sleep disordered breathing depends on the detection of respiratory-related events: apneas, hypopneas, snores, or respiratory event-related arousals from sleep studies. While a number of automatic detection methods have been proposed, their reproducibility has been an issue, in part due to the absence of a generally accepted protocol for evaluating their results. With sleep measurements this is usually treated as a classification problem and the accompanying issue of localization is not treated as similarly critical. To address these problems we present a detection evaluation protocol that is able to qualitatively assess the match between two annotations of respiratory-related events. This protocol relies on measuring the relative temporal overlap between two annotations in order to find an alignment that maximizes their F1-score at the sequence level. This protocol can be used in applications which require a precise estimate of the number of events, total event duration, and a joint estimate of event number and duration. We assess its application using a data set that contains over 10,000 manually annotated snore events from 9 subjects, and show that when using the American Academy of Sleep Medicine Manual standard, two sleep technologists can achieve an F1-score of 0.88 when identifying the presence of snore events. In addition, we drafted rules for marking snore boundaries and showed that one sleep technologist can achieve F1-score of 0.94 at the same tasks. Finally, we compared this protocol against the protocol that is used to evaluate sleep spindle detection and highlighted the differences.

The authors discuss the challenges of machine- and deep learning-based automatic analysis of obstructive sleep apnea with respect to known issues with the signal interpretation, patient physiology, and the apnea-hypopnea index. Their goal is to provide guidance for sleep and machine learning professionals working in this area of sleep medicine. They suggest that machine learning approaches may well be better targeted at examining and attempting to improve the diagnostic criteria, in order to build a more nuanced understanding of the detailed circumstances surrounding OSA, rather than merely attempting to reproduce human scoring., Competing Interests: Disclosure No relevant conflict of interest to disclose., (Copyright © 2021 Elsevier Inc. All rights reserved.)

This article provides an overview of the current use, limitations, and future directions of the variety of subjective and objective sleep assessments available. This article argues for various ways and sources of collecting, combining, and using data to enlighten clinical practice and the sleep research of the future. It highlights the prospects of digital management platforms to store and present the data, and the importance of codesign when developing such platforms and other new instruments. It also discusses the abundance of opportunities that data science and machine learning open for the analysis of data., Competing Interests: Disclosure Dr E.S. Arnardottir discloses lecture fees from Nox Medical, Philips, and ResMed. Dr A.S. Islind and Dr M. Óskarsdóttir have nothing to disclose. The work in this article is sponsored in part by the Sleep Revolution, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 965417 and by NordForsk (NordSleep project 90458-06111) via the Icelandic Centre for Research., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: Evaluate the effect of respiratory inductance plethysmography (RIP) belt design on the reliability and quality of respiratory signals. A comparison of cannula flow to disposable cut-to-fit, semi-disposable folding and disposable RIP belts was performed in clinical home sleep apnea testing (HSAT) studies., Methods: This was a retrospective study using clinical HSAT studies. The signal reliability of cannula, thorax, and abdomen RIP belts was determined by automatically identifying periods during which the signals did not represent respiratory airflow and breathing movements. Results were verified by manual scoring. RIP flow quality was determined by examining the correlation between the RIP flow and cannula flow when both signals were considered reliable., Results: Of 767 clinical HSAT studies, mean signal reliability of the cut-to-fit, semi-disposable, and disposable thorax RIP belts was 83.0 ± 26.2%, 76.1 ± 24.4%, and 98.5 ± 9.3%, respectively. The signal reliability of the cannula was 92.5 ± 16.1%, 87.0 ± 23.3%, and 85.5 ± 24.5%, respectively. The automatic assessment of signal reliability for the RIP belts and cannula flow had a sensitivity of 50% and a specificity of 99% compared with manual assessment. The mean correlation of cannula flow to RIP flow from the cut-to-fit, semi-disposable, and disposable RIP belts was 0.79 ± 0.24, 0.52 ± 0.20, and 0.86 ± 0.18, respectively., Conclusion: The design of RIP belts affects the reliability and quality of respiratory signals. The disposable RIP belts that had integrated contacts and did not fold on top of themselves performed the best. The cut-to-fit RIP belts were most likely to be unreliable, and the semi-disposable folding belts produced the lowest-quality RIP flow signals compared to the cannula flow signal., (© 2021. The Author(s).)

