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Annals of the American Thoracic Society Aug 2023Positive airway pressure (PAP) is the first-choice treatment for obstructive sleep apnea (OSA). However, its real-world effectiveness is often questioned because of...
Positive airway pressure (PAP) is the first-choice treatment for obstructive sleep apnea (OSA). However, its real-world effectiveness is often questioned because of usage issues. The relationship between patient sleepiness and PAP usage has been assessed in relatively small and selected populations within the research context. To assess the impact of patient-reported sleep outcomes, particularly self-reported sleepiness and its change during therapy, on PAP usage in the real-world setting. Deidentified data for U.S.-based patients receiving PAP therapy were examined. Eligible patients were registered in the myAir app and provided self-reported sleepiness at baseline and after 7, 14, 21, and 28 days of PAP between November 2019 and April 2020. A total of 95,397 registered patients met all eligibility criteria and were included in the analysis (mean age, 49.6 ± 13.0 yr; 61.6% male). Daytime sleepiness was the most common reason for PAP therapy initiation (57.1% of patients), and 42.2% of all patients had self-reported moderate to severe OSA. Self-reported sleepiness improved with PAP therapy in most patients over the assessment period, with 62.1% of patients reporting "no" or "slight" sleepiness at Day 28. There was a dose-dependent association between improvement in self-reported sleepiness at Day 28 and PAP usage, and this finding was maintained at Day 360. Self-reported sleepiness at Day 28 was associated with achieving U.S. Centers for Medicare & Medicaid Services compliance at 90 days (approximately 90% for those with no or slight sleepiness vs. <70% for those with residual very or extreme sleepiness); average daily PAP usage over 360 days was ⩾5.0 and ⩽3.7 hours, respectively, for those with no or slight versus very or extreme sleepiness. This study demonstrates the feasibility of capturing patient-reported outcomes via a digital platform. Patient-reported outcomes appear to be associated with PAP usage, especially self-reported sleepiness and its response to therapy. Capturing patient-reported outcomes using digital solutions during the course of treatment has the potential to enhance patient outcomes by providing actionable insights.
Topics: Humans; Male; Aged; United States; Adult; Middle Aged; Female; Continuous Positive Airway Pressure; Self Report; Sleepiness; Medicare; Sleep Apnea, Obstructive; Patient Compliance
PubMed: 37126852
DOI: 10.1513/AnnalsATS.202206-482OC -
Italian Journal of Pediatrics Jun 2021This study aimed to provide a summary of the measures to assess narcoleptic symptoms or complications in pediatric narcolepsy patients. (Review)
Review
PURPOSE
This study aimed to provide a summary of the measures to assess narcoleptic symptoms or complications in pediatric narcolepsy patients.
METHODS
We searched in the National Center for Biotechnology Information (NCBI) for measures of narcoleptic symptoms for pediatric patients. Further review was conducted if relevant questionnaires or information were mentioned.
RESULTS
There were only two narcolepsy-specific questionnaires, the narcolepsy severity scale and Ullanlinna Narcolepsy Scale, neither of them was developed or validated in the pediatric population. For cataplexy, all the measures were study-specific diaries and were not validated questionnaires. For excessive daytime sleepiness, the Epworth Sleepiness Scale was most frequently used to measure excessive daytime sleepiness in children. For nighttime sleep, the Children's Sleep Habits Questionnaire was most frequently used. For depression, the Children Depression Inventory was the most frequently used. For attention-deficit/hyperactivity disorder, the Child Behavior Checklist was the most frequently used. For quality of life, KIDSCREEN was most frequently used.
CONCLUSIONS
At present, there is a lack of disease-specific and validated questionnaires for pediatric narcoleptic patients. This need can be met by modifying and adjusting the existing adult questionnaires and developing new questionnaires for pediatric narcoleptic patients.
Topics: Attention Deficit Disorder with Hyperactivity; Cataplexy; Child; Depression; Humans; Narcolepsy; Sleepiness; Surveys and Questionnaires
PubMed: 34078436
DOI: 10.1186/s13052-021-01068-7 -
Revista Do Colegio Brasileiro de... Dec 2016to evaluate sleep quality and daytime sleepiness of residents and medical students.
OBJECTIVE
to evaluate sleep quality and daytime sleepiness of residents and medical students.
METHODS
we applied a socio-demographic questionnaire, the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) to a population of residents and medical students.
