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Deutsche Medizinische Wochenschrift... Jan 2016Obstructive sleep apnea (OSA) is a clinically significant condition associated with an increase in cardiovascular risk, daytime sleepiness and in risk of accidents.... (Review)
Review
Obstructive sleep apnea (OSA) is a clinically significant condition associated with an increase in cardiovascular risk, daytime sleepiness and in risk of accidents. Diagnosis usually relies on a detailed anamnesis and an ambulatory nocturnal polygraphy. Suspecting the presence of OSA or a persisting unclear daytime sleepiness in need of treatment further polysomnographic diagnosis should be performed in a specialized sleep center. Cardiorespiratory polysomnography is the diagnostic gold standard in differentiating sleep-related breathing and movement disorders.
Topics: Diagnosis, Differential; Diagnostic Techniques, Cardiovascular; Diagnostic Techniques, Respiratory System; Humans; Polysomnography; Sleep Apnea, Obstructive; Sleep Medicine Specialty
PubMed: 26710202
DOI: 10.1055/s-0041-106846 -
Annual International Conference of the... Jul 2022Sleep state classification is essential for managing and comprehending sleep patterns, and it is usually the first step in identifying sleep disorders. Polysomnography...
Sleep state classification is essential for managing and comprehending sleep patterns, and it is usually the first step in identifying sleep disorders. Polysomnography (PSG), the gold standard, is intrusive and inconvenient for regular/long-term sleep monitoring. Many sleep-monitoring techniques have recently seen a resurgence as a result of the rise of neural networks and advanced computing. Ballistocardiography (BCG) is an example of such a technique, in which vitals are monitored in a contactless and unobtrusive manner by measuring the body's reaction to cardiac ejection forces. A Multi-Headed Deep Neural Network is proposed in this study to accurately classify sleep-wake state and predict sleep-wake time using BCG sensors. This method achieves a 95.5% sleep-wake classification score. Two studies were conducted in a controlled and uncontrolled environment to assess the accuracy of sleep-awake time prediction. Sleep-awake time prediction achieved an accuracy score of 94.16% in a controlled environment on 115 subjects and 94.90% in an uncontrolled environment on 350 subjects. The high accuracy and contactless nature make this proposed system a convenient method for long-term monitoring of sleep states, and it may also aid in identifying sleep stages and other sleep-related disorders. Clinical Relevance- Current sleep-wake state classification methods, such as actigraphy and polysomnography, necessitate patient contact and a high level of patient compliance. The proposed BCG method was found to be comparable to the gold standard PSG and most wearable actigraphy techniques, and also represents an effective method of contactless sleep monitoring. As a result, clinicians can use it to easily screen for sleep disorders such as dyssomnia and sleep apnea, even from the comfort of one's own home.
Topics: Humans; Ballistocardiography; Deep Learning; Polysomnography; Sleep; Sleep Wake Disorders
PubMed: 36086100
DOI: 10.1109/EMBC48229.2022.9871831 -
Advances in Experimental Medicine and... 2022Measurement methods with graded complexity for use in the lab as well as for home sleep testing (HST) are available for the diagnosis of sleep apnea, and there are...
Measurement methods with graded complexity for use in the lab as well as for home sleep testing (HST) are available for the diagnosis of sleep apnea, and there are different classification systems in existence. Simplified HST measurements, which record fewer parameters than traditional four- to six-channel devices, can indicate sleep apnea and can be used as screening tool in high-prevalence patient groups. Peripheral arterial tonometry (PAT) is a technique which can be suitable for the diagnosis of sleep apnea in certain cases. Different measurement methods are used, which has an influence on the significance of the results. New minimal-contact and non-contact technologies of recording and analysis of surrogate parameters are under development. If they are validated by clinical studies, it will be possible to detect sleep apnea in need of treatment more effectively. In addition, this could become a solution to monitor the effectiveness of such treatment.
