639 resultados para daytime sleepiness


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OBJECTIVE: To estimate the prevalence of excessive daytime sleepiness (EDS) and its associated factors in a mixed population of employed Australian workers. METHODS: Study participants (n = 707) were volunteers from various Melbourne workplaces, participating in a workplace physical activity program in 2008. Daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS), with EDS defined as ESS scores >10. RESULTS: In this population of adult employees (40.0% male; mean age 40.2 ± 10.4 years), prevalence of EDS was 16.0%. Characteristics associated with EDS and higher ESS scores were age, higher body mass index, markers of poorer diet, and markers of poorer mental health. CONCLUSIONS: Excessive daytime sleepiness is potentially an important contributor to lower productivity and poorer mental health in the workplace. Our finding suggests that workplace health programs aimed at improving diet and body weight may also help alleviate EDS.

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Previous studies have revealed that students who work and study build up sleep deficits during the workweek, which can trigger a sleep rebound during days off. The objective of this study was to investigate the impact of working/non-working on sleepiness during days off among high school students. The study population, aged 14-21 years, attended evening classes in Sao Paulo, Brazil. For the study, the students completed questionnaires on living conditions, health, and work; wore actigraphs; and completed the Karolinska Sleepiness Scale (KSS). To predict sleepiness, a logistic regression analysis was performed. Excessive sleepiness was observed on the first day off among working students. Results suggest that working is a significant predictor for sleepiness and that two shifts of daily systematic activities, study and work, might lead to excessive daytime sleepiness on the first day off. Further, this observed excessive sleepiness may reflect the sleep debt accumulated during the workweek.

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To assess frequency and characteristics of excessive daytime sleepiness (EDS) in restless legs syndrome (RLS) and the evolution of EDS under different RLS therapies.

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We aimed to investigate the differential roles of hypocretin versus dopamine dysfunction versus excessive daytime sleepiness (EDS) in the development of hyposmia. Olfaction in patients with Parkinson disease, restless leg syndrome, narcolepsy with cataplexy, EDS, and healthy controls was compared.

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BACKGROUND/AIMS Clinical differentiation between organic hypersomnia and non-organic hypersomnia (NOH) is challenging. We aimed to determine the diagnostic value of sleepiness and performance tests in patients with excessive daytime sleepiness (EDS) of organic and non-organic origin. METHODS We conducted a retrospective comparison of the multiple sleep latency test (MSLT), pupillography, and the Steer Clear performance test in three patient groups complaining of EDS: 19 patients with NOH, 23 patients with narcolepsy (NAR), and 46 patients with mild to moderate obstructive sleep apnoea syndrome (OSAS). RESULTS As required by the inclusion criteria, all patients had Epworth Sleepiness Scale (ESS) scores >10. The mean sleep latency in the MSLT indicated mild objective sleepiness in NOH (8.1 ± 4.0 min) and OSAS (7.2 ± 4.1 min), but more severe sleepiness in NAR (2.5 ± 2.0 min). The difference between NAR and the other two groups was significant; the difference between NOH and OSAS was not. In the Steer Clear performance test, NOH patients performed worst (error rate = 10.4%) followed by NAR (8.0%) and OSAS patients (5.9%; p = 0.008). The difference between OSAS and the other two groups was significant, but not between NOH and NAR. The pupillary unrest index was found to be highest in NAR (11.5) followed by NOH (9.2) and OSAS (7.4; n.s.). CONCLUSION A high error rate in the Steer Clear performance test along with mild sleepiness in an objective sleepiness test (MSLT) in a patient with subjective sleepiness (ESS) is suggestive of NOH. This disproportionately high error rate in NOH may be caused by factors unrelated to sleep pressure, such as anergia, reduced attention and motivation affecting performance, but not conventional sleepiness measurements.

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Sleep-disordered breathing and excessive sleepiness may be more common in commercial vehicle drivers than in the general population. The relative importance of factors causing excessive sleepiness and accidents in this population remains unclear. We measured the prevalence of excessive sleepiness and sleep-disordered breathing and assessed accident risk factors in 2,342 respondents to a questionnaire distributed to a random sample of 3,268 Australian commercial vehicle drivers and another 161 drivers among 244 invited to undergo polysomnography. More than half (59.6%) of drivers had sleep-disordered breathing and 15.8% had obstructive sleep apnea syndrome. Twenty-four percent of drivers had excessive sleepiness. Increasing sleepiness was related to an increased accident risk. The sleepiest 5% of drivers on the Epworth Sleepiness Scale and Functional Outcomes of Sleep Questionnaire had an in-creased risk of an accident (odds ratio [OR] 1.91, p = 0.02 and OR 2.23, p < 0.01, respectively) and multiple accidents (OR 2.67, p < 0.01 and OR 2.39, p = 0.01), adjusted for established risk factors. There was an increased accident risk with narcotic analgesic use (OR 2.40, p < 0.01) and antihistamine use (OR 3.44, p = 0.04). Chronic excessive sleepiness and sleep-disordered breathing are common in Australian commercial vehicle drivers. Accident risk was related to increasing chronic sleepiness and antihistamine and narcotic analgesic use.

