Quantitative sleep EEG and polysomnographic predictors of driving simulator performance in obstructive sleep apnea

All Obstructive Sleep Apnea Events Are Not Created Equal: The Relationship between Event-related Hypoxemia and Physiologic Response

Rationale: Obstructive sleep apnea (OSA) severity is typically assessed by the apnea-hypopnea index (AHI), a frequency-based metric that allocates equal weight to all respiratory events. However, more severe events may have a greater physiologic impact. Objectives: The purpose of this study was to determine whether the degree of event-related hypoxemia would be associated with the postevent physiologic response. Methods: Patients with OSA (AHI, ⩾5/h) from the multicenter Canadian Sleep and Circadian Network cohort were studied. Using mixed-effect linear regression, we examined associations between event-related hypoxic burden (HBev) assessed by the area under the event-related oxygen saturation recording with heart rate changes (ΔHRev), vasoconstriction (vasoconstriction burden [VCBev] assessed with photoplethysmography), and electroencephalographic responses (power ratio before and after events). Results: Polysomnographic recordings from 658 patients (median [interquartile range] age, 55.00 [45.00, 64.00] yr; AHI, 27.15 [14.90, 64.05] events/h; 42% female) were included in the analyses. HBev was associated with an increase in all physiologic responses after controlling for age, sex, body mass index, sleep stage, total sleep time, and study centers; for example, 1 standard deviation increase in HBev was associated with 0.21 [95% confidence interval, 0.2, 0.22], 0.08 [0.08, 0.09], and 0.22 [0.21, 0.23] standard deviation increases in ΔHRev, VCBev, and β-power ratio, respectively. Conclusions: Increased event-related hypoxic burden was associated with greater responses across a broad range of physiologic signals. Future metrics that incorporate information about the variability of these physiologic responses may have promise in providing a more nuanced assessment of OSA severity.

Electroencephalographic slowdowns during sleep are associated with cognitive impairment in patients who have obstructive sleep apnea but no dementia

OBJECTIVES

To research the relationship between quantitative electroencephalogram (qEEG) and impaired cognitive function patients who have obstructive sleep apnea (OSA) but no dementia.

METHODS

Subjects who complained of snoring between March 2020 and April 2021 in the Sleep Medicine Center of Weihai Municipal Hospital were included. All subjects underwent overnight in-laboratory polysomnography (PSG) and were assessed using a neuropsychological scale. Standard fast fourier transform (FFT) was used to obtain the electroencephalogram (EEG) power spectral density curve, and to calculate the delta, theta, alpha, and beta relative power and the ratio between slow and fast frequencies. Binary logistic regression was used to assess the risk factors for cognitive impairment in patients who had OSA but no dementia. Correlation analysis was performed to determine the relationship between qEEG and cognitive impairment.

RESULTS

A total of 175 participants without dementia who met the inclusion criteria were included in this study. There were 137 patients with OSA, including 76 with mild cognitive impairment (OSA + MCI), 61 without mild cognitive impairment (OSA-MCI), and 38 participants without OSA (non-OSA). The relative theta power in the frontal lobe in stage 2 of non-rapid eye movement sleep (NREM 2) in OSA + MCI was higher than that in OSA-MCI (P = 0.038) and non-OSA (P = 0.018). Pearson correlation analysis showed that the relative theta power in the frontal lobe in NREM 2 was negatively correlated with Mini-Mental State Examination (MMSE) scores, Montreal Cognitive Assessment (MoCA) Beijing version scores, and MoCA subdomains scores (visual executive function, naming, attention, language, abstraction, delayed recall and orientation) outside language.

CONCLUSIONS

In patients who had OSA but no dementia, the EEG slower frequency power increased. The relative theta power in the frontal lobe in NREM 2 was associated with MCI of patients with OSA. These results suggest that the slowing of theta activity may be one of the neurophysiological changes in the early stage of cognitive impairment in patients with OSA.

Shedding light on neurofilament involvement in cognitive decline in obstructive sleep apnea and its possible role as a biomarker

Obstructive sleep apnea is one of the most common sleep disorders with a high estimated global prevalence and a large number of associated comorbidities in general as well as specific neuropsychiatric complications such as cognitive impairment. The complex pathogenesis and effects of the disorder including chronic intermittent hypoxia and sleep fragmentation may lead to enhanced neuronal damage, thereby contributing to neuropsychiatric pathologies. Obstructive sleep apnea has been described as an independent risk factor for several neurodegenerative diseases, including Alzheimer's disease and all-cause dementia. The influence of obstructive sleep apnea on cognitive deficits is still a topic of recent debate, and several mechanisms, including neurodegeneration and depression-related cognitive dysfunction, underlying this correlation are taken into consideration. The differentiation between both pathomechanisms of cognitive impairment in obstructive sleep apnea is a complex clinical issue, requiring the use of multiple and costly diagnostic methods. The studies conducted on neuroprotection biomarkers, such as brain-derived neurotrophic factors and neurofilaments, are recently gaining ground in the topic of cognition assessment in obstructive sleep apnea patients. Neurofilaments as neuron-specific cytoskeletal proteins could be useful non-invasive indicators of brain conditions and neurodegeneration, which already are observed in many neurological diseases leading to cognitive deficits. Additionally, neurofilaments play an important role as a biomarker in other sleep disorders such as insomnia. Thus, this review summarizes the current knowledge on the involvement of neurofilaments in cognitive decline and neurodegeneration in obstructive sleep apnea patients as well as discusses its possible role as a biomarker of these changes.

EEG Power Spectral Density in NREM Sleep is Associated with the Degree of Hypoxia in Patients with Obstructive Sleep Apnea

Purpose

Obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder. Research conducted on patients with OSA using electroencephalography (EEG) has revealed a noticeable shift in the overnight polysomnography (PSG) power spectrum. To better quantify the effects of OSA on brain function and to identify the most reliable predictors of pathological cortical activation, this study quantified the PSG power and its association with the degree of hypoxia in OSA patients.

Patients and Methods

This retrospective study recruited 93 patients with OSA. OSA patients were divided into three groups based on their apnea-hypopnea index (AHI) scores. The clinical characteristics and sleep macrostructure of these patients were examined, followed by an analysis of PSG signals. Power spectral density (PSD) in five frequency bands was analyzed during nonrapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wakefulness. Finally, correlation analysis was conducted to assess the relationships among PSD, PSG parameters, and serum levels of S100β and uric acid.

Results

Obstructive sleep apnea occurred during both the NREM and REM sleep phases. Except for a decrease in the duration of N2 sleep and an increase in the microarousal index, there were no significant differences in sleep architecture based on disease severity. Compared to the mild OSA group, the theta and alpha band PSD in the frontal and occipital regions during NREM sleep and wakefulness were significantly decreased in the moderate and severe OSA groups. Correlation analysis revealed that theta PSD in N1 and N3 stages were negatively correlated the AHI, oxygen desaturation index, SaO2<90% and microarousal index.

