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Epilepsia Jun 2023Disability in patients with epilepsy (PWEs) is multifactorial: beyond seizure frequency/severity, PWEs are prone to a range of neuropsychiatric, cognitive, and somatic...
OBJECTIVES
Disability in patients with epilepsy (PWEs) is multifactorial: beyond seizure frequency/severity, PWEs are prone to a range of neuropsychiatric, cognitive, and somatic comorbidities that significantly affect quality of life. Here, we explored how variations in seizure severity and the burden of self-reported somatic/neuropsychiatric symptoms correlate with disruptions to 24 h activity patterns (rest-activity rhythms [RARs]), determined through wrist accelerometry/actigraphy.
METHODS
Multiday wrist-actigraphy recordings were obtained from 59 adult patients with focal epilepsy (44% male, ages 18-72), who contemporaneously responded to validated psychometric instruments to measure anxiety, depression, sleepiness, and somatic symptoms. We conducted a similar in silico psychometric-actigraphic correlation in a publicly available data set of 1747 Hispanic subjects (35% male, ages 18-65) from the Study of Latinos (SOL) Sueño Ancillary Study. RARs were analyzed via a sigmoidally-transformed cosine model (quantifying amplitude, steepness, acrophase, and robustness) and nonparametric measures to estimate RAR stability, fragmentation, and sleep.
RESULTS
Compared with matched SOL subjects, RARs from PWE subjects featured a significantly lower amplitude, a wider rest phase, and significantly more total daily sleep. Within PWEs, similar RAR distortions were associated with seizure intractability and/or anticonvulsant polytherapy, whereas high anxiety, depression, and somatic symptom scores were associated with lower RAR robustness and acrophase delay. We applied the SOL data set to train logistic regression models to dichotomously classify subjective anxiety, depression, and sleepiness symptoms using demographic and RAR parameters. When tested on PWEs, these models predicted prevalent anxiety and depression symptom burden (accuracy ~70%) but failed to predict subjective sleepiness.
SIGNIFICANCE
Together these results demonstrate that RAR features may encode prevalent depression and anxiety symptoms in patients with focal epilepsy, potentially offering wearable-derived endpoints to adjunct clinical care and drug/device trials. With larger PWE-specific actigraphic-psychometric data sets, we may identify RAR signatures that may more precisely correlate with varying seizure frequency, the burden of anticonvulsant therapy, and prevalent mood/anxiety symptoms.
Topics: Humans; Male; Adult; Female; Actigraphy; Anticonvulsants; Quality of Life; Sleepiness; Epilepsy; Seizures; Epilepsies, Partial
PubMed: 37029747
DOI: 10.1111/epi.17611 -
Sleep Medicine Jun 2019Poor quality and inadequate sleep are associated with impaired cognitive, motor, and behavioral components of sport performance and increased injury risk. While prior...
OBJECTIVE/BACKGROUND
Poor quality and inadequate sleep are associated with impaired cognitive, motor, and behavioral components of sport performance and increased injury risk. While prior work identifies sports-related concussions as predisposing factors for poor sleep, the role of sleep as a sports-related concussion risk factor is unknown. The purpose of this study was to quantify the effect of poor sleep quality and insomnia symptoms on future sports-related concussion risk.
PATIENTS/METHODS
In this study, 190 NCAA Division-1 athletes completed a survey battery, including the Insomnia Severity Index (ISI) and National Health and Nutrition Examination Survey (NHANES) Sleep module. Univariate risk ratios for future sports-related concussions were computed with ISI and NHANES sleepiness scores as independent predictors. An additional multiple logistic regression model including sport, sports-related concussion history, and significant univariate predictors jointly assessed the odds of sustaining a concussion.
RESULTS
Clinically moderate-to-severe insomnia severity (RR = 3.13, 95% CI: 1.320-7.424, p = 0.015) and excessive daytime sleepiness two or more times per month (RR = 2.856, 95% CI: 0.681-11.977, p = 0.037) increased concussion risk. These variables remained significant and comparable in magnitude in a multivariate model adjusted for sport participation.
