825 resultados para sleep complaints
Resumo:
Background: Disturbed sleep is a core feature of narcolepsy with cataplexy (NC). Few studies have independently assessed sleep-disordered breathing (SDB) and periodic limb movements (PLMs) in non-homogeneous series of patients with and without cataplexy. We systematically assessed both SDB and PLMs in well-defined NC patients. Methods: We analyzed the clinical and polysomnographic features of 35 consecutive NC patients (mean age 40 ± 16 years, 51% males, 23/23 hypocretin-deficient) to assess the prevalence of SDB (apnea-hypopnea index >5) and PLMs (periodic leg movements in sleep (PLMI) >15) together with their impact on nocturnal sleep and daytime sleepiness using the multiple sleep latency test. Results: 11 (31%) and 14 (40%) patients had SDB and PLMs, respectively. SDB was associated with older age (49 ± 16 vs. 35 ± 13 years, p = 0.02), higher BMI (30 ± 5 vs. 27 ± 6, p = 0.05), and a trend towards higher PLMI (25 ± 20 vs. 12 ± 23, p = 0.052), whereas PLMs with older age (50 ± 16 vs. 33 ± 11 years, p = 0.002) and reduced and fragmented sleep (e.g. sleep efficiency of 82 ± 12% vs. 91 ± 6%, p = 0.015; sleep time of 353 ± 66 vs. 395 ± 28, p = 0.010). SDB and PLMs were also mutually associated (p = 0.007), but not correlated to daytime sleepiness. Conclusions: SDB and PLMs are highly prevalent and associated in NC. Nevertheless, SDB and PLMs are rarely severe, suggesting an overall limited effect on clinical manifestations.
Resumo:
STUDY OBJECTIVES: To describe the time structure of leg movements (LM) in obstructive sleep apnea (OSA) syndrome, in order to advance understanding of their clinical significance. LOCATION: Sleep Research Centre, Oasi Institute (IRCCS), Troina, Italy. SETTING: Sleep laboratory. PATIENTS: Eighty-four patients (16 females, 68 males, mean age 55.1 y, range 29-74 y). METHODS: Respiratory-related leg movements (RRLM) and those unrelated to respiratory events (NRLM) were examined within diagnostic polysomnograms alone and together for their distributions within the sleep period and for their periodicity. MEASUREMENTS AND RESULTS: Patients with OSA and RRLM exhibited more periodic leg movements in sleep (PLMS), particularly in NREM sleep. A gradual decrease in number of NRLM across the sleep period was observed in patients with RRLM. This pattern was less clear for RRLM. Frequency histograms of intermovement intervals of all LMs in patients with RRLM showed a prominent first peak at 4 sec, and a second peak at approximately 24 sec coincident with that of PLMS occurring in the absence of OSA. A third peak of lowest amplitude was the broadest with a maximum at approximately 42 sec. In patients lacking RRLM, NRLM were evident with a single peak at 2-4 sec. A stepwise linear regression analysis showed that, after controlling for a diagnosis of restless legs syndrome and apnea-hypopnea index, PLMS remained significantly associated with RRLM. CONCLUSION: The time structure of leg movements occurring in conjunction with respiratory events exhibit features of periodic leg movements in sleep occurring alone, only with a different and longer period. This brings into question the validity, both biologic and clinical, of scoring conventions with their a priori exclusion from consideration as periodic leg movements in sleep.
Resumo:
Heart rate and breathing rate fluctuations represent interacting physiological oscillations. These interactions are commonly studied using respiratory sinus arrhythmia (RSA) of heart rate variability (HRV) or analyzing cardiorespiratory synchronization. Earlier work has focused on a third type of relationship, the temporal ratio of respiration rate and heart rate (HRR). Each method seems to reveal a specific aspect of cardiorespiratory interaction and may be suitable for assessing states of arousal and relaxation of the organism. We used HRR in a study with 87 healthy subjects to determine the ability to relax during 5 day-resting periods in comparison to deep sleep relaxation. The degree to which a person during waking state could relax was compared to somatic complaints, health-related quality of life, anxiety and depression. Our results show, that HRR is barely connected to balance (LF/HF) in HRV, but significantly correlates to the perception of general health and mental well-being as well as to depression. If relaxation, as expressed in HRR, during day-resting is near to deep sleep relaxation, the subjects felt healthier, indicated better mental well-being and less depressive moods.