Conclusion

These findings imply that patients with more severe OSA exhibited considerable NREM hypoxia and abnormal brain activity in the frontal and occipital regions. Therefore, sleep EEG oscillation may be a useful neurophysiological indicator for assessing brain function and disease severity in patients with OSA.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.

Abnormal interaction between cortical regions of obstructive sleep apnea hypopnea syndrome children

Obstructive sleep apnea hypopnea syndrome negatively affects the cognitive function of children. This study aims to find potential biomarkers for obstructive sleep apnea hypopnea syndrome in children by investigating the patterns of sleep electroencephalography networks. The participants included 16 mild obstructive sleep apnea hypopnea syndrome children, 12 severe obstructive sleep apnea hypopnea syndrome children, and 13 healthy controls. Effective brain networks were constructed using symbolic transfer entropy to assess cortical information interaction. The information flow pattern in the participants was evaluated using the parameters cross-within variation and the ratio of posterior-anterior information flow. Obstructive sleep apnea hypopnea syndrome children had a considerably higher symbolic transfer entropy in the full frequency band of N1, N2, and rapid eye movement (REM) stages (P < 0.05), and a significantly lower symbolic transfer entropy in full frequency band of N3 stage (P < 0.005), in comparison with the healthy controls. In addition, the cross-within variation of the β frequency band across all sleep stages were significantly lower in the obstructive sleep apnea hypopnea syndrome group than in the healthy controls (P < 0.05). What is more, the posterior-anterior information flowin the β frequency band of REM stage was significantly higher in mild obstructive sleep apnea hypopnea syndrome children than in the healthy controls (P < 0.05). These findings may serve as potential biomarkers for obstructive sleep apnea hypopnea syndrome in children and provide new insights into the pathophysiological mechanisms.

REM-OSA as a Tool to Understand Both the Architecture of Sleep and Pathogenesis of Sleep Apnea-Literature Review

Sleep is a complex physiological state, which can be divided into the non-rapid eye movement (NREM) phase and the REM phase. Both have some unique features and functions. This difference is best visible in electroencephalography recordings, respiratory system activity, arousals, autonomic nervous system activity, or metabolism. Obstructive sleep apnea (OSA) is a common condition characterized by recurrent episodes of pauses in breathing during sleep caused by blockage of the upper airways. This common condition has multifactorial ethiopathogenesis (e.g., anatomical predisposition, sex, obesity, and age). Within this heterogenous syndrome, some distinctive phenotypes sharing similar clinical features can be recognized, one of them being REM sleep predominant OSA (REM-OSA). The aim of this review was to describe the pathomechanism of REM-OSA phenotype, its specific clinical presentation, and its consequences. Available data suggest that in this group of patients, the severity of specific cardiovascular and metabolic complications is increased. Due to the impact of apneas and hypopneas predominance during REM sleep, patients are more prone to develop hypertension or glucose metabolism impairment. Additionally, due to the specific function of REM sleep, which is predominantly fragmented in the REM-OSA, this group presents with decreased neurocognitive performance, reflected in memory deterioration, and mood changes including depression. REM-OSA clinical diagnosis and treatment can alleviate these outcomes, surpassing the traditional treatment and focusing on a more personalized approach, such as using longer therapy of continuous positive airway pressure or oral appliance use.

Sub-Scalp Implantable Telemetric EEG (SITE) for the Management of Neurological and Behavioral Disorders beyond Epilepsy

Sub-scalp Implantable Telemetric EEG (SITE) devices are under development for the treatment of epilepsy. However, beyond epilepsy, continuous EEG analysis could revolutionize the management of patients suffering from all types of brain disorders. This article reviews decades of foundational EEG research, collected from short-term routine EEG studies of common neurological and behavioral disorders, that may guide future SITE management and research. Established quantitative EEG methods, like spectral EEG power density calculation combined with state-of-the-art machine learning techniques applied to SITE data, can identify new EEG biomarkers of neurological disease. From distinguishing syncopal events from seizures to predicting the risk of dementia, SITE-derived EEG biomarkers can provide clinicians with real-time information about diagnosis, treatment response, and disease progression.

Associations of Baseline Sleep Microarchitecture with Cognitive Function After 8 Years in Middle-Aged and Older Men from a Community-Based Cohort Study

Purpose

Prospective studies examining associations between baseline sleep microarchitecture and future cognitive function recruited from small samples with predominantly short follow-up. This study examined sleep microarchitecture predictors of cognitive function (visual attention, processing speed, and executive function) after 8 years in community-dwelling men.

Patients and Methods

Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (2010-2011), with 157 completing baseline (2007-2010) and follow-up (2018-2019) cognitive assessments (trail-making tests A [TMT-A] and B [TMT-B] and the standardized mini-mental state examination [SMMSE]). Whole-night F4-M1 sleep EEG recordings were processed following artifact exclusion, and quantitative EEG characteristics were obtained using validated algorithms. Associations between baseline sleep microarchitecture and future cognitive function (visual attention, processing speed, and executive function) were examined using linear regression models adjusted for baseline obstructive sleep apnoea, other risk factors, and cognition.

Results

The final sample included men aged (mean [SD]) 58.9 (8.9) years at baseline, overweight (BMI 28.5 [4.2] kg/m²), and well educated (75.2% ≥Bachelor, Certificate, or Trade), with majorly normal baseline cognition. Median (IQR) follow-up was 8.3 (7.9, 8.6) years. In adjusted analyses, NREM and REM sleep EEG spectral power was not associated with TMT-A, TMT-B, or SMMSE performance (all p>0.05). A significant association of higher N3 sleep fast spindle density with worse TMT-B performance (B=1.06, 95% CI [0.13, 2.00], p=0.026) did not persist following adjustment for baseline TMT-B performance.

Conclusion

In this sample of community-dwelling men, sleep microarchitecture was not independently associated with visual attention, processing speed, or executive function after 8 years.

The Health Effects of 72 Hours of Simulated Wind Turbine Infrasound: A Double-Blind Randomized Crossover Study in Noise-Sensitive, Healthy Adults

BACKGROUND

Large electricity-generating wind turbines emit both audible sound and inaudible infrasound at very low frequencies that are outside of the normal human range of hearing. Sufferers of wind turbine syndrome (WTS) have attributed their ill-health and particularly their sleep disturbance to the signature pattern of infrasound. Critics have argued that these symptoms are psychological in origin and are attributable to nocebo effects.

OBJECTIVES

We aimed to test the effects of 72 h of infrasound (1.6-20 Hz at a sound level of ∼90 dB pk re 20μPa, simulating a wind turbine infrasound signature) exposure on human physiology, particularly sleep.

METHODS

We conducted a randomized double-blind triple-arm crossover laboratory-based study of 72 h exposure with a >10-d washout conducted in a noise-insulated sleep laboratory in the style of a studio apartment. The exposures were infrasound (∼90  dB pk), sham infrasound (same speakers not generating infrasound), and traffic noise exposure [active control; at a sound pressure level of 40-50 dB LAeq,night and 70 dB LAFmax transient maxima, night (2200 to 0700 hours)]. The following physiological and psychological measures and systems were tested for their sensitivity to infrasound: wake after sleep onset (WASO; primary outcome) and other measures of sleep physiology, wake electroencephalography, WTS symptoms, cardiovascular physiology, and neurobehavioral performance.