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Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.

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Background: When experiencing sleep problems for the first time, consumers may often approach community pharmacists for advice as they are easily accessible health care professionals in the community. In Australian community pharmacies there are no specific tools available for use by pharmacists to assist with the assessment and handling of consumers with sleep enquiries. Objective: To assess the feasibility of improving the detection of sleep disorders within the community through the pilot of a newly developed Community Pharmacy Sleep Assessment Tool (COP-SAT). Method: The COP-SAT was designed to incorporate elements from a number of existing, standardized, and validated clinical screening measures. The COP-SAT was trialed in four Australian community pharmacies over a 4-week period. Key findings: A total of 241 community pharmacy consumers were assessed using the COP-SAT. A total of 74 (30.7%) were assessed as being at risk of insomnia, 26 (10.7%) were at risk of daytime sleepiness, 19 (7.9%) were at risk of obstructive sleep apnea, and 121 (50.2%) were regular snorers. A total of 116 (48.1%) participants indicated that they consume caffeine before bedtime, of which 55 (47%) had associated symptoms of sleep onset insomnia. Moreover, 85 (35%) consumed alcohol before bedtime, of which 50 (58%) experienced fragmented sleep, 50 (58%) were regular snorers, and nine (10.6%) had apnea symptoms. The COP-SAT was feasible in the community pharmacy setting. The prevalence of sleep disorders in the sampled population was high, but generally consistent with previous studies on the general population. Conclusion: A large proportion of participants reported sleep disorder symptoms, and a link was found between the consumption of alcohol and caffeine substances at bedtime and associated symptoms. While larger studies are needed to assess the clinical properties of the tool, the results of this feasibility study have demonstrated that the COP-SAT may be a practical tool for the identification of patients at risk of developing sleep disorders in the community.

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Childbirth is an extraordinary, everyday experience; in 2011, 301 617 infants were born in Australia [1], resulting in countless potential occurrences of sleep disturbance and subsequent daytime sleepiness. While the relationship between sleep and sleepiness has been heavily investigated in the vulnerable sub-populations of shift workers and patients with sleep disorders, comparatively postpartum women have been overlooked. Previous research has reported slower reaction times to the Psychomotor Vigilance Task [2] and shorter sleep onset in the multiple sleep latency test [3] in new mothers compared with control women. However little is known about change in sleep and sleepiness over time or potential interactions with infant care behaviour choices, such as co-sleeping (mother and infant sharing a bed). This study aims to investigate change in new mothers sleep quantity, sleep quality and resulting daytime sleepiness over postpartum weeks 6, 12 and 18, while evaluating the impact of co-sleeping.

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Introduction: Mothers’ sleep during the postpartum period is commonly characterised by bouts of sleep across the night, resulting in low sleep efficiency and daytime sleepiness. Understanding of the nature of mothers’ sleep disruption needs to incorporate indices of both sleep quantity and sleep quality, but objective assessment of sleep disturbance experienced during the first postpartum months has not been investigated in great detail. This longitudinal study aimed to objectively measure mothers’ sleep during the first 18 weeks postpartum, to ascertain the level of sleep disturbance experienced. Method: Eleven mothers (Mean age = 29.82, SD = 4.45) from Australia wore Actiwatch-2 devices for up to 7 days and nights at 6, 12 and 18 weeks postpartum. For each night of recording, a number of sleep bouts were identified. Total sleep time (TST) was calculated as the total number of minutes across the night within these bouts. Sleep efficiency was calculated as the percentage of minutes across the night classified as being part of a sleep bout, with higher scores indicating higher efficiency. Sleep quality captured the efficiency of sleep within sleep bouts, and was calculated as the percentage of epochs classified as sleep within sleep bouts, with higher scores indicating higher sleep quality. Results: At 6 weeks postpartum, mean total sleep time was 420.22 minutes (SD = 50.61). Total sleep time did not significantly differ across the assessment; however there was a trend towards an increase over time. Sleep efficiency increased across the time periods (F(2,10) = 10.30, p = .001), with a significant increase between week 12 and week 18. At 6 weeks postpartum, mean sleep quality was 93.15% (SD = 2.68) and scores did not significantly change across the assessment periods. While there was no relationship between sleep efficiency and sleep quality during weeks 6 and 12, a significant positive relationship was observed at week 18, r2 = .52, p = .013. Conclusions: Within this sample, a low level of disruption was consistently shown within the mothers’ night time sleep bouts. However, overall sleep efficiency suggested a significant proportion of time spent awake between sleep bouts. While TST remained stable over time, overall sleep efficiency improved, suggesting the mothers’ sleep was becoming more consolidated. A single sleep bout a night was not often experienced.

