Epilepsy and Sleep-Related Breathing Disturbances

Multimodal transcutaneous auricular vagus nerve stimulation: An option in the treatment of sleep bruxism in a "polyvagal" context

OBJECTIVE

To consider the possible role of the vagus nerve (VN) in the pathophysiology of sleep bruxism (SB) and introduce a multimodal protocol of transcutaneous auricular stimulation of the VN in the treatment of SB patients.

METHODS

Ten patients with SB underwent four sessions of electric transcutaneous auricular vagus nerve stimulation (ta-VNS) in specific auricular areas. The patients were advised to manually stimulate the same areas between sessions. Masticatory muscle activity and sleep parameters were measured by a polysomnography (PSG) before and after the treatment. Heart rate variability (HRV) parameters were measured during each stimulation.

RESULTS

PSG analysis revealed a statistically significant reduction in tonic SB index and tonic contraction time. HRV parameters showed a statistically significant increase in mean values of the vagal tone after each session of stimulation. No side effect was reported.

CONCLUSION

The stimulation of the VN might have a role in the treatment of SB.

Obstructive sleep apnea is associated with risk for sudden unexpected death in epilepsy (SUDEP) using rSUDEP-7

BACKGROUND AND OBJECTIVE

Evaluate relationships between PSG-confirmed OSA and SUDEP risk using the revised SUDEP Risk Inventory (rSUDEP-7).

METHODS

Identified adults with epilepsy (AWE) who underwent PSG 2004-2016 at Cleveland Clinic. OSA was defined as apnea-hypopnea index (AHI)- ≥-5/h sleep; moderate/severe OSA as AHI≥15. SUDEP risk was assessed using rSUDEP-7: higher rSUDEP-7 score, greater SUDEP risk. Associations between rSUDEP-7 score and OSA groups (AHI≥15 vs. <15) were evaluated using Wilcoxon rank-sum tests and multivariable linear models adjusting for age, sex, BMI, and smoking status. Spearman correlations measured relationships between rSUDEP-7 score with AHI and oxygen desaturation indices (ODI).

RESULTS

OSA was present in 134 (62.6 %) of 214 AWE; moderate/severe in 75 (35 %). AWE with AHI≥15 were more likely to be male and older, had higher BMI, greater frequency of tonic-clonic seizures (TCS), longer epilepsy duration, and more likely to have drug-resistant epilepsy (DRE) and sleep-related seizures (all p< 0.05). The median rSUDEP-7 score was 1 (0,3) but 37.4 % had a score ≥3 (high SUDEP risk), and 11.7 % ≥5 (highest SUDEP risk). rSUDEP-7 scores were higher in those with AHI≥15 (3 vs. 1, p = 0.001). Higher AHI and ODI 3% positively correlated with rSUDEP-7 (p=0.002 and p=0.016) while SpO2 nadir negatively correlated with rSUDEP-7 (p=0.007). After adjustments, AWE with AHI≥15 had mean rSUDEP-7 score 1.14 points (95% CI 0.55-1.72, p<0.001) higher than those with AHI<15.

DISCUSSION

AWE with PSG-confirmed moderate/severe OSA especially those who are older and have GTC had higher rSUDEP-7 scores potentially increasing their risk for SUDEP. Our findings support routine screening for OSA in AWE. Further studies confirming the significance and impact of OSA on SUDEP risk are needed.

The Clinical Spectrum of the Parasomnias

Parasomnias are defined as abnormal movements or behaviors that occur in sleep or during arousals from sleep. Parasomnias vary in frequency from episodic events that arise from incomplete sleep state transition. The framework by which parasomnias are categorized and diagnosed is based on the International Classification of Sleep Disorders-Third Edition, Text Revision (ICSD-3-TR), published by the American Academy of Sleep Medicine. The recent Third Edition, Text Revision (ICSD-3-TR) of the ICSD provides an expert consensus of the diagnostic requirements for sleep disorders, including parasomnias, based on an extensive review of the current literature.

