Age related disparities in sleep apnea diagnosis using a wearable device: Implications of 4% vs. 3% hypopnea scoring criteria.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) diagnosis relies on the Apnea-Hypopnea Index (AHI), with discrepancies arising from the 3% and 4% desaturation criteria. This study investigates age-related variations in OSA severity classification, utilizing data from 1201 adult patients undergoing Home Sleep Apnea Testing (HSAT) with SleepImage Ring@. METHODS: The study employs Bland-Altman analysis to compare AHI values obtained with the 3% and 4% desaturation criteria. Age-stratified analysis explores discrepancies across different age groups. RESULTS: The analysis reveals a systematic bias favoring the 3% criterion, impacting the quantification of apnea events. Age-specific patterns demonstrate diminishing agreement between criteria with increasing age. CONCLUSION: This comprehensive study underscores the importance of standardized criteria in OSA diagnosis. The findings emphasize age-specific considerations and ethical concerns, providing crucial insights for optimizing patient care and advancing sleep medicine practices.

Multi-night home assessment of sleep structure in OSA with and without insomnia.

OBJECTIVE: To explore sleep structure in participants with obstructive sleep apnea (OSA) and comorbid insomnia (COMISA) and participants with OSA without insomnia (OSA-only) using both single-night polysomnography and multi-night wrist-worn photoplethysmography/accelerometry. METHODS: Multi-night 4-class sleep-staging was performed with a validated algorithm based on actigraphy and heart rate variability, in 67 COMISA (23 women, median age: 51 years) and 50 OSA-only (15 women, median age: 51) participants. Sleep statistics were compared using linear regression models and mixed-effects models. Multi-night variability was explored using a clustering approach and between- and within-participant analysis. RESULTS: Polysomnographic parameters showed no significant group differences. Multi-night measurements, during 13.4 ± 5.2 nights per subject, demonstrated a longer sleep onset latency and lower sleep efficiency for the COMISA group. Detailed analysis of wake parameters revealed longer mean durations of awakenings in COMISA, as well as higher numbers of awakenings lasting 5 min and longer (WKN≥5min) and longer wake after sleep onset containing only awakenings of 5 min or longer. Within-participant variance was significantly larger in COMISA for sleep onset latency, sleep efficiency, mean duration of awakenings and WKN≥5min. Unsupervised clustering uncovered three clusters; participants with consistently high values for at least one of the wake parameters, participants with consistently low values, and participants displaying higher variability. CONCLUSION: Patients with COMISA more often showed extended, and more variable periods of wakefulness. These observations were not discernible using single night polysomnography, highlighting the relevance of multi-night measurements to assess characteristics indicative for insomnia.

Erectile dysfunction in patient with obstructive sleep apnea: effects of continuous positive airway pressure.

BACKGROUND: Obstructive sleep apnea (OSA) is linked to various health complications, including erectile dysfunction (ED), which is more prevalent in individuals with OSA. This study explored ED in Korean OSA patients and assessed the impact of continuous positive airway pressure (CPAP) therapy on ED. METHODS: A total of 87 male patients with OSA from four different sleep centers underwent physical measurements and completed sleep and mental health (MH) questionnaires, including the Korean version of the International index of erectile function (IIEF), before and three months after initiating CPAP therapy. RESULTS: After three months of CPAP therapy, the patients demonstrated a significant improvement in ED as measured on the IIEF. However, the study found no significant correlation between the duration of CPAP use and the improvement in IIEF score. It did identify the SF36 quality of life assessment as a significant factor influencing ED improvement after CPAP. CONCLUSIONS: ED is a prevalent issue that escalates with age and is associated with OSA. CPAP therapy has shown potential in alleviating ED symptoms, particularly in those with underlying psychological conditions, although further research is required to confirm these findings and understand the underlying mechanisms.

Instrumental assessment of sleep bruxism: A systematic review and meta-analysis.