RESULTS

We randomized 37 noise-sensitive but otherwise healthy adults (18-72 years of age; 51% female) into the study before a COVID19-related public health order forced the study to close. WASO was not affected by infrasound compared with sham infrasound (-1.36 min; 95% CI: -6.60, 3.88, p=0.60) but was worsened by the active control traffic exposure compared with sham by 6.07 min (95% CI: 0.75, 11.39, p=0.02). Infrasound did not worsen any subjective or objective measures used.

DISCUSSION

Our findings did not support the idea that infrasound causes WTS. High level, but inaudible, infrasound did not appear to perturb any physiological or psychological measure tested in these study participants. https://doi.org/10.1289/EHP10757.

Power spectral analysis of the sleep electroencephalogram in positional obstructive sleep apnea

OBJECTIVE/BACKGROUND

Previous studies have shown that obstructive sleep apnoea (OSA) is associated with reduced delta EEG and increased beta EEG power and increased EEG slowing ratio. There are however no studies that explore differences in sleep EEG between positional obstructive sleep apnoea (pOSA) and non-positional obstructive sleep apnoea (non-pOSA) patients.

PATIENTS/METHODS

556 of 1036 consecutive patients (246 of 556 were female) undertaking polysomnography (PSG) for the suspicion of OSA met the inclusion criteria for this study. We calculated power spectra of each sleep epoch using Welch's method with ten, 4-s overlapping windows. Outcome measures such as Epworth Sleepiness Scale, SF-36 Quality of Life, Functional Outcomes of Sleep Questionnaire and Pyschomotor Vigilance Task were compared between the groups.

RESULTS

Patients with pOSA had greater delta EEG power in NREM and greater N3 proportions compared to their non-pOSA counterparts. There were no differences in theta (4-8Hz), alpha (8-12Hz), sigma (12-15Hz) or beta (15-25Hz) EEG power or EEG slowing ratio between the two groups. There were also no differences in the outcome measures between these two groups. The division of pOSA into spOSA and siOSA groups showed better sleep parameters in siOSA but with no difference in sleep power spectra.

CONCLUSIONS

This study partially supports our hypothesis in showing that pOSA, compared to non-pOSA, is associated with increased delta EEG power but did not show any variation to beta EEG power or EEG slowing ratio. This limited improvement in sleep quality did not translate to measurable changes to outcomes, suggesting beta EEG power or EEG slowing ratio may be key factors.

Theta-Alpha Variability on Admission EEG Is Associated With Outcome in Pediatric Cerebral Malaria

PURPOSE

Pediatric cerebral malaria has high rates of mortality and neurologic morbidity. Although several biomarkers, including EEG, are associated with survival or morbidity, many are resource intensive or require skilled interpretation for clinical use. Automation of quantitative interpretation of EEG may be preferable in resource-limited settings, where trained interpreters are rare. As currently used quantitative EEG factors do not adequately describe the spectrum of variability seen in studies from children with cerebral malaria, the authors developed and validated a new quantitative EEG variable, theta-alpha variability (TAV).

METHODS

The authors developed TAV, a new quantitative variable, as a composite of multiple automated EEG outputs. EEG records from 194 children (6 months to 14 years old) with cerebral malaria were analyzed. Independent EEG interpreters performed standard quantitative and qualitative analyses, with the addition of the newly created variable. The associations of TAV with other quantitative EEG factors, a qualitative assessment of variability, and outcomes were assessed.

RESULTS

Theta-alpha variability was not highly correlated with alpha, theta, or delta power and was not associated with qualitative measures of variability. Children whose EEGs had higher values of TAV had a lower risk of death (odds ratio = 0.934, 95% confidence interval = 0.902-0.966) or neurologic sequelae (odds ratio = 0.960, 95% confidence interval = 0.932-0.990) compared with those with lower values. Receiver operating characteristic analysis in predicting death at a TAV threshold of 0.244 yielded a sensitivity of 74% and specificity of 70% for an area under the receiver operating characteristic curve of 0.755.

CONCLUSIONS

Theta-alpha variability is independently associated with outcome in pediatric cerebral malaria and can predict death with high sensitivity and specificity. Automated determination of this newly created EEG factor holds promise as a potential method to increase the clinical utility of EEG in resource-limited settings by allowing interventions to be targeted to those at higher risk of death or disability.

Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review

STUDY OBJECTIVES

Polysomnograms (PSGs) collect a plethora of physiologic signals across the night. However, few of these PSG data are incorporated into standard reports, and hence, ultimately, under-utilized in clinical decision making. Recently, there has been substantial interest regarding novel alternative PSG metrics that may help to predict obstructive sleep apnea (OSA)-related outcomes better than standard PSG metrics such as the apnea-hypopnea index. We systematically review the recent literature for studies that examined the use of alternative PSG metrics in the context of OSA and their association with health outcomes.

METHODS

We systematically searched EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews for studies published between 2000 and 2022 for those that reported alternative metrics derived from PSG in adults and related them to OSA-related outcomes.

RESULTS

Of the 186 initial studies identified by the original search, data from 31 studies were ultimately included in the final analysis. Numerous metrics were identified that were significantly related to a broad range of outcomes. We categorized the outcomes into 2 main subgroups: (1) cardiovascular/metabolic outcomes and mortality and (2) cognitive function- and vigilance-related outcomes. Four general categories of alternative metrics were identified based on signals analyzed: autonomic/hemodynamic metrics, electroencephalographic metrics, oximetric metrics, and respiratory event-related metrics.

CONCLUSIONS

We have summarized the current landscape of literature for alternative PSG metrics relating to risk prediction in OSA. Although promising, further prospective observational studies are needed to verify findings from other cohorts, and to assess the clinical utility of these metrics.

CITATION

Hajipour M, Baumann B, Azarbarzin A, et al. Association of alternative polysomnographic features with patient outcomes in obstructive sleep apnea: a systematic review. J Clin Sleep Med. 2023;19(2):225-242.

Effects of severe obstructive sleep apnea on functional prognosis in the acute phase of ischemic stroke and quantitative electroencephalographic markers

OBJECTIVE

To investigate the effect of severe obstructive sleep apnea (OSA) on functional prognosis in the acute phase and quantitative electroencephalography (EEG) markers during sleep in ischemic stroke patients.

METHODS

This study included 125 mild-to-moderate acute ischemic stroke patients with OSA who underwent polysomnography (PSG) within one week of stroke onset between January 2015 and June 2020. Patients were grouped according to their apnea-hypopnea index (</≥ 30/h). Poor functional prognosis was defined as modified Rankin Scale score ≥3. The EEG recorded by PSG was extracted during different sleep stages for power spectrum analysis. The delta/alpha power ratio (DAR), (delta + theta)/(alpha + beta) ratio (the slowing ratio, TSR), and the relative power (RP) of each frequency band were calculated. Differences in clinical, PSG, and quantitative EEG characteristics were compared between the groups. Additionally, we explored predictors of poor functional prognosis.