The 'catalogue of knowledge and skills' for sleep medicine presents the blueprint for a curriculum, a textbook, and an examination on sleep medicine. The first catalogue of knowledge and skills was presented by the European Sleep Research Society in 2014. It was developed following a formal Delphi procedure. A revised version was needed in order to incorporate changes that have occurred in the meantime in the International Classification of Sleep Disorders, updates in the manual for scoring sleep and associated events, and, most important, new knowledge in sleep physiology and pathophysiology. In addition, another major change can be observed in sleep medicine: a paradigm shift in sleep medicine has taken place. Sleep medicine is no longer a small interdisciplinary field in medicine. Sleep medicine has increased in terms of recognition and importance in medical care. Consequently, major medical fields (e.g. pneumology, cardiology, neurology, psychiatry, otorhinolaryngology, paediatrics) recognise that sleep disorders become a necessity for education and for diagnostic assessment in their discipline. This paradigm change is considered in the catalogue of knowledge and skills revision by the addition of new chapters., (© 2021 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Objectives: Besides hypoxaemia severity, heart rate variability has been linked to cognitive decline in obstructive sleep apnoea (OSA) patients. Thus, our aim was to examine whether the frequency domain features of a nocturnal photoplethysmogram (PPG) can be linked to poor performance in the psychomotor vigilance task (PVT)., Methods: PPG signals from 567 suspected OSA patients, extracted from Type 1 diagnostic polysomnography, and corresponding results of PVT were retrospectively examined. The frequency content of complete PPGs was determined, and analyses were conducted separately for men (n=327) and women (n=240). Patients were grouped into PVT performance quartiles based on the number of lapses (reaction times ≥500 ms) and within-test variation in reaction times. The best-performing (Q1) and worst-performing (Q4) quartiles were compared due the lack of clinical thresholds in PVT., Results: We found that the increase in arterial pulsation frequency (APF) in both men and women was associated with a higher number of lapses. Higher APF was also associated with higher within-test variation in men, but not in women. Median APF (β=0.27, p=0.01), time spent under 90% saturation (β=0.05, p<0.01), female sex (β=1.29, p<0.01), older age (β=0.03, p<0.01) and subjective sleepiness (β=0.07, p<0.01) were significant predictors of belonging to Q4 based on lapses. Only female sex (β=0.75, p<0.01) and depression (β=0.91, p<0.02) were significant predictors of belonging to Q4 based on the within-test variation., Conclusions: In conclusion, increased APF in PPG provides a possible polysomnography indicator for deteriorated vigilance especially in male OSA patients. This finding highlights the connection between cardiorespiratory regulation, vigilance and OSA. However, our results indicate substantial sex-dependent differences that warrant further prospective studies., Competing Interests: Conflict of interest: S. Kainulainen reports grants from the Academy of Finland (grant number 313697), The Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041779 and 5041768), the Competitive State Research Financing of Expert Responsibility Area of Tampere University Hospital (grants VTR3221, VTR3228 and EVO2089), the Päivikki & Sakari Sohlberg Foundation, The Research Foundation of the Pulmonary Diseases, and the Alfred Kordelin Foundation, during the conduct of the study. Conflict of interest: B. Duce has nothing to disclose. Conflict of interest: H. Korkalainen reports grants from the Academy of Finland (grant number 313697), The Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041780 and 5041767), the Respiratory Foundation of Kuopio Region, the Päivikki & Sakari Sohlberg Foundation, The Research Foundation of the Pulmonary Diseases, and the Foundation of the Finnish Anti-Tuberculosis Association, during the conduct of the study. Conflict of interest: A. Leino reports grants from The Research Committee of the Kuopio University Hospital Catchment Area (project number 5041776), the Päivikki & Sakari Sohlberg Foundation, The Research Foundation of the Pulmonary Diseases, The Finnish Cultural Foundation, and the Respiratory Foundation of Kuopio Region, during the conduct of the study. Conflict of interest: R. Huttunen reports grants from Business Finland and The Research Committee of Kuopio University Hospital Catchment Area during the conduct of the study. Conflict of interest: L. Kalevo reports grants from the Academy of Finland (grant number 313697), The Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041764 and 5041770) and the Research Foundation of the Pulmonary Diseases during the conduct of the study. Conflict of interest: E.S. Arnardottir reports grants, personal fees and nonfinancial support from Nox Medical, and personal fees from Philips and ResMed, outside the submitted work. Conflict of interest: A. Kulkas reports grants from Seinäjoki Central Hospital, the Competitive State Research Financing of Expert Responsibility Area of Tampere University Hospital and the Tampere Tuberculosis Foundation during the conduct of the study. Conflict of interest: S. Myllymaa reports grants from the Academy of Finland (grant number 313697), The Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041770), the Paulo Foundation and the Tampere Tuberculosis Foundation during the conduct of the study. Conflict of interest: J. Töyräs reports grants from the Academy of Finland (decision number 313697), Kuopio University Hospital (project number 5041767) and Business Finland (decision number 5133/31/2018) during the conduct of the study. Conflict of interest: T. Leppänen reports grants from The Research Committee of the Kuopio University Hospital Catchment Area for the State Research Funding (project number 5041767), the Academy of Finland (decision numbers 313697 and 323536), the Tampere Tuberculosis Foundation and the Respiratory Foundation of Kuopio Region during the conduct of the study., (Copyright ©ERS 2020.)