This systematic review and meta-analysis (MA) aimed to evaluate the diagnostic validity of portable electromyography (EMG) diagnostic devices compared to the reference standard method polysomnography (PSG) in assessing sleep bruxism. This systematic review was completed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement and was registered with PROSPERO prior to the accomplishment of the main search. Ten clinical studies on humans, assessing the diagnostic accuracy of portable instrumental approaches with respect to PSG, were included in the review. Methodological shortcomings were identified by QUADAS-2 quality assessment. The certainty of the evidence analysis was established by different levels of evidence according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. A meta-analysis of diagnostic test accuracy was performed with multiple thresholds per study applying a two-stage random effects model, using the thresholds offered by the studies and based on the number of EMG bruxism events per hour presented by the participants. Five studies were included. The MA indicated that portable EMG diagnostic devices showed a very good diagnostic capacity, although a high variability is evident in the studies with some outliers. Very low quality of evidence due to high risk of bias and high heterogeneity among included studies suggests that portable devices have shown high sensitivity and specificity when diagnosing sleep bruxism (SB) compared to polysomnography. The tests performed in the MA found an estimated optimal cut-off point of 7 events/hour of SB with acceptably high sensitivity and specificity for the EMG portable devices.

The OSA patient journey: pathways for diagnosis and treatment among commercially insured individuals in the United States.

STUDY OBJECTIVES: The aims of this study were to characterize obstructive sleep apnea (OSA) care pathways among commercially insured individuals in the United States and to investigate between-groups differences in population, care delivery, and economic aspects. METHODS: We identified adults with OSA using a large, national administrative claims database (January 1, 2016-February 28, 2020). Inclusion criteria included a diagnostic sleep test on or within ≤ 12 months of OSA diagnosis (index date) and 12 months of continuous enrollment before and after the index date. Exclusion criteria included prior OSA treatment or central sleep apnea. OSA care pathways were identified using sleep testing health care procedural health care common procedure coding system/current procedural terminology codes then selected for analysis if they were experienced by ≥ 3% of the population and assessed for baseline demographic/clinical characteristics that were also used for model adjustment. Primary outcome was positive airway pressure initiation rate; secondary outcomes were time from first sleep test to initiation of positive airway pressure, sleep test costs, and health care resource utilization. Associations between pathway type and time to treatment initiation were assessed using generalized linear models. RESULTS: Of 86,827 adults with OSA, 92.1% received care in 1 of 5 care pathways that met criteria: home sleep apnea testing (HSAT; 30.8%), polysomnography (PSG; 23.6%), PSG-Titration (19.8%), Split-night (14.8%), and HSAT-Titration (3.2%). Pathways had significantly different demographic and clinical characteristics. HSAT-Titration had the highest positive airway pressure initiation rate (84.6%) and PSG the lowest (34.4%). After adjustments, time to treatment initiation was significantly associated with pathway (P < .0001); Split-night had shortest duration (median, 28 days), followed by HSAT (36), PSG (37), PSG-Titration (58), and HSAT-Titration (75). HSAT had the lowest sleep test costs and health care resource utilization. CONCLUSIONS: Distinct OSA care pathways exist and are associated with differences in population, care delivery, and economic aspects. CITATION: Wickwire EM, Zhang X, Munson SH, et al. The OSA patient journey: pathways for diagnosis and treatment among commercially insured individuals in the United States. J Clin Sleep Med. 2024;20(4):505-514.

Selecting a sleep tracker from EEG-based, iteratively improved, low-cost multisensor, and actigraphy-only devices.

AIMS: Evaluate the performance of 6 wearable sleep trackers across 4 classes (EEG-based headband, research-grade actigraphy, iteratively improved consumer tracker, low-cost consumer tracker). FOCUS TECHNOLOGY: Dreem 3 headband, Actigraph GT9X, Oura Ring Gen3, Fitbit Sense, Xiaomi Mi Band 7, Axtro Fit3. REFERENCE TECHNOLOGY: In-lab polysomnography with 3-reader, consensus sleep scoring. SAMPLE: Sixty participants (26 males) across 3 age groups (18-30, 31-50, and 51-70years). DESIGN: Overnight in a sleep laboratory from habitual sleep time to wake time. CORE ANALYTICS: Discrepancy and epoch-by-epoch analyses for sleep/wake (2-stage) and sleep-stage (4-stage; wake/light/deep/rapid eye movement) classification (devices vs. polysomnography). CORE OUTCOMES: EEG-based Dreem performed the best (2-stage kappa=0.76, 4-stage kappa=0.76-0.86) with the lowest total sleep time, sleep efficiency, sleep onset latency, and wake after sleep onset discrepancies vs. polysomnography. This was followed by the iteratively improved consumer trackers: Oura (2-stage kappa=0.64, 4-stage kappa=0.55-0.70) and Fitbit (2-stage kappa=0.58, 4-stage kappa=0.45-0.60) which had comparable total sleep time and sleep efficiency discrepancies that outperformed accelerometry-only Actigraph (2-stage kappa=0.47). The low-cost consumer trackers had poorest overall performance (2-stage kappa<0.31, 4-stage kappa<0.33). IMPORTANT ADDITIONAL OUTCOMES: Proportional biases were driven by nights with poorer sleep (longer sleep onset latencies and/or wake after sleep onset). CORE CONCLUSION: EEG-based Dreem is recommended when evaluating poor quality sleep or when highest accuracy sleep-staging is required. Iteratively improved non-EEG sleep trackers (Oura, Fitbit) balance classification accuracy with well-tolerated, and economic deployment at-scale, and are recommended for studies involving mostly healthy sleepers. The low-cost trackers, can log time in bed but are not recommended for research use.