An approach to detect and predict epileptic seizures with high accuracy using convolutional neural networks and single-lead-ECG signal

One of the epileptic patients' challenges is to detect the time of seizures and the possibility of predicting. This research aims to provide an algorithm based on deep learning to detect and predict the time of seizure from one to two minutes before its occurrence. The proposed Convolutional Neural Network (CNN) can detect and predict the occurrence of focal epilepsy seizures through single-lead-ECG signal processing instead of using EEG signals. The structure of the proposed CNN for seizure detection and prediction is the same. Considering the requirements of a wearable system, after a few light pre-processing steps, the ECG signal can be used as input to the neural network without any manual feature extraction step. The desired neural network learns purposeful features according to the labelled ECG signals and then performs the classification of these signals. Training of 39-layer CNN for seizure detection and prediction has been done separately. The proposed method can detect seizures with an accuracy of 98.84% and predict them with an accuracy of 94.29%. With this approach, the ECG signal can be a promising indicator for the construction of portable systems for monitoring the status of epileptic patients.

Sleep and Epilepsy

The relationship between sleep and epilepsy is both intimate and bidirectional. The molecular mechanisms which control circadian rhythm and the sleep/wake cycle are dysregulated in epileptogenic tissue and are themselves effected by molecular pathways for epilepsy. Sleep affects the frequency of interictal epileptiform discharges and recent research has raised new questions regarding the impact of discharges on sleep function and cognition. Epileptiform discharges themselves affect sleep architecture and increase the risk of sleep disorders. Several sleep-related epilepsy syndromes have undergone changes in their classification which highlights their intimate relationship to sleep and novel screening tools have been developed to help clinicians better differentiate epileptic seizures from sleep-related paroxysmal events. Improving sleep and addressing sleep disorders has been associated with improved seizure control and increased well-being in people with epilepsy. These interactions are discussed in detail in this review.

Optimizing Electrode Configurations for Wearable EEG Seizure Detection Using Machine Learning

Epilepsy, a prevalent neurological disorder, profoundly affects patients' quality of life due to the unpredictable nature of seizures. The development of a reliable and user-friendly wearable EEG system capable of detecting and predicting seizures has the potential to revolutionize epilepsy care. However, optimizing electrode configurations for such systems, which is crucial for balancing accuracy and practicality, remains to be explored. This study addresses this gap by developing a systematic approach to optimize electrode configurations for a seizure detection machine-learning algorithm. Our approach was applied to an extensive database of prolonged annotated EEG recordings from 158 epilepsy patients. Multiple electrode configurations ranging from one to eighteen were assessed to determine the optimal number of electrodes. Results indicated that the performance was initially maintained as the number of electrodes decreased, but a drop in performance was found to have occurred at around eight electrodes. Subsequently, a comprehensive analysis of all eight-electrode configurations was conducted using a computationally intensive workflow to identify the optimal configurations. This approach can inform the mechanical design process of an EEG system that balances seizure detection accuracy with the ease of use and portability. Additionally, this framework holds potential for optimizing hardware in other machine learning applications. The study presents a significant step towards the development of an efficient wearable EEG system for seizure detection.

Respiratory brain impulse propagation in focal epilepsy

Respiratory brain pulsations pertaining to intra-axial hydrodynamic solute transport are markedly altered in focal epilepsy. We used optical flow analysis of ultra-fast functional magnetic resonance imaging (fMRI) data to investigate the velocity characteristics of respiratory brain impulse propagation in patients with focal epilepsy treated with antiseizure medication (ASM) (medicated patients with focal epilepsy; ME, n = 23), drug-naïve patients with at least one seizure (DN, n = 19) and matched healthy control subjects (HC, n = 75). We detected in the two patient groups (ME and DN) several significant alterations in the respiratory brain pulsation propagation velocity, which showed a bidirectional change dominated by a reduction in speed. Furthermore, the respiratory impulses moved more in reversed or incoherent directions in both patient groups vs. the HC group. The speed reductions and directionality changes occurred in specific phases of the respiratory cycle. In conclusion, irrespective of medication status, both patient groups showed incoherent and slower respiratory brain impulses, which may contribute to epileptic brain pathology by hindering brain hydrodynamics.