Topics: Humans; Manometry; Polysomnography; Sleep; Sleep Apnea Syndromes; Sleep Apnea, Obstructive
PubMed: 36217083
DOI: 10.1007/978-3-031-06413-5_9 -
Indoor Air May 2022To date, although many studies had focused on the impact of environmental factors on sleep, how to choose the proper assessment method for objective sleep quality was... (Review)
Review
To date, although many studies had focused on the impact of environmental factors on sleep, how to choose the proper assessment method for objective sleep quality was often ignored, especially for healthy subjects in bedroom environment. In order to provide methodological guidance for future research, this paper reviewed the assessments of objective sleep quality applied in environmental researches, compared them from the perspective of accuracy and interference, and statistically analyzed the impact of experimental type and subjects' information on method selection. The review results showed that, in contrast to polysomnography (PSG), the accuracy of actigraphy (ACT), respiratory monitoring-oxygen saturation monitoring (RM-OSM), and electrocardiograph (ECG) could reach up to 97%, 80.38%, and 79.95%, respectively. In terms of sleep staging, PSG and ECG performed the best, ACT the second, and RM-OSM the worst; as compared to single methods, mix methods were more accurate and better at sleep staging. PSG interfered with sleep a great deal, while ECG and ACT could be non-contact, and thus, the least interference with sleep was present. The type of experiment significantly influenced the choice of assessment method (p < 0.001), 85.3% of researchers chose PSG in laboratory study while 82.5% ACT in field study; moreover, PSG was often used in a relatively small number of young subjects, while ACT had a wide applicable population. In general, researchers need to pay more attention at selection of assessments in future studies, and this review can be used as a reliable reference for experimental design.
Topics: Actigraphy; Air Pollution, Indoor; Humans; Polysomnography; Sleep; Sleep Stages
PubMed: 35622713
DOI: 10.1111/ina.13034 -
Journal of Sleep Research Aug 2021The aim of the study was to assess the scorability of the signals of four poly(somno)graphy devices and transcutaneous carbon dioxide tracings (PtcCO ) of one device in...
The aim of the study was to assess the scorability of the signals of four poly(somno)graphy devices and transcutaneous carbon dioxide tracings (PtcCO ) of one device in children. The presence (0%, < 25%, 25%-50%, 50%-75%, 75%-99%, 100% of recording time) and quality (bad, average, good) of the signal of each sensor were analysed. During a 5-month period, 364 poly(somno)graphies were performed in 12 different hospital units. Forty-one children had poor/bad cooperation, and 13 severe behaviour disorders. Seventy-one and 293 poly(somno)graphies were performed in children aged ≤ 2 and > 2 years, respectively; nine poly(somno)graphies failed. For the four poly(somno)graphy devices, the signal was present during 99% of recording time for the electroencephalogram, 99% for thoracic belt, 97% for abdominal belt, 97% for body position, 95% for the microphone, 92% for pulse oximetry, 87% for tracheal sound, 71% for oronasal thermistor, 52% (41% for ≤ 2 years, 55% for > 2 years old) for nasal pressure and 86% for PtcCO . The signal was of good quality in 98% of poly(somno)graphies for body position, 96% for microphone, 96% for thoracic belt, 95% for pulse oximetry, 91% for abdominal belt, 91% for tracheal sound, 82% for oronasal thermistor, 78% for electroencephalogram, 73% for nasal pressure and 46% of PtcCO recordings. The scorability was comparable between devices. Nasal pressure and oronasal thermistor had the lowest scorability, especially in children aged ≤ 2 years. This underlines the necessity of the development or improvement of alternative, ideally face-free, sensors, or miniaturized devices adapted for infants and children.
Topics: Adolescent; Carbon Dioxide; Child; Child, Preschool; Electroencephalography; Humans; Infant; Oximetry; Polysomnography
PubMed: 33675114
DOI: 10.1111/jsr.13241 -
Otolaryngologic Clinics of North America Jun 2024Obstructive sleep apnea (OSA) is associated with long-term cardiovascular and respiratory comorbidities and increased burden on the health-care system. Early and... (Review)
Review
Obstructive sleep apnea (OSA) is associated with long-term cardiovascular and respiratory comorbidities and increased burden on the health-care system. Early and accurate diagnosis is essential to reduce physical and financial implications of the disease. Polysomnography uses neurophysiologic channels as well as basic respiratory and sleep parameters to best estimate the presence and/or severity of OSA. Although home sleep testing may have the potential for more variable results, it is a viable alternative to increase access to diagnosis of OSA and facilitate initiation of positive airway pressure.