Preliminary assessment of portable sleep monitoring for diagnosis of obstructive sleep apnea in children.

OBJECTIVE: By observing the differences in sleep parameters between portable sleep monitoring (PM) and polysomnography (PSG) in children, we aimed to investigate the diagnostic value and feasibility of PM in children with suspected obstructive sleep apnea (OSA). STUDY DESIGN: This prospective study enrolled consecutive children (aged 3-14 years) with suspected OSA in Shenzhen Children's Hospital. They had PSG and PM in the sleep laboratory. Clinical parameters of the two sleep monitoring methods were compared. RESULTS: A total of 58 children participated. They were classified into two groups according to age: 28 children aged 3 to 5 years and 30 children aged 6 to 14 years. No significant differences were observed in apnea-hypopnea index (AHI), lowest oxygen saturation (LSaO2), and mean oxygen saturation (MSaO2) between PM and PSG, but the sleep efficiency with PM was significantly higher (3-5 years age: 92.2 ± 11.3% vs 85.2 ± 14.3%, 6-14 years age: 93.2 ± 14.5% vs 84.8 ± 16.3%, both P < 0.05) than the sleep efficiency with PSG. Pearson correlation analysis indicated a strong correlation between AHI, LSaO2, MSaO2, and sleep efficiency measured by PSG and PM. Receiver operating characteristic curve (ROC) analysis showed that PM was a reliable diagnostic tool for OSA. PM has high sensitivity (3-5 years age: 95.8%, 6-14 years age: 96.3%) and low specificity (3-5 years age: 25.0%, 6-14 years age: 33.3%) for OSA in children. Thus, there is a low rate of missed diagnoses, but there is some inaccuracy in excluding children who do not have OSA. CONCLUSION: The results showed that PM has a good correlation with the various parameters of PSG. PM may be a reliable tool for diagnosing moderate and severe OSA in children, especially those who cannot cooperate with PSG or who have limited access to PSG.

Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement.

STUDY OBJECTIVES: To efficiently improve the scoring competency of scorers with varying levels of experience across regions in Taiwan, we developed a training program with a cloud-based polysomnography scoring platform to evaluate and improve interscorer agreement. METHODS: A total of 70 scorers from 34 sleep centers in Taiwan (job tenure: 0.5-39.0 years) completed a scoring test. All scorers scored a 742-epoch (30 s/epoch) overnight polysomnography recording of a patient with a moderate apnea-hypopnea index. Subsequently, 8 scoring experts delivered 8 interactive online lectures (each lasting 30 minutes). The training program included identifying scoring weaknesses, highlighting the latest scoring rules, and providing physicians' perspectives. Afterward, the scorers completed the second scoring test on the same participant. Changes in agreement from the first to second scoring test were identified. Sleep staging, sleep parameters, and respiratory events were considered for evaluating scoring agreement. RESULTS: The scorers' agreement in overall sleep stage scoring significantly increased from 74.6 to 82.3% (median score). The proportion of scorers with an agreement of ≥ 80% increased from 20.0% (14/70) to 58.6% (41/70) after the online training program. In addition, the scorers' agreement in overall respiratory-event scoring increased to 88.8% (median score) after training. The scorers with a job tenure of 2.0-4.9 years exhibited the highest level of improvement in overall sleep staging (their median agreement increased from 72.8 to 84.9%; P < .001). CONCLUSIONS: Our interactive online training program efficiently targeted the scorers' scoring weaknesses identified in the first scoring test, leading to substantial improvements in scoring proficiency. CITATION: Liao Y-S, Wu M-C, Li C-X, Lin W-K, Lin C-Y, Liang S-F. Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement. J Clin Sleep Med. 2024;20(2):271-278.

