-
Inflammopharmacology Apr 2023COVID-19 is often associated with long-lasting pulmonary symptoms. Data are scarce about interstitial lung disease (ILD) in patients following COVID-19 hospitalization... (Review)
Review
COVID-19 is often associated with long-lasting pulmonary symptoms. Data are scarce about interstitial lung disease (ILD) in patients following COVID-19 hospitalization with persistent symptoms. We retrospectively reviewed all cases sent to pulmonary post-COVID evaluation due to persistent symptoms between February 2021 and February 2022 (N = 318). All patients with suspected ILD (N = 44) were reviewed at the multidisciplinary discussion. Patient characteristics, symptoms, time since hospitalization, detailed lung function measurements and 6-min walk test (6MWT) were evaluated. The post-COVID ILD suspected group included more men (68.2 vs. 31.8%) with significantly older age compared to the control group (64.0 ± 12.3 vs. 51.3 ± 14.9 years). Most patient needed hospital care for COVID-19 pneumonia (68.6% of all patients and 84.1% of ILD suspected group) and average time since hospitalization was 2.4 ± 2.3 months. Persisting symptoms included fatigue (34%), dyspnoea (25.2%), cough (22.6%), and sleep disorders (insomnia 13.2%; sleepiness 8.2%). Post-COVID ILD presented more often with new symptoms of cough and sleepiness. Functional impairment, especially decreased walking distance and desaturation during 6-min walk test (6MWT) were detected in the ILD-suspected group. Respiratory function test in the post-COVID ILD group showed slight restrictive ventilatory pattern (FVC: 76.7 ± 18.1%, FEV1: 83.5 ± 19.1%, TLC: 85.6 ± 28.1%) and desaturation during 6MWT were detected in 41% of patients. LDCT changes were mainly ground glass opacities (GGO) and/or reticular abnormalities in most cases affecting < 10% of the lungs. Our data indicate that suspected post-COVID ILD is affecting 13.8% of symptomatic patients. High resolution chest CT changes were mainly low extent GGO/reticulation, while long-term lung structural changes need further evaluation.
Topics: Male; Humans; Cough; Retrospective Studies; Sleepiness; COVID-19; Lung Diseases, Interstitial; Lung
PubMed: 36961666
DOI: 10.1007/s10787-023-01191-3 -
Psychophysiology Aug 2021We systematically examined the temporal relationships between subjective sleepiness and both physiological drowsiness and performance impairment in a controlled...
We systematically examined the temporal relationships between subjective sleepiness and both physiological drowsiness and performance impairment in a controlled laboratory setting. Eighteen healthy young adults (8 women; M = 21.44 ± 3.24 years) underwent 40 hr of extended wakefulness, completing a bihourly Karolinska Sleepiness Scale (KSS) and 10-min Psychomotor Vigilance Task (PVT). Microsleeps and slow eye movements (SEMs) were scored during the PVT. KSS scores increased 3 hr prior to performance impairment (p < .001) and 4-6 hr prior to physiological sleepiness (p < .001). There were strong within-subject correlations between KSS and PVT lapses (r = 0.75, p < .001) and physiological drowsiness (r > 0.60, p < .001). Between-subjects product-moment correlations were more modest but showed a significant positive increase across time awake, suggesting that subjective sleepiness and objective outcomes were more tightly correlated after sleep loss. Cross-correlations showed significant positive correlations at 0-lag (p < .034); however, a high proportion of participants showed maximal correlations at positive lags, suggesting KSS was associated with future objective impairment. Within individuals, subjective sleepiness was highly correlated with objective impairment, between-subject correlations were more modest, possibly due to interindividual vulnerability to sleep loss. These results suggest that subjective sleepiness represents an inbuilt early warning system for subsequent drowsiness and performance impairment.