CONCLUSION
Insomnia and daytime sleepiness are independently associated with increased sports-related concussion risk. More completely identifying bidirectional relationships between concussions and sleep requires further research. Clinicians and athletes should be cognizant of this relationship and take proactive measures - including assessing and treating sleep-disordered breathing, limiting insomnia risk factors, improving sleep hygiene, and developing daytime sleepiness management strategies - to reduce sports-related concussion risk and support overall athletic performance.
Topics: Athletes; Athletic Injuries; Brain Concussion; Disorders of Excessive Somnolence; Female; Humans; Male; Risk Factors; Self Report; Severity of Illness Index; Sleep Initiation and Maintenance Disorders; Sleepiness; Sports; Surveys and Questionnaires; Young Adult
PubMed: 31132574
DOI: 10.1016/j.sleep.2019.03.008 -
Journal of Medical Signals and Sensors 2022Drowsy driving is one of the leading causes of severe accidents worldwide. In this study, an analyzing method based on drowsiness level proposed to detect drowsiness...
BACKGROUND
Drowsy driving is one of the leading causes of severe accidents worldwide. In this study, an analyzing method based on drowsiness level proposed to detect drowsiness through electroencephalography (EEG) measurements and vehicle dynamics data.
METHODS
A driving simulator was used to collect brain data in the alert and drowsy states. The tests were conducted on 19 healthy men. Brain signals from the parietal, occipital, and central parts were recorded. Observer Ratings of Drowsiness (ORD) were used for the drowsiness stages assessment. This study used an innovative method, analyzing drowsiness EEG data were in respect to ORD instead of time. Thirteen features of EEG signal were extracted, then through Neighborhood Component Analysis, a feature selection method, 5 features including mean, standard deviation, kurtosis, energy, and entropy are selected. Six classification methods including K-nearest neighbors (KNN), Regression Tree, Classification Tree, Naive Bayes, Support vector machines Regression, and Ensemble Regression are employed. Besides, the lateral position and steering angle as a vehicle dynamic data were used to detect drowsiness, and the results were compared with classification result based on EEG data.
RESULTS
According to the results of classifying EEG data, classification tree and ensemble regression classifiers detected over 87.55% and 87.48% of drowsiness at the moderate level, respectively. Furthermore, the classification results demonstrate that if only the single-channel P4 is used, higher performance can achieve than using data of all the channels (C3, C4, P3, P4, O1, O2). Classification tree classifier and regression classifiers showed 91.31% and 91.12% performance with data from single-channel P4. The best classification results based on vehicle dynamic data were 75.11 through KNN classifier.
CONCLUSION
According to this study, driver drowsiness could be detected at the moderate drowsiness level based on features extracted from a single-channel P4 data.
PubMed: 36726417
DOI: 10.4103/jmss.jmss_124_21 -
International Journal of Environmental... Apr 2022The study examined sleep and sleepiness among shift working Helicopter Emergency Medical Service pilots from Norway (Norwegian Air Ambulance; NAA) and Austria...
The study examined sleep and sleepiness among shift working Helicopter Emergency Medical Service pilots from Norway (Norwegian Air Ambulance; NAA) and Austria (Christophorus Flugrettungverein; CFV). Both pilot groups (N = 47) worked seven consecutive 24 h shifts. Sleep was assessed by diaries and actigraphy while sleepiness was assessed by the Karolinska Sleepiness Scale, all administered throughout the workweek. The results indicated that all pilots had later bedtime (p < 0.05) and wake-up time (p < 0.01) as they approached the workweek end, but no change during the workweek was evident regarding wake after sleep onset, time in bed, total sleep time, or sleep efficiency. The NAA pilots had later bedtime (p < 0.001) and wake-up time (p < 0.001), spent more time awake after sleep onset (p < 0.001), more time in bed (p < 0.001), slept longer (p < 0.01), and had lower sleep efficiency (p < 0.001) compared with the CFV pilots. The sleepiness levels of all pilots were slightly elevated on the first workday but lower on the following workdays (day 2p < 0.001, day 3p < 0.05). For both pilot groups, no major change in sleep or sleepiness parameters throughout the workweek was detected. The NAA pilots reported somewhat more disturbed sleep but obtained more sleep compared with the CFV pilots.