The publication of "The Sleep Apnea Syndromes" by Guilleminault et al. in the 1970s hallmarked the discovery of a new disease entity involving serious health consequences. Obstructive sleep apnea was shown to be the most important disorder among the sleep apnea syndromes (SAS). In the course of time, it was found that the prevalence of obstructive sleep apnea reached the proportions of a global epidemic, with a major impact on public health, safety and the economy. Early on, a metric was introduced to gauge the seriousness of obstructive sleep apnea, based on the objective measurement of respiratory events during nocturnal sleep. The apnea index and later on the apnea-hypopnea index, being the total count of overnight respiratory events divided by the total sleep time in hours, were embraced as principle measures to establish the diagnosis of obstructive sleep apnea and to rate its severity. The current review summarises the historical evolution of the apnea-hypopnea index, which has been subject to many changes, and has been criticised for not capturing relevant clinical features of obstructive sleep apnea. In fact, the application of the apnea-hypopnea index as a continuous exposure variable is based on assumptions that it represents a disease state of obstructive sleep apnea and that evocative clinical manifestations are invariably caused by obstructive sleep apnea if the apnea-hypopnea index is above diagnostic threshold. A critical appraisal of the extensive literature shows that both assumptions are invalid. This conclusion prompts a reconsideration of the role of the apnea-hypopnea index as the prime diagnostic metric of clinically relevant obstructive sleep apnea., (© 2020 European Sleep Research Society.)

Current diagnostic parameters estimating obstructive sleep apnoea (OSA) severity have a poor connection to the psychomotor vigilance of OSA patients. Thus, we aimed to investigate how the severity of apnoeas, hypopnoeas and intermittent hypoxaemia is associated with impaired vigilance.We retrospectively examined type I polysomnography data and corresponding psychomotor vigilance tasks (PVTs) of 743 consecutive OSA patients (apnoea-hypopnoea index (AHI) ≥5 events·h -1 ). Conventional diagnostic parameters ( e.g. AHI and oxygen desaturation index (ODI)) and novel parameters ( e.g. desaturation severity and obstruction severity) incorporating duration of apnoeas and hypopnoeas as well as depth and duration of desaturations were assessed. Patients were grouped into quartiles based on PVT outcome variables. The odds of belonging to the worst-performing quartile were assessed. Analyses were performed for all PVT outcome variables using binomial logistic regression.A relative 10% increase in median depth of desaturations elevated the odds (OR range 1.20-1.37, p<0.05) of prolonged mean and median reaction times as well as increased lapse count. Similarly, an increase in desaturation severity (OR range 1.26-1.52, p<0.05) associated with prolonged median reaction time. Female sex (OR range 2.21-6.02, p<0.01), Epworth Sleepiness Scale score (OR range 1.05-1.07, p<0.01) and older age (OR range 1.01-1.05, p<0.05) were significant risk factors in all analyses. In contrast, increases in conventional AHI, ODI and arousal index were not associated with deteriorated PVT performance.These results show that our novel parameters describing the severity of intermittent hypoxaemia are significantly associated with increased risk of impaired PVT performance, whereas conventional OSA severity and sleep fragmentation metrics are not. These results underline the importance of developing the assessment of OSA severity beyond the AHI., Competing Interests: Conflict of interest: S. Kainulainen reports grants from Academy of Finland (grant number 313697), the Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041779 and 5041768), the Competitive State Research Financing of Expert Responsibility Area of Tampere University Hospital (grants VTR3221, VTR3228 and EVO2089), Päivikki and Sakari Sohlberg Foundation and the Research Foundation of the Pulmonary Diseases, during the conduct of the study. Conflict of interest: B. Duce has nothing to disclose. Conflict of interest: H. Korkalainen reports grants from Academy of Finland (grant number 313697), the Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041780 and 5041767), Respiratory Foundation of Kuopio Region, Päivikki and Sakari Sohlberg Foundation, the Research Foundation of the Pulmonary Diseases, Foundation of the Finnish Anti-Tuberculosis Association, during the conduct of the study. Conflict of interest: A. Oksenberg has nothing to disclose. Conflict of interest: A. Leino reports grants from the Research Committee of the Kuopio University Hospital Catchment Area (project number 5041776), Päivikki and Sakari Sohlberg Foundation, the Research Foundation of the Pulmonary Diseases, the Finnish Cultural Foundation and Respiratory Foundation of Kuopio Region, during the conduct of the study. Conflict of interest: E.S. Arnardottir reports grants, personal fees and non-financial support from Nox Medical, personal fees from Philips and ResMed, outside the submitted work. Conflict of interest: A. Kulkas reports grants from Seinäjoki Central Hospital, Competitive State Research Financing of Expert Responsibility Area of Tampere University Hospital (VTR3221 and VTR3228 and Tampere Tuberculosis foundation, during the conduct of the study. Conflict of interest: S. Myllymaa reports grants from Academy of Finland (grant number 313697), the Research Committee of the Kuopio University Hospital Catchment Area (project numbers 5041770), Paulo Foundation and Tampere Tuberculosis Foundation, during the conduct of the study. Conflict of interest: J. Töyräs reports grants from Academy of Finland (decision number 313697), Kuopio University Hospital (project number 5041767) and Business Finland (decision number 5133/31/2018), during the conduct of the study. Conflict of interest: T. Leppänen reports grants from the Research Committee of the Kuopio University Hospital Catchment Area for the State Research Funding (project number 5041767), Academy of Finland (decision numbers 313697 and 323536), Tampere Tuberculosis Foundation and Respiratory Foundation of Kuopio Region, during the conduct of the study., (Copyright ©ERS 2020.)