Topics: Adolescent; Adult; Arousal; Awareness; Female; Humans; Male; Psychomotor Performance; Sleepiness; Time Factors; Young Adult
PubMed: 34032305
DOI: 10.1111/psyp.13839 -
Sleep Medicine Clinics Dec 2019Sleepiness accounts for approximately 20% of major highway motor vehicle accidents (MVAs) and the most common medical disorder associated with sleepiness is obstructive... (Review)
Review
Sleepiness accounts for approximately 20% of major highway motor vehicle accidents (MVAs) and the most common medical disorder associated with sleepiness is obstructive sleep apnea (OSA). OSA patients are 2 to 3 times more likely to have an MVA than the general population, although continuous positive airway pressure therapy can remove this excess risk. Several jurisdictions have introduced regulations to limit driving in patients with moderate or severe OSA associated with sleepiness until the disorder is effectively treated. Successful implementation of such regulations requires education regarding risk-benefit relationships of relevant stakeholders, including patients, clinicians, and employers in the transportation industry.
Topics: Accidents, Traffic; Automobile Driving; Continuous Positive Airway Pressure; Humans; Sleep Apnea, Obstructive; Sleepiness
PubMed: 31640877
DOI: 10.1016/j.jsmc.2019.08.006 -
European Journal of Sport Science Mar 2021Daytime napping is a common practice in high-performance athletes, and is widely assumed to reflect sleepiness arising from sports-related sleep debt. The possibility...
Daytime napping is a common practice in high-performance athletes, and is widely assumed to reflect sleepiness arising from sports-related sleep debt. The possibility that athlete naps may also be indicative of 'sleepability', a capacity to nap on demand that is only weakly related to homeostatic sleep pressure, has not previously been tested. The present study compared daytime sleep latencies in high-performance athletes and non-athlete controls using a single nap opportunity model. Elite ( = 10), and sub-elite ( = 10) athletes, and non-athlete controls ( = 10) attended the laboratory for a first adaption trial, and a subsequent experimental trial. Subjective sleepiness was assessed using the Karolinska Sleepiness Scale (KSS) at 14:00, 14:30 and immediately prior to a 20-minute nap opportunity at 15:00. Sleep latencies were measured using polysomnography, and defined as the time from lights out to the first epoch of any stage of sleep (N1, N2, N3, REM). In unadjusted comparisons with non-athlete controls, elite athletes showed significantly shorter sleep latencies in both the adaptation ( < 0.05) and experimental trials ( < 0.05). These significant differences were maintained in models controlling for pre-trial KSS scores and pre-trial total sleep time (all < 0.05). Sleep latency scores for sub-elite athletes showed similar trends, but were more labile. These results are consistent with a conclusion that, among elite athletes, napping behaviour can reflect sleepability and may not necessarily result from nocturnal sleep disruption and daytime sleepiness.
Topics: Analysis of Variance; Athletes; Athletic Performance; Female; Humans; Male; Polysomnography; Rest; Sleep; Sleep Latency; Sleepiness; Time Factors; Young Adult
PubMed: 32174283
DOI: 10.1080/17461391.2020.1743765 -
Chronobiology International Mar 2022Sleep is an essential component of the daily cycle. Age and puberty-related declines in sleep duration, delays in chronotype, and an increase in social jet lag have been...
Sleep is an essential component of the daily cycle. Age and puberty-related declines in sleep duration, delays in chronotype, and an increase in social jet lag have been consistently reported. This study examined chronotype and gender-based differences in adolescents' sleep quality, depression level, and academic achievements. Eight hundred fifteen school students (372 male and 443 female) aged 14 to 20 years voluntarily participated in this study. Horne and Östberg Morningness-Eveningness Questionnaire (MEQ) was used to measure their chronotype. Sleep duration, sleep quality, and daytime sleepiness were assessed by the Pediatric Daytime Sleepiness Scale (PDSS) and Epworth Sleepiness Scale (ESS). Pittsburghs Sleep Quality Index (PSQI) was used to evaluate sleep habits. Cleveland Adolescent Sleepiness Questionnaire (CASQ) was used to measure the sleep pattern of the students. Zung Self-Rating Depression Scale (SDS) was used to assess the level of depression for the students. Our results show neither type of students dominated the population studied but interestingly, in comparison to evening type, morning type individuals were higher among the population. Chronotype-based sleep quality and academic performances were observed, and higher depression levels, poor sleep quality, poor academic performances were observed in evening type compared to neither type and morning type. In contrast to males, females had a poor sleep pattern (CASQ) and a higher depression level (SDS). Altogether, our study shows the effect of chronotype and gender on sleep quality and depression levels among school students.
