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Objective. Sleep staging based on full polysomnography is the gold standard in the diagnosis of many sleep disorders. It is however costly, complex, and obtrusive due to the use of multiple electrodes. Automatic sleep staging based on single-channel electro-oculography (EOG) is a promising alternative, requiring fewer electrodes which could be self-applied below the hairline. EOG sleep staging algorithms are however yet to be validated in clinical populations with sleep disorders. Approach. We utilized the SOMNIA dataset, comprising 774 recordings from subjects with various sleep disorders, including insomnia, sleep-disordered breathing, hypersomnolence, circadian rhythm disorders, parasomnias, and movement disorders. The recordings were divided into train (574), validation (100), and test (100) groups. We trained a neural network that integrated transformers within a U-Net backbone. This design facilitated learning of arbitrary-distance temporal relationships within and between the EOG and hypnogram. Main results. For 5-class sleep staging, we achieved median accuracies of 85.0% and 85.2% and Cohen’s kappas of 0.781 and 0.796 for left and right EOG, respectively. The performance using the right EOG was significantly better than using the left EOG, possibly because in the recommended AASM setup, this electrode is located closer to the scalp. The proposed model is robust to the presence of a variety of sleep disorders, displaying no significant difference in performance for subjects with a certain sleep disorder compared to those without. Significance. The results show that accurate sleep staging using single-channel EOG can be done reliably for subjects with a variety of sleep disorders.

Non-rapid eye movement parasomnia disorders, also called disorders of arousal, are characterized by abnormal nocturnal behaviours, such as confusional arousals or sleep walking. Their pathophysiology is not yet fully understood, and objective diagnostic criteria are lacking. It is known, however, that behavioural episodes occur mostly in the beginning of the night, after an increase in slow-wave activity during slow-wave sleep. A better understanding of the prospect of such episodes may lead to new insights in the underlying mechanisms and eventually facilitate objective diagnosis. We investigated temporal dynamics of transitions from slow-wave sleep of 52 patients and 79 controls. Within the patient group, behavioural and non-behavioural N3 awakenings were distinguished. Patients showed a higher probability to wake up after an N3 bout ended than controls, and this probability increased with N3 bout duration. Bouts longer than 15 min resulted in an awakening in 73% and 34% of the time in patients and controls, respectively. Behavioural episodes reduced over sleep cycles due to a reduction in N3 sleep and a reducing ratio between behavioural and non-behavioural awakenings. In the first two cycles, N3 bouts prior to non-behavioural awakenings were significantly shorter than N3 bouts advancing behavioural awakenings in patients, and N3 awakenings in controls. Our findings provide insights in the timing and prospect of both behavioural and non-behavioural awakenings from N3, which may result in prediction and potentially prevention of behavioural episodes. This work, moreover, leads to a more complete characterization of a prototypical hypnogram of parasomnias, which could facilitate diagnosis.

Objective: To study the effect of clonidine administrated as a co-analgesic during scoliosis surgery, on the neuromonitoring of spinal motor pathways. Methods: Using standardized intraoperative monitoring, we compared the time course of peripherally and transcranially electrically evoked motor potentials (TcEMEPs) before and after injection of a single bolus of clonidine in children under total intravenous anesthesia (TIVA). MEP data were obtained from 9 patients and somatosensory evoked potentials (SSEPs) were obtained from 2 patients. The potential effect of clonidine on mean blood pressure (BP) was controlled. Results: TcEMEPs from upper and lower limbs rapidly showed significant drops in amplitude after the injection of clonidine. Amplitudes reached minimal values within five minutes and remained very weak for at least 10–20 minutes during which monitoring of the central motor pathways was severely compromised. SSEPs were not altered during maximal amplitude depression of the TcEMEPS. Conclusions: This is the first report showing that clonidine severely interferes with neuromonitoring of the spinal cord motor pathways. The results are discussed in light of the literature describing the effects of dexmedetomidine, another α-2 adrenergic agonist. The experimental and literature data point to central mechanisms taking place at both the spinal and cerebral levels. Therefore, clonidine as well as other α-2 adrenergic agonists should be used with extreme caution in patients for whom neuromonitoring of the motor pathways is required during surgery., SCOPUS: ar.j, info:eu-repo/semantics/published