Variability and predictability in sleep patterns of chronic insomniacs

Abstract

SUMMAR Y Sleep of chronic insomniacs is often characterized by extensive night-to-night variability. To date, no study has examined this variability with long series of daily sleep data. The present study examined night-to-night variability with a sample of 106 participants meeting DSM-IV diagnostic criteria for persistent primary insomnia. Participants completed daily sleep diaries for an average of 31 days (range: 18-56). Sleep efficiency, sleep onset latency and wake after sleep onset were derived from this measure. Despite evidence of extensive night variability, results showed that sleep patterns could be classified in three clusters. The first one was characterized by a high probability of having poor sleep, the second one by a low and decreasing probability, and the third one by a constant median probability of having a poor sleep, which is an unpredictable sleep pattern. In the first cluster, poor sleep was expected each night for patients with a predominance mixed insomnia including the three insomnia subtypes. In the second cluster, patients presented moderate insomnia, sleep-onset latency below the threshold level and a predominance of sleep-maintenance insomnia. In the third pattern, poor nights seemed unpredictable for patients with moderate to severe insomnia associated with the lowest proportion of sleep-maintenance insomnia. Overall, sleep was predictable for about two-thirds of individuals, whereas it was unpredictable for about one-third. These findings confirm the presence of extensive variability in the sleep of chronic insomniacs and that poor sleep may be predictable for some of them. Additional research is needed to characterize those sleep patterns in terms of clinical features and temporal course.

Effects of Yoga and Aerobic Exercise on Actigraphic Sleep Parameters in Menopausal Women with Hot Flashes

“…14,30 The CV values at both baseline and week 11-12 in our study were similar to those reported in community-dwelling, relatively healthy middle-aged and older women and men. 25,26 The focus of this analysis was not on examining the extent of nightto-night variability in relation to perceived sleep quality, hot flashes, or other baseline characteristics, but such an analysis would enhance understanding of the effect of sleep variability on symptoms and quality of life.…”

Complexity analysis of sleep and alterations with insomnia based on non-invasive techniques

“…One reason for this is that individuals with insomnia usually demonstrate night-tonight variability in their sleep and as such one or two nights of PSG are unlikely to be representative [8][9][10]. An alternative to PSG is actigraphy, which involves the use of an accelerometer worn on either the wrist or ankle.…”

Characterization of Patients Who Present With Insomnia: Is There Room for a Symptom Cluster-Based Approach?

“…There have been previous attempts to identify nighttime and daytime symptom cluster profiles in patients with insomnia disorder using data-driven approaches. [8][9][10][11][12][13] Similar attempts have been published characterizing the heterogeneity of obstructive sleep apnea. 14,15 However, most of these studies used cluster analysis to characterize this heterogeneity.…”

“…A number of studies have highlighted differential outcomes associated with short versus long objective sleep. [38][39][40][41][42]59 In contrast to these top-down approaches, data-driven methods, such as cluster analysis, have been applied to this area and have revealed that daytime symptoms such as sleepiness, fatigue, mood and sleep hygiene practices, 9 nighttime symptoms such as objective sleep parameters, 10 night-to-night variability and longitudinal development of subjective sleep variables, 11,17 and dysfunctional beliefs about sleep 12 uniquely fall together in identifiable and meaningful clusters. Others have used both sleep and psychiatric history, and daytime and nighttime symptoms to identify symptom clusters.…”