Topics: Actigraphy; Aircraft; Austria; Emergency Medical Services; Fatigue; Humans; Pilots; Sleep; Sleepiness; Wakefulness; Work Schedule Tolerance
PubMed: 35409992
DOI: 10.3390/ijerph19074311 -
Scientific Reports Feb 2022Drowsiness is a leading cause of accidents on the road as it negatively affects the driver's ability to safely operate a vehicle. Neural activity recorded by EEG...
Drowsiness is a leading cause of accidents on the road as it negatively affects the driver's ability to safely operate a vehicle. Neural activity recorded by EEG electrodes is a widely used physiological correlate of driver drowsiness. This paper presents a novel dynamical modeling solution to estimate the instantaneous level of the driver drowsiness using EEG signals, where the PERcentage of eyelid CLOSure (PERCLOS) is employed as the ground truth of driver drowsiness. Applying our proposed modeling framework, we find neural features present in EEG data that encode PERCLOS. In the decoding phase, we use a Bayesian filtering solution to estimate the PERCLOS level over time. A data set that comprises 18 driving tests, conducted by 13 drivers, has been used to investigate the performance of the proposed framework. The modeling performance in estimation of PERCLOS provides robust and repeatable results in tests with manual and automated driving modes by an average RMSE of 0.117 (at a PERCLOS range of 0 to 1) and average High Probability Density percentage of 62.5%. We further hypothesized that there are biomarkers that encode the PERCLOS across different driving tests and participants. Using this solution, we identified possible biomarkers such as Theta and Delta powers. Results show that about 73% and 66% of the Theta and Delta powers which are selected as biomarkers are increasing as PERCLOS grows during the driving test. We argue that the proposed method is a robust and reliable solution to estimate drowsiness in real-time which opens the door in utilizing EEG-based measures in driver drowsiness detection systems.
Topics: Automobile Driving; Bayes Theorem; Biomarkers; Delta Rhythm; Electroencephalography; Eyelids; Female; Humans; Male; Monitoring, Physiologic; Sleepiness; Theta Rhythm
PubMed: 35173189
DOI: 10.1038/s41598-022-05810-x -
Molecular Metabolism Jun 2018Cytokines such as IL-1 seems to play a role in the pathogenesis of fatigue associated with some chronic diseases and anti-inflammatory treatment has been shown to reduce... (Randomized Controlled Trial)
Randomized Controlled Trial
OBJECTIVES
Cytokines such as IL-1 seems to play a role in the pathogenesis of fatigue associated with some chronic diseases and anti-inflammatory treatment has been shown to reduce these symptoms. Ingestion of a calorie rich meal leads to postprandial fatigue, and is associated with increased systemic concentrations of cytokines, which is more pronounced in obese than lean subjects. We investigated whether postprandial fatigue is regulated by IL-1, and therefore reduced by IL-1 antagonism, in lean and obese subjects.
METHODS
In a double-blind, crossover study in 8 lean and 8 obese male subjects, randomized to receive either saline (placebo) or the IL-1 receptor antagonist anakinra, we investigated whether postprandial fatigue was regulated by IL-1. To promote postprandial fatigue, subjects ran 30 min prior to a high-fat, high-carbohydrate meal. Fatigue was determined using the Stanford Sleepiness Scale and blood samples were drawn at baseline and after the intervention.
RESULTS
IL-1 antagonism led to a reduction in postprandial fatigue and this effect was more pronounced in obese than lean individuals.
CONCLUSIONS
We conclude that IL-1 is involved in the regulation of postprandial fatigue under physiologic conditions in lean and obese individuals. It remains to be shown whether this effect translates into clinical relevant effects.
Topics: Adolescent; Adult; Diet, Carbohydrate Loading; Diet, High-Fat; Fatigue; Humans; Interleukin 1 Receptor Antagonist Protein; Interleukin-1; Male; Middle Aged; Obesity; Postprandial Period; Sleepiness
PubMed: 29705519
DOI: 10.1016/j.molmet.2018.04.001 -
Revista Da Associacao Medica Brasileira... 2023It is known that obstructive sleep apnea syndrome affects many systems due to hypoxemia and hypercarbia. We aimed to demonstrate with the utilization of...
