Circadian adaptation to night shift work is associated with higher REM sleep duration

Sleep schedules and MSLT-based diagnosis of narcolepsy type 2 and idiopathic hypersomnia: Exploring potential associations in a large clinical sample

Differential diagnosis of narcolepsy type 2 and idiopathic hypersomnia relies on the frequency of sleep-onset rapid eye movement periods observed on the Multiple Sleep Latency Test. This study investigated whether variations in sleep schedules, particularly delayed sleep-wake patterns, contribute to the diagnostic distinction between narcolepsy type 2 and idiopathic hypersomnia. The study included 871 patients aged 18-39 years (316 with narcolepsy type 2, 555 with idiopathic hypersomnia). These patients were diagnosed based on MSLT results following polysomnography from November 2013 to November 2017. Patients' sleep habits, including bedtime and wake-up times on weekdays and weekends during the 2 weeks preceding the polysomnography/Multiple Sleep Latency Test, were assessed using self-reported sleep logs. A multivariate logistic regression analysis was conducted to identify factors associated with narcolepsy type 2 diagnosis. The analysis revealed that being male (p < 0.001), younger age (p < 0.001), shorter weekday sleep duration (p < 0.05), and a delayed weekday sleep midpoint time (p < 0.01) were significantly associated with a diagnosis of narcolepsy type 2. The study suggests that the conventionally fixed schedule of polysomnography and Multiple Sleep Latency Test administration may have contributed to the increased occurrence of sleep-onset rapid eye movement periods particularly in individuals with a delayed sleep-wake schedule.

Interrelationships between sleep quality, circadian phase and rapid eye movement sleep: Deriving chronotype from sleep architecture

The relationship between sleep quality, circadian rhythms, and REM sleep has not been deliberately investigated in previous scientific reports. Here, we aim to examine the associations between these factors by specifically focusing on the temporal dynamics of REM sleep in all night records, as well as to provide a new, objective, EEG-derived chronotype indicator. To achieve those aims, a wearable EEG headband recorded home sleep database was analyzed in terms of total sleep time (TST), REM dynamics, core body temperature, wrist actigraphy, Munich Chronotype Questionnaire, Pittsburgh Sleep Quality Index, subjective morning sleep quality, and Likert Sleepiness Scale. Furthermore, records from the Budapest-Munich database of polysomnography (PSG) were analyzed for REM sleep patterns, TST, arousal dynamics, and age. The results show that the timing of the crest of REM propensity (REMmaxprop) reliably correlated with weekly average actigraphy sleep midpoints, subjective chronotype measures, and also tended to be associated with core body temperature. Additionally, REMmaxprop emerged at earlier times in children and middle-aged participants as compared to teenagers and young adults. Subjective sleep quality exclusively reflected the shortening of headband-recorded sleep as compared to weekly average TST. REM percent negatively correlated with NREM arousal density. It can be concluded that the overnight REM sleep dynamic (REMmaxprop) is a putative indicator of circadian phase/chronotype with potential relevance for home sleep studies. However, sleep quality indices are less conclusive in between-subjects design, urging the need for longitudinal investigations allowing interindividual analyses.

Assessing cardiovascular stress based on heart rate variability in female shift workers: a multiscale-multifractal analysis approach

Introduction

Sleep-wake cycle disruption caused by shift work may lead to cardiovascular stress, which is observed as an alteration in the behavior of heart rate variability (HRV). In particular, HRV exhibits complex patterns over different time scales that help to understand the regulatory mechanisms of the autonomic nervous system, and changes in the fractality of HRV may be associated with pathological conditions, including cardiovascular disease, diabetes, or even psychological stress. The main purpose of this study is to evaluate the multifractal-multiscale structure of HRV during sleep in healthy shift and non-shift workers to identify conditions of cardiovascular stress that may be associated with shift work.

Methods

The whole-sleep HRV signal was analyzed from female participants: eleven healthy shift workers and seven non-shift workers. The HRV signal was decomposed into intrinsic mode functions (IMFs) using the empirical mode decomposition method, and then the IMFs were analyzed using the multiscale-multifractal detrended fluctuation analysis (MMF-DFA) method. The MMF-DFA was applied to estimate the self-similarity coefficients, α(q, τ), considering moment orders (q) between -5 and +5 and scales (τ) between 8 and 2,048 s. Additionally, to describe the multifractality at each τ in a simple way, a multifractal index, MFI(τ), was computed.

Results

Compared to non-shift workers, shift workers presented an increase in the scaling exponent, α(q, τ), at short scales (τ < 64 s) with q < 0 in the high-frequency component (IMF1, 0.15-0.4 Hz) and low-frequency components (IMF2-IMF3, 0.04-0.15 Hz), and with q> 0 in the very low frequencies (IMF4, < 0.04 Hz). In addition, at large scales (τ> 1,024 s), a decrease in α(q, τ) was observed in IMF3, suggesting an alteration in the multifractal dynamic. MFI(τ) showed an increase at small scales and a decrease at large scales in IMFs of shift workers.

Conclusion

This study helps to recognize the multifractality of HRV during sleep, beyond simply looking at indices based on means and variances. This analysis helps to identify that shift workers show alterations in fractal properties, mainly on short scales. These findings suggest a disturbance in the autonomic nervous system induced by the cardiovascular stress of shift work.