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Objectives Actigraphy can reliably assess sleep in healthy adults and be used to estimate total sleep time in suspected obstructive sleep apnoea (OSA) patients. We compared sleep quality for Continuous Positive Air Pressure (CPAP) treated OSA patients and controls, evaluating the impact of stopping CPAP for one night. Methods 11 men, aged 51–75 years (m = 65.6 years), compliant CPAP users, treated for 1–19 years (m = 7.8 years) wore Cambridge Neurotechnology Ltd actiwatches for one night while using CPAP and for one night sleeping without CPAP. A control group of 11 healthy men, aged 63–74 years (m = 64.1 years) slept normally whilst wearing an actiwatch. Subsequent daytime sleepiness was recorded using Karolinska sleepiness scores (KSS). Results Actimetry showed no significant differences between actual sleep time, sleep efficiency, sleep disturbance index or number of wake bouts when comparing OSA participants using CPAP, with controls; there was no difference in subsequent daytime sleepiness, control KSS = 4.21, OSA KSS = 4.17. Without CPAP there was no significant difference in sleep length or sleep onset latency compared with using CPAP, but there was a significant impact on sleep quality as shown by: increased sleep disturbance index from 7.9 to 13.8 [t(10) = 3.510, P < 0.05], decreased percent of actual sleep from 92.05% to 86.15% [t(10) = 3.51, P < 0.05], decreased sleep efficiency from 86.6% to 81% [t(10) = 2.204, P < 0.05] and increased number of wake bouts from 29 to 42.5 [t(10) = 3.877, P < 0.05]. Daytime sleepiness became significantly worse increasing from KSS 4.17 to 6.27 [t(10) = )4.96, P < 0.05]. Conclusion There was no disparity in sleep quality or KSS scores between CPAP treated OSA patients and healthy controls of a similar age. Treated OSA patients obtained quality sleep with no elevated day time sleepiness. However, cessation of treatment for one night caused sleep quality to deteriorate despite a comparable sleep time; the deterioration in sleep quality could explain the increase in daytime sleepiness. OSA patients need to know that even short-term noncompliance with CPAP treatment significantly impairs sleep quality, leading to excessive sleepiness during monotonous tasks such as driving. Actigraphy successfully identified nights of non-compliance in treated OSA patients; but did not differentiate between the sleep of CPAP treated OSA patients and healthy controls.

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Sleep disturbance after mild traumatic brain injury (mTBI) is commonly reported as debilitating and persistent. However, the nature of this disturbance is poorly understood. This study sought to characterize sleep after mTBI compared with a control group. A cross-sectional matched case control design was used. Thirty-three persons with recent mTBI (1–6 months ago) and 33 age, sex, and ethnicity matched controls completed established questionnaires of sleep quality, quantity, timing, and sleep-related daytime impairment. The mTBI participants were compared with an independent sample of close-matched controls (CMCs; n=33) to allow partial internal replication. Compared with controls, persons with mTBI reported significantly greater sleep disturbance, more severe insomnia symptoms, a longer duration of wake after sleep onset, and greater sleep-related impairment (all medium to large effects, Cohen's d>0.5). No differences were found in sleep quantity, timing, sleep onset latency, sleep efficiency, or daytime sleepiness. All findings except a measure of sleep timing (i.e., sleep midpoint) were replicated for CMCs. These results indicate a difference in the magnitude and nature of perceived sleep disturbance after mTBI compared with controls, where persons with mTBI report poorer sleep quality and greater sleep-related impairment. Sleep quantity and timing did not differ between the groups. These preliminary findings should guide the provision of clearer advice to patients about the aspects of their sleep that may change after mTBI and could inform treatment selection.

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Tese de mestrado, Ciências do Sono, Faculdade de Medicina, Universidade de Lisboa, 2015