OBJECTIVE
It is known that obstructive sleep apnea syndrome affects many systems due to hypoxemia and hypercarbia. We aimed to demonstrate with the utilization of well-standardized questionnaire tools and electrophysiological tests that cognitive impairment, depression, autonomic dysfunction, and metabolic syndrome may occur in association with obstructive sleep apnea syndrome.
METHODS
The electrophysiological examination protocol of autonomic nervous system functions was performed with sympathetic skin response and R-R Interval. Patients were administered Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Montreal Cognitive Assessment, and Hamilton Depression Rating Scale by physicians in face-to-face interviews.
RESULTS
This study included 148 participants, consisting of 73 patients and 75 controls. There was a statistically significant difference between the patient group and control group with regard to sympathetic skin response, R-R Interval, post-hyperventilation R-R Interval, and R-R Interval variation (p<0.001). A statistically significant difference was observed between the patient group and control group in terms of median Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, and Montreal Cognitive Assessment scores. It was observed that the control group achieved significantly better scores than the patient group in delayed recall (p<0.001) and language (p<0.05) categories.
CONCLUSION
Obstructive sleep apnea syndrome patients should be screened for diseases, especially in the cardiovascular system, that cause serious morbidity and impair functionality such as dementia and depression. We believe that many comorbid diseases encountered in obstructive sleep apnea syndrome patients can be prevented with early diagnosis and continuous positive airway pressure treatment.
Topics: Humans; Sleepiness; Sleep Apnea, Obstructive; Surveys and Questionnaires; Continuous Positive Airway Pressure
PubMed: 36820771
DOI: 10.1590/1806-9282.20221082 -
Journal of Child Psychology and... Sep 2019Children with attention-deficit/hyperactivity disorder (ADHD) experience greater sleep problems than their peers. Although adolescence is generally a developmental...
BACKGROUND
Children with attention-deficit/hyperactivity disorder (ADHD) experience greater sleep problems than their peers. Although adolescence is generally a developmental period characterized by insufficient sleep, few studies have used a multi-informant, multi-method design, to examine whether sleep differs in adolescents with and without ADHD.
METHODS
Targeted recruitment was used to enroll an approximately equal number of eighth-grade adolescents (mean age = 13 years) with (n = 162) and without ADHD (n = 140). Adolescents and parents completed global ratings of sleep problems; adolescents, parents, and teachers completed ratings of daytime sleepiness. Adolescents wore actigraphs and completed a daily sleep diary for approximately 2 weeks.
RESULTS
Adolescents with ADHD were more likely than adolescents without ADHD to obtain insufficient sleep on school days (per diary) and weekends (per diary and actigraphy). Adolescents with ADHD were also more likely to report falling asleep in class and to have stayed up all night at least twice in the previous 2 weeks (14% and 5% reported all-nighters for ADHD and comparison, respectively). In regression analyses controlling for a number of variables known to impact sleep (e.g. pubertal development, sex, medication use, having an externalizing, anxiety, or depression diagnosis), ADHD remained associated with shorter diary and actigraphy school night sleep duration, adolescent- and parent-reported daytime sleepiness, and parent-reported difficulties initiating and maintaining sleep and total sleep disturbance. Controlling for other variables, the odds of being classified with clinically elevated parent-reported sleep disturbance were 6.20 times greater for adolescents with ADHD.
CONCLUSIONS
Findings provide some of the clearest evidence yet that adolescents with ADHD experience more sleep problems and sleepiness than their peers without ADHD. It may be especially important to assess for sleep problems in adolescents with ADHD and to evaluate whether existing sleep interventions are effective, or can be optimized, for use in adolescents with ADHD who also have sleep problems.
Topics: Actigraphy; Adolescent; Attention Deficit Disorder with Hyperactivity; Child; Female; Humans; Male; Parents; Psychometrics; School Teachers; Self Report; Sleep Wake Disorders; Sleepiness; Time Factors
PubMed: 31032953
DOI: 10.1111/jcpp.13061 -
Nature and Science of Sleep 2022Driving while drowsy is a major cause of traffic accidents globally. Recent technologies for detection and alarm within automobiles for this condition are limited by...
