247 resultados para Sleep EEG
Resumo:
BACKGROUND: Being a caregiver for a spouse with Alzheimer's disease is associated with increased risk for cardiovascular illness, particularly for males. This study examined the effects of caregiver gender and severity of the spouse's dementia on sleep, coagulation, and inflammation in the caregiver. METHODS: Eighty-one male and female spousal caregivers and 41 non-caregivers participated (mean age of all participants 70.2 years). Full-night polysomnography (PSG) was recorded in each participants home. Severity of the Alzheimer's disease patient's dementia was determined by the Clinical Dementia Rating (CDR) scale. The Role Overload scale was completed as an assessment of caregiving stress. Blood was drawn to assess circulating levels of D-dimer and Interleukin-6 (IL-6). RESULTS: Male caregivers who were caring for a spouse with moderate to severe dementia spent significantly more time awake after sleep onset than female caregivers caring for spouses with moderate to severe dementia (p=.011), who spent a similar amount of time awake after sleep onset to caregivers of low dementia spouses and to non-caregivers. Similarly, male caregivers caring for spouses with worse dementia had significantly higher circulating levels of D-dimer (p=.034) than females caring for spouses with worse dementia. In multiple regression analysis (adjusted R(2)=.270, p<.001), elevated D-dimer levels were predicted by a combination of the CDR rating of the patient (p=.047) as well as greater time awake after sleep onset (p=.046). DISCUSSION: The findings suggest that males caring for spouses with more severe dementia experience more disturbed sleep and have greater coagulation, the latter being associated with the disturbed sleep. These findings may provide insight into why male caregivers of spouses with Alzheimer's disease are at increased risk for illness, particularly cardiovascular disease.
Resumo:
BACKGROUND AND PURPOSE: Due to the increasing importance of quality of life assessments in obstructive sleep apnea (OSA) patients and due to an increased use of the International Classification of Functioning, Disability and Health (ICF), for comparative purposes it is essential to understand the relationship between health-related quality of life (HRQOL) instruments and the ICF. The purpose of this study was to compare the content covered by OSA-specific instruments using the ICF. PATIENTS AND METHODS: OSA-specific instruments were identified, including the Calgary Sleep Apnea Quality of Life Index, the Functional Outcomes of Sleep Questionnaire, the Obstructive Sleep Apnea Patient-Oriented Severity Index, and the Quebec Sleep Questionnaire, and linked to the ICF by six health professionals according to standardized guidelines. The degree of agreement between health professionals was calculated by means of the kappa statistic. RESULTS: A total of 308 concepts were identified and linked to 78 different ICF categories; 35 categories of the component body function, one category of the component body structure, 38 categories of the component activities and participation, and four categories of the component environmental factors. Only contents within the chapters mental functions, mobility and social life were addressed by all instruments. Forty-seven categories were covered by only one instrument. CONCLUSION: The ICF proved highly useful for the comparison of HRQOL instruments. This analysis may help researchers and clinicians to choose the most appropriate HRQOL instrument for a specific purpose as well as help to compare study outcomes of studies using different instruments for HRQOL assessment.
Resumo:
BACKGROUND: With the International Classification of Functioning, Disability and Health (ICF), we can now rely on a globally agreed-upon framework and system for classifying the typical spectrum of problems in the functioning of persons given the environmental context in which they live. ICF Core Sets are subgroups of ICF items selected to capture those aspects of functioning that are most likely to be affected by sleep disorders. OBJECTIVE: The objective of this paper is to outline the developmental process for the ICF Core Sets for Sleep. METHODS: The ICF Core Sets for Sleep will be defined at an ICF Core Sets Consensus Conference, which will integrate evidence from preliminary studies, namely (a) a systematic literature review regarding the outcomes used in clinical trials and observational studies, (b) focus groups with people in different regions of the world who have sleep disorders, (c) an expert survey with the involvement of international clinical experts, and (d) a cross-sectional study of people with sleep disorders in different regions of the world. CONCLUSION: The ICF Core Sets for Sleep are being designed with the goal of providing useful standards for research, clinical practice and teaching. It is hypothesized that the ICF Core Sets for Sleep will stimulate research that leads to an improved understanding of functioning, disability, and health in sleep medicine. It is of further hope that such research will lead to interventions and accommodations that improve the restoration and maintenance of functioning and minimize disability among people with sleep disorders throughout the world.
Resumo:
Elevated platelet count might reflect increased inflammation as an etiological factor for venous thromboembolism (VTE). Poor sleep, fatigue, and exhaustion are all associated with inflammation and are also common sequelae of chronic psychological stress that previously predicted increased risk of VTE. We hypothesized that platelet count would be high in patients with VTE who sleep poorly and who are fatigued and exhausted. We investigated 205 patients scheduled for thrombophilia work-up > or =3 months after an objectively diagnosed venous thromboembolic event. They completed the Jenkins Sleep Questionnaire to rate subjective sleep quality and the short forms of the Multidimensional Fatigue Symptom Inventory and Maastricht Vital Exhaustion Questionnaire. Platelet count was determined by a mechanical Coulter counter. Analyses controlled for age, sex, body mass index, time since the index event, and medication. After taking into account these covariates, poorer sleep quality (p = 0.001; DeltaR(2)= 0.046), high fatigue (p = 0.008; DeltaR(2)= 0.032), and vital exhaustion (p = 0.050; DeltaR(2)= 0.017) were all associated with elevated platelet count. In addition, high level of fatigue mediated the relationship between poor sleep quality and elevated platelet count (p = 0.046). Poor sleep quality, high levels of fatigue, and vital exhaustion were identified as correlates of an elevated platelet count in patients with a previous episode of VTE. Given the emerging role of inflammatory processes in VTE, the findings suggest a mechanism through which behavioral and chronic psychological stressors might contribute to incident and recurrent venous thrombotic events.
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A publication entitled “A default mode of brain function” initiated a new way of looking at functional imaging data. In this PET study the authors discussed the often-observed consistent decrease of brain activation in a variety of tasks as compared with the baseline. They suggested that this deactivation is due to a task-induced suspension of a default mode of brain function that is active during rest, i.e. that there exists intrinsic well-organized brain activity during rest in several distinct brain regions. This suggestion led to a large number of imaging studies on the resting state of the brain and to the conclusion that the study of this intrinsic activity is crucial for understanding how the brain works. The fact that the brain is active during rest has been well known from a variety of EEG recordings for a very long time. Different states of the brain in the sleep–wake continuum are characterized by typical patterns of spontaneous oscillations in different frequency ranges and in different brain regions. Best studied are the evolving states during the different sleep stages, but characteristic EEG oscillation patterns have also been well described during awake periods (see Chapter 1 for details). A highly recommended comprehensive review on the brain's default state defined by oscillatory electrical brain activities is provided in the recent book by György Buzsaki, showing how these states can be measured by electrophysiological procedures at the global brain level as well as at the local cellular level.
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Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.
Resumo:
Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.