Poor Sleep and Impaired Self-Care: Towards a Comprehensive Model Linking Sleep, Cognition, and Heart Failure Outcomes

Background: Persons with heart failure (HF) have significantly lower sleep quantity and quality than persons without HF. The purpose of this article is to propose a conceptual model describing how poor sleep may contribute to inadequate self-care and untoward outcomes in persons with HF. Aims: Our overarching hypothesis is that sleep affects self-care and outcomes through its effects on cognition. Building on the work of others, we outline a conceptual model that illustrates that even transient sleep disruption prevents sleep-related restorative processes and contributes to cognitive dysfunction—especially in the 25–50% of HF patients with existing cognitive impairment. Poor sleep may be sufficient to impair cognition to a level that interferes with higher order functions involved in effective HF self-care practices. Through these mechanisms, inadequate sleep may contribute to poor outcomes such as low health-related quality of life and greater risk of unplanned hospitalization. Conclusion: The proposed model (1) bridges physical, neuropsychological and behavioral phenomena, (2) suggests a mechanism by which poor sleep affects daytime behavior, and (3) is empirically testable. Exploring factors that interfere with sleep may improve self-care and outcomes in persons with HF

Dynamic ensemble prediction of cognitive performance in spaceflight

During spaceflight, astronauts face a unique set of stressors, including microgravity, isolation, and confinement, as well as environmental and operational hazards. These factors can negatively impact sleep, alertness, and neurobehavioral performance, all of which are critical to mission success. In this paper, we predict neurobehavioral performance over the course of a 6-month mission aboard the International Space Station (ISS), using ISS environmental data as well as self-reported and cognitive data collected longitudinally from 24 astronauts. Neurobehavioral performance was repeatedly assessed via a 3-min Psychomotor Vigilance Test (PVT-B) that is highly sensitive to the effects of sleep deprivation. To relate PVT-B performance to time-varying and discordantly-measured environmental, operational, and psychological covariates, we propose an ensemble prediction model comprising of linear mixed effects, random forest, and functional concurrent models. An extensive cross-validation procedure reveals that this ensemble outperforms any one of its components alone. We also identify the most important predictors of PVT-B performance, which include an individual's previous PVT-B performance, reported fatigue and stress, and temperature and radiation dose. This method is broadly applicable to settings where the main goal is accurate, individualized prediction of human behavior involving a mixture of person-level traits and irregularly measured time series

Effects of sleep deprivation on neural functioning: an integrative review

Sleep deprivation has a broad variety of effects on human performance and neural functioning that manifest themselves at different levels of description. On a macroscopic level, sleep deprivation mainly affects executive functions, especially in novel tasks. Macroscopic and mesoscopic effects of sleep deprivation on brain activity include reduced cortical responsiveness to incoming stimuli, reflecting reduced attention. On a microscopic level, sleep deprivation is associated with increased levels of adenosine, a neuromodulator that has a general inhibitory effect on neural activity. The inhibition of cholinergic nuclei appears particularly relevant, as the associated decrease in cortical acetylcholine seems to cause effects of sleep deprivation on macroscopic brain activity. In general, however, the relationships between the neural effects of sleep deprivation across observation scales are poorly understood and uncovering these relationships should be a primary target in future research