State of the science and recommendations for using wearable technology in sleep and circadian research.

Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.

Neighborhood determinants of sleep and the moderating role of cultural factors among native adolescents.

OBJECTIVE: This study examined the association between neighborhood social environment and sleep among urban American Indian and Alaska Native (AI/AN) adolescents as well as the moderating role of cultural factors in this association. METHOD: The analytic sample included 133 urban AI/AN adolescents (age 12-16, 57.1% female, Mage = 14.03, SDage = 1.35). Perceived neighborhood social environment included safety and cohesion. Cultural factors included AI/AN cultural identification and historical loss. Sleep duration, efficiency, and wake after sleep onset (WASO) were measured via actigraphy. Sleep disturbance was measured via a questionnaire. RESULTS: Greater neighborhood safety was significantly associated with lower sleep disturbance (b = -2.17, SE = 0.8, p = .008), higher sleep efficiency (b = 1.75, SE = 0.64, p = .006), and lower WASO (b = -8.60, SE = 3.34, p = .01). Neighborhood cohesion was not associated with any sleep outcomes. Cultural factors moderated the association between neighborhood social environment and sleep outcomes (p < .05). Specifically, both neighborhood safety and cohesion were associated with lower sleep disturbance, only among individuals reporting higher levels of AI/AN cultural identification. Further, neighborhood safety was associated with greater sleep efficiency and lower WASO (i.e., better sleep) only among adolescents with higher contemplation of historical loss. CONCLUSIONS: Findings highlight the importance of considering cultural factors in addressing sleep and health disparities. AI/AN cultural identification and a sense of historical loss may be important targets for identifying adolescents who might benefit the most from policies and interventions focused on improving the social environment in order to improve sleep and other health outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Enhancing OSA Assessment with Explainable AI.

Explainable Artificial Intelligence (xAI) is a rapidly growing field that focuses on making deep learning models interpretable and understandable to human decision-makers. In this study, we introduce xAAEnet, a novel xAI model applied to the assessment of Obstructive Sleep Apnea (OSA) severity. OSA is a prevalent sleep disorder that can lead to numerous medical conditions and is currently assessed using the Apnea-Hypopnea Index (AHI). However, AHI has been criticized for its inability to accurately estimate the effect of OSAs on related medical conditions. To address this issue, we propose a human-centric xAI approach that emphasizes similarity between apneic events as a whole and reduces subjectivity in diagnosis by examining how the model makes its decisions. Our model was trained and tested on a dataset of 60 patients' Polysomnographic (PSG) recordings. Our results demonstrate that the proposed model, xAAEnet, outperforms models with traditional architectures such as convolutional regressor, autoencoder (AE), and variational autoencoder (VAE). This study highlights the potential of xAI in providing an objective OSA severity scoring method.Clinical relevance- This study provides an objective OSA severity scoring technique which could improve the management of apneic patients in clinical practice.

Advancements in Wearable EEG Technology for Improved Home-Based Sleep Monitoring and Assessment: A Review.

Sleep is a fundamental aspect of daily life, profoundly impacting mental and emotional well-being. Optimal sleep quality is vital for overall health and quality of life, yet many individuals struggle with sleep-related difficulties. In the past, polysomnography (PSG) has served as the gold standard for assessing sleep, but its bulky nature, cost, and the need for expertise has made it cumbersome for widespread use. By recognizing the need for a more accessible and user-friendly approach, wearable home monitoring systems have emerged. EEG technology plays a pivotal role in sleep monitoring, as it captures crucial brain activity data during sleep and serves as a primary indicator of sleep stages and disorders. This review provides an overview of the most recent advancements in wearable sleep monitoring leveraging EEG technology. We summarize the latest EEG devices and systems available in the scientific literature, highlighting their design, form factors, materials, and methods of sleep assessment. By exploring these developments, we aim to offer insights into cutting-edge technologies, shedding light on wearable EEG sensors for advanced at-home sleep monitoring and assessment. This comprehensive review contributes to a broader perspective on enhancing sleep quality and overall health using wearable EEG sensors.