RAFNet: Restricted attention fusion network for sleep apnea detection

Sleep apnea (SA) is a common sleep-related breathing disorder, which would lead to damage of multiple systemic organs or even sudden death. In clinical practice, portable device is an important tool to monitor sleep conditions and detect SA events by using physiological signals. However, SA detection performance is still limited due to physiological signals with time-variability and complexity. In this paper, we focus on SA detection with single lead ECG signals, which can be easily collected by a portable device. Under this context, we propose a restricted attention fusion network called RAFNet for sleep apnea detection. Specifically, RR intervals (RRI) and R-peak amplitudes (Rpeak) are generated from ECG signals and divided into one-minute-long segments. To alleviate the problem of insufficient feature information of the target segment, we combine the target segment with two pre- and post-adjacent segments in sequence, (i.e. a five-minute-long segment), as the input. Meanwhile, by leveraging the target segment as the query vector, we propose a new restricted attention mechanism with cascaded morphological and temporal attentions, which can effectively learn the feature information and depress redundant feature information from the adjacent segments with adaptive assigning weight importance. To further improve the SA detection performance, the target and adjacent segment features are fused together with the channel-wise stacking scheme. Experiment results on the public Apnea-ECG dataset and the real clinical FAH-ECG dataset with sleep apnea annotations show that the RAFNet greatly improves SA detection performance and achieves competitive results, which are superior to those achieved by the state-of-the-art baselines.

The mechanism of sudden unexpected death in epilepsy: A mini review

Sudden unexpected death in epilepsy (SUDEP) is defined as a sudden, unexpected, non-traumatic, non-drowning death in a person with epilepsy. SUDEP is generally considered to result from seizure-related cardiac dysfunction, respiratory depression, autonomic nervous dysfunction, or brain dysfunction. Frequency of generalized tonic clonic seizures (GTCS), prone posture, and refractory epilepsy are considered risk factors. SUDEP has also been associated with inherited cardiac ion channel disease and severe obstructive sleep apnea. Most previous studies of SUDEP mechanisms have focused on cardiac and respiratory dysfunction and imbalance of the neural regulatory system. Cardiac-related mechanisms include reduction in heart rate variability and prolongation of QT interval, which can lead to arrhythmias. Laryngospasm and amygdala activation may cause obstructive and central apnea, respectively. Neural mechanisms include impairment of 5-HT and adenosine neuromodulation. The research to date regarding molecular mechanisms of SUDEP is relatively limited. Most studies have focused on p-glycoprotein, catecholamines, potassium channels, and the renin-angiotensin system, all of which affect cardiac and respiratory function.

Improvement of catatonia-induced rapid respiratory failure with electroconvulsive therapy: A case report

We encountered a case of sudden respiratory failure during treatment of catatonia that required intensive care. Electroconvulsive therapy (ECT) was administered in the intensive care unit while the patient was under systemic control. The catatonia symptom was relieved, and respiratory failure improved. Although a proximal venous thrombus was observed, anticoagulation therapy was continued during ECT, and the patient was successfully treated without causing a pulmonary embolism. It is crucial to monitor the patient's physical and psychological symptoms because respiratory status may deteriorate rapidly in a catatonic state.

Obstructive and central sleep apnoea in a patient with medically intractable epilepsy

A woman in her 30s with medically intractable epilepsy and Lennox-Gastaut Syndrome on multiple antiseizure medications and with a deep brain stimulator presented to the epilepsy monitoring unit with increased seizure frequency. She was noted to have periods of apparent apnoea time linked to bursts of epileptiform activity on continuous video EEG monitoring. Once the clinical seizures were controlled, she was discharged to the sleep laboratory. She was noted to have obstructive and central sleep apnoea, which improved with the use of positive airway pressure. Central sleep apnoeas were time linked to electrographic seizures. Ictal central apnoea can easily be overlooked and is likely more common than currently recognised in patients with epilepsy. Ictal central apnoea may be a biomarker for sudden unexpected death in epilepsy.

