Background: Normal sleep is associated with typical physiological changes in both the central and autonomic nervous systems. In particular, nocturnal blood pressure dipping has emerged as a strong marker of normal sleep physiology, whereas the absence of dipping or reverse dipping has been associated with cardiovascular risk. However, nocturnal blood pressure is not measured commonly in clinical practice. Heart rate (HR) dipping in sleep may be a similar important marker and is measured routinely in at-home and in-laboratory sleep testing.
Methods: We performed a retrospective cross-sectional analysis of diagnostic polysomnography in a clinically heterogeneous cohort of n=1047 adults without sleep apnea.
Results: We found that almost half of the cohort showed an increased HR in stable nonrapid eye movement sleep (NREM) compared to wake, while only 13.5% showed a reduced NREM HR of at least 10% relative to wake. The strongest correlates of HR dipping were younger age and male sex, whereas the periodic limb movement index (PLMI), sleep quality, and Epworth Sleepiness Scale (ESS) scores were not correlated with HR dipping. PLMI was however significantly correlated with metrics of impaired HR variability (HRV): increased low-frequency power and reduced high-frequency power. HRV metrics were unrelated to sleep quality or the ESS value. Following the work of Vgontzas et al, we also analyzed the sub-cohort with insomnia symptoms and short objective sleep duration. Interestingly, the sleep-wake stage-specific HR values depended upon insomnia symptoms more than sleep duration.
Conclusion: While our work demonstrates heterogeneity in cardiac metrics (HR and HRV), the population analysis suggests that pathological signatures of HR (nondipping and elevation) are common even in this cohort selected for the absence of sleep apnea. Future prospective work in clinical populations will further inform risk stratification and set the stage for testing interventions.
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http://dx.doi.org/10.2147/NSS.S155733 | DOI Listing |
JMIR Form Res
December 2024
Department of Sports Science, College of Education, Zhejiang University, No. 866, Yuhangtang Road, Hangzhou, 310030, China, 86 18667127699.
Background: Smartwatches are increasingly popular for physical activity and health promotion. However, ongoing validation studies on commercial smartwatches are still needed to ensure their accuracy in assessing daily activity levels, which is important for both promoting activity-related health behaviors and serving research purposes.
Objective: This study aimed to evaluate the accuracy of a popular smartwatch, the Huawei Watch GT2, in measuring step count (SC), total daily activity energy expenditure (TDAEE), and total sleep time (TST) during daily activities among Chinese adults, and test whether there are population differences.
JMIR Ment Health
December 2024
Otsuka Pharmaceutical Development & Commercialization, Inc, 508 Carnegie Center Drive, Princeton, NJ, 08540, United States, 1 609 535 9035.
Background: Sleep-wake patterns are important behavioral biomarkers for patients with serious mental illness (SMI), providing insight into their well-being. The gold standard for monitoring sleep is polysomnography (PSG), which requires a sleep lab facility; however, advances in wearable sensor technology allow for real-world sleep-wake monitoring.
Objective: The goal of this study was to develop a PSG-validated sleep algorithm using accelerometer (ACC) and electrocardiogram (ECG) data from a wearable patch to accurately quantify sleep in a real-world setting.
Nat Sci Sleep
December 2024
Department of Anesthesiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People's Republic of China.
Purpose: Numerous studies have identified a correlation between sleep and delirium; however, the causal relationship remains ambiguous. This bidirectional two-sample Mendelian randomization (MR) study was conducted to examine the possible causal relationships between sleep traits and delirium.
Patients And Methods: Utilizing genome-wide association studies (GWAS), we identified ten sleep traits: chronotype, sleep duration, short sleep duration, long sleep duration, daytime napping, daytime sleepiness, insomnia, number of sleep episodes (NSE), sleep efficiency, and rapid eye movement sleep behavior disorder (RBD).
Nat Sci Sleep
December 2024
Department of Physical Education & Sport Sciences, University of Limerick, Castletroy, Limerick, Ireland.
Purpose: It is presumed by many that acute sleep loss results in degraded in-game esports (competitive, organized video game play) performance. However, this has not been experimentally investigated to date. The objective of the current experiment was to elucidate whether ~29hrs of total sleep deprivation impacts in-game performance for the popular esport
Patients And Methods: Twenty skill-matched pairs (N = 40 total) were recruited.
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