Many different subjective tools are being used to measure excessive daytime sleepiness (EDS) but the most widely used is the Epworth Sleepiness Scale (ESS). However, it is unclear if using the ESS is adequate on its own when assessing EDS. The aim of this study was to estimate the characteristics and prevalence of EDS using the ESS and the Basic Nordic Sleep Questionnaire (BNSQ) in general population samples. Participants aged 40 years and older answered questions about sleepiness, health, sleep-related symptoms and quality of life. Two groups were defined as suffering from EDS: those who scored >10 on the ESS (with increased risk of dozing off) and those reporting feeling sleepy during the day ≥3 times per week on the BNSQ. In total, 1,338 subjects (53% male, 74.1% response rate) participated, 13.1% reported an increased risk of dozing off, 23.2% reported feeling sleepy and 6.4% reported both. The prevalence of restless leg syndrome, nocturnal gastroesophageal reflux, difficulties initiating and maintaining sleep and nocturnal sweating was higher among subjects reporting feeling sleepy compared to non-sleepy subjects. Also, subjects reporting feeling sleepy had poorer quality of life and reported more often feeling unrested during the day than non-sleepy subjects. However, subjects reporting increased risk of dozing off (ESS > 10) without feeling sleepy had a similar symptom profile as the non-sleepy subjects. Therefore, reporting only risk of dozing off without feeling sleepy may not reflect problematic sleepiness and more instruments in addition to ESS are needed when evaluating daytime sleepiness., (© 2019 European Sleep Research Society.)