RESULTS
hundred five residents and 101 undergraduate medical students participated. Residents presented higher mean PSQI (6.76±2.81) with poorer sleep quality when compared with undergraduates (5.90±2.39); Both had similar measures of sleepiness by ESS (p=0.280), but residents showed lower duration and lower subjective sleep quality.
CONCLUSION
medical students and residents presented sleep deprivation, indicating the need for preventive actions in the medical area.
Topics: Adult; Female; Humans; Internship and Residency; Male; Physicians; Sleep Deprivation; Sleep Stages; Students, Medical; Surveys and Questionnaires
PubMed: 28273216
DOI: 10.1590/0100-69912016006005 -
Frontiers in Endocrinology 2022Misalignment between the environment and one's circadian system is a common phenomenon (e.g., jet lag) which can have myriad negative effects on physical and mental... (Randomized Controlled Trial)
Randomized Controlled Trial
Misalignment between the environment and one's circadian system is a common phenomenon (e.g., jet lag) which can have myriad negative effects on physical and mental health, mental and physiological performance, and sleep. Absent any intervention, the circadian system adjusts only 0.5-1.0 h per day to a shifted light-dark and sleep-wake schedule. Bright light facilitates circadian adjustment, but in field studies, bright light is only modestly better than no stimulus. Evidence indicates that exercise and melatonin can be combined with bright light to elicit larger shifts but no study has combined all of these stimuli or administered them at the times that are known to elicit the largest effects on the circadian system. The aims of this study are to compare the effects of different treatments on circadian adjustment to simulated jet lag in a laboratory. Following 2 weeks of home recording, 36 adults will spend 6.5 consecutive days in the laboratory. Following an 8 h period of baseline sleep recording on the participant's usual sleep schedule on Night 1 (e.g., 0000-0800 h), participants will undergo a 26 h circadian assessment protocol involving 2 h wake intervals in dim light and 1 h of sleep in darkness, repeated throughout the 26 h. During this protocol, all urine voidings will be collected; mood, sleepiness, psychomotor vigilance, and pain sensitivity will be assessed every 3 h, forehead temperature will be assessed every 90 min, and anaerobic performance (Wingate test) will be tested every 6 h. Following, the circadian assessment protocol, the participant's sleep-wake and light dark schedule will be delayed by 8 h compared with baseline (e.g., 0800-1400 h), analogous to travelling 8 times zones westward. This shifted schedule will be maintained for 3 days. During the 3 days on the delayed schedule, participants will be randomized to one of 3 treatments: (1) Dim Red Light + Placebo Capsules, (2) Bright Light Alone, (3) Bright Light + Exercise + Melatonin. During the final 26 h, all conditions and measures of the baseline circadian protocol will be repeated. Acclimatization will be defined by shifts in circadian rhythms of aMT6s, psychomotor vigilance, Wingate Anaerobic performance, mood, and sleepiness, and less impairments in these measures during the shifted schedule compared with baseline. We posit that Bright Light Alone and Bright Light + Exercise + Melatonin will elicit greater shifts in circadian rhythms and less impairments in sleep, mood, performance, and sleepiness compared with Dim Red Light + Placebo Capsules. We also posit that Bright Light + Exercise + Melatonin will elicit greater shifts and less impairments than Bright Light Alone.
Topics: Adult; Humans; Melatonin; Sleepiness; Jet Lag Syndrome; Sleep; Acclimatization
PubMed: 36465660
DOI: 10.3389/fendo.2022.964681 -
Seizure Mar 2023To investigate the safety of perampanel in different disorders and doses. (Meta-Analysis)
Meta-Analysis Review
PURPOSE
To investigate the safety of perampanel in different disorders and doses.
METHODS
Embase, the Cochrane Library, Medline, and ClinicalTrials.gov were searched from inception to July 2022 for randomized controlled trials (RCTs). The meta-analysis was performed by using Review Manager 5.3 and R 4.2.1 software.
RESULTS
A total of 17 RCTs with 5711 subjects were included in the final analysis. The double-blind treatment phase was from 12 weeks to 48 weeks. Our results showed that 11 adverse events (aggression, ataxia, balance disorder, dizziness, fall, fatigue, irritability, rash, somnolence, vertigo, and weight increase) were statistically significantly associated with perampanel, and 4 of them (ataxia, dizziness, fatigue, and somnolence) showed a clear dose-response relationship. Psychiatric adverse events occurred most frequently among serious treatment-emergent adverse events (TEAEs). At 8 mg/day, seven adverse events (aggression, balance disorder, dizziness, fatigue, irritability, vertigo, and weight increase) occurred more frequently in patients with epilepsy than in patients with other disorders, whereas dose discontinuation rates due to adverse events were lower in patients with epilepsy than in patients with other disorders.