Topics: Humans; Polysomnography; Sleep Apnea, Obstructive; Continuous Positive Airway Pressure
PubMed: 38042667
DOI: 10.1016/j.otc.2023.11.003 -
Sleep Medicine Reviews Feb 2023Sleepiness involves many dimensions that require investigation. Since sleepiness is often defined operationally, we exhaustively inventoried all the assessment tools... (Review)
Review
Sleepiness involves many dimensions that require investigation. Since sleepiness is often defined operationally, we exhaustively inventoried all the assessment tools designed to measure it in an umbrella review, without any preconceptions, i.e. a review of reviews. We included all reviews and systematic reviews related to sleepiness assessment tools published up to March 2021. Three investigators independently assessed the eligibility of studies for inclusion and identified 36 relevant reviews. In total, 99 tools were identified and classified into 8 categories. We classified them depending on their category, their publication year and the number of mentions in the 36 included reviews. The 6 most frequently cited were the Epworth sleepiness scale, the multiple sleep latency test, the maintenance of wakefulness test, the Stanford sleepiness scale, the Karolinska sleepiness scale, and the psychomotor vigilance task. Despite the limitation that we may have missed some recently developed tools, this historical perspective on sleepiness measurement is a first step toward a better delineation of the different dimensions underlying the constructs of sleepiness, and will serve as a basis for further discussion in the clinical and research sleep community.
Topics: Adult; Humans; Wakefulness; Disorders of Excessive Somnolence; Sleepiness; Sleep; Polysomnography
PubMed: 36455433
DOI: 10.1016/j.smrv.2022.101718 -
Journal of Medical Internet Research Jul 2023Digital clinical tools are a new technology that can be used in the screening or diagnosis of obstructive sleep apnea (OSA), notwithstanding the crucial role of... (Review)
Review
BACKGROUND
Digital clinical tools are a new technology that can be used in the screening or diagnosis of obstructive sleep apnea (OSA), notwithstanding the crucial role of polysomnography, the gold standard.
OBJECTIVE
This study aimed to identify, gather, and analyze the most accurate digital tools and smartphone-based health platforms used for OSA screening or diagnosis in the adult population.
METHODS
We performed a comprehensive literature search of PubMed, Scopus, and Web of Science databases for studies evaluating the validity of digital tools in OSA screening or diagnosis until November 2022. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal tool for diagnostic test accuracy studies. The sensitivity, specificity, and area under the curve (AUC) were used as discrimination measures.
RESULTS
We retrieved 1714 articles, 41 (2.39%) of which were included in the study. From these 41 articles, we found 7 (17%) smartphone-based tools, 10 (24%) wearables, 11 (27%) bed or mattress sensors, 5 (12%) nasal airflow devices, and 8 (20%) other sensors that did not fit the previous categories. Only 8 (20%) of the 41 studies performed external validation of the developed tool. Of these, the highest reported values for AUC, sensitivity, and specificity were 0.99, 96%, and 92%, respectively, for a clinical cutoff of apnea-hypopnea index (AHI)≥30. These values correspond to a noncontact audio recorder that records sleep sounds, which are then analyzed by a deep learning technique that automatically detects sleep apnea events, calculates the AHI, and identifies OSA. Looking at the studies that only internally validated their models, the work that reported the highest accuracy measures showed AUC, sensitivity, and specificity values of 1.00, 100%, and 96%, respectively, for a clinical cutoff AHI≥30. It uses the Sonomat-a foam mattress that, aside from recording breath sounds, has pressure sensors that generate voltage when deformed, thus detecting respiratory movements, and uses it to classify OSA events.
CONCLUSIONS
These clinical tools presented promising results with high discrimination measures (best results reached AUC>0.99). However, there is still a need for quality studies comparing the developed tools with the gold standard and validating them in external populations and other environments before they can be used in clinical settings.
TRIAL REGISTRATION
PROSPERO CRD42023387748; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=387748.
Topics: Adult; Humans; Surveys and Questionnaires; Sleep Apnea, Obstructive; Sleep Apnea Syndromes; Sleep; Polysomnography
PubMed: 37494079
DOI: 10.2196/47735 -
Journal of Clinical Sleep Medicine :... Apr 2022The objective of this meta-analysis was to analyze agreement in apnea-hypopnea index (AHI) determination between peripheral arterial tonometry (PAT) and polysomnography... (Meta-Analysis)
Meta-Analysis
STUDY OBJECTIVES
The objective of this meta-analysis was to analyze agreement in apnea-hypopnea index (AHI) determination between peripheral arterial tonometry (PAT) and polysomnography (PSG) studies.