Predicting Visit Cost of Obstructive Sleep Apnea Using Electronic Healthcare Records With Transformer.

BACKGROUND: Obstructive sleep apnea (OSA) is growing increasingly prevalent in many countries as obesity rises. Sufficient, effective treatment of OSA entails high social and financial costs for healthcare. OBJECTIVE: For treatment purposes, predicting OSA patients' visit expenses for the coming year is crucial. Reliable estimates enable healthcare decision-makers to perform careful fiscal management and budget well for effective distribution of resources to hospitals. The challenges created by scarcity of high-quality patient data are exacerbated by the fact that just a third of those data from OSA patients can be used to train analytics models: only OSA patients with more than 365 days of follow-up are relevant for predicting a year's expenditures. METHODS AND PROCEDURES: The authors propose a translational engineering method applying two Transformer models, one for augmenting the input via data from shorter visit histories and the other predicting the costs by considering both the material thus enriched and cases with more than a year's follow-up. This method effectively adapts state-of-the-art Transformer models to create practical cost prediction solutions that can be implemented in OSA management, potentially enhancing patient care and resource allocation. RESULTS: The two-model solution permits putting the limited body of OSA patient data to productive use. Relative to a single-Transformer solution using only a third of the high-quality patient data, the solution with two models improved the prediction performance's [Formula: see text] from 88.8% to 97.5%. Even using baseline models with the model-augmented data improved the [Formula: see text] considerably, from 61.6% to 81.9%. CONCLUSION: The proposed method makes prediction with the most of the available high-quality data by carefully exploiting details, which are not directly relevant for answering the question of the next year's likely expenditure. Clinical and Translational Impact Statement: Public Health- Lack of high-quality source data hinders data-driven analytics-based research in healthcare. The paper presents a method that couples data augmentation and prediction in cases of scant healthcare data.

Sleep in children from northeastern Brazil with congenital Zika syndrome: assessment using polysomnography.

STUDY OBJECTIVES: We performed this study to describe the characteristics of sleep in children with congenital Zika syndrome through polysomnographic assessment. METHODS: Polysomnography with neurological setup and capnography was performed. Respiratory events were scored according to American Academy of Sleep Medicine criteria. Children were classified based on neuroclinical examination as having corticospinal plus neuromuscular abnormalities or exclusively corticospinal abnormalities. Neuroradiological classification was based on imaging exams, with children classed as having supratentorial plus infratentorial abnormalities or exclusively supratentorial abnormalities. RESULTS: Of 65 children diagnosed with congenital Zika syndrome, sleep apnea was present in 23 children (35.4%), desaturation in 26 (40%), and snoring in 13 (20%). The most prevalent apnea type was central in 15 children (65.2%), followed by obstructive apnea in 5 (21.7%) and mixed type in 3 (13%). The average of the lowest saturation recorded was slightly below normal (89.1 ± 4.9%) and the mean partial pressure of end-tidal carbon dioxide value was normal. Periodic leg movements were present in 48 of 65 children. Lower ferritin levels were observed in 84.6% of children. Palatine and pharyngeal tonsils (adenoids) were small in most children and not associated with the presence of obstructive apnea. Ventriculomegaly and subcortical and nucleus calcification were the most frequent neuroimaging findings. Supratentorial and infratentorial anomalies were present in 26.7% (16 of 60) and exclusively supratentorial changes in 73.3% (44 of 60). In the neuroclinical classification, isolated corticospinal changes were more frequent and the mean peak in capnography was lower in this group. There was no difference regarding the presence of apnea for children in the neuroclinical and neuroradiological classification groups. CONCLUSIONS: Sleep disorders were frequent in children with congenital Zika syndrome, with central sleep apnea being the main finding. CITATION: Brandão Marquis V, de Oliveira Melo A, Pradella-Hallinan M, et al. Sleep in children from northeastern Brazil with congenital Zika syndrome: assessment using polysomnography. J Clin Sleep Med. 2023;19(10):1759-1767.