CONCLUSION
The safety profile of perampanel is dependent on diseases and dose. The risk of adverse events was statistically significantly higher, with doses exceeding 4 mg/day. Despite a higher risk of adverse events, patients with epilepsy had a lower perampanel discontinuation rate than patients with other disorders.
Topics: Humans; Epilepsies, Partial; Anticonvulsants; Dizziness; Sleepiness; Treatment Outcome; Epilepsy; Pyridones; Double-Blind Method; Fatigue; Vertigo; Ataxia; Drug Therapy, Combination; Randomized Controlled Trials as Topic
PubMed: 36724644
DOI: 10.1016/j.seizure.2023.01.013 -
Biological Psychology Oct 2020Two independent lines of evidence suggest that drowsiness and mind-wandering share common neurocognitive processes indexed by ocular parameters (e.g., eyeblink frequency...
Two independent lines of evidence suggest that drowsiness and mind-wandering share common neurocognitive processes indexed by ocular parameters (e.g., eyeblink frequency and pupil dynamics). Mind-wandering and drowsiness frequently co-occur, however, such that it remains unclear whether observed oculometric variations are related to mind-wandering, drowsiness, or a mix of both. To address this issue, we assessed fluctuations in mind-wandering and sleepiness during a sustained attention task while ocular parameters were recorded. Results showed that oculometric variations during mind-wandering were fully explained by increased sleepiness. However, mind-wandering and sleepiness had additive deleterious effects on performance that were not fully explained by ocular parameters. These findings suggest that oculometric variations during task performance reflect increased drowsiness rather than processes specifically involved in mind-wandering, and that the neurocognitive processes indexed by oculometric parameters (e.g., regulatory processes of the locus coeruleus norepinephrine system) do not fully explain how mind-wandering and sleepiness cause attentional lapses.
Topics: Attention; Humans; Pupil; Sleepiness; Task Performance and Analysis
PubMed: 32871227
DOI: 10.1016/j.biopsycho.2020.107950 -
Frontiers in Neuroscience 2021Brief fragments of sleep shorter than 15 s are defined as microsleep episodes (MSEs), often subjectively perceived as sleepiness. Their main characteristic is a slowing...
Brief fragments of sleep shorter than 15 s are defined as microsleep episodes (MSEs), often subjectively perceived as sleepiness. Their main characteristic is a slowing in frequency in the electroencephalogram (EEG), similar to stage N1 sleep according to standard criteria. The maintenance of wakefulness test (MWT) is often used in a clinical setting to assess vigilance. Scoring of the MWT in most sleep-wake centers is limited to classical definition of sleep (30 s epochs), and MSEs are mostly not considered in the absence of established scoring criteria defining MSEs but also because of the laborious work. We aimed for automatic detection of MSEs with machine learning, i.e., with deep learning based on raw EEG and EOG data as input. We analyzed MWT data of 76 patients. Experts visually scored wakefulness, and according to recently developed scoring criteria MSEs, microsleep episode candidates (MSEc), and episodes of drowsiness (ED). We implemented segmentation algorithms based on convolutional neural networks (CNNs) and a combination of a CNN with a long-short term memory (LSTM) network. A LSTM network is a type of a recurrent neural network which has a memory for past events and takes them into account. Data of 53 patients were used for training of the classifiers, 12 for validation and 11 for testing. Our algorithms showed a good performance close to human experts. The detection was very good for wakefulness and MSEs and poor for MSEc and ED, similar to the low inter-expert reliability for these borderline segments. We performed a visualization of the internal representation of the data by the artificial neuronal network performing best using t-distributed stochastic neighbor embedding (t-SNE). Visualization revealed that MSEs and wakefulness were mostly separable, though not entirely, and MSEc and ED largely intersected with the two main classes. We provide a proof of principle that it is feasible to reliably detect MSEs with deep neuronal networks based on raw EEG and EOG data with a performance close to that of human experts. The code of the algorithms (https://github.com/alexander-malafeev/microsleep-detection) and data (https://zenodo.org/record/3251716) are available.
PubMed: 33841068
DOI: 10.3389/fnins.2021.564098 -
PloS One 2023Driver drowsiness is a widely recognized cause of motor vehicle accidents. Therefore, a reduction in drowsy driving crashes is required. Many studies evaluating the...