Topics: Academic Performance; Adolescent; Child; Circadian Rhythm; Disorders of Excessive Somnolence; Female; Humans; Male; Sleep; Sleep Quality; Sleepiness; Students; Surveys and Questionnaires
PubMed: 34794352
DOI: 10.1080/07420528.2021.2002350 -
European Journal of Neurology Mar 2023Fatigue, a disabling symptom in many neuromuscular disorders, has been reported also in Charcot-Marie-Tooth disease (CMT). The presence of fatigue and its correlations...
BACKGROUND AND PURPOSE
Fatigue, a disabling symptom in many neuromuscular disorders, has been reported also in Charcot-Marie-Tooth disease (CMT). The presence of fatigue and its correlations in CMT was investigated.
METHODS
The Modified Fatigue Impact Scale (MFIS) was administered to CMT patients from the Italian Registry and a control group. An MFIS score >38 indicated abnormal fatigue. The correlation with disease severity and clinical characteristics, the Hospital Anxiety and Depression Scale and Epworth Sleepiness Scale scores, and drug use was analysed.
RESULTS
Data were collected from 251 CMT patients (136 women) and 57 controls. MFIS total (mean ± standard deviation 32 ± 18.3, median 33), physical (18.9 ± 9.7, 20) and psychosocial (2.9 ± 2.4, 3) scores in CMT patients were significantly higher than controls. Abnormal fatigue occurred in 36% of the patients who, compared to patients with normal scores, had more severe disease (median CMT Examination Score 9 vs. 7), more frequent use of foot orthotics (22% vs. 11%), need of support for walking (21% vs. 8%), hand disability (70% vs. 52%) and positive sensory symptoms (56% vs. 36%). Patients with abnormal fatigue had significantly increased frequency of anxiety/depression/general distress (Hospital Anxiety and Depression Scale), somnolence (Epworth Sleepiness Scale), obesity (body mass index ≥ 30) and use of anxiolytic/antidepressant or anti-inflammatory/analgesic drugs.
CONCLUSIONS
Fatigue is a relevant symptom in CMT as 36% of our series had scores indicating abnormal fatigue. It correlated with disease severity but also with anxiety, depression, sleepiness and obesity, indicating different components in the generation of fatigue. CMT patients' management must include treatment of fatigue and of its different generators, including general distress, sleepiness and obesity.
Topics: Humans; Female; Charcot-Marie-Tooth Disease; Sleepiness; Walking; Fatigue; Upper Extremity
PubMed: 36458502
DOI: 10.1111/ene.15643 -
Risk assessment of road traffic accidents related to sleepiness during driving: a systematic review.Eastern Mediterranean Health Journal =... Sep 2022Injuries due to accidental crash are the 8th leading cause of death worldwide. Sleepiness results in disrupted neurological function and is a major risk factor for road... (Review)
Review
BACKGROUND
Injuries due to accidental crash are the 8th leading cause of death worldwide. Sleepiness results in disrupted neurological function and is a major risk factor for road traffic accidents.
AIMS
This systematic review assessed the relationship between sleepiness during driving and road traffic accidents.
METHODS
A systematic review was conducted using online databases such as Wiley Online Library, JSTOR, Medline, and PubMed. Full-text, English language articles published between May 2000 and November 2020 were retrieved. Road traffic accident was set as the outcome of interest and sleepiness during driving as the exposure. The review included studies containing adjusted risk estimates (95% confidence interval). Ten cross-sectional studies (N = 55,945), 5 case-control studies (N = 3821), and 2 cohort studies (N =16,875) were included.
RESULTS
Over 50% of the participants in the different studies experienced sleep deprivation ranging from 3.5% to 67.3%. Abe et al. reported the highest (58%) frequency of sleepiness during driving in their cross-sectional study in Japan, and Nabi et al. reported the lowest (1.1%) in their cohort study in France.
CONCLUSION
Sleepiness and sleep deprivation were related to road traffic accidents; and sleep deprivation was the main contributor to drowsiness while driving.
Topics: Accidents, Traffic; Automobile Driving; Cohort Studies; Cross-Sectional Studies; Humans; Risk Assessment; Risk Factors; Sleep Deprivation; Sleepiness
PubMed: 36205209
DOI: 10.26719/emhj.22.055 -
Journal of Safety Research Feb 2020Due to the negative impact on road safety from driver drowsiness and distraction, several studies have been conducted, usually under driving simulator and naturalistic...