The role of sleep state and time of day in modulating breathing in epilepsy: implications for sudden unexpected death in epilepsy

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death among patients with refractory epilepsy. While the exact etiology of SUDEP is unknown, mounting evidence implicates respiratory dysfunction as a precipitating factor in cases of seizure-induced death. Dysregulation of breathing can occur in epilepsy patients during and after seizures as well as interictally, with many epilepsy patients exhibiting sleep-disordered breathing (SDB), such as obstructive sleep apnea (OSA). The majority of SUDEP cases occur during the night, with the victim found prone in or near a bed. As breathing is modulated in both a time-of-day and sleep state-dependent manner, it is relevant to examine the added burden of nocturnal seizures on respiratory function. This review explores the current state of understanding of the relationship between respiratory function, sleep state and time of day, and epilepsy. We highlight sleep as a particularly vulnerable period for individuals with epilepsy and press that this topic warrants further investigation in order to develop therapeutic interventions to mitigate the risk of SUDEP.

Respiratory dysfunction in two rodent models of chronic epilepsy and acute seizures and its link with the brainstem serotonin system

Patients with drug-resistant epilepsy can experience respiratory alterations, notably during seizures. The mechanisms underlying long-term alterations in respiratory function remain unclear. As the brainstem 5-HT system is a prominent modulator of respiratory function, this study aimed at determining whether epilepsy is associated with alterations in both the respiratory function and brainstem serotonin (5-HT) system in rats. Epilepsy was triggered by pilocarpine-induced status epilepticus in rats. Our results showed that 30–50% of epileptic (EPI) rats exhibited a sharp decrease in oxygen consumption (SDOC), low metabolic rate of oxygen, and slow regular ventilation (EPI/SDOC + rats). These alterations were detected only in rats with chronic epilepsy, independent of behavioral seizures, were persistent over time, and not associated with death. In these rats, 5-HT fiber density in the nucleus tractus solitarius was lower than that in the control and EPI/SDOC− rats. Both EPI/SDOC + rats and DBA/2 mice that present with audiogenic-induced seizure followed by fatal respiratory arrest—a model of sudden and expected death in epilepsy—had increased transcript levels of tryptophan hydroxylase 2 and 5-HT presynaptic transporter. Thus, our data support that 5-HT alterations are associated with chronic and acute epilepsy-related respiratory dysfunction.

The role of monoaminergic neurons in modulating respiration during sleep and the connection with SUDEP

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death among epilepsy patients, occurring even more frequently in cases with anti-epileptic drug resistance. Despite some advancements in characterizing SUDEP, the underlying mechanism remains incompletely understood. This review summarizes the latest advances in our understanding of the pathogenic mechanisms of SUDEP, in order to identify possible targets for the development of new strategies to prevent SUDEP. Based on our previous research along with the current literature, we focus on the role of sleep-disordered breathing (SDB) and its related neural mechanisms to consider the possible roles of monoaminergic neurons in the modulation of respiration during sleep and the occurrence of SUDEP. Overall, this review suggests that targeting the monoaminergic neurons is a promising approach to preventing SUDEP. The proposed roles of SDB and related monoaminergic neural mechanisms in SUDEP provide new insights for explaining the pathogenesis of SUDEP.

Beyond Seizure Control: Treating Comorbidities in Epilepsy via Targeting of the P2X7 Receptor

Epilepsy is one of the most common chronic diseases of the central nervous system (CNS). Treatment of epilepsy remains, however, a clinical challenge with over 30% of patients not responding to current pharmacological interventions. Complicating management of treatment, epilepsy comes with multiple comorbidities, thereby further reducing the quality of life of patients. Increasing evidence suggests purinergic signalling via extracellularly released ATP as shared pathological mechanisms across numerous brain diseases. Once released, ATP activates specific purinergic receptors, including the ionotropic P2X7 receptor (P2X7R). Among brain diseases, the P2X7R has attracted particular attention as a therapeutic target. The P2X7R is an important driver of inflammation, and its activation requires high levels of extracellular ATP to be reached under pathological conditions. Suggesting the therapeutic potential of drugs targeting the P2X7R for epilepsy, P2X7R expression increases following status epilepticus and during epilepsy, and P2X7R antagonism modulates seizure severity and epilepsy development. P2X7R antagonism has, however, also been shown to be effective in treating conditions most commonly associated with epilepsy such as psychiatric disorders and cognitive deficits, which suggests that P2X7R antagonisms may provide benefits beyond seizure control. This review summarizes the evidence suggesting drugs targeting the P2X7R as a novel treatment strategy for epilepsy with a particular focus of its potential impact on epilepsy-associated comorbidities.

