Multi-Night Home Assessment of Total Sleep Time Misperception in Obstructive Sleep Apnea with and Without Insomnia Symptoms.

Total sleep time (TST) misperception has been reported in obstructive sleep apnea (OSA). However, previous findings on predictors were inconsistent and predominantly relied on single-night polysomnography, which may alter patients' sleep perception. We leveraged advances in wearable sleep staging to investigate predictors of TST misperception in OSA over multiple nights in the home environment.

Cognitive complaints in patients with untreated obstructive sleep apnea versus patients with neurological and respiratory diseases: prevalence, severity and risk factors.

Purpose: Little is known about cognitive complaints (self-reported problems in cognitive functioning) in patients with Obstructive Sleep Apnea (OSA). We compared the prevalence and severity of cognitive complaints in patients with untreated OSA to patients with neurological and respiratory diseases. We also studied risk factors for cognitive complaints across these diseases, including OSA.

A multi-task learning model using RR intervals and respiratory effort to assess sleep disordered breathing.

Background: Sleep-disordered breathing (SDB) affects a significant portion of the population. As such, there is a need for accessible and affordable assessment methods for diagnosis but also case-finding and long-term follow-up. Research has focused on exploiting cardiac and respiratory signals to extract proxy measures for sleep combined with SDB event detection.

Multi-night home assessment of sleep structure in OSA with and without insomnia.

Objective: To explore sleep structure in participants with obstructive sleep apnea (OSA) and comorbid insomnia (COMISA) and participants with OSA without insomnia (OSA-only) using both single-night polysomnography and multi-night wrist-worn photoplethysmography/accelerometry.

Methods: Multi-night 4-class sleep-staging was performed with a validated algorithm based on actigraphy and heart rate variability, in 67 COMISA (23 women, median age: 51 years) and 50 OSA-only (15 women, median age: 51) participants. Sleep statistics were compared using linear regression models and mixed-effects models.

Temporal dynamics of awakenings from slow-wave sleep in non-rapid eye movement parasomnia.

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.

Performance of cardiorespiratory-based sleep staging in patients using beta blockers.

Study Objectives: Automatic sleep staging based on cardiorespiratory signals from home sleep monitoring devices holds great clinical potential. Using state-of-the-art machine learning, promising performance has been reached in patients with sleep disorders. However, it is unknown whether performance would hold in individuals with potentially altered autonomic physiology, for example under the influence of medication.

Heart rate response to cortical arousals in patients with isolated obstructive sleep apnea and with comorbid insomnia (COMISA).

Purpose: Comorbid insomnia often occurs in patients with obstructive sleep apnea (OSA), referred to as COMISA. Cortical arousals manifest as a common feature in both OSA and insomnia, often accompanied by elevated heart rate (HR). Our objective was to evaluate the heart rate response to nocturnal cortical arousals in patients with COMISA and patients with OSA alone.

The impact of healthy pregnancy on features of heart rate variability and pulse wave morphology derived from wrist-worn photoplethysmography.

Due to the association between dysfunctional maternal autonomic regulation and pregnancy complications, tracking non-invasive features of autonomic regulation derived from wrist-worn photoplethysmography (PPG) measurements may allow for the early detection of deteriorations in maternal health. However, even though a plethora of these features-specifically, features describing heart rate variability (HRV) and the morphology of the PPG waveform (morphological features)-exist in the literature, it is unclear which of these may be valuable for tracking maternal health. As an initial step towards clarity, we compute comprehensive sets of HRV and morphological features from nighttime PPG measurements.

Maternal cardiorespiratory coupling: differences between pregnant and nonpregnant women are further amplified by sleep-stage stratification.

Pregnancy complications are associated with abnormal maternal autonomic regulation. Subsequently, thoroughly understanding maternal autonomic regulation during healthy pregnancy may enable the earlier detection of complications, in turn allowing for the improved management thereof. Under healthy autonomic regulation, reciprocal interactions occur between the cardiac and respiratory systems, i.

Autonomic arousal detection and cardio-respiratory sleep staging improve the accuracy of home sleep apnea tests.

The apnea-hypopnea index (AHI), defined as the number of apneas and hypopneas per hour of sleep, is still used as an important index to assess sleep disordered breathing (SDB) severity, where hypopneas are confirmed by the presence of an oxygen desaturation or an arousal. Ambulatory polygraphy without neurological signals, often referred to as home sleep apnea testing (HSAT), can potentially underestimate the severity of sleep disordered breathing (SDB) as sleep and arousals are not assessed. We aim to improve the diagnostic accuracy of HSATs by extracting surrogate sleep and arousal information derived from autonomic nervous system activity with artificial intelligence.