PURPOSE
Driving while drowsy is a major cause of traffic accidents globally. Recent technologies for detection and alarm within automobiles for this condition are limited by their reliability, practicality, cost, and lack of clinical validation. In this study, we developed an early drowsiness detection algorithm and device based on the "gold standard brain biophysiological signal" and facial expression digital data.
METHODS
The data were obtained from 10 participants. Artificial neural networks (ANN) were adopted as the model. Composite features of facial descriptors (ie, eye aspect ratio (EAR), mouth aspect ratio (MAR), face length (FL), and face width balance (FWB)) extracted from two-second video frames were investigated.
RESULTS
The ANN combined with the EAR and MAR features had the most sensitivity (70.12%) while the ANN combined with the EAR, MAR, and FL features had the most accuracy and specificity (60.76% and 58.71%, respectively). In addition, by applying the discrete Fourier transform (DFT) to the composite features, the ANN combined with the EAR and MAR features again had the highest sensitivity (72.25%), while the ANN combined with the EAR, MAR, and FL features had the highest accuracy and specificity (60.40% and 54.10%, respectively).
CONCLUSION
The ANN with DFT combined with the EAR, MAR, and FL offered the best performance. Our direct driver sleepiness detection system developed from the integration of biophysiological information and internal validation provides a valuable algorithm, specifically toward alertness level.
PubMed: 36132745
DOI: 10.2147/NSS.S376755 -
Chest Mar 2024In people with OSA, excessive daytime sleepiness is a prominent symptom and can persist despite adherence to CPAP, the first-line therapy for OSA. Pitolisant was...
BACKGROUND
In people with OSA, excessive daytime sleepiness is a prominent symptom and can persist despite adherence to CPAP, the first-line therapy for OSA. Pitolisant was effective in reducing daytime sleepiness in two 12-week randomized controlled trials (RCTs), one in patients adherent to CPAP (BF2.649 in Patients With OSA and Treated by CPAP But Still Complaining of EDS [HAROSA 1]) and the other in patients refusing or not tolerating CPAP (BF2.649 in Patients With OSA, Still Complaining of EDS and Refusing to be Treated by CPAP [HAROSA 2]).
RESEARCH QUESTION
Does the efficacy and safety of pitolisant persist when these patients take it long-term?
STUDY DESIGN AND METHODS
All adults included in the HAROSA 1 and HAROSA 2 RCTs (both pitolisant and placebo arms) were offered pitolisant (up to 20 mg/d) after completion of the short-term double-anonymized phase (ie, from week 13) in an open-label cohort study. The primary efficacy outcome was the change in Epworth Sleepiness Scale score between baseline and week 52. Safety outcomes were treatment-emergent adverse event(s) (TEAE[s]), serious TEAEs, and special interest TEAEs.
RESULTS
Out of 512 adults included in the two RCTs, 376 completed the 1-year follow-up. The pooled mean difference in Epworth Sleepiness Scale score from baseline to 1 year for the intention-to-treat sample was -8.0 (95% CI, -8.3 to -7.5). The overall proportions of TEAEs, serious TEAEs, and TEAEs of special interest were 35.1%, 2.0%, and 11.1%, respectively, without any significant difference between patients in the initial pitolisant and placebo arms. No cardiovascular safety issues were reported.
INTERPRETATION
Pitolisant is effective in reducing daytime sleepiness over 1 year in adults with OSA, with or without CPAP treatment. Taken for 1 year, it has a good safety profile (including cardiovascular).
TRIAL REGISTRATION
ClinicalTrials.gov; Nos.: NCT01071876 and NCT01072968; URL: www.
CLINICALTRIALS
gov.
Topics: Adult; Humans; Sleepiness; Piperidines; Disorders of Excessive Somnolence; Continuous Positive Airway Pressure; Sleep Apnea, Obstructive; Treatment Outcome
PubMed: 37979718
DOI: 10.1016/j.chest.2023.11.017