Vagus nerve stimulation therapy in people with drug-resistant epilepsy (CORE-VNS): rationale and design of a real-world post-market comprehensive outcomes registry

Introduction

The Vagus Nerve Stimulation Therapy System (VNS Therapy) is an adjunctive neuromodulatory therapy that can be efficacious in reducing the frequency and severity of seizures in people with drug-resistant epilepsy (DRE). CORE-VNS aims to examine the long-term safety and clinical outcomes of VNS in people with DRE.

Methods and analysis

The CORE-VNS study is an international, multicentre, prospective, observational, all-comers, post-market registry. People with DRE receiving VNS Therapy for the first time as well as people being reimplanted with VNS Therapy are eligible. Participants have a baseline visit (prior to device implant). They will be followed for a minimum of 36 months and a maximum of 60 months after implant. Analysis endpoints include seizure frequency (average number of events per month), seizure severity (individual-rated categorical outcome including very mild, mild, moderate, severe or very severe) as well as non-seizure outcomes such as adverse events, use of antiseizure medications, use of other non-pharmacological therapies, quality of life, validated measures of quality of sleep (Pittsburgh Sleep Quality Index or Children’s Sleep Habit Questionnaire) and healthcare resource utilisation. While the CORE-VNS registry was not expressly designed to test hypotheses, subgroup analyses and exploratory analysis that require hypothesis testing will be conducted across propensity score matched treatment groups, where possible based on sampling.

Ethics and dissemination

The CORE-VNS registry has already enrolled 823 participants from 61 centres across 15 countries. Once complete, CORE-VNS will represent one of the largest real-world clinical data sets to allow a more comprehensive understanding of the management of DRE with adjunctive VNS. Manuscripts derived from this database will shed important new light on the characteristics of people receiving VNS Therapy; the practical use of VNS across different countries, and factors influencing long-term response.

Trail registration number

NCT03529045.

Obstructive sleep apnea and sudden unexpected death in epilepsy in unselected patients with epilepsy: are they associated?

PURPOSE

We aimed to determine (1) the frequency of high-risk sudden unexpected death in epilepsy (SUDEP) in patients with epilepsy who have had obstructive sleep apnea (OSA) in different stages of sleep using the revised SUDEP risk inventory (rSUDEP-7) score instrument and (2) the factors associated with high risk SUDEP in patients with epilepsy who have had OSA.

METHODS

We conducted a cross-sectional study of consecutive subjects who are more than 15 years old without known sleep disorders, recruited from a single epilepsy clinic in a tertiary care facility. Participants underwent polysomnography. Scoring was performed by two blinded board-certified sleep physicians. The relationships between rSUDEP-7 scores and OSA measures were evaluated using Wilcoxon rank-sum test, chi-squared test, and quantile regression.

RESULTS

Our study population consisted of 95 participants. Overall median (IQR) apnea-hypopnea index (AHI) of our populations was 2.3 (0.7,7.5) events rate per hour; 12 (75%) patients had moderate OSA and 4 (25%) patients had severe OSA. Nine patients had a rSUDEP-7 score of 5 to 7. There was no significant difference between total rSUDEP-7 score or rSUDEP-7 score of > 5 or < 5 and total AHI, supine AHI, non-supine AHI, NREM AHI, or REM AHI; similarly, (2) there was no significant difference in total rSUDEP-7 score between AHI of < 15 or > 15.

CONCLUSION

Our study reveals no association between AHI score, OSA, and total rSUDEP-7 score or rSUDEP-7 score of > 5. The pathophysiology underlying SUDEP appears complex. We need further studies on SUDEP to help elucidate the cardiorespiratory mechanisms and predisposing factors.