The Use of Respiratory Effort Improves an ECG-Based Deep Learning Algorithm to Assess Sleep-Disordered Breathing.

Background: Sleep apnea is a prevalent sleep-disordered breathing (SDB) condition that affects a large population worldwide. Research has demonstrated the potential of using electrocardiographic (ECG) signals (heart rate and ECG-derived respiration, EDR) to detect SDB. However, EDR may be a suboptimal replacement for respiration signals.

A computationally efficient algorithm for wearable sleep staging in clinical populations.

This study describes a computationally efficient algorithm for 4-class sleep staging based on cardiac activity and body movements. Using an accelerometer to calculate gross body movements and a reflective photoplethysmographic (PPG) sensor to determine interbeat intervals and a corresponding instantaneous heart rate signal, a neural network was trained to classify between wake, combined N1 and N2, N3 and REM sleep in epochs of 30 s. The classifier was validated on a hold-out set by comparing the output against manually scored sleep stages based on polysomnography (PSG).

Prevalence and risk factors of burden among caregivers of older emergency department patients.

The number of older individuals that live independently at home is rising. These older individuals often rely on caregivers who have a similar age and health status. Therefore, caregivers may experience a high burden.

Contactless Camera-Based Sleep Staging: The HealthBed Study.

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different HRV metrics indirectly reflect the expression of sleep stages.

Interpretation and further development of the hypnodensity representation of sleep structure.

The recently-introduced hypnodensity graph provides a probability distribution over sleep stages per data window (i.e. an epoch).

Psychomotor Vigilance Performance in Participants with Excessive Daytime Sleepiness in Obstructive Sleep Apnea or Narcolepsy Compared with SAFTE-FAST Model Predictions.

Introduction: Excessive daytime sleepiness (EDS) associated with narcolepsy or obstructive sleep apnea (OSA) can impair vigilance/attention. Solriamfetol, a dopamine/norepinephrine reuptake inhibitor, is approved to treat EDS associated with narcolepsy (75-150 mg/day) or OSA (37.5-150 mg/day).

Effects of solriamfetol on on-the-road driving in participants with narcolepsy: A randomised crossover trial.

Objective: To evaluate the impact of solriamfetol, a dopamine and norepinephrine reuptake inhibitor, on on-the-road driving performance in participants with narcolepsy.

Methods: In this randomised, double-blind, placebo-controlled, crossover study, driving performance during a 1 h on-road driving test was assessed at 2 and 6 h post-dose following 7 days of treatment with solriamfetol (150 mg/day for 3 days, followed by 300 mg/day for 4 days) or placebo. The primary endpoint was standard deviation of lateral position (SDLP) at 2 h post-dose.

Prescription Drugs Used in Insomnia.

In insomnia, the subjective aspects of the sleep complaint are paramount in the diagnostic criteria. Epidemiologic studies increasingly point to a link between insomnia and somatic morbidity and mortality, but until now, only in the subgroup of objectively poor sleepers. Although pharmacologic treatment might offer some benefits to this subgroup of insomnia patients, to date, there is no evidence that hypnotics can ameliorate their health risks.

Idling for Decades: A European Study on Risk Factors Associated with the Delay Before a Narcolepsy Diagnosis.

Purpose: Narcolepsy type-1 (NT1) is a rare chronic neurological sleep disorder with excessive daytime sleepiness (EDS) as usual first and cataplexy as pathognomonic symptom. Shortening the NT1 diagnostic delay is the key to reduce disease burden and related low quality of life. Here we investigated the changes of diagnostic delay over the diagnostic years (1990-2018) and the factors associated with the delay in Europe.

Effects of solriamfetol on on-the-road driving performance in participants with excessive daytime sleepiness associated with obstructive sleep apnoea.

Objective: To evaluate the impact of solriamfetol, a dopamine and norepinephrine reuptake inhibitor, on on-the-road driving in participants with excessive daytime sleepiness (EDS) associated with obstructive sleep apnoea (OSA).

Methods: Eligible participants were aged 21-75 years with OSA and EDS (Maintenance of Wakefulness Test mean sleep latency <30 minutes and Epworth Sleepiness Scale score ≥10). Participants were randomised 1:1 to solriamfetol (150 mg/day [3 days], then 300 mg/day [4 days]) or placebo for 7 days, before crossover to the other treatment paradigm.

Data-Driven Phenotyping of Central Disorders of Hypersomnolence With Unsupervised Clustering.

Background And Objectives: Recent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers.