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Sleep Oct 2021Assess the validity of a subjective measure of sleepiness as an indicator of sleep drive by quantifying associations between intraindividual variation in evening...
STUDY OBJECTIVES
Assess the validity of a subjective measure of sleepiness as an indicator of sleep drive by quantifying associations between intraindividual variation in evening sleepiness and bedtime, sleep duration, and next morning and subsequent evening sleepiness, in young adults.
METHODS
Sleep timing and sleepiness were assessed in 19 students in late autumn and late spring on a total of 771 days. Karolinska Sleepiness Scales (KSS) were completed at half-hourly intervals at fixed clock times starting 4 h prior to participants' habitual bedtime, and in the morning. Associations between sleepiness and sleep timing were evaluated by mixed model and nonparametric approaches and simulated with a mathematical model for the homeostatic and circadian regulation of sleepiness.
RESULTS
Intraindividual variation in evening sleepiness was very large, covering four or five points on the 9-point KSS scale, and was significantly associated with subsequent sleep timing. On average, a one point higher KSS value was followed by 20 min earlier bedtime, which led to 11 min longer sleep, which correlated with lower sleepiness next morning and the following evening. Associations between sleepiness and sleep timing were stronger in early compared to late sleepers. Model simulations indicated that the directions of associations between sleepiness and sleep timing are in accordance with their homeostatic and circadian regulation, even though much of the variance in evening sleepiness and details of its time course remain unexplained by the model.
CONCLUSION
Subjective sleepiness is a valid indicator of the drive for sleep which, if acted upon, can reduce insufficient sleep.
Topics: Circadian Rhythm; Humans; Sleep; Sleep Deprivation; Sleepiness; Wakefulness; Young Adult
PubMed: 33991415
DOI: 10.1093/sleep/zsab123 -
BMC Public Health Aug 2023Insomnia disorder is a highly prevalent, significant public health concern associated with substantial and growing health burden. There are limited real-world data...
BACKGROUND
Insomnia disorder is a highly prevalent, significant public health concern associated with substantial and growing health burden. There are limited real-world data assessing the burden of insomnia disorder on daytime functioning and its association with comorbidities. The objective of this study was to leverage large-scale, real-world data to assess the burden of untreated insomnia disorder in terms of daytime impairment and clinical outcomes.
METHODS
This United States medical claims database study compares patients diagnosed with insomnia disorder but not receiving treatment ('untreated insomnia' cohort) to patients without an insomnia disorder diagnosis and without treatment ('non-insomnia' cohort). International Classification of Disease, Tenth Revision codes were used as a proxy to represent the three symptom domains (Sleepiness, Alert/Cognition, Mood) of the Insomnia Daytime Symptoms and Impacts Questionnaire (IDSIQ), a newly developed and validated tool used in clinical studies to assess daytime functioning in insomnia disorder. Chronic Fatigue (R53.83) and Other Fatigue (R53.83), Somnolence (R40.0) and Disorientation (R41.0) were selected as categories representing one or more IDSIQ domains. Clinical outcomes included cardiovascular events, psychiatric disorders, cognitive impairment and metabolic disorders.
RESULTS
Approximately 1 million patients were included (untreated insomnia: n = 139,959; non-insomnia: n = 836,975). Compared with the 'non-insomnia' cohort, the 'untreated insomnia' cohort was more likely to experience daytime impairments, with mean differences in occurrences per 100 patient-years for: (a) fatigue, at 27.35 (95% confidence interval [CI] 26.81, 27.77, p < 0.01); (b) dizziness, at 4.66 (95% CI 4.40, 4.90, p < 0.01); (c) somnolence, at 4.18 (95% CI 3.94, 4.43, p < 0.01); and (d) disorientation, at 0.92 (95% CI 0.77, 1.06, p < 0.01). During the 1-year look-back period, patients in the 'untreated insomnia' cohort were also more likely to have been diagnosed with arterial hypertension (40.9% vs. 26.3%), psychiatric comorbidities (40.1% vs. 13.2%), anxiety (29.2% vs. 8.5%), depression (26.1% vs. 8.1%) or obesity (21.3% vs. 11.1%) compared with those in the 'non-insomnia' cohort.
CONCLUSIONS
This large-scale study confirms the substantial burden of insomnia disorder on patients in a real-world setting, with significant daytime impairment and numerous comorbidities. This reinforces the need for timely insomnia disorder diagnosis and treatments that improve both sleep, as well as daytime functioning.