Sleep assessment in adults with Down syndrome: correlation between functionality and polysomnographic findings.

BACKGROUND: Sleep disorders have a negative impact on health, being associated with neurocognitive problems, cardiovascular diseases and obesity, influencing children's development and learning. OBJECTIVE: To assess the sleep pattern of people with Down syndrome (DS) and correlate changes with functionality and behavior. METHODS: A cross-sectional study was conducted to evaluate the sleep pattern in adults with DS > 18 years old. Twenty-two participants were assessed using the Pittsburgh Sleep Quality Index, the Functional Independence Measure and the Strengths and Difficulties Questionnaire, and the 11 who presented indications of disorders by the screening questionnaires were referred to polysomnography. Statistical tests were performed using a significance level of 5%, including sample normality tests and correlation tests (sleep and functionality). RESULTS: Impairment in sleep architecture was found due to an increase in the rate of awakenings in 100% of the participants, a decrease in the number of slow waves, and a high prevalence of sleep disordered breathing (SDB), with higher averages in the Apnea and Hypopnea Index (AHI) in the group. There was a negative correlation between sleep quality and global functionality (p = 0.011) and the motor (p = 0.074), cognitive (p = 0.010), and personal care (p = 0.072) dimensions in the group. Global and hyperactivity behavior changes were related to worse sleep quality (p = 0.072; p = 0.015, respectively). CONCLUSION: There is an impairment in the sleep quality of adults with DS, with an increase in the rate of awakenings, a decrease in the number of slow waves, and a high prevalence of SDB affecting this population in the functional and behavioral aspects.

ANTECEDENTES: Os distúrbios de sono têm impacto negativo na saúde, estando associados a problemas neurocognitivos, doenças cardiovasculares e obesidade, influenciando no desenvolvimento e aprendizado. OBJETIVO: Avaliar o padrão de sono de pessoas com síndrome de Down (SD) e correlacionar as alterações com a funcionalidade e comportamento. MéTODOS: Foi realizado um estudo transversal para avaliação do padrão de sono em adultos com SD > 18 anos. Foram avaliados 22 participantes, através do Índice de Qualidade do Sono de Pittsburgh, da Medida de Independência Funcional e do Questionaário de Capacidades e Dificuldades. Os 11 participantes que apresentaram indicativos de presença de distúrbios pelos questionários de triagem foram indicados a polissonografia. Os testes estatísticos foram realizados com nível de significância de 5%, incluindo testes de normalidade e testes de correlação (sono e funcionalidade). RESULTADOS: Foi encontrado prejuízo na arquitetura de sono pelo aumento do índice de despertares em 100% dos participantes, diminuição na quantidade de ondas lentas, e alta prevalência de distúrbio respiratório do sono (DRS), com maiores médias nos Índices de Apneia e Hipopneia (IAH). Houve correlação negativa entre a qualidade de sono e a funcionalidade global (p = 0,011), e as dimensões motora (p = 0,074), cognitiva (p = 0,010) e cuidados pessoais (p = 0,072). As alterações de comportamento global e comportamentos de hiperatividade foram relacionados à pior qualidade do sono (p = 0,072; p = 0,015, respectivamente). CONCLUSãO: Existe prejuízo na qualidade de sono de adultos com SD, com aumento de índice de despertares, diminuição na quantidade de ondas lentas, e alta prevalência de DRS, afetando essa população nos aspectos funcionais e comportamentais.

At-home wireless sleep monitoring patches for the clinical assessment of sleep quality and sleep apnea.

Although many people suffer from sleep disorders, most are undiagnosed, leading to impairments in health. The existing polysomnography method is not easily accessible; it's costly, burdensome to patients, and requires specialized facilities and personnel. Here, we report an at-home portable system that includes wireless sleep sensors and wearable electronics with embedded machine learning. We also show its application for assessing sleep quality and detecting sleep apnea with multiple patients. Unlike the conventional system using numerous bulky sensors, the soft, all-integrated wearable platform offers natural sleep wherever the user prefers. In a clinical study, the face-mounted patches that detect brain, eye, and muscle signals show comparable performance with polysomnography. When comparing healthy controls to sleep apnea patients, the wearable system can detect obstructive sleep apnea with an accuracy of 88.5%. Furthermore, deep learning offers automated sleep scoring, demonstrating portability, and point-of-care usability. At-home wearable electronics could ensure a promising future supporting portable sleep monitoring and home healthcare.

