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Sleep & Breathing = Schlaf & Atmung Mar 2022There are no studies comparing tests performed at home with those carried out in the laboratory, using the same device. The only studies that have been performed...
AIM
There are no studies comparing tests performed at home with those carried out in the laboratory, using the same device. The only studies that have been performed have compared the device used at home with the standard polygraph used in the laboratory. The purpose of this study was therefore to verify the accuracy of the home diagnosis of obstructive sleep apnea syndrome (OSAS) via unassisted type 2 portable polysomnography, compared with polysomnography using the same equipment in a sleep laboratory.
METHODS
To avoid any possible order effect on the apnea-hypopnea index (AHI), we randomly created two groups of 20-total 40 patients, according to the test sequence. One of the groups had the first test at home and the second test in the laboratory (H-L); the other group had the first test in the laboratory and the second at home (L-H). The second test always took place on the night immediately following the first test. All polysomnographic monitoring was undertaken with the same equipment, an Embletta X100 system (Embla, Natus Inc., Middleton, USA). The Embletta X100 is a portable polygraph that records eleven polygraph signs: (1) electroencephalogram C4/A; (2) electroencephalogram O2/M1; (3) submental EMG; (4) electrooculogram of the right side; (5) nasal cannula (air flow); (6) respiratory effort against a plethysmographic chest strap; (7) respiratory effort against an abdominal plethysmographic belt; (8) heart rate; (9) saturation of oxyhemoglobin; (10) snoring; and (11) body position.
RESULTS
There was no difference in sleep efficiency between the group monitored in the laboratory and the group tested at home (p = 0.30). There was no difference in total sleep time (p = 0.11) or sleep latency (p = 0.52), or in the latency in phases N2 and N3 between the monitoring in the laboratory and at home (N2 p = 0.24; N3 p = 0.09). Some differences occurred regarding the PSG that took place at home, with longer duration of wake after sleep onset (WASO) and longer latency for REM sleep, due to failure of the patient to start the monitoring by pressing the "events" button on the device. In the distribution of sleep phases, there was no difference between the group monitored in the laboratory and the group tested at home.
CONCLUSION
Results from home sleep monitoring correlate well with the laboratory "gold standard" and may be an option for diagnosing OSAS in selected patients.
Topics: Adult; Diagnostic Equipment; Equipment Design; Female; Humans; Male; Middle Aged; Monitoring, Ambulatory; Polysomnography; Sleep Apnea, Obstructive
PubMed: 33837916
DOI: 10.1007/s11325-021-02372-6 -
Journal of Clinical Sleep Medicine :... Nov 2017Perfectionism has been suggested to represent a predisposing factor for poor sleep. However, previous studies have relied on self-reported measures. The association...
STUDY OBJECTIVES
Perfectionism has been suggested to represent a predisposing factor for poor sleep. However, previous studies have relied on self-reported measures. The association between perfectionism and poor sleep measured by polysomnography (PSG) warrants further investigation.
METHODS
The current retrospective exploratory study used the Frost Multidimensional Perfectionism Scale and PSG in an unselected sample of 334 consecutive sleep laboratory patients (140 males, 194 females, 44.6 ± 15.9 years). Data were analyzed using linear regression analyses.
RESULTS
High levels of perfectionism were associated with PSG-determined markers of poor sleep in the first sleep laboratory night. The total Frost Multidimensional Perfectionism Scale score was significantly associated with the number of nocturnal awakenings in the first sleep laboratory night. The subscales "concern over mistakes" and "personal standards" of perfectionism were significantly associated with markers of poor sleep. In contrast, there were only a few associations between perfectionism and PSG variables of the second sleep laboratory night.
CONCLUSIONS
This pattern of results suggests that high levels of perfectionism may predispose individuals to sleep disturbances in the context of acute stressors. Thus, the influence of perfectionism on poor sleep should be further investigated to improve treatment.
Topics: Adult; Female; Humans; Male; Perfectionism; Polysomnography; Retrospective Studies; Sleep Initiation and Maintenance Disorders
PubMed: 28992830
DOI: 10.5664/jcsm.6806 -
Journal of Sleep Research Apr 2022The clinical relevance of rapid eye movement sleep-related obstructive sleep apnea (REM OSA) is supported by its associated adverse health outcomes and impact on optimal...