Resumo:
Lucid dreams – dreams in which the dreamer is aware that is dreaming – most frequently occur during REM sleep, yet there is some evidence suggesting that lucid dreaming can occur during NREM sleep as well. By conducting a sleep laboratory study on lucid dreams, we found two possible instances of lucidity during NREM sleep which are reported here. While lucid dreaming during NREM sleep seems to be much rarer and more difficult to achieve, it appears to be possible and is most likely to occur during N1 sleep, somewhat less likely during N2 sleep and yet to be observed during N3 sleep. Future studies should explore induction methods, underlying neural mechanisms and perceptual/dream content differences between REM and NREM lucid dreams. Furthermore, a consensus agreement is needed to define what is meant by lucid dreaming and create a vocabulary that is helpful in clarifying variable psychophysiological states that can support self-reflective awareness.
Developmental changes in sleep biology and potential effects on adolescent behavior and caffeine use
Resumo:
Adolescent development includes changes in the biological regulatory processes for the timing of sleep. Circadian rhythm changes and changes to the sleep-pressure system (sleep homeostasis) during adolescence both favor later timing of sleep. These changes, combined with prevailing social pressures, are responsible for most teens sleeping too late and too little; those who sleep least report consuming more caffeine. Although direct research findings are scarce, the likelihood of use and abuse of caffeine-laden products grows across the adolescent years due, in part, to excessive sleepiness
Resumo:
Although the increases in cognitive capacities of adolescent humans are concurrent with significant cortical restructuring, functional associations between these phenomena are unclear. We examined the association between cortical development, as measured by the sleep EEG, and cognitive performance in a sample of 9/10 year olds followed up 1 to 3 years later. Our cognitive measures included a response inhibition task (Stroop), an executive control task (Trail Making), and a verbal fluency task (FAS). We correlated sleep EEG measures of power and intra-hemispheric coherence at the initial assessment with performance at that assessment. In addition we correlated the rate of change across assessments in sleep EEG measures with the rate of change in performance. We found no correlation between sleep EEG power and performance on cognitive tasks for the initial assessment. In contrast, we found a significant correlation of the rate of change in intra-hemispheric coherence for the sigma band (11 to 16 Hz) with rate of change in performance on the Stroop (r = 0.61; p<0.02) and Trail Making (r = -0.51; p<0.02) but no association for the FAS. Thus, plastic changes in connectivity (i.e., sleep EEG coherence) were associated with improvement in complex cognitive function.
Resumo:
The aim of this descriptive analysis was to examine sleep timing, circadian phase, and phase angle of entrainment across adolescence in a longitudinal study design. Ninety-four adolescents participated; 38 (21 boys) were 9-10 years ("younger cohort") and 56 (30 boys) were 15-16 years ("older cohort") at the baseline assessment. Participants completed a baseline and then follow-up assessments approximately every six months for 2.5 years. At each assessment, participants wore a wrist actigraph for at least one week at home to measure self-selected sleep timing before salivary dim light melatonin onset (DLMO) phase - a marker of the circadian timing system - was measured in the laboratory. Weekday and weekend sleep onset and offset and weekend-weekday differences were derived from actigraphy. Phase angles were the time durations from DLMO to weekday sleep onset and offset times. Each cohort showed later sleep onset (weekend and weekday), later weekend sleep offset, and later DLMO with age. Weekday sleep offset shifted earlier with age in the younger cohort and later in the older cohort after age 17. Weekend-weekday sleep offset differences increased with age in the younger cohort and decreased in the older cohort after age 17. DLMO to sleep offset phase angle narrowed with age in the younger cohort and became broader in the older cohort. The older cohort had a wider sleep onset phase angle compared to the younger cohort; however, an age-related phase angle increase was seen in the younger cohort only. Individual differences were seen in these developmental trajectories. This descriptive study indicated that circadian phase and self-selected sleep delayed across adolescence, though school-day sleep offset advanced until no longer in high school, whereupon offset was later. Phase angle changes are described as an interaction of developmental changes in sleep regulation interacting with psychosocial factors (e.g., bedtime autonomy)
Resumo:
To test whether humans can encode words during sleep we played everyday words to men while they were napping and assessed priming from sleep played words following waking. Words were presented during non rapid eye movement (NREM) sleep. Priming was assessed using a semantic and a perceptual priming test. These tests measured differences in the proces sing of words that had been or had not been played during sleep. Synonyms to sleep played words were the targets in the semantic priming test that tapped the meaning of sleep played words. All men responded to sleep played words by producing up states in their electroencephalogram. Up states are NREM sleep specific phases of briefly increased neuronal excitability. The word evoked up states might have promoted word processing during sleep. Yet, the mean performance in the priming tests administered following sleep was at chance level, which suggests that participants as a group failed to show priming following sleep. However, performance in the two priming tests was positively correlated to each other and to the magnitude of the word evoked up states. Hence, the larger a participant’s word evoked up states, the larger his perceptual and semantic priming. Those participants who scored high on all variables must have encoded words during sleep. We conclude that some humans are able to encode words during sleep, but more research is needed to pin down the factors that modulate this ability.