RESULTS

Patients with severe OSA had a higher proportion of hypertension, lower relative power of high-frequency bands, and higher delta RP, TSR, and DAR (p < 0.05). Severe OSA was associated with a 3.6-fold increase in risk of poor prognosis (p < 0.05). Increased delta RP and TSR, as well as decreased alpha, beta, and sigma RP, may be independent predictors of a poor functional prognosis.

CONCLUSIONS

Severe OSA is an independent risk factor for a poor functional prognosis in patients with acute ischemic stroke, and quantitative EEG during sleep showed a significant slow wave enhancement, suggesting more severe brain dysfunction. The treatment of severe OSA may improve functional prognosis.

Role of precision medicine in obstructive sleep apnoea

Obstructive sleep apnoea is a substantial clinical and public health problem because it contributes to harmful effects on quality of life, daytime symptoms, road traffic incidents, and cardiometabolic disease. Increasingly, obstructive sleep apnoea is recognised as a heterogeneous disease, and patients have varied susceptibility to long term complications and different responses to treatment. This narrative review summarises the current knowledge of precision medicine in obstructive sleep apnoea, particularly the role of symptom clusters, polysomnogram phenotypes, physiological endotypes, and circulating biomarkers in defining subtypes. In the near future, the prognostic accuracy of these measures in predicting long term complications in obstructive sleep apnoea will likely be improved, together with better matching of treatments to disease subtypes.

Sensorimotor Cortical Activity during Respiratory Arousals in Obstructive Sleep Apnea

Intensity of respiratory cortical arousals (RCA) is a pathophysiologic trait in obstructive sleep apnea (OSA) patients. We investigated the brain oscillatory features related to respiratory arousals in moderate and severe OSA. Raw electroencephalography (EEG) data recorded during polysomnography (PSG) of 102 OSA patients (32 females, mean age 51.6 ± 12 years) were retrospectively analyzed. Among all patients, 47 had moderate (respiratory distress index, RDI = 15−30/h) and 55 had severe (RDI > 30/h) OSA. Twenty RCA per sleep stage in each patient were randomly selected and a total of 10131 RCAs were analyzed. EEG signals obtained during, five seconds before and after the occurrence of each arousal were analyzed. The entropy (approximate (ApEn) and spectral (SpEn)) during each sleep stage (N1, N2 and REM) and area under the curve (AUC) of the EEG signal during the RCA was computed. Severe OSA compared to moderate OSA patients showed a significant decrease (p < 0.0001) in the AUC of the EEG signal during the RCA. Similarly, a significant decrease in spectral entropy, both before and after the RCA was observed, was observed in severe OSA patients when compared to moderate OSA patients. Contrarily, the approximate entropy showed an inverse pattern. The highest increase in approximate entropy was found in sleep stage N1. In conclusion, the dynamic range of sensorimotor cortical activity during respiratory arousals is sleep-stage specific, dependent on the frequency of respiratory events and uncoupled from autonomic activation. These findings could be useful for differential diagnosis of severe OSA from moderate OSA.

Adverse driving behaviors are associated with sleep apnea severity and age in cognitively normal older adults at risk for Alzheimer's disease

Alzheimer's disease (AD) pathology accumulates for decades before the onset of cognitive decline. Cognitively normal individuals with biomarker evidence of AD brain pathology (i.e. biomarker + or preclinical AD) can be differentiated from individuals without AD brain pathology based on naturalistic driving data, such as hard acceleration or braking and speeding, measured using in-vehicle dataloggers. Older adults are at increased risk of injury and death from motor vehicle crashes and driving cessation is also linked to negative health outcomes. Identifying potentially modifiable risk factors that increase driving risk may prolong safe driving in old age. Sleep apnea is associated with adverse driving behaviors across the age span. In this study, we hypothesized that high-risk driving behaviors would be associated with increased sleep apnea severity and AD pathology. We found that higher sleep apnea severity measured by a home sleep apnea test was associated with a higher incidence of adverse driving behaviors even after controlling for multiple confounders (β = 0.24 ± 0.09, p < 0.01). This association was independent of AD biomarker positivity (i.e. increased t-tau/Aβ 42 ratio). Increasing age was associated with a higher likelihood of high-risk driving behaviors in individuals with AD brain pathology (β = 0.12 ± 0.04, p < 0.01), but a lower likelihood in individuals without AD brain pathology (β = -0.06 ± 0.03, p < 0.05). These findings suggest that adverse driving behaviors linked to a higher rate of traffic crashes in older adults are associated with sleep apnea severity and AD pathology even in cognitively unimpaired individuals. Further studies are needed to determine if treatment of sleep apnea decreases high-risk driving behaviors and therefore motor vehicle crashes.

Improvements in cognitive function and quantitative sleep electroencephalogram in obstructive sleep apnea after six months of continuous positive airway pressure treatment

STUDY OBJECTIVES

Untreated obstructive sleep apnea (OSA) is associated with cognitive deficits and altered brain electrophysiology. We evaluated the effect of continuous positive airway pressure (CPAP) treatment on quantitative sleep electroencephalogram (EEG) measures and cognitive function.

METHODS

We studied 167 patients with OSA (age 50 ± 13, AHI 35.0 ± 26.8) before and after 6 months of CPAP. Cognitive tests assessed working memory, sustained attention, visuospatial scanning, and executive function. All participants underwent overnight polysomnography at baseline and after CPAP. Power spectral analysis was performed on EEG data (C3-M2) in a sub-set of 90 participants. Relative delta EEG power and sigma power in NREM and EEG slowing in REM were calculated. Spindle densities (events/min) in N2 were also derived using automated spindle event detection. All outcomes were analysed as change from baseline.

RESULTS

Cognitive function across all cognitive domains improved after six months of CPAP. In our sub-set, increased relative delta power (p < .0001) and reduced sigma power (p = .001) during NREM were observed after the 6-month treatment period. Overall, fast and slow sleep spindle densities during N2 were increased after treatment.

CONCLUSIONS

Cognitive performance was improved and sleep EEG features were enhanced when assessing the effects of CPAP. These findings suggest the reversibility of cognitive deficits and altered brain electrophysiology observed in untreated OSA following six months of treatment.

Association between early stage N2 sleep spindle burst characteristics and vigilance groups: an observational study on patients from a tertiary sleep centre

OBJECTIVE

Obstructive Sleep Apnoea (OSA) is associated with impaired vigilance. This paper examines the hypothesis that sleep spindle (Sp) characteristics during nocturnal sleep can be mapped to vigilance deficits measured by the Psychomotor Vigilance Task (PVT) in patients with OSA.