Phenotyping REM OSA by means of peripheral arterial tone-based home sleep apnea testing and polysomnography: A critical assessment of the sensitivity and specificity of both methods.
The clinical relevance of rapid eye movement sleep-related obstructive sleep apnea (REM OSA) is supported by its associated adverse health outcomes and impact on optimal treatment strategies. To date, no assessment of REM OSA phenotyping performance has been conducted for any type of sleep testing technology. The objective of this study was to assess this for polysomnography and peripheral arterial tone-based home sleep apnea testing (PAT HSAT). In a dataset comprising 261 participants, the sensitivity and specificity of the agreement on REM OSA phenotyping was assessed for two independent scorings of polysomnography and a synchronously administered PAT HSAT. The sensitivity and specificity of REM OSA phenotyping were 0.87 and 0.89, respectively, for the polysomnography inter-scorer comparison, and 0.68 and 0.97 for the PAT HSAT on a single-night basis, using the conventional minimum required rapid eye movement sleep time of 30 min. Polysomnography-based REM OSA phenotyping was found to be sensitive and specific even for a single-night testing protocol. Peripheral arterial tone-based REM OSA phenotyping showed a lower sensitivity but a slightly higher specificity compared to polysomnography. In order to increase performance and conclusiveness of peripheral arterial tone-based REM OSA phenotyping, a multi-night protocol of 2-5 nights could be considered. Finally, the minimum required rapid eye movement sleep time could be lowered from the conventional 30 min to 15 min without significantly lowering REM OSA phenotyping sensitivity and specificity, while increasing the level of phenotyping conclusiveness.
Topics: Humans; Polysomnography; Sensitivity and Specificity; Sleep; Sleep Apnea, Obstructive; Sleep, REM
PubMed: 34510622
DOI: 10.1111/jsr.13481 -
Journal of Neural Engineering Oct 2023Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential...
Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential for the diagnosis of sleep disorders, as frequent and excessive occurrences of arousals disrupt sleep stage patterns and lead to poor sleep quality, negatively impacting physical and mental health. Polysomnography is a traditional method for arousal and sleep stage detection that is time-consuming and prone to high variability among experts.. In this paper, we propose a novel multi-task learning approach for arousal and sleep stage detection using fully convolutional neural networks. Our model, FullSleepNet, accepts a full-night single-channel EEG signal as input and produces segmentation masks for arousal and sleep stage labels. FullSleepNet comprises four modules: a convolutional module to extract local features, a recurrent module to capture long-range dependencies, an attention mechanism to focus on relevant parts of the input, and a segmentation module to output final predictions.By unifying the two interrelated tasks as segmentation problems and employing a multi-task learning approach, FullSleepNet achieves state-of-the-art performance for arousal detection with an area under the precision-recall curve of 0.70 on Sleep Heart Health Study and Multi-Ethnic Study of Atherosclerosis datasets. For sleep stage classification, FullSleepNet obtains comparable performance on both datasets, achieving an accuracy of 0.88 and an F1-score of 0.80 on the former and an accuracy of 0.83 and an F1-score of 0.76 on the latter.. Our results demonstrate that FullSleepNet offers improved practicality, efficiency, and accuracy for the detection of arousal and classification of sleep stages using raw EEG signals as input.
Topics: Electroencephalography; Sleep Stages; Sleep; Polysomnography; Arousal
PubMed: 37769664
DOI: 10.1088/1741-2552/acfe3a -
Sleep Medicine Reviews Oct 2018Sleep quality appears to be altered by traumatic brain injury (TBI). However, whether persistent post-injury changes in sleep architecture are present is unknown and... (Meta-Analysis)
Meta-Analysis Review
Sleep quality appears to be altered by traumatic brain injury (TBI). However, whether persistent post-injury changes in sleep architecture are present is unknown and relatively unexplored. We conducted a systematic review and meta-analysis to assess the extent to which chronic TBI (>6 months since injury) is characterized by changes to sleep architecture. We also explored the relationship between sleep architecture and TBI severity. In the fourteen included studies, sleep was assessed with at least one night of polysomnography in both chronic TBI participants and controls. Statistical analyses, performed using Comprehensive Meta-Analysis software, revealed that chronic TBI is characterized by relatively increased slow wave sleep (SWS). A meta-regression showed moderate-severe TBI is associated with elevated SWS, reduced stage 2, and reduced sleep efficiency. In contrast, mild TBI was not associated with any significant alteration of sleep architecture. The present findings are consistent with the hypothesis that increased SWS after moderate-severe TBI reflects post-injury cortical reorganization and restructuring. Suggestions for future research are discussed, including adoption of common data elements in future studies to facilitate cross-study comparability, reliability, and replicability, thereby increasing the likelihood that meaningful sleep (and other) biomarkers of TBI will be identified.