Topics: Humans; Adult; Sleep Initiation and Maintenance Disorders; Sleepiness; Cohort Studies; Wakefulness; Sleep
PubMed: 37537544
DOI: 10.1186/s12889-023-16329-9 -
CNS Neuroscience & Therapeutics Jun 2022To characterize the rapid weight gain (RWG) phenotype associated with the onset of childhood narcolepsy and to determine whether it could constitute a marker of severity...
OBJECTIVES
To characterize the rapid weight gain (RWG) phenotype associated with the onset of childhood narcolepsy and to determine whether it could constitute a marker of severity of the disease.
METHODS
RWG was defined using the BMI z-score slope reported to one year (>0.67 SD) from symptom onset to disease diagnosis. We compared the clinical, metabolic, and sleep characteristics between patients with or without RWG at diagnosis. Pharmacological management, anthropometric, and clinical progression were also evaluated during the follow-up.
RESULTS
A total of 84 de novo narcoleptic pediatric patients were included; their median age at diagnosis was 12.0 years; 59.5% boys, 90.5% cataplexy, and 98.7% HLA-DQB1*06:02, 57% had RWG profile. RWG patients were younger at diagnosis than non-RWG patients, despite a shorter diagnostic delay. They had a higher BMI z-score and a higher prevalence of obesity at diagnosis, but not at symptom onset, and higher adapted Epworth Sleepiness Scale and Insomnia Severity Index scores than non-RWG patients. No differences on nocturnal polysomnography and multiple sleep latency tests were found between groups at disease diagnosis. After a median follow-up of 5 years, RWG patients still had a higher BMI z-score and a higher prevalence of obesity despite benefiting from the same therapeutic management and displaying improvement in sleepiness and school difficulties.
CONCLUSIONS
Narcoleptic RWG patients were younger, sleepier, and the prevalence of obesity was higher at diagnosis despite a shorter diagnostic delay than that of non-RWG patients. These patients had also a higher risk of developing a long-term obesity, despite a positive progression of their narcoleptic symptoms. RGW could then represent a maker of a more severe phenotype of childhood narcolepsy, which should inspire a prompt and more offensive management to prevent obesity and its complications.
Topics: Child; Delayed Diagnosis; Humans; Narcolepsy; Obesity; Phenotype; Sleepiness; Weight Gain
PubMed: 35212159
DOI: 10.1111/cns.13811 -
Sensors (Basel, Switzerland) Jun 2022Drowsiness is one of the main causes of road accidents and endangers the lives of road users. Recently, there has been considerable interest in utilizing features...
Drowsiness is one of the main causes of road accidents and endangers the lives of road users. Recently, there has been considerable interest in utilizing features extracted from electroencephalography (EEG) signals to detect driver drowsiness. However, in most of the work performed in this area, the eyeblink or ocular artifacts present in EEG signals are considered noise and are removed during the preprocessing stage. In this study, we examined the possibility of extracting features from the EEG ocular artifacts themselves to perform classification between alert and drowsy states. In this study, we used the BLINKER algorithm to extract 25 blink-related features from a public dataset comprising raw EEG signals collected from 12 participants. Different machine learning classification models, including the decision tree, the support vector machine (SVM), the K-nearest neighbor (KNN) method, and the bagged and boosted tree models, were trained based on the seven selected features. These models were further optimized to improve their performance. We were able to show that features from EEG ocular artifacts are able to classify drowsy and alert states, with the optimized ensemble-boosted trees yielding the highest accuracy of 91.10% among all classic machine learning models.
Topics: Algorithms; Electroencephalography; Humans; Machine Learning; Signal Processing, Computer-Assisted; Support Vector Machine
PubMed: 35808261
DOI: 10.3390/s22134764 -
Chinese Journal of Traumatology =... Oct 2017To identify and appraise the published studies assessing interventions accounting for reducing fatigue and sleepiness while driving. (Review)
Review
PURPOSE
To identify and appraise the published studies assessing interventions accounting for reducing fatigue and sleepiness while driving.
METHODS
This systematic review searched the following electronic databases: Medline, Science direct, Scopus, EMBASE, PsycINFO, Transport Database, Cochrane, BIOSIS, ISI Web of Knowledge, specialist road injuries journals and the Australian Transport and Road Index database. Additional searches included websites of relevant organizations, reference lists of included studies, and issues of major injury journals published within the past 15 years. Studies were included if they investigated interventions/exposures accounting for reducing fatigue and sleepiness as the outcome, measured any potential interventions for mitigation of sleepiness and were written in English. Meta-analysis was not attempted because of the heterogeneity of the included studies.
