Analysis of Sleep Fragmentation and Sleep Structure in Patients With Sleep Apnea and Normal Volunteers

Abstract

Sleep disorders have a high prevalence. Sleep disorders are recognized first by the complaint of nonrestorative sleep. A quantification of the disorder is done by the investigation in a sleep laboratory. The investigation in the sleep laboratory examines the EEG, EOG and EMG to derive sleep stages. This is a labor intensive sleep scoring after the polysomnography investigation. Usually the time course of the sleep stages is quantified in terms of percentages of stages related to total sleep time and the latencies for the individual stages. The additional feature of transitions between sleep stages and the disruption of sleep, which corresponds to periods of wakefulness during sleep are not evaluated systematically. We have evaluated these transitions using a statistical approach. We have detected systematic differences in the distributions o sleep stages and wake states during sleep. This differences were investigates in normal subjects and patients with sleep apnea. Then these differences were investigated in different species. The difference in the distributions can be explained only by fundamentally different regulation of sleep and wakefulness.

Quantification of the Fragmentation of Rest-Activity Patterns in Elderly Individuals Using a State Transition Analysis

“…Our state-transitional approach to the analysis of actigraphic data builds upon the work of others who have applied similar approaches to the analysis of polysomnographic data. [12][13][14][15][16][17][18][19][20][21][22][23][39][40] While specific analyses vary, all of these approaches involve considering polysomnographic data as a series of transitions between discrete states, and describing the frequency and temporal distribution of these transitions. Some have used a Mar-not differ significantly between men and women, allowing men and women to be pooled for the purposes of this analysis.…”

“…Among these are approaches that model such data as a series of transitions between discrete states, and seek to describe the frequency and distribution of such transitions. [10][11][12][13][14][15][16][17][18][19][20][21][22][23] We are not familiar with any attempt to apply these statetransition approaches to actigraphic data. Actigraphy is less physiologically comprehensive than polysomnography; however, as it can be done economically and nonintrusively for long periods of time outside of the laboratory setting, it has some…”

Unique sleep‐stage transitions determined by obstructive sleep apnea severity, age and gender

“…The complex interactions of different neuronal networks result in stable and rapid transitions (Saper, Fuller, Pedersen, Lu, & Scammell, 2010). In obstructive sleep apnea (OSA), patients' sleep is increasingly fragmented, caused by arousals, leading to excessive daytime sleepiness (Bianchi, Cash, Mietus, Peng, & Thomas, 2010;Pataka & Riha, 2009;Penzel et al, 2005). Apart from daytime sleepiness, manifold co-morbidities and high economic costs are associated with the disorder (AlGhanim, Comondore, Fleetham, Marra, & Ayas, 2008;Parati, Lombardi, & Narkiewicz, 2007).…”

Survival analysis indicates that age-related decline in sleep continuity occurs exclusively during NREM sleep

“…Survival-based analyses allow the quantification of the relative distribution of bout lengths, and can provide information about the underlying physiology involved in initiating, maintaining, and terminating each sleep state. This method has been used in individuals with sleep apnea to quantify the differences in the hazard of awakening (Norman, et al, 2006,Penzel, et al, 2005) and falling back to sleep (Penzel, et al, 2005) compared with unaffected individuals.…”