Evaluation of a Structured Screening Assessment to Detect Isolated Rapid Eye Movement Sleep Behavior Disorder.

BACKGROUND: Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) cohorts have provided insights into the earliest neurodegenerative processes in α-synucleinopathies. Even though polysomnography (PSG) remains the gold standard for diagnosis, an accurate questionnaire-based algorithm to identify eligible subjects could facilitate efficient recruitment in research. OBJECTIVE: This study aimed to optimize the identification of subjects with iRBD from the general population. METHODS: Between June 2020 and July 2021, we placed newspaper advertisements, including the single-question screen for RBD (RBD1Q). Participants' evaluations included a structured telephone screening consisting of the RBD screening questionnaire (RBDSQ) and additional sleep-related questionnaires. We examined anamnestic information predicting PSG-proven iRBD using logistic regressions and receiver operating characteristic curves. RESULTS: Five hundred forty-three participants answered the advertisements, and 185 subjects fulfilling inclusion and exclusion criteria were screened. Of these, 124 received PSG after expert selection, and 78 (62.9%) were diagnosed with iRBD. Selected items of the RBDSQ, the Pittsburgh Sleep Quality Index, the STOP-Bang questionnaire, and age predicted iRBD with high accuracy in a multiple logistic regression model (area under the curve >80%). When comparing the algorithm to the sleep expert decision, 77 instead of 124 polysomnographies (62.1%) would have been carried out, and 63 (80.8%) iRBD patients would have been identified; 32 of 46 (69.6%) unnecessary PSG examinations could have been avoided. CONCLUSIONS: Our proposed algorithm displayed high diagnostic accuracy for PSG-proven iRBD cost-effectively and may be a convenient tool for research and clinical settings. External validation sets are warranted to prove reliability. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Beyond Polysomnography: Clinical Assessment of Pediatric Sleep Health and Sleep Problems.

This chapter reviews the Peds B-SATED model of pediatric sleep health and common pediatric sleep problems. Aspects of pediatric sleep health and sleep problems are considered across development, from infants through adolescents. Finally, information about clinical screening in both primary and specialty care is discussed, and subjective sleep questionnaires are reviewed.

Assessment of Muscular Weakness in Severe Sleep Apnea Patients: A Prospective Study.

OBJECTIVE: There are no official diagnostic tools to evaluate the weakness of the genioglossus muscle. We have developed a protocol for muscular assessment in patients with severe obstructive sleep apnea-hypopnea syndrome (OSAHS) and evaluated its effectiveness. STUDY DESIGN: Case and controls prospective study. SETTING: Sleep Unit Hospital Quironsalud Marbella (Spain). METHODS: Twenty-nine cases and 20 controls were recruited. Patients were examined by a phonoaudiologist that performed biometric measurements and the Orofacial Myofunctional Evaluation With Scores (OMES), Friedman, and Epworth Sleepiness Scale (ESS). In addition, upper airway muscle strength measures were performed using the Iowa Oral Performance Instrument (IOPI) and Tongue Digital Spoon (TDS). RESULTS: The final cohort consisted of 49 subjects, including 29 cases and 20 controls. According to the univariate and multivariate logistic regression analyses, ESS, OMES protocol, IOPI score, and TDS were associated with severe OSAHS. Multivariate regression revealed an IOPI score below 48 kps with an adjusted odds ratio (OR) of 9.96 (95% confidence interval [CI] 2.5-39.1, p = .001), and a 0.72 specificity (Spe), a 0.79 sensitivity (Sens), and a 0.82 area under the curve (AUC). Similarly, an OMES score lower than 200 had an adjusted risk ratio of 4.02 (95% CI 2-7, p < .001), 1 Spe, 0.79 Sens, and 0.98 AUC; and finally, TDS scores lower than 201 g/cm2 showed an adjusted OR of 27 (95% CI 4.74-153.6, p = .0001), 0.66 Spe, a 0.93 Sens, and a 0.86 AUC. CONCLUSION: Our findings suggest that severe OSAHS patients present different muscle patterns than controls.