RESULTS
Of 63 studies identified, 18 met the inclusion criteria. Based on results of our review, many interventions in the world have been used to reduce drowsiness while driving such as behavioral (talking to passengers, face washing, listening to the radio, no alcohol use, limiting the driving behavior at the time of 12 p.m. - 6 a.m. etc), educational interventions and also changes in the environment (such as rumble strips, chevrons, variable message signs, etc). Meta-analysis on the effect of all these interventions was impossible due to the high heterogeneity in methodology, effect size and interventions reported in the assessed studies.
CONCLUSION
Results of present review showed various interventions in different parts of the world have been used to decrease drowsy driving. Although these interventions can be used in countries with high incidence of road traffic accidents, precise effect of each intervention is still unknown. Further studies are required for comparison of the efficiency of each intervention and localization of each intervention according to the traffic patterns of each country.
Topics: Accidents, Traffic; Automobile Driving; Fatigue; Humans; Sleep Stages
PubMed: 28689801
DOI: 10.1016/j.cjtee.2017.03.005 -
BMC Pharmacology & Toxicology Apr 2023Standard doses of second-generation H-antihistamines (sgAHs) as first-line treatment are not always effective in treating chronic spontaneous urticaria (CSU), and hence... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Standard doses of second-generation H-antihistamines (sgAHs) as first-line treatment are not always effective in treating chronic spontaneous urticaria (CSU), and hence an increase in the dose of sgAHs is recommended. However, literature evaluating the efficacy and safety of this treatment remains inconclusive, highlighting the need for a systematic review and meta-analysis. The aim of this systematic review and meta-analysis was to evaluate the efficacy and safety of high-dose sgAHs compared with standard-dose sgAHs in treating CSU.
METHODS
A systematic literature search of double-blind, randomized controlled trials (RCT) utilizing multiple doses of sgAHs was performed by searching the electronic databases Medline, Embase, PsycInfo, Cochrane databases, and Web of Science. Bibliographies were also manually searched. The Cochrane Risk of Bias Tool for assessing risk of bias was used to assess the quality of randomized controlled trials (RCTs). Two reviewers screened studies, extracted data, and evaluated the risk of bias independently. The response rate, the number of adverse events, somnolence, and withdrawal due to adverse events were extracted from each article. The data were combined and analyzed to quantify the safety and efficacy of the treatment. RevMan (V5.3) software was used for data synthesis.
RESULTS
A total of 13 studies were identified, seven of which met the eligibility criteria for the meta-analysis. Our pooled meta-analyses showed that high-dose sgAHs was associated with a significantly higher response rate than standard-dose (RR 1.13, 95% CI 1.02 to 1.26; P = 0.02). Conversely, high doses of sgAHs were associated with significantly higher somnolence rates than standard dose (RD 0.05, 95% CI 0.01 to 0.09; P = 0.02). There was no significant difference in adverse events or withdrawal due to adverse events between standard- and high-dose treatments.
CONCLUSIONS
Our analyses showed that a high dose of sgAHs (up to two times the standard dose) might be more effective than a standard dose in CSU treatment. High-dose and standard-dose sgAHs showed similar adverse events, except for somnolence, where incidence was found to be dose-dependent in some studies. However, given the limited number of studies, our meta-analysis results should be interpreted with caution.
Topics: Humans; Sleepiness; Randomized Controlled Trials as Topic; Chronic Urticaria; Histamine H1 Antagonists, Non-Sedating; Histamine Antagonists
PubMed: 37024900
DOI: 10.1186/s40360-023-00665-y -
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 -
Neuropsychobiology 2015During the last few decades, much knowledge has been gained about sleep being a heterogeneous condition with several distinct sleep stages that represent fundamentally... (Review)
Review
During the last few decades, much knowledge has been gained about sleep being a heterogeneous condition with several distinct sleep stages that represent fundamentally different physiological states. The same applies for the wake state which also comprises distinct global functional states (called vigilance stages). However, various terms and concepts have been introduced describing different aspects of wakefulness, and accordingly several methods of assessment exist, e.g. sleep laboratory assessments (Multiple Sleep Latency Test, Maintenance of Wakefulness Test), questionnaires (Epworth Sleepiness Scale, Karolinska Sleepiness Scale), behavioural tasks (Psychomotor Vigilance Test) or electroencephalography (EEG)-based assessments (Alpha Attenuation Test, Karolinska Drowsiness Test). Furthermore, several theoretical concepts about the regulation of sleep and wakefulness have been put forward, and physiological correlates have been identified. Most relevant for healthy functioning is the regulation of brain arousal and the adaption of wakefulness to the environmental and situational needs so that the optimal balance between energy conservation and responsiveness can be obtained. Since one approach to the assessment of brain arousal regulation is the classification of EEG vigilance stages, a computer-based algorithm (Vigilance Algorithm Leipzig) has been introduced, allowing classification of EEG vigilance stages in EEG recordings under resting conditions. The time course of EEG vigilance stages in EEGs of 15-20 min duration allows estimation of the individual arousal regulation (hyperstable, adaptive, or unstable vigilance pattern). The vigilance model of affective disorders and attention-deficit/hyperactivity disorder links a disturbed arousal regulation to the pathogenesis of psychiatric disorders and accordingly helps to explain and possibly also predict treatment effects of pharmacological and non-pharmacological interventions for these conditions.