Purpose: To determine the agreement between the manual scoring of home sleep apnea tests (HSATs) by international sleep technologists and automated scoring systems., Methods: Fifteen HSATs, previously recorded using a type 3 monitor, were saved in European Data Format. The studies were scored by nine experienced technologists from the sleep centers of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC) using the locally available software. Each study was scored separately by human scorers using the nasal pressure (NP), flow derived from the NP signal (transformed NP), or respiratory inductive plethysmography (RIP) flow. The same procedure was followed using two automated scoring systems: Remlogic (RLG) and Noxturnal (NOX)., Results: The intra-class correlation coefficients (ICCs) of the apnea-hypopnea index (AHI) scoring using the NP, transformed NP, and RIP flow were 0.96 [95% CI 0.93-0.99], 0.98 [0.96-0.99], and 0.97 [0.95-0.99], respectively. Using the NP signal, the mean differences in AHI between the average of the manual scoring and the automated systems were - 0.9 ± 3.1/h (AHI RLG vs AHI MANUAL ) and - 1.3 ± 2.6/h (AHI NOX vs AHI MANUAL ). Using the transformed NP, the mean differences in AHI were - 1.9 ± 3.3/h (AHI RLG vs AHI MANUAL ) and 1.6 ± 3.0/h (AHI NOX vs AHI MANUAL ). Using the RIP flow, the mean differences in AHI were - 2.7 ± 4.5/h (AHI RLG vs AHI MANUAL ) and 2.3 ± 3.4/h (AHI NOX vs AHI MANUAL )., Conclusions: There is very strong agreement in the scoring of the AHI for HSATs between the automated systems and experienced international technologists. Automated scoring of HSATs using commercially available software may be useful to standardize scoring in future endeavors involving international sleep centers.

Purpose: The inflammatory markers chitinase-3-like protein 1 (CHI3L1) and chitotriosidase (CHIT1) have both been associated with cardiovascular complications. The aim of this preliminary observational study was to assess the roles and interaction of obstructive sleep apnea (OSA) severity and body mass index (BMI) with plasma CHI3L1 levels and CHIT1 activity in patients with moderate to severe OSA. The second aim was to assess the roles and interaction of positive airway pressure (PAP) treatment and BMI on the expression of the same proteins., Methods: The study included 97 OSA patients with an apnea-hypopnea index (AHI) ≥ 15 and full usage of PAP treatment after 4 months. Plasma CHI3L1 levels and CHIT1 activity were measured before and after treatment., Results: Multiple linear regression analysis demonstrated an independent association of BMI on CHI3L1 levels (p < 0.05) but not on CHIT1 activity. The OSA severity markers (AHI and oxygen desaturation index) did not independently or in interaction with BMI levels associate with CHI3L1 levels or with CHIT1 activity (p > 0.05). A two-way repeated measures ANOVA revealed a significant interaction between PAP treatment effect (before vs. after) and BMI groups (< 35 kg/m 2 vs. ≥ 35 kg/m 2 ) on CHI3L1 levels (p = 0.03) but not on CHIT1 activity (p = 0.98)., Conclusions: Obesity independently associated with CHI3L1 levels. Association between OSA severity and CHI3L1 levels or CHIT1 activity (independent of or dependent on obesity level) could not be confirmed. However, decrease was observed in CHI3L1 levels after PAP treatment in severely obese OSA patients but not in those less obese.

Study Objectives: To examine the level of physical activity (PA) before and following positive airway pressure (PAP) treatment in adults who have obstructive sleep apnea (OSA) with obesity versus without obesity., Methods: Simultaneous waist accelerometer and wrist actigraphy recordings were obtained in 129 adults with obesity and 69 adults without obesity and who had OSA prior to and following 4 months of PAP therapy and in 52 patients in a control group. Primary PA measurements were average steps per day on waist accelerometry and average counts per minute (CPM) per day on wrist actigraphy., Results: At baseline, participants with obesity and OSA exhibited fewer steps per day on waist accelerometer and fewer CPM per day on wrist actigraphy compared to participants without obesity and with OSA (despite similar apnea-hypopnea index between groups). Following PAP treatment, participants with OSA had modestly increased CPM per day on wrist actigraphy (17.69 [95% confidence interval (CI), 5.67-29.71], P = .005) and increased light PA time (0.26 [95% CI, 0.07-0.44] hours, P = .008) on waist accelerometer. Participants without obesity and with OSA had greater improvements in PA measures on average compared to participants with obesity and OSA, although the differences were not statistically significant. Weight increased following PAP treatment in the participants with obesity and OSA (1.71 [95% CI, 0.41-3.02] kg, P = .010) but was unchanged in the group without obesity (0.93 [95% CI, -0.89 to 2.76] kg, P = .311)., Conclusions: Compared to study participants without obesity and with OSA, participants with obesity and OSA had reduced PA at baseline. PA increased significantly in participants without obesity, with OSA, and who were adherent to PAP treatment. Results indicate that treatment of OSA is unlikely to be associated with a change in PA in adults with obesity and OSA and help explain the absence of weight loss following PAP treatment in adults with OSA., Clinical Trial Registration: Registry: ClinicalTrials.gov, title: The Effects of Treating Obese and Lean Patients With Sleep Apnea (PISA), identifier: NCT01578031, URL: https://clinicaltrials.gov/ct2/show/NCT01578031., (© 2018 American Academy of Sleep Medicine.)