INTRODUCTION
Due to the negative impact on road safety from driver drowsiness and distraction, several studies have been conducted, usually under driving simulator and naturalistic conditions. Nevertheless, emerging technologies offer the opportunity to explore novel data. The present study explores retrospective data, which was gathered by an app designed to monitor the driver, which is available to any driver owning a smartphone.
METHOD
Drowsiness and distraction alerts emitted during the journey were aggregated by continuous driving (called sub-journey). The data include 273 drivers who made 634 sub-journeys. Two binary logit models were used separately to analyze the probability of a drowsiness and distraction event occurring. Variables describing the continuous driving time (sub-journey time), the journey time (a set of sub-journeys), the number of breaks, the breaking duration time and the first sub-journey (categorical variable) were included. Additionally, categorical variables representing the gender and age of the drivers were also incorporated.
RESULTS
Despite the limitations of the retrospective data, interesting findings were obtained. The results indicate that the main risk factor of inattention is driving continuously (i.e., without stopping), but it is irrelevant whether the stop is long or short as well as the total time spent on the journey. The probability of distraction events occurring during the journey is higher than drowsiness events. Yet, the impact of increasing the driving time of the journey and stopping during the journey on the probability of drowsiness is higher than the probability of distraction. Additionally, this study reveals that the elderly are more prone to drowsiness. The data also include a group of drivers, who did not provide information on gender and age, who were found to be associated to drowsiness and distraction risk.
CONCLUSIONS
The study shows that data gathered by an app have the potential to contribute to investigating drowsiness and distraction. Practical applications: Drivers are highly recommended to frequently stop during the journey, even for a short period of time to prevent drowsiness and distraction.
Topics: Adult; Aged; Distracted Driving; Female; Humans; Male; Middle Aged; Probability; Retrospective Studies; Sleepiness; Smartphone; Young Adult
PubMed: 32199573
DOI: 10.1016/j.jsr.2019.12.024 -
Physiological Measurement Jul 2021. Sleepiness-related motor vehicle crashes, caused by lack of sleep or driving during night-time hours, often result in serious injury or fatality. Sleepiness detection... (Review)
Review
. Sleepiness-related motor vehicle crashes, caused by lack of sleep or driving during night-time hours, often result in serious injury or fatality. Sleepiness detection technology is rapidly emerging as a sleepiness risk mitigation strategy for drivers. Continuous monitoring technologies assess and alert to driver sleepiness in real-time, while fit for duty technologies provide a single assessment of sleepiness state. The aim of this rapid review was to evaluate and compare sleepiness detection technologies in relation to specifications, cost, target consumer group and validity.. We evaluated a range of sleepiness detection technologies suitable for consumer groups ranging from regular drivers in private vehicles through to work-related drivers within large businesses.. Continuous monitoring technologies typically ranged between $100 and $3000 AUD and had ongoing monthly costs for telematics functionality and manager alerts. Fit for duty technologies had either a one-off purchase cost or a monthly subscription cost. Of concern, the majority of commercial continuous monitoring technologies lacked scientific validation. While some technologies had promising findings in terms of their ability to detect and reduce driver sleepiness, further validation work is required. Field studies that evaluate the sensitivity and specificity of technology alerts under conditions that are regularly experienced by drivers are necessary. Additionally, there is a need for longitudinal naturalistic driving studies to determine whether sleepiness detection technologies actually reduce sleepiness-related crashes or near-crashes.. There is an abundance of sleepiness detection technologies on the market, but a majority lacked validation. There is a need for these technologies and their validation to be regulated by a driver safety body. Otherwise, consumers will base their technology choices on cost and features, rather than the ability to save lives.
Topics: Accidents, Traffic; Automobile Driving; Humans; Sleep; Sleepiness; Wakefulness
PubMed: 34338222
DOI: 10.1088/1361-6579/abfbb8 -
Neurology India 2023
Topics: Humans; Intracranial Hypotension; Sleepiness; Retrospective Studies; Magnetic Resonance Imaging
PubMed: 38174503
DOI: 10.4103/0028-3886.391367