APPROACH

The PVT was performed prior to In-laboratory Polysomnography for 250 patients. PVT outcomes were clustered into three Vigilance Groups (VGs). Spindles were scored manually for a Training Cohort of 55 patients, (9491 Sps) across different blocks of NREM sleep (SBs) and validated in a Test Cohort (25 patients, 4867 Sps). We proposed a novel set of Sp features including a Spindle Burst Index (SBI), which quantifies the burst characteristics of spindles and constructed models mapping them to VGs. We also explored the performance of conventional Sp features (such as Sp number and density) in our modelling approach.

MAIN RESULTS

In the Training Cohort, we observed statistically significant differences in the SBI across VGs and SBs independent of OSA severity (1st Stage N2 SBI; p=<0.001 across VGs). In the Test Cohort, a Model based on the proposed SBI predicted VG membership with 88% accuracy. A model based on conventional Sp features mapped to VGs with 70.7% accuracy, and a model using mixed burst and conventional features reached an accuracy of 88%.

SIGNIFICANCE

Spindle features measured during diagnostic In-laboratory PSG can be mapped to PVT outcomes. The novel SBI proved useful for exploring the relationship between PVT outcomes and sleep. Further studies in larger populations are needed to verify these conclusions.

Electroencephalography Theta/Beta Ratio Decreases in Patients with Severe Obstructive Sleep Apnea

Purpose

Accumulating evidence suggests that theta/beta ratio (TBR), an electroencephalographic (EEG) frequency band parameter, might serve as an objective marker of executive cognitive control in healthy adults. Obstructive sleep apnea (OSA) has a detrimental impact on patients' behavior and cognitive performance while whether TBR is different in OSA population has not been reported. This study aimed to explore the difference in relative EEG spectral power and TBR during sleep between patients with severe OSA and non-OSA groups.

Patients and Methods

142 participants with in-laboratory nocturnal PSG recording were included, among which 100 participants suffered severe OSA (apnea hypopnea index, AHI > 30 events/hour; OSA group) and 42 participants had no OSA (AHI ≤ 5 events/h; control group). The fast Fourier transformation was used to compute the EEG power spectrum for total sleep duration within contiguous 30-second epochs of sleep. The demographic and polysomnographic characteristics, relative EEG spectral power and TBR of the two groups were compared.

Results

It was found that the beta band power during NREM sleep and total sleep was significantly higher in the OSA group than controls (p < 0.001, p = 0.012, respectively), and the theta band power during NREM sleep and total sleep was significantly lower in the OSA group than controls (p = 0.019, p = 0.014, respectively). TBR during NREM sleep, REM sleep and total sleep was significantly lower in the OSA group compared to the control group (p < 0.001 for NREM sleep and total sleep, p = 0.015 for REM sleep). TBR was negatively correlated with AHI during NREM sleep (r=-0.324, p < 0.001) and total sleep (r=-0. 312, p < 0.001).

Conclusion

TBR was significantly decreased in severe OSA patients compared to the controls, which was attributed to both increased beta power and decreased theta power. TBR may be a stable EEG-biomarker of OSA patients, which may accurately and reliably identify phenotype of patients.

The association between sleep microarchitecture and cognitive function in middle-aged and older men: a community-based cohort study

STUDY OBJECTIVES

Sleep microarchitecture parameters determined by quantitative power spectral analysis (PSA) of electroencephalograms (EEGs) have been proposed as potential brain-specific markers of cognitive dysfunction. However, data from community samples remains limited. This study examined cross-sectional associations between sleep microarchitecture and cognitive dysfunction in community-dwelling men.

METHODS

Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (PSG) (2010-2011). All-night EEG recordings were processed using PSA following artefact exclusion. Cognitive testing (2007-2010) included the inspection time task, trail-making tests A (TMT-A) and B (TMT-B), and Fuld object memory evaluation. Complete case cognition, PSG, and covariate data were available in 366 men. Multivariable linear regression models controlling for demographic, biomedical, and behavioral confounders determined cross-sectional associations between sleep microarchitecture and cognitive dysfunction overall and by age-stratified subgroups.

RESULTS

In the overall sample, worse TMT-A performance was associated with higher NREM theta and REM theta and alpha but lower delta power (all p<0.05). In men ≥65 years, worse TMT-A performance was associated with lower NREM delta but higher NREM and REM theta and alpha power (all p<0.05). Furthermore, in men ≥65 years, worse TMT-B performance was associated with lower REM delta but higher theta and alpha power (all p<0.05).

CONCLUSIONS

Sleep microarchitecture parameters may represent important brain-specific markers of cognitive dysfunction, particularly in older community-dwelling men. Therefore, this study extends the emerging community-based cohort literature on a potentially important link between sleep microarchitecture and cognitive dysfunction. Utility of sleep microarchitecture for predicting prospective cognitive dysfunction and decline warrants further investigation.

On-road driving impairment following sleep deprivation differs according to age

Impaired driving performance due to sleep loss is a major contributor to motor-vehicle crashes, fatalities, and serious injuries. As on-road, fully-instrumented studies of drowsy driving have largely focused on young drivers, we examined the impact of sleep loss on driving performance and physiological drowsiness in both younger and older drivers of working age. Sixteen ‘younger’ adults (M = 24.3 ± 3.1 years [21–33 years], 9 males) and seventeen ‘older’ adults (M = 57.3 ± 5.2, [50–65 years], 9 males) undertook two 2 h drives on a closed-loop track in an instrumented vehicle with a qualified instructor following (i) 8 h sleep opportunity the night prior (well-rested), and (ii) after 29-h of total sleep deprivation (TSD). Following TSD, both age groups displayed increased subjective sleepiness and lane departures (p < 0.05), with younger drivers exhibiting 7.37 × more lane departures, and 11 × greater risk of near crash events following sleep loss. While older drivers exhibited a 3.5 × more lane departures following sleep loss (p = 0.008), they did not have a significant increase in near-crash events (3/34 drives). Compared to older adults, younger adults had 3.1 × more lane departures (p = < 0.001), and more near crash events (79% versus 21%, p = 0.007). Ocular measures of drowsiness, including blink duration, number of long eye closures and PERCLOS increased following sleep loss for younger adults only (p < 0.05). These results suggest that for older working-aged adults, driving impairments observed following sleep loss may not be due to falling asleep. Future work should examine whether this is attributed to other consequences of sleep loss, such as inattention or distraction from the road.

New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences

Current approaches to quantify and diagnose sleep disorders and circadian rhythm disruption are imprecise, laborious, and often do not relate well to key clinical and health outcomes. Newer emerging approaches that aim to overcome the practical and technical constraints of current sleep metrics have considerable potential to better explain sleep disorder pathophysiology and thus to more precisely align diagnostic, treatment and management approaches to underlying pathology. These include more fine-grained and continuous EEG signal feature detection and novel oxygenation metrics to better encapsulate hypoxia duration, frequency, and magnitude readily possible via more advanced data acquisition and scoring algorithm approaches. Recent technological advances may also soon facilitate simple assessment of circadian rhythm physiology at home to enable sleep disorder diagnostics even for “non-circadian rhythm” sleep disorders, such as chronic insomnia and sleep apnea, which in many cases also include a circadian disruption component. Bringing these novel approaches into the clinic and the home settings should be a priority for the field. Modern sleep tracking technology can also further facilitate the transition of sleep diagnostics from the laboratory to the home, where environmental factors such as noise and light could usefully inform clinical decision-making. The “endpoint” of these new and emerging assessments will be better targeted therapies that directly address underlying sleep disorder pathophysiology via an individualized, precision medicine approach. This review outlines the current state-of-the-art in sleep and circadian monitoring and diagnostics and covers several new and emerging approaches to better define sleep disruption and its consequences.