Purpose: Ferritin is an intracellular iron storage protein and a marker of inflammation. Studies have shown that subjects with obstructive sleep apnea (OSA) have higher levels of circulating pro-inflammatory cytokines, but little is known about the association between ferritin and OSA. The aims of the study were to evaluate serum ferritin (S-Ferritin) levels in OSA patients compared to levels in the general population and also examine the effect of obesity level and treatment with positive airway pressure (PAP) on S-Ferritin levels., Methods: The OSA subjects (n = 796) were part of the Icelandic Sleep Apnea Cohort. The control subjects (n = 637) were randomly chosen Icelanders who participated in an epidemiological study. Propensity score (PS) methodologies were employed to minimize selection bias and strengthen causal inferences when comparing non-randomized groups. S-Ferritin levels were measured and all participants answered the same detailed questionnaire about sleep and health. Only OSA patients underwent a sleep study and were re-invited for a 2-year follow-up., Results: S-Ferritin levels were significantly higher in OSA males than controls (213.3 vs. 197.3 μg/L, p = 0.007). However, after adjusting for confounders and using our PS methodology, no significant difference was found. S-Ferritin levels were not correlated with severity of OSA, obesity level, or clinical symptoms. Also, no significant change in S-Ferritin levels was found with 2 years of PAP treatment., Conclusions: S-Ferritin levels are comparable in OSA patients and controls and do not change consistently with obesity level or PAP treatment in our sample.

The prevalence and consequences of nasal obstruction in untreated obstructive sleep apnea patients are not known. The study objectives were to investigate the frequency of subjective and objective nasal obstruction in untreated sleep apnea patients and the associations with sleep and quality of life. Patients in the Icelandic Sleep Apnea Cohort were subjected to a type 3 sleep study, answered questionnaires and had their nasal dimensions measured by acoustic rhinometry. In total, 810 patients participated (including 153 females), aged 54.5 ± 10.6 years [mean ± standard deviation (SD)] with an apnea/hypopnea index 44.7 ± 20.7 h -1 . Nocturnal nasal obstruction (greater than or equal to three times per week) was reported by 35% of the patients. These patients had smaller nasal dimensions measured by the minimum cross-sectional area within the smaller nasal valve (0.42 ± 0.17 versus 0.45 ± 0.16 cm 2 , P = 0.013), reported more daytime sleepiness (Epworth Sleepiness Scale score 12.5 ± 4.9 versus 10.8 ± 5.0; P < 0.001) and slightly lower mental quality of life than patients without nocturnal nasal obstruction. Nocturnal nasal obstruction is reported in one-third of the sleep apnea patients and they are more likely to suffer from daytime sleepiness and slightly reduced quality of life than other sleep apnea patients., (© 2017 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Study Objectives: A recent study of patients with moderate-severe obstructive sleep apnea (OSA) in Iceland identified three clinical clusters based on symptoms and comorbidities. We sought to verify this finding in a new cohort in Iceland and examine the generalizability of OSA clusters in an international ethnically diverse cohort., Methods: Using data on 972 patients with moderate-severe OSA (apnea-hypopnea index [AHI] ≥ 15 events per hour) recruited from the Sleep Apnea Global Interdisciplinary Consortium (SAGIC), we performed a latent class analysis of 18 self-reported symptom variables, hypertension, cardiovascular disease, and diabetes., Results: The original OSA clusters of disturbed sleep, minimally symptomatic, and excessively sleepy replicated among 215 SAGIC patients from Iceland. These clusters also generalized to 757 patients from five other countries. The three clusters had similar average AHI values in both Iceland and the international samples, suggesting clusters are not driven by OSA severity; differences in age, gender, and body mass index were also generally small. Within the international sample, the three original clusters were expanded to five optimal clusters: three were similar to those in Iceland (labeled disturbed sleep, minimal symptoms, and upper airway symptoms with sleepiness) and two were new, less symptomatic clusters (labeled upper airway symptoms dominant and sleepiness dominant). The five clusters showed differences in demographics and AHI, although all were middle-aged (44.6-54.5 years), obese (30.6-35.9 kg/m2), and had severe OSA (42.0-51.4 events per hour) on average., Conclusions: Results confirm and extend previously identified clinical clusters in OSA. These clusters provide an opportunity for a more personalized approach to the management of OSA.

