Abstract: A portable digital recording system and the Nightingale sleep analyser have been applied to record polygraphical sleep signals in patients suffering from chronic pain. Using ambulatory recording the patient can sleep at home making the sleep more natural and reducing the costs. The recording system gives digital recordings of very good quality. It is shown that the Nightingale sleep analyser performs automatic sleep analysis with a quality comparable to visual interrater performance on disordered sleep. It furthermore provides means for extraction of spectral information useful for the description of the sleep-wakefulness processes and for diagnosing the sleep disorders. Using AR-model-based power spectral analysis, it is also shown that the power content in the alpha band relative to the delta power is significantly higher in patients suffering from non-specific chronic pain as compared to normal persons.
Several electroencephalographic (EEG) abnormalities have been observed during sleep in patients suffering from the fibromyalgia syndrome (FMS). In this study, 12 patients with fibromyalgia and 14 control subjects had two polysomnographic recordings obtained at home. Data from the second night were subjected to blinded manual scoring as well as signal processing using linked or 'step-wise' clustering for pattern recognition. In this procedure, a common learning set was generated using the spectral information in three 2 min EEG samples from each of the sleep stages selected from five patients with FMS and five controls. In this way, 17 characteristic EEG classes were defined. All 2 s EEG segments from the whole night from all subjects were then assigned to one of these classes. Five of the classes (dominated by 0.5–4.5 Hz activity) were more frequent in the control group, whereas three other classes (dominated by 8–11 Hz activity) were prevalent in the patient group. This trend was consistent in all sleep stages, although most striking in non-rapid eye movement (NREM) sleep. The predominance of these classes in the patient group may correspond to the alpha-EEG sleep anomaly previously reported in subjects with FMS. More importantly, as the EEG power in the lowest frequency range (prevalent in controls) probably is a marker for restorative sleep, the findings may reflect important aspects of sleep disturbances in subjects suffering from FMS, thereby contributing to some of the daytime symptoms in these patients.
Sleep disturbances and related daytime complaints are frequent in rheumatoid arthritis (RA). The aim of the current study was therefore to evaluate the effect of a newer hypnotic on sleep structure and clinical parameters in RA. Forty outpatients were randomized to a two week treatment regimen with either 7.5 mg zopiclone or placebo at bedtime. Clinical examinations were performed before and after treatment and the degree of pain, fatigue, sleepiness, morning stiffness, and activities of daily living were assessed. Two sleep questionnaires were also completed weekly. Polysomnography was performed before the study and after 14 days of treatment. Recordings were evaluated using conventional sleep scoring as well as frequency analysis of the electroencephalography (EEG). Patients in the zopiclone group had subjective improvement of sleep, but otherwise no differences in pain score or the other clinical parameters were found. Conventional sleep assessments showed only minor changes during treatment, but frequency analysis demonstrated a shift from the lower towards the higher EEG frequencies in the active treatment group. Although the modulation of the EEG can represent a non-specific pharmacologic epiphenomenon, it might also reflect a disturbance of sleep microstructure. In conclusion, treatment with zopiclone may be of value for subjective sleep complaints in selected patients with RA, but it is doubtful whether hypnotics improve daytime symptoms in this patient group.
Even though stroke patients not uncommonly suffer from sleep disturbance, post‐stroke sleep disorder is one of the least studied sequela of stroke. We present a case study providing polysomnographic evidence for the successful alleviation of persistent insomnia in a non‐depressed stroke patient by treatment with the selective serotonin reuptake inhibitor citalopram. During open treatment with citalopram the patient's sleep efficiency index improved considerably, and REM latency gradually increased. Possible causes of post‐stroke insomnia are discussed, and the suggestion is made that post‐stroke sleep disorder might possibly be attributable to stroke‐induced disruption of pathways involved in the neurophysiology of sleep, e.g. serotonergic neurotransmission.
Sleep complaints are frequent in patients with rheumatoid arthritis (RA) and sleep disturbances may contribute to pain and other daytime complaints. The aims of the current study were to compare ambulatory sleep recordings from consecutively selected patients with RA to those obtained in healthy controls, and to study the relationships between sleep structure and clinical symptoms. Sleep recordings were obtained from 41 out-patients with RA and 19 matched controls. All had clinical examinations and completed different questionnaires. Recordings were scored traditionally and, moreover, the electroencephalography (EEG) was subjected to frequency analysis. For the study of sleep-wake interactions in the patients, a graphical chain model was used. The patients had many sleep-related complaints. An increase in the number of periodic movements of the legs (PML) during sleep was seen in comparison with controls, but otherwise only minor differences were observed in classical sleep stages. Data from frequency analysis showed an increase in alpha (8-12 Hz)-EEG activity in sleep stages non-rapid eye movement (NREM) 2-4 in most sleep cycles. The statistical model demonstrated a complex but independent correlation between morning stiffness, pain and joint tenderness on the one hand, and awakenings, stage NREM2, slow-wave sleep and stage REM on the other, probably reflecting a relationship between sleep patterns and pain in RA. In conclusion, only the increase in PML and alpha-EEG activity distinguished the sleep in RA patients from that of healthy controls. However, the demonstrated interaction between daytime complaints and sleep patterns may increase the understanding and treatment of the disease. In future research, graphical chain models may improve our understanding of complex relationships between multiple variables.
Alpha electroencephalography (EEG) predominance has been described during sleep in patients suffering from the fibromyalgia syndrome (FMS). However, EEG power density in the lower frequency bands probably better reflects the restorative functions of sleep. This study was conducted to describe the energy in all frequency bands in the sleep EEG. Ambulatory sleep recordings were performed on 12 women with FMS and 14 control women. Epochs were classified according to standard criteria. Moreover, all 2-s segments (n = 287 355) of the EEG in non-rapid-eye-movement (NREM) 2–4 sleep were subjected to frequency analysis using autoregressive modelling. Frequency bands were: delta (0.5–3.5 Hz), theta (3.5–8 Hz), alpha (8–12 Hz), sigma (12–14.5 Hz) and beta (14.5–25 Hz). In patients with FMS, there was a predominance of EEG power in the higher frequency bands [two-way analysis of variance (ANOVA), alpha: P = 0.043; sigma: P = 0.004] at the expense of the lower frequencies (ANOVA, delta: P = 0.005; theta: P = 0.008). The same trends were obtained for the individual sleep cycles. The calculations of total delta power in the time domain showed an exponentially declining curve in healthy subjects, but a flatter decline in FMS. The decreased power in the low-frequency range might reflect a disorder in homoeostatic and circadian mechanisms during sleep and may contribute to daytime symptoms in patients with fibromyalgia.