Electroencephalographic Activity and Cognitive Function in Middle-Aged Patients with Obstructive Sleep Apnea Before and After Continuous Positive Airway Pressure Treatment

PURPOSE

To investigate the effect of continuous positive airway pressure (CPAP) on sleep electroencephalogram (EEG) activity in patients with obstructive sleep apnea (OSA) and to examine the correlation between quantitative EEG changes and cognitive function.

PATIENTS AND METHODS

A total of 69 men and 11 women were collected with an average age of 39.61 ± 7.67 years old from among middle-aged patients who had first visits with snoring as their main complaint. All of them completed sleep questionnaires, neurocognitive tests and night polysomnography (PSG). The patients in the OSA group also completed the second night of PSG monitoring under CPAP after pressure titration. A power spectrum analysis of EEG was used, and the correlation between the frequency powers of EEG and the scores of the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Mini-Mental State Examination (MMSE), and the Montreal Cognitive Assessment (MoCA) were further analyzed.

RESULTS

Compared with the control group, the delta/alpha power ratio (DAR) and the (delta + theta)/(alpha + beta) power ratio (the slowing ratio, TSR) of the OSA group before CPAP were higher (P < 0.05). The DAR and TSR of the OSA patients decreased significantly after CPAP. ESS scores were correlated with parameters such as respiratory-related microarousal index (RRMAI), apnea hypopnea index (AHI), and the average absolute power of delta, DAR and TSR (P < 0.05). The PSQI, MMSE and MoCA scores were not correlated with the average absolute power of each frequency band, DAR or TSR (P > 0.05).

CONCLUSION

Patients with OSA have greater slow frequency EEG activity during sleep than the control group. CPAP treatment reversed the slow frequency EEG activity in patients with OSA.

EEG microstate in obstructive sleep apnea patients

Obstructive sleep apnea (OSA) is a common sleep respiratory disease. Previous studies have found that the wakefulness electroencephalogram (EEG) of OSA patients has changed, such as increased EEG power. However, whether the microstates reflecting the transient state of the brain is abnormal is unclear during obstructive hypopnea (OH). We investigated the microstates of sleep EEG in 100 OSA patients. Then correlation analysis was carried out between microstate parameters and EEG markers of sleep disturbance, such as power spectrum, sample entropy and detrended fluctuation analysis (DFA). OSA_OH patients showed that the microstate C increased presence and the microstate D decreased presence compared to OSA_withoutOH patients and controls. The fifth microstate E appeared during N1-OH, but the probability of other microstates transferring to microstate E was small. According to the correlation analysis, OSA_OH patients in N1-OH showed that the microstate D was positively correlated with delta power, and negatively correlated with beta and alpha power; the transition probability of the microstate B → C and E → C was positively correlated with alpha power. In other sleep stages, the microstate parameters were not correlated with power, sample entropy and FDA. We might interpret that the abnormal transition of brain active areas of OSA patients in N1-OH stage leads to abnormal microstates, which might be related to the change of alpha activity in the cortex.

Perception versus Reality: The Relationship between Subjective and Objective Measures of Sleep When On-call under Simulated Laboratory Conditions

BACKGROUND

On-call working arrangements have been shown to negatively impact sleep. However, workers may perceive their sleep to be worse than it actually is. The aim of this study was to compare participants' pre- and post-sleep estimates of sleep duration and sleep quality with objectively measured sleep when on-call under laboratory conditions.

PARTICIPANTS

72 healthy, adult males.

METHODS

Analyses were performed on three interrelated studies, all of which consisted of four nights in a sleep laboratory. Following adaptation and baseline nights were two on-call nights (sleep opportunity 23:00 h - 07:00 h). Before and after each sleep opportunity, participants provided subjective estimates of sleep. Sleep was objectively measured using polysomnography.

RESULTS

Estimated sleep duration (6.74 ± 1.13 h) and sleep onset latency (20.55 ± 14.85 min) were significantly poorer than objectively measured sleep outcomes (sleep duration 7.21 ± 1.25 h; sleep latency 13.20 ± 10.06 min). Of the variance in post-sleep estimated sleep duration, 14% was associated with objectively measured minutes of N3 (R²Δ = 0.55) and REM (R²Δ = 0.75). Additionally, 14% of post-sleep sleep quality estimation variance was associated with minutes of N2 (R²Δ = 0.60) and N3 (R²Δ = 0.79), measured by polysomnography.

CONCLUSIONS

Some objective measures of sleep were associated with subjective estimates of sleep duration and sleep quality. However, individuals may overestimate sleep onset latency and underestimate sleep duration during on-call periods. It may be beneficial for on-call workers to actively reflect on feelings of fatigue/alertness for workplace fatigue management, rather than relying solely on estimates of sleep.

Sleepiness Behind the Wheel and the Implementation of European Driving Regulations

Sleep disturbance and sleepiness are established risk factors for driving accidents and obstructive sleep apnea (OSA) is the most prevalent medical disorder associated with excessive daytime sleepiness. Because effective treatment of OSA reduces accident risk, several jurisdictions have implemented regulations concerning the ability of patients with OSA to drive, unless effectively treated. This review provides a practical guide for clinicians who may be requested to certify a patient with OSA as fit to drive regarding the scope of the problem, the role of questionnaires and driving simulators to evaluate sleepiness, and the benefit of treatment on accident risk.

Physiological correlates of the Epworth Sleepiness Scale reveal different dimensions of daytime sleepiness

The Epworth Sleepiness Scale is commonly used to examine self-reported daytime sleepiness in clinical populations; the physiologic correlates of this scale, however, are not well understood. Furthermore, how well this scale correlates with parallel objective and self-reported concepts of daytime sleepiness is not well described. As such, we used machine learning algorithms to examine the association between Epworth Sleepiness Scale scores and 55 sleep and medical variables in the Sleep Heart Health Study (N = 2105). Secondary analyses examined data stratified by age and gender and the relationship between the Epworth and other measures of daytime sleepiness. Analyses of the main data set resulted in low explained variance (7.15%-10.0%), with self-reported frequency of not getting enough sleep as most important predictor (10.3%-13.9% of the model variance). Stratification by neither age nor gender significantly improved explained variance. Cross-correlational analysis revealed low correlation of other daytime sleepiness measures to Epworth scores. We find that Epworth scores are not well explained by habitual or polysomnographic sleep values, or other biomedical characteristics. These analyses indicate that there are different, potentially orthogonal dimensions of the concept of "daytime sleepiness" that may be driven by different aspects of sleep physiology. As the physiologic correlates of the Epworth Sleepiness Scale remain to be elucidated, interpretation of the clinical meaning of these scores should be done with caution.

EEG Power Spectral Analysis of Abnormal Cortical Activations During REM/NREM Sleep in Obstructive Sleep Apnea

Objective: To characterize electroencephalogram (EEG) power in different frequency bands during rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep in patients with obstructive sleep apnea (OSA). Methods: Retrospective data on 151 patients were collected and divided into three groups: primary snoring group (AHI < 5/h), mild-moderate OSA group (6 ≤ AHI < 30/h), and severe OSA group (AHI ≥ 30/h). EEG recordings in the frontal, central, and occipital regions were extracted from both REM and NREM sleep, to compute the normalized spectral power densities in the delta, theta, alpha, sigma, beta, and gamma frequency bands, using Fast Fourier Transform. Correlations between the computed EEG power and PSG parameters were analyzed. Results: In NREM sleep, elevated normalized power spectral density (PSD) in the delta band was observed in the severe OSA group compared to the other two groups. In contrast, the PSD of the other frequency bands showed a corresponding decrease in the severe OSA group. In REM sleep, similar changes were observed in the frontal region. Delta band PSD was positively correlated with Apnea Hypopnea Index (AHI) (r = 0.33), longest time of apnea, oxygen desaturation index (ODI) (r = 0.34), percent sleep time below 90% SaO₂ (T90%) (r = 0.30), Arousal Index (ArI) (r = 0.29), and negatively correlated with N3%, minimum oxygen saturation (minSaO₂). Conclusion: Our findings provide neurophysiological evidence for pathological cortical activation during REM/NREM sleep, which may be associated with the arousals and cognitive impairments in OSA. The technique of power spectral analysis could prove a potentially useful tool in complementing traditional PSG parameters in assessing disease burden to guide therapeutic decisions.

Effects of surgery for obstructive sleep apnea on cognitive function and driving performance

BACKGROUND

Obstructive sleep apnea (OSA) is associated with a significantly increased risk of motor vehicle accidents in addition to such cognitive impairments as attention and memory deficits. The aim of the study was to examine the effect of upper airway surgery for OSA on driving and cognitive function.

METHODS

Adult patients who underwent surgery for OSA at a tertiary medical center in 2016-2019 were prospectively recruited. Patients were assessed before and 3-6 months after surgery with a self-report and neurocognitive battery and a driving simulation platform.

RESULTS

The cohort included 32 patients of average age 46.9 ± 11.6 years. During the 3 years before treatment, 9 patients had been involved in road accidents and 18 were detained by police for traffic violations. After surgery, there was a significant decrease in the Epworth Sleepiness Scale (13.7 vs. 8.1, p 0.043) and a significant reduction in time to completion of the Color Trail Test (part 1: 21.4 vs 18.7 s, p = 0.049; part 2: 46.8 vs 40.5 s, p = 0.038). Improvements in divided attention and selective attention response times were noted on the advanced stages of the Useful Field of Vision Scale (p = 0.013, p = 0.054). Before surgery, patients showed a high tendency to drive over the speed limit and to cross the dividing line to the opposite lane on the simulation test. Nevertheless, all considered themselves good drivers. These tendencies decreased after treatment.

CONCLUSIONS

Surgery for OSA can significantly improve driving performance and cognitive function.

Are Individuals with Low Trait Anxiety Better Suited to On-Call Work?

Research has indicated that individuals with certain traits may be better suited to shiftwork and non-standard working arrangements. However, no research has investigated how individual differences impact on-call outcomes. As such, this study investigated the impact of trait anxiety on sleep and performance outcomes on-call. Seventy male participants (20–35 years) completed an adaptation night, a control night, and two on-call nights in a laboratory. Trait anxiety was determined using the State Trait Anxiety Inventory (STAI) X-2, and participants completed the STAI X-1 prior to bed each night to assess state anxiety. Sleep was measured using polysomnography and quantitative electroencephalographic analysis. Performance was assessed using a 10-min psychomotor vigilance task (PVT) performed each day at 0930, 1200, 1430 and 1700 h. Data pooled from three separate but inter-related studies was used for these analyses. Results indicated that the effects of trait anxiety on state anxiety, sleep and performance outcomes on-call were generally limited. These findings suggest that on-call outcomes are not negatively affected by higher levels of trait anxiety.

Obstructive Sleep Apnea and Its Treatment in Aging: Effects on Alzheimer's disease Biomarkers, Cognition, Brain Structure and Neurophysiology

Here we review the impact of obstructive sleep apnea (OSA) on biomarkers of Alzheimer's disease (AD) pathogenesis, neuroanatomy, cognition and neurophysiology, and present the research investigating the effects of continuous positive airway pressure (CPAP) therapy. OSA is associated with an increase in AD markers amyloid-β and tau measured in cerebrospinal fluid (CSF), by Positron Emission Tomography (PET) and in blood serum. There is some evidence suggesting CPAP therapy normalizes AD biomarkers in CSF but since mechanisms for amyloid-β and tau production/clearance in humans are not completely understood, these findings remain preliminary. Deficits in the cognitive domains of attention, vigilance, memory and executive functioning are observed in OSA patients with the magnitude of impairment appearing stronger in younger people from clinical settings than in older community samples. Cognition improves with varying degrees after CPAP use, with the greatest effect seen for attention in middle age adults with more severe OSA and sleepiness. Paradigms in which encoding and retrieval of information are separated by periods of sleep with or without OSA have been done only rarely, but perhaps offer a better chance to understand cognitive effects of OSA than isolated daytime testing. In cognitively normal individuals, changes in EEG microstructure during sleep, particularly slow oscillations and spindles, are associated with biomarkers of AD, and measures of cognition and memory. Similar changes in EEG activity are reported in AD and OSA, such as "EEG slowing" during wake and REM sleep, and a degradation of NREM EEG microstructure. There is evidence that CPAP therapy partially reverses these changes but large longitudinal studies demonstrating this are lacking. A diagnostic definition of OSA relying solely on the Apnea Hypopnea Index (AHI) does not assist in understanding the high degree of inter-individual variation in daytime impairments related to OSA or response to CPAP therapy. We conclude by discussing conceptual challenges to a clinical trial of OSA treatment for AD prevention, including inclusion criteria for age, OSA severity, and associated symptoms, the need for a potentially long trial, defining relevant primary outcomes, and which treatments to target to optimize treatment adherence.

Buckle up!

Die Verkehrsmedizin als Teil der Rechtsmedizin erfüllt in der Schweiz eine wichtige präventive Aufgabe in der Sicherung aller Verkehrsteilnehmer: Sie begutachtet die medizinisch basierte Fahrfähigkeit und Fahreignung. Als empirisch konsolidiertes Querschnittsfach hat sie Informationen aus einer Vielzahl von medizinischen Fachgebieten. Wie reagiert die Verkehrsmedizin aber auf den vermehrten Anspruch evidenzbasierter Gutachten und auf anstehende Herausforderungen?

Über einen historischen Abriss motivierten wir die Vorteile und das Potential einer teilweise durch Fahrsimulation ergänzten Untersuchung und einer dediziert auf Fahrsimulation basierenden, klinisch-prospektiven Forschung.

Neben vorhandener Literatur stützen sich historische Aspekte u.a. auf vorhandene Expertise. Die Bewertung der Fahrsimulation für die Verkehrs- bzw. Rechtsmedizin der Schweiz stützt sich auf die Diskussion selektierter Literatur.

Auftrag und Anspruch der Verkehrsmedizin haben sich mehrfach verändert. Eine übersichtsartige Betrachtung existenter Literatur legt nahe, dass massgeschneiderte Fahrsimulatoren Teil einer modernisierten Verkehrsmedizin sein können, um anstehende Herausforderungen adäquat adressieren zu können. Bisher existiert kein derartiges dediziertes Forschungsinstrument in der Schweiz.

Eine auf verkehrsmedizinische Fragestellungen massgeschneiderte, realitätsnahe und niedrigschwellige Fahrsimulation als Werkzeug für klinische Studien und Individualuntersuchungen verspricht neben einer wissenschaftlichen Produktivität einen umsetzbaren und vermittelbaren Mehrwert für das übergeordnete Ziel der Sicherheit aller Verkehrsteilnehmer.

Sleep EEG microstructure is associated with neurobehavioural impairment after extended wakefulness in obstructive sleep apnea

PURPOSE

Using quantitative EEG (qEEG) analysis, we investigated sleep EEG microstructure as correlates of neurobehavioural performance after 24 h of extended wakefulness in untreated OSA.

METHODS

Eight male OSA patients underwent overnight polysomnography (PSG) at baseline followed by 40 h awake with repeated performance testing (psychomotor vigilance task [PVT] and AusEd driving simulator). EEG slowing during REM and spindle density during NREM sleep were calculated using power spectral analysis and a spindle detection algorithm at frontal and central electrode sites. Correlations between sleep EEG microstructure measures and performance after 24-h awake were assessed.

RESULTS

Greater EEG slowing during REM sleep was associated with slower PVT reaction times (rho = - 0.79, p = 0.02), more PVT lapses (rho = 0.87, p = 0.005) and more AusEd crashes (rho = 0.73, p = 0.04). Decreased spindle density in NREM sleep was also associated with slower PVT reaction times (rho = 0.89, p = 0.007). Traditional PSG measures of disease severity were not consistent correlates of neurobehavioural performance in OSA.

CONCLUSIONS

Sleep EEG microstructure measures recorded during routine PSG are associated with impaired vigilance in OSA patients after sleep deprivation.

SIGNIFICANCE

Quantitative brain oscillatory (or EEG)-based measures of sleep may better reflect the deleterious effects of untreated OSA than traditional PSG metrics in at-risk individuals. Trial Registration ACTRN12606000066583.

Effect of Positive Airway Pressure Therapy on Drowsy Driving in a Large Clinic-Based Obstructive Sleep Apnea Cohort

STUDY OBJECTIVES

Drowsy driving related to obstructive sleep apnea (OSA) represents an important public health problem with limited data on the effect of positive airway pressure (PAP) therapy. We hypothesize that PAP therapy will reduce self-reported drowsy driving in a large clinic-based OSA cohort.

METHODS

Drowsy driving (self-reported near-accidents/accidents) incidents from baseline to after PAP therapy (stratified by adherence) were compared in a cohort of 2,059 patients with OSA who initiated PAP therapy from January 1, 2010 to December 31, 2014. Multivariable logistic regression models evaluated the dependence of change in drowsy driving incidents on other factors, including change in Epworth Sleepiness Scale (ESS) and Patient Health Questionnaire-9 (PHQ9) scores.

RESULTS

In the entire cohort (age 56.0 ± 13.1 years, 45.4% female, 76.0% white, average follow-up 124.4 ± 67.3 days), drowsy driving incidents reduced from 14.2 to 6.9% after PAP therapy (P < .001). In subgroups, drowsy driving incidents reduced from 14% to 5.3% (P < .001) in patients who self-reported adherence to PAP therapy and 14.1% to 5.3% (P < .001) in patients objectively adherent to PAP therapy. For each one-point improvement in Epworth Sleepiness Scale score, the odds of drowsy driving decreased by about 14% (odds ratio 0.86, 95% confidence interval 0.82 to 0.90).

CONCLUSIONS

In this clinic-based cohort, drowsy driving improved after adherent PAP usage, with greater drowsy driving risk for those with greater sleep propensity. This highlights the importance of and need for routine drowsy driving assessments and careful clinical attention to PAP adherence and sleep propensity in this population. Our findings should be confirmed and may be used to provide support for initiatives to address the public health issue of drowsy driving.

Overnight heart rate variability and next day cortisol response during simulated on-call conditions

OBJECTIVE

This study had two specific objectives, 1) to investigate the impact of being on-call on overnight heart rate variability during sleep and; 2) to examine whether being on-call overnight impacted next-day salivary cortisol concentrations.

METHODS

Data are reported from three within-subject laboratory studies (n = 24 in each study) that assessed varying on-call conditions. Healthy male participants (n = 72 total) completed a four-night laboratory protocol, comprising an adaptation night, a control night, and two counterbalanced on-call nights with varying on-call conditions. These on-call conditions were designed to determine the impact of, Study 1: the likelihood of receiving a call (definitely, maybe), Study 2: task stress (high-stress, low-stress), and Study 3: chance of missing the alarm (high-chance, low-chance), on measures of physiological stress. Overnight heart rate variability (HRV) (during sleep) was measured using two-lead electrocardiography, and time- and frequency-domain variables were analysed. Saliva samples were collected at 15-min time intervals from 0700-0800 h to determine cortisol awakening response outcomes and at four daily time points (0930 h, 1230 h, 1430 h, and 1730 h) to assess diurnal cortisol profiles.

RESULTS

There were few differences in HRV measures during sleep across all three studies. The only exception was in Study 1 where the standard deviation of the time interval between consecutive heartbeats and the root mean square of consecutive differences between heartbeats were lower across all sleep stages in the definitely condition, when compared to control. Across all three studies, being on-call overnight also had little impact on next-day cortisol awakening response (CAR), with the exception of Study 2 where the 1) CAR area under the curve with respect to increase was blunted in the high-stress condition, compared to the control and low-stress conditions and, 2) CAR reactivity was higher in low-stress condition, compared with the high-stress condition. In Study 1, diurnal cortisol area under the curve with respect to ground was lower in the on-call conditions (definitely and maybe) when compared to control. There were no differences in diurnal cortisol measures in Study 3.

CONCLUSION

This is the first study to investigate how different aspects of being on-call affect physiological stress responses. Overall, relatively little differences in measures of overnight heart rate variability and next-day cortisol response were recorded in all three studies. Further research utilising real on-call work tasks, not just on-call expectations (as in the current study) will help determine the impact