Study Objectives: Distinct clinical phenotypes of obstructive sleep apnea (OSA) have been identified: Disturbed Sleep, Minimally Symptomatic, and Sleepy. Determining whether these phenotypes respond differently to standard treatment helps us to create a foundation for personalized therapies. We compared responses to positive airway pressure (PAP) therapy in these clinical OSA phenotypes., Methods: The study sample included 706 patients from the Icelandic Sleep Apnea Cohort with moderate-to-severe OSA who were prescribed PAP. Linear and logistic mixed models were used to compare 2-year changes in demographics, comorbid diseases, and sleep-related health issues within and across OSA clinical phenotypes. Relationships between changes in symptoms and PAP adherence were also examined., Results: Overall, effect sizes were moderate to large when comparing sleepiness, insomnia-related, and apneic symptom changes in the Sleepy group with changes in other two groups, especially those in the Minimally Symptomatic group. Within the Disturbed Sleep group, PAP users and nonusers demonstrated similar changes in insomnia-related symptoms. The Minimally Symptomatic group remained relatively asymptomatic, but reported significant decreases in daytime sleepiness and physical fatigue; PAP users generally had larger improvements. The Sleepy group had reductions in nearly all measured symptoms, including large reductions in drowsy driving; almost all of these improvements were greater among PAP users than nonusers., Conclusions: OSA treatment response patterns differed by initial clinical phenotype and PAP adherence. Individuals with insomnia-related symptoms may require additional targeted therapy for these complaints. These findings underscore the need for a personalized approach to management that recognizes patients with a range of OSA presentations.

This European guideline for the diagnosis and treatment of insomnia was developed by a task force of the European Sleep Research Society, with the aim of providing clinical recommendations for the management of adult patients with insomnia. The guideline is based on a systematic review of relevant meta-analyses published till June 2016. The target audience for this guideline includes all clinicians involved in the management of insomnia, and the target patient population includes adults with chronic insomnia disorder. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) system was used to grade the evidence and guide recommendations. The diagnostic procedure for insomnia, and its co-morbidities, should include a clinical interview consisting of a sleep history (sleep habits, sleep environment, work schedules, circadian factors), the use of sleep questionnaires and sleep diaries, questions about somatic and mental health, a physical examination and additional measures if indicated (i.e. blood tests, electrocardiogram, electroencephalogram; strong recommendation, moderate- to high-quality evidence). Polysomnography can be used to evaluate other sleep disorders if suspected (i.e. periodic limb movement disorder, sleep-related breathing disorders), in treatment-resistant insomnia, for professional at-risk populations and when substantial sleep state misperception is suspected (strong recommendation, high-quality evidence). Cognitive behavioural therapy for insomnia is recommended as the first-line treatment for chronic insomnia in adults of any age (strong recommendation, high-quality evidence). A pharmacological intervention can be offered if cognitive behavioural therapy for insomnia is not sufficiently effective or not available. Benzodiazepines, benzodiazepine receptor agonists and some antidepressants are effective in the short-term treatment of insomnia (≤4 weeks; weak recommendation, moderate-quality evidence). Antihistamines, antipsychotics, melatonin and phytotherapeutics are not recommended for insomnia treatment (strong to weak recommendations, low- to very-low-quality evidence). Light therapy and exercise need to be further evaluated to judge their usefulness in the treatment of insomnia (weak recommendation, low-quality evidence). Complementary and alternative treatments (e.g. homeopathy, acupuncture) are not recommended for insomnia treatment (weak recommendation, very-low-quality evidence)., (© 2017 European Sleep Research Society.)

Study Objectives: Debate persists as to whether obstructive sleep apnea (OSA) is an independent risk factor for atherosclerosis. The purpose of this study was to compare carotid intima-media thickness (IMT), an early sign of atherosclerosis, in obese and nonobese adults with OSA before and following positive airway pressure (PAP) treatment., Methods: A total of 206 adults newly diagnosed with OSA with an apnea-hypopnea index (AHI) of 15-75 events/hour and 53 controls with AHI <10 were studied. Waist circumference was used to classify participants as obese and nonobese. Bilateral common carotid artery B-mode ultrasound was performed at baseline to assess IMT, arterial diameter, arterial-wall mass, and circumferential wall stress. Measurements were repeated in 118 participants with OSA who completed a 4-month PAP treatment and had an average daily use over that period of ≥4 hours/day., Results: No significant differences in carotid IMT, diameter, or arterial-wall mass were present at baseline between participants with OSA and controls stratified by waist circumference, after adjusting for other cardiovascular risk factors. In participants with OSA, who had adequate PAP adherence over the 4-month treatment, carotid artery diameter significantly increased (mean change [95% confidence interval] = 0.13 [0.06, 0.20] mm; p = .0004), but no significant changes in carotid IMT, arterial-wall mass, and circumferential stress were observed in obese and nonobese participants., Conclusions: Regardless of obesity status, carotid IMT is not increased in adults with moderate to severe OSA versus controls and does not change following 4 months of PAP treatment., (© Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Introduction: Sleep length has been associated with obesity and various adverse health outcomes. The possible association of sleep length and respiratory symptoms has not been previously described. The aim of this study was to investigate the association between sleep length and respiratory symptoms and whether such an association existed independent of obesity., Methods: This is a multicentre, cross-sectional, population-based study performed in 23 centres in 10 different countries. Participants (n=5079, 52.3% males) were adults in the third follow-up of the European Community Respiratory Health Survey III. The mean±SD age was 54.2±7.1 (age range 39-67 years). Information was collected on general and respiratory health and sleep characteristics., Results: The mean reported nighttime sleep duration was 6.9±1.0 hours. Short sleepers (<6 hours per night) were n=387 (7.6%) and long sleepers (≥9 hours per night) were n=271 (4.3%). Short sleepers were significantly more likely to report all respiratory symptoms (wheezing, waking up with chest tightness, shortness of breath, coughing, phlegm and bronchitis) except asthma after adjusting for age, gender, body mass index (BMI), centre, marital status, exercise and smoking. Excluding BMI from the model covariates did not affect the results. Short sleep was related to 11 out of 16 respiratory and nasal symptoms among subjects with BMI ≥30 and 9 out of 16 symptoms among subjects with BMI <30. Much fewer symptoms were related to long sleep, both for subjects with BMI <30 and ≥30., Conclusions: Our results show that short sleep duration is associated with many common respiratory symptoms, and this relationship is independent of obesity., Competing Interests: Competing interests: None declared.

The objective of this study was to evaluate the determinants of long-term adherence to positive airway pressure treatment among patients with obstructive sleep apnea, with special emphasis on patients who stop positive airway pressure treatment within 1 year. This is a prospective long-term follow-up of subjects in the Icelandic Sleep Apnea Cohort who were diagnosed with obstructive sleep apnea between 2005 and 2009, and started on positive airway pressure treatment. In October 2014, positive airway pressure adherence was obtained by systematically evaluating available clinical files (n = 796; 644 males, 152 females) with moderate to severe obstructive sleep apnea (apnea-hypopnea index ≥15 events per h). The mean follow-up time was 6.7 ± 1.2 years. In total, 123 subjects (15.5%) returned their positive airway pressure device within the first year, 170 (21.4%) returned it later and 503 (63.2%) were still using positive airway pressure. The quitters within the first year had lower body mass index, milder obstructive sleep apnea, less sleepiness, and more often had symptoms of initial and late insomnia compared with long-term positive airway pressure users at baseline. Both initial and late insomnia were after adjustment still significantly associated with being an early quitter among subjects with body mass index <30 kg m -2 , but not among those with body mass index ≥30 kg m -2 . The prevalence of early quitters decreased significantly during the study period (2005-2009). Almost two-thirds of patients with moderate to severe obstructive sleep apnea are positive airway pressure users after 7 years. Obesity level, obstructive sleep apnea severity and daytime sleepiness are important determinants of long-term adherence. Symptoms of initial and late insomnia are associated with early quitting on positive airway pressure among non-obese subjects., (© 2016 European Sleep Research Society.)

Traditional techniques to assess respiratory disturbances during sleep allow the accurate diagnosis of moderate and severe cases of obstructive sleep apnea but have serious limitations in mild obstructive sleep apnea and cases with signs of obstructive breathing during sleep without apneas and hypopneas. This article describes advantages and limitations of available techniques to measure obstructive breathing during sleep by measuring flow limitation, respiratory effort, and snoring. Standardization of these techniques is crucial for moving the field further and understanding the pathophysiologic role of obstructive breathing itself, and not solely focusing on the associated outcomes of arousals and oxygen desaturations., (Copyright © 2016 Elsevier Inc. All rights reserved.)