Topics: Animals; Arousal; Brain; Electroencephalography; Humans; Mental Disorders; Sleep; Wakefulness
PubMed: 26901462
DOI: 10.1159/000439384 -
International Journal of Environmental... Sep 2022This study identified clinical nurses' fatigue and related factors during the COVID-19 pandemic. This was a cross-sectional study. Data were collected from South Korean...
This study identified clinical nurses' fatigue and related factors during the COVID-19 pandemic. This was a cross-sectional study. Data were collected from South Korean hospitals on 234 nurses' general characteristics, fatigue, depression, occupational stress, insomnia, and perceived daytime sleepiness using a structured questionnaire. The prevalence of fatigue was 62.0%, depression 52.1%, insomnia 20.7%, and daytime sleepiness 36.1%. Insomnia, sleepiness, depression, and occupational stress were significantly associated with fatigue. Ward nurses who cared for COVID-19 patients within the past month had significantly higher occupational stress related to organizational climate than those who had not provided care, and ICU nurses who cared for COVID-19 patients had significantly higher job insecurity-related occupational stress. Nurses have a high prevalence of fatigue and depression during the pandemic. Thus, insomnia, sleepiness, depression, and occupational stress must be reduced to lower nurses' fatigue. Caring for COVID-19 patients was not significantly associated with fatigue, but there were significant differences in occupational stress between nurses who provided such care and those who did not. Work environment-specific strategies are needed to reduce nurses' occupational stress during the pandemic.
Topics: COVID-19; Cross-Sectional Studies; Disorders of Excessive Somnolence; Fatigue; Humans; Nurses; Occupational Stress; Pandemics; Sleep Initiation and Maintenance Disorders; Sleepiness; Surveys and Questionnaires
PubMed: 36141652
DOI: 10.3390/ijerph191811380 -
BMC Public Health Sep 2022Sufficient sleep is important to an individual's health and well-being, but also for school achievement among adolescents. This study investigates the associations...
BACKGROUND
Sufficient sleep is important to an individual's health and well-being, but also for school achievement among adolescents. This study investigates the associations between sleepiness, sleep deficits, and school achievements among adolescents.
METHODS
This trend study involved a representative sample of Norwegian adolescents based on the "Trends in International Mathematics and Science Study" (TIMSS), N = 4499 (2015) and N = 4685 (2019) and their teachers. The students were 9th graders from a Norwegian compulsory secondary school. The survey included questions on students' sleepiness as students reported in 2019 and sleep deficits among students that limited teaching in class as their teachers reported in 2015 and 2019. Regression, triangulation, and mediation analyses were used. Mplus was used to perform the statistical analyses.
RESULTS
The results revealed significant negative associations between sleep deficits and school achievements, adjusted for gender, socioeconomic status (SES), and minority status among Norwegian 9th graders. These results were found for both mathematics and science achievements in 2015 and 2019. Sleepiness that the students reported was negatively associated with school achievements in 2019. Trend and mediation analyses showed that sleep deficits explained 18 and 11% of the decrease in mathematics and science achievements, respectively, from 2015 to 2019.
CONCLUSIONS
Sleep deficits were associated with school achievements in mathematics and science among Norwegian 9th graders. Mediation analyses revealed that sleep deficits explained a significant part of the decline in academic achievements. Insufficient sleep may have negative public health implications and influence adolescents' academic achievements and competences, and should therefore be discussed in both the educational and health systems.
Topics: Academic Success; Adolescent; Humans; Mathematics; Schools; Sleep; Sleepiness; Students
PubMed: 36131267
DOI: 10.1186/s12889-022-14161-1