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.

No abstract

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.

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 n subjects suffering from FMS, thereby contributing to some of the daytime symptoms in these patients.

No abstract