Rapid eye movement sleep disturbance in patients with refractory epilepsy: A polysomnographic study

OBJECTIVE/BACKGROUND

Patients with epilepsy have disrupted sleep architecture and a higher prevalence of sleep disturbance. Moreover, obstructive sleep apnea (OSA) is more common among patients with refractory epilepsy. Few studies have compared subjective sleep quality, sleep architecture, and prevalence of OSA between patients with refractory epilepsy and those with medically controlled epilepsy. Therefore, this study aimed to evaluate the differences in sleep quality, sleep architecture, and prevalence of OSA between patients with refractory epilepsy and patients with medically controlled epilepsy.

PATIENTS

This retrospective case-control study included 38 patients with refractory epilepsy and 96 patients with medically controlled epilepsy. Sleep parameters and indices of sleep-related breathing disorders were recorded by standard in-laboratory polysomnography. The scores from sleep questionnaires on sleep quality and daytime sleepiness were compared between the two groups.

RESULTS

Patients with refractory epilepsy versus medically controlled epilepsy had statistically significantly decreased rapid eye movement (REM) sleep (13.5 ± 6.1% vs. 16.2 ± 6.1%) and longer REM latency (152.2 ± 84.1 min vs. 117.2 ± 61.9 min). Further, no differences were found in the prevalence of sleep-related breathing disorders, subjective sleep quality, prevalence of daytime sleepiness, and quality of life. Although not statistically significant, patients with refractory epilepsy have a lower rate of OSA compared with those with medically controlled epilepsy (21.1% vs. 30.2%).

CONCLUSIONS

Patients with refractory epilepsy had more disrupted REM sleep regulation than those with medically controlled epilepsy. Although patients with epilepsy have a higher risk of OSA, in this study patients with refractory epilepsy were not susceptible to OSA.

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: A population-based time-series study

OBJECTIVE

The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures.

METHODS

Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined.

RESULTS

The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH₄, and NO. Six air pollutants, namely CH₄, NO, CO, NO₂, PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R² = 0.422).

CONCLUSION

The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.

Corticoperipheral neuromuscular disconnection in obstructive sleep apnoea

The roles of central nervous mechanisms and cortical output in obstructive sleep apnoea remain unclear. We addressed corticomuscular coupling between cortical sensorimotor areas and lower facial motor units as a mechanistic pathway and as a possible surrogate marker of corticoperipheral motor control in obstructive sleep apnoea. In this exploratory cross-sectional retrospective study, we analysed EEG (C3 and C4 leads) and chin EMG from polysomnography recordings in 86 participants (22 females; age range: 26–81 years): 27 with mild (respiratory disturbance index = 5–15 events/h), 21 with moderate (15–30 events/h) and 23 with severe obstructive sleep apnoea (&gt;30 events/h) and 15 control subjects (&lt;5 events/h). By computing C3-/C4-EEG–chin EMG coherence of signal dynamics in time and frequency domains, we investigated corticomuscular coupling between cortical sensorimotor areas and lower facial motor units with increasing obstructive sleep apnoea severity during the entire sleeping time, during different sleep stages and during obstructive respiratory events, including 5 s before (stable breathing) and after events (breathing resumption). In addition, we studied a possible influence of body mass index and autonomic nervous system activation. We found that both average and respiratory event-specific corticomuscular coupling between cortical sensorimotor areas and lower facial motor units weakened significantly with increasing obstructive sleep apnoea severity, was strongest during N3 and weakened in N1, N2 and rapid eye movement stages (in decreasing order). Coupling increases significantly during the obstructive respiratory events compared with coupling just before and following them. Results were independent of body mass index or autonomic nervous system activation. We conclude that obstructive respiratory events in obstructive sleep apnoea are very strongly associated both quantitatively and temporally with the degree of disconnection within the cortical sensorimotor areas—lower facial motor units pathway. This quite coordinated activity pattern suggests a cortical sensorimotor area-driven obstructive respiratory event pattern generator and a central motor output disorder in obstructive sleep apnoea.

A Sleepy Patient With Frequent Falls

Chada A, Dholakia S, Rye D. A sleepy patient with frequent falls. J Clin Sleep Med . 2019;15(11):1691–1693.