Topics: Brain Injuries, Traumatic; Chronic Disease; Humans; Polysomnography; Sleep Stages
PubMed: 29452727
DOI: 10.1016/j.smrv.2018.01.004 -
Journal of Psychiatric Research Jun 2022Anxiety and depression are common psychiatric conditions associated with significant morbidity and healthcare costs. Sleep is an evolutionarily conserved health state....
Anxiety and depression are common psychiatric conditions associated with significant morbidity and healthcare costs. Sleep is an evolutionarily conserved health state. Anxiety and depression have a bidirectional relationship with sleep. This study reports on the use of analysis of polysomnographic data using deep learning methods to detect the presence of anxiety and depression. Polysomnography data on 940 patients performed at an academic sleep center during the 3-year period from 01/01/2016 to 12/31/2018 were identified for analysis. The data were divided into 3 subgroups: 205 patients with Anxiety/Depression, 349 patients with no Anxiety/Depression, and 386 patients with likely Anxiety/Depression. The first two subgroups were used for training and testing of the deep learning algorithm, and the third subgroup was used for external validation of the resulting model. Hypnograms were constructed via automatic sleep staging, with the 12-channel PSG data being transformed into three-channel RGB (red, green, blue channels) images for analysis. Composite patient images were generated and utilized for training the Xception model, which provided a validation set accuracy of 0.9782 on the ninth training epoch. In the independent test set, the model achieved a high accuracy (0.9688), precision (0.9533), recall (0.9630), and F1-score (0.9581). Classification performance of most other mainstream deep learning models was comparable. These findings suggest that machine learning techniques have the potential to accurately detect the presence of anxiety and depression from analysis of sleep study data. Further studies are needed to explore the utility of these techniques in the field of psychiatry.
Topics: Anxiety; Deep Learning; Depression; Humans; Polysomnography; Sleep Stages
PubMed: 35358832
DOI: 10.1016/j.jpsychires.2022.03.027 -
Current Hypertension Reviews 2016Sleep Apnea is a very common condition that has serious cardiovascular sequelae such as hypertension, heart failure, and stroke. Since the advent of modern computers and... (Review)
Review
Sleep Apnea is a very common condition that has serious cardiovascular sequelae such as hypertension, heart failure, and stroke. Since the advent of modern computers and digital circuits, several streams of new technologies have been introduced to enhance the traditional diagnostic method of polysomnography and offer alternatives that are more accessible, comfortable, and economic. The categories presented in this review include portable polygraphy, mattress-like devices, remote sensing, and acoustic technologies. These innovations are classified as a function of their physical structure and the capabilities of their sensing technologies, due to the importance of these factors in determining the end-user experiences (both patients and medical professionals). Each of those categories offers unique strengths, which then make them particularly suitable for specific applications and end users. To our knowledge, this is a unique approach in presenting and classifying sleep apnea diagnostic innovations.
Topics: Acoustics; Equipment Design; Humans; Polysomnography; Predictive Value of Tests; Prognosis; Remote Sensing Technology; Reproducibility of Results; Respiration; Sleep; Sleep Apnea Syndromes; Transducers
PubMed: 26778198
DOI: 10.2174/1573402112666160114094337 -
Handbook of Clinical Neurology 2019Actigraphy involves acquisition of data using a movement sensor worn continuously on the nondominant wrist, typically for a week or more. Computer-based algorithms... (Review)
Review
Actigraphy involves acquisition of data using a movement sensor worn continuously on the nondominant wrist, typically for a week or more. Computer-based algorithms estimate sleep episodes by analysis of continuous minutes of no to low movement, or spans of time when movement is relatively low compared with movements during presumed ambulatory wakefulness. Inherent advantages of actigraphy over polysomnography include its noninvasive nature, cost-effectiveness, lesser burden on patients/research participants, and ability to collect data over multiple days/nights, thereby allowing examination of sleep-wake patterning. Therefore, actigraphy is emerging as a common method to objectively assess sleep parameters providing estimates of sleep duration and continuity. Modes of actigraphy data collection, scoring algorithms, sleep quality/disturbance measures, validation studies, and clinical and research applications are discussed.