Driver drowsiness is a widely recognized cause of motor vehicle accidents. Therefore, a reduction in drowsy driving crashes is required. Many studies evaluating the crash risk of drowsy driving and developing drowsiness detection systems, have used observer rating of drowsiness (ORD) as a reference standard (i.e. ground truth) of drowsiness. ORD is a method of human raters evaluating the levels of driver drowsiness, by visually observing a driver. Despite the widespread use of ORD, concerns remain regarding its convergent validity, which is supported by the relationship between ORD and other drowsiness measures. The objective of the present study was to validate video-based ORD, by examining correlations between ORD levels and other drowsiness measures. Seventeen participants performed eight sessions of a simulated driving task, verbally responding to Karolinska sleepiness scale (KSS), while infra-red face video, lateral position of the participant's car, eye closure, electrooculography (EOG), and electroencephalography (EEG) were recorded. Three experienced raters evaluated the ORD levels by observing facial videos. The results showed significant positive correlations between the ORD levels and all other drowsiness measures (i.e., KSS, standard deviation of the lateral position of the car, percentage of time occupied by slow eye movement calculated from EOG, EEG alpha power, and EEG theta power). The results support the convergent validity of video-based ORD as a measure of driver drowsiness. This suggests that ORD might be suitable as a ground truth for drowsiness.
Topics: Humans; Automobile Driving; Sleepiness; Wakefulness; Accidents, Traffic; Eye Movements; Electroencephalography; Sleep Stages
PubMed: 37155637
DOI: 10.1371/journal.pone.0285557 -
International Journal of Environmental... Dec 2021Since seafarers are known to be exposed to numerous job-related stress factors that can cause fatigue, sleepiness, and disturbed sleep behaviour, the aim of this review... (Review)
Review
Since seafarers are known to be exposed to numerous job-related stress factors that can cause fatigue, sleepiness, and disturbed sleep behaviour, the aim of this review was to provide an overview of the subjective and objective measurement methods of these strains. Using a systematic review, 166 studies were identified within the period of January 2010 to December 2020 using the PubMed database. Of the 21 studies selected, 13 used both subjective and objective measurement methods. Six studies used only subjective and two studies only objective methods. For subjective assessment, 12 different questionnaires could be identified as well as activity and sleeping logs. Actigraphy and reaction time tests (RTT) were the most common objective methods. In single cases, electrooculography (EOG), pupillometry and ambulatory polysomnography (PSG) were used. Measurement-related limitations due to vessel-related impacts were less often reported than expected. No restrictions of daily routines on board were described, and only single-measurement disturbances due to ship movements were mentioned. The present literature review reveals that there are various routines to measure fatigue, sleepiness, and sleep behaviour on board. A combination of subjective and objective methods often appears to be beneficial. The frequent use of actigraphy and RTT on board suggests good feasibility and reliable measurements with these methods. The use of ambulatory PSG in maritime-like contexts suggests that this method would also be feasible on board.
Topics: Fatigue; Humans; Ships; Sleep; Sleepiness; Surveys and Questionnaires; Wakefulness
PubMed: 35010383
DOI: 10.3390/ijerph19010120 -
Sensors (Basel, Switzerland) Mar 2020Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to...
Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to existing works, this paper proposes a generic model using multiple-objective genetic algorithm optimized deep multiple kernel learning support vector machine that is capable to recognize both driver drowsiness and stress. This algorithm simplifies the research formulations and model complexity that one model fits two applications. Results reveal that the proposed algorithm achieves an average sensitivity of 99%, specificity of 98.3% and area under the receiver operating characteristic curve (AUC) of 97.1% for driver drowsiness recognition. For driver stress recognition, the best performance is yielded with average sensitivity of 98.7%, specificity of 98.4% and AUC of 96.9%. Analysis also indicates that the proposed algorithm using multiple-objective genetic algorithm has better performance compared to the grid search method. Multiple kernel learning enhances the performance significantly compared to single typical kernel. Compared with existing works, the proposed algorithm not only achieves higher accuracy but also addressing the typical issues of dataset in simulated environment, no cross-validation and unreliable measurement stability of input signals.
Topics: Algorithms; Automobile Driving; Humans; ROC Curve; Sleepiness; Stress, Psychological; Support Vector Machine
PubMed: 32156100
DOI: 10.3390/s20051474