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This retrospective study describes the effects of long-term treatment with melatonin in 33 adolescents (age range, 10-18 years) with delayed sleep phase syndrome (DSPS). Patients were treated with oral melatonin, 3 to 5 mg/day for an average period of 6 months. During the treatment, sleep onset was advanced and sleep duration was longer. Treatment was also associated with a decrease in the proportion of patients reporting school difficulties. No adverse effects of melatonin were noted. This study indicates that long-term treatment with melatonin can be beneficial for adolescents with DSPS in terms of sleep-wake schedule and school performance. [ABSTRACT FROM AUTHOR]

A patient who developed an irregular sleep-wake pattern following prolactin-secreting pituitary microadenoma is described. The patient reported difficulties in sleep onset and awakening at the desired time, which caused major dysfunction in his daily life activities. Despite these difficulties, the sleep-related complaints of the patient remained unrecognized for as long as three yrs. Statistical analyses of the patient's rest-activity patterns revealed that the disruption of the sleep-wake circadian rhythm originated from a disharmony between ultradian (semicircadian) and circadian components. The circadian component displayed shorter than 24 h periodicity most of the time, but the semicircadian component fluctuated between longer and shorter than 12 h periods. Additionally, desynchrony in terms of period length was found in the tentative analyses of the rest-activity pattern, salivary melatonin, and oral temperature. While the salivary melatonin time series data could be characterized by a best-fit cosine curve of 24 h, the time series data of oral temperature was more compatible with 28 h best-fit curve. The rest-activity cycle during the simultaneous measurements, however, was best approximated by a best-fit curve of 21h. The dysregulation of circadian rhythms occurred concomitantly, but not beforehand, with the onset of pituitary disease, thus suggesting an association between the two phenomena. This association may have interesting implications to the modeling of the circadian time-keeping system. This case also highlights the need to raise the awareness to circadian rhythm sleep disorders and to consider disruptions of sleep-wake cycle in patients with pituitary adenoma. [ABSTRACT FROM AUTHOR]

Certain sleep-wake schedule disorders (SWSDs) cannot be successfully managed clinically using conventional methods of sleep therapy. We describe two cases of SWSD, the first following head trauma and the second originating during childhood, that had been misdiagnosed by physicians for many years. After conventional treatment for SWSD with light therapy and melatonin failed to bring about substantial improvement, it was determined that they were suffering from an incurable disability. Hence, we propose new medical terminology for such cases—SWSD disability. SWSD disability is an untreatable pathology of the circadian time structure. Patients suffering from SWSD disability should be encouraged to accept the fact that they suffer from a permanent disability, and that their quality of life can only be improved if they are willing to undergo rehabilitation. It is imperative that physicians recognize the medical condition of SWSD disability in their patients and bring it to the notice of the public institutions responsible for vocational and social rehabilitation. (Chronobiology International, 18(6), 1019–1027, 2001) [ABSTRACT FROM AUTHOR]

Abstract: Arousals are considered one of the main causes of daytime sleepiness. They impede the proper flow of sleep cycles and cause weariness. Manual scoring of arousals is time-consuming, requires expert knowledge, and has high inter-scorer variability. A major difficulty in detecting arousals automatically is the existing variance across patients. Based on data mining techniques, we present a different approach to the automatic detection of arousals that overcomes the hurdle of differences in signal characteristics across patients. Offline we used a training-set of adult patients to define a set of general rules to detect arousals (termed meta-rules). This was done by analyzing the correlations between occurrences of arousals and the EEG, EMG, pulse and SaO2 signals as follows: (1) each signal was mathematically projected into several spaces (termed projected-signals); (2) from each such projected-signal, the algorithm extracted time points that indicated meaningful changes (termed critical-points); (3) data mining techniques were applied to all the critical-points to discover patterns of repeating behavior; (4) classes of patterns which were highly correlated with manually scored arousals were formalized as meta-rules. Online we used a test-set of adult patients from two other different sleep laboratories. Using the meta-rules, the algorithm extracted individual rules for each patient (termed actual-rules), and used them to automatically detect the patients’ arousals. These arousals were significantly correlated (R =0.88, p <0.0001; sensitivity=75.2%, positive predictive value=76.5%) with those detected manually by experts. Since the total number of arousals is a measure of sleep quality, this algorithm constitutes a novel approach to automatically estimate sleep quality. [Copyright &y& Elsevier]

Abstract: Autonomic function during sleep and wakefulness has been extensively investigated, however information concerning autonomic changes during the wake to sleep transition is scarce. The objective of the present study was to non-invasively characterize autonomic function and additional physiologic changes during sleep onset in normal and abnormal sleep. The estimation of autonomic function was based on time–frequency analysis of the RR interval series, using the power components in the very-low-frequency range (0.005–0.04 Hz), low-frequency (0.04–0.15 Hz), and high-frequency range (0.15–0.5 Hz). The ratio of low to high frequency power represented the sympathovagal balance. Thirty-four subjects who underwent whole night polysomnography were divided into 3 groups according to their complaints and study results: normal subjects, apneic patients (OSAS), and subjects with various sleep disorders (VSD). The results indicated a significant increase in RR interval during sleep onset, although its variability decreased; respiratory rate did not change, yet respiration became more stable; EMG amplitude and its variability decreased with sleep onset. Very-low-frequency power started to decrease significantly 2 min before sleep onset in all groups; low-frequency power decreased and high-frequency power did not change significantly in all groups, accordingly their ratio decreased and reflected a shift towards parasympathetic predominance. Although autonomic function displayed similar behavior in all subjects, OSAS and VSD patients presented a higher sympathovagal balance reflecting enhanced sympathetic predominance in those groups compared to normal subjects, both before and after sleep onset. All parameters reached a nadir at a defined time point during the process of falling asleep. We conclude that the wake–sleep transition period represents a transitional process between two physiologically different states; this transition starts with a decrease in the very slow oscillations in heart rate that anticipates a step-change resetting of autonomic function, followed by a decrease in sympathovagal balance towards the end of the process. [Copyright &y& Elsevier]