METHODS
Mean AHI bias and standard deviation extracted from Bland-Altman plots reported in studies were pooled in a meta-analysis, which was then used to calculate percentage errors of limit agreement in AHI determination by PAT using PSG AHI as the reference. Individual participant data (where reported in studies) were used to compute Cohen's kappa to assess agreement between PSG and PAT on sleep apnea severity and for computing the sensitivity and specificity of PAT at different AHI thresholds using PSG AHI as the reference.
RESULTS
From 17 studies and 1,318 participants (all underwent simultaneous PSG and use of the WatchPAT device), a pooled mean AHI bias of 0.30 (standard error [SE], 0.74) and a WatchPAT AHI percentage error of 230% was calculated. The meta-analysis of Cohen's kappa for agreement between PSG and WatchPAT studies for classifying patients with no sleep apnea, mild, moderate, or severe sleep apnea severity was 0.45 (SE, 0.06), 0.29 (SE, 0.05), 0.25 (SE, 0.07), and 0.64 (SE, 0.05), respectively. At AHI thresholds of 5, 15 and 30 events/h, WatchPAT studies showed pooled sensitivities and specificities of 94.11% and 43.47%, 92.21% and 72.39%, and 74.11% and 87.10%, respectively. Likelihood ratios were not significant at any AHI threshold.
CONCLUSIONS
The results of this meta-analysis suggest clinically significant discordance between WatchPAT and PSG measurements of AHI, significant sleep apnea severity misclassification by PAT studies, and poor diagnostic test performance.
CITATION
Iftikhar IH, Finch CE, Shah AS, Augunstein CA, Ioachimescu OC. A meta-analysis of diagnostic test performance of peripheral arterial tonometry studies. 2022;18(4):1093-1102.
Topics: Diagnostic Tests, Routine; Humans; Manometry; Polysomnography; Sensitivity and Specificity; Sleep Apnea Syndromes; Sleep Apnea, Obstructive
PubMed: 34879903
DOI: 10.5664/jcsm.9808 -
Journal of Clinical Sleep Medicine :... Jul 2024Wearable devices that monitor sleep stages and heart rate offer the potential for longitudinal sleep monitoring in patients with neurodegenerative diseases. Sleep...
STUDY OBJECTIVES
Wearable devices that monitor sleep stages and heart rate offer the potential for longitudinal sleep monitoring in patients with neurodegenerative diseases. Sleep quality reduces with disease progression in Huntington's disease (HD). However, the involuntary movements characteristic of HD may affect the accuracy of wrist-worn devices. This study compares sleep stage and heart rate data from the Fitbit Charge 4 (FB) against polysomnography (PSG) in participants with HD.
METHODS
Ten participants with manifest HD wore an FB during overnight hospital-based PSG, and 9 of these participants continued to wear the FB for 7 nights at home. Sleep stages (30-second epochs) and minute-by-minute heart rate were extracted and compared against PSG data.
RESULTS
FB-estimated total sleep and wake times and sleep stage times were in good agreement with PSG, with intraclass correlations of 0.79-0.96. However, poor agreement was observed for wake after sleep onset and the number of awakenings. FB detected waking with 68.6 ± 15.5% sensitivity and 93.7 ± 2.5% specificity, rapid eye movement sleep with high sensitivity and specificity (78.7 ± 31.9%, 95.6 ± 2.3%), and deep sleep with lower sensitivity but high specificity (56.4 ± 28.8%, 95.0 ± 4.8%). FB heart rate was strongly correlated with PSG, and the mean absolute error between FB and PSG heart rate data was 1.16 ± 0.42 beats/min. At home, longer sleep and shorter wake times were observed compared with hospital data, whereas percentage sleep stage times were consistent with hospital data.
CONCLUSIONS
Results suggest the potential for long-term monitoring of sleep patterns using wrist-worn wearable devices as part of symptom management in HD.
CITATION
Doheny EP, Renerts K, Braun A, et al. Assessment of Fitbit Charge 4 for sleep stage and heart rate monitoring against polysomnography and during home monitoring in Huntington's disease. . 2024;20(7):1163-1171.
Topics: Humans; Polysomnography; Male; Huntington Disease; Female; Heart Rate; Middle Aged; Wearable Electronic Devices; Sleep Stages; Adult; Monitoring, Ambulatory
PubMed: 38450553
DOI: 10.5664/jcsm.11098