Topics: Actigraphy; Humans; Polysomnography; Sleep Stages; Sleep Wake Disorders
PubMed: 31277861
DOI: 10.1016/B978-0-444-64032-1.00024-2 -
European Archives of... Apr 2020It is not easy to assess how severe and annoying a patient's snoring is. Solid parameters are lacking; snorers cannot deliver a reliable self-assessment and it is... (Randomized Controlled Trial)
Randomized Controlled Trial
PURPOSE
It is not easy to assess how severe and annoying a patient's snoring is. Solid parameters are lacking; snorers cannot deliver a reliable self-assessment and it is uncertain whether bed partners' statements can be relied upon. The purpose of the present study was therefore to investigate whether and how well snoring assessment based on acoustic parameters and bed partners' reporting agree.
METHODS
In a double-blind, placebo-controlled study on snoring treatment, several acoustic parameters [snoring index (SI), percentage snoring time (ST), sound pressure level, sound energy, loudness, psychoacoustic annoyance and psychoacoustic snore score (PSS)] were measured in 18 subjects during 24 polysomnographies. Bed partners also assessed snoring annoyance and loudness as well as treatment outcome.
RESULTS
No correlation was found between the subjective annoyance caused by snoring and the acoustic parameters. Regarding perceived loudness, there was a moderate, significant correlation with loudness (N) and PSS over the hour with the highest SI. SI, ST, LAeq and maximum sound pressure level dB(A) showed no significant correlation. After the intervention only mean sound energy LAeq over the entire night showed a significant correlation (r = 0.782; p = 0.022) with bed partners' assessments. However, this result was not confirmed in the second control night.
CONCLUSIONS
The non-existent or only weak correlation between bed partners' ratings and objective parameters indicate that snoring severity should be evaluated with caution. Neither acoustic parameters, at least for one measurement over just one night, nor bed partners' ratings should be used as the sole basis for snoring assessment.
Topics: Acoustics; Humans; Polysomnography; Psychoacoustics; Snoring; Sound Spectrography
PubMed: 32016523
DOI: 10.1007/s00405-020-05813-2 -
Journal of Sleep Research Aug 2019Actigraphy is increasingly used in practice and research studies because of its relative low cost and decreased subject burden. How multiple nights of at-home actigraphy...
Actigraphy is increasingly used in practice and research studies because of its relative low cost and decreased subject burden. How multiple nights of at-home actigraphy compare to one independent night of in-laboratory polysomnography (PSG) has not been examined in people with insomnia. Using event markers (MARK) to set time in bed (TIB) compared to automatic program analysis (AUTO) has not been systematically evaluated. Subjects (n = 30) meeting DSM-5 criteria for insomnia and in-laboratory PSG sleep efficiency (SE) of <85% were studied. Subjects were free of psychiatric, sleep or circadian disorders, other chronic conditions and medications that effect sleep. Subjects had an in-laboratory PSG, then were sent home for 7 nights with Philips Actiwatch Spectrum Plus. Data were analysed using Philips Actiware version 6. Using the mean of seven nights, TIB, total sleep time (TST), SE, sleep-onset latency (SOL) and wake after sleep onset (WASO) were examined. Compared to PSG, AUTO showed longer TIB and TST and less WASO. MARK only differed from PSG with decreased WASO. Differences between the PSG night and the following night at home were found, with better sleep on the first night home. Actigraphy in people with insomnia over seven nights is a valid indicator of sleep compared to an independent in-laboratory PSG. Event markers increased the validity of actigraphy, showing no difference in TIB, TST, SE and SOL. AUTO was representative of SE and SOL. Increased SE and TST without increased TIB suggests possible compensatory sleep the first at night home after in-laboratory PSG.
Topics: Actigraphy; Female; Humans; Male; Middle Aged; Polysomnography; Sleep Initiation and Maintenance Disorders
PubMed: 30941838
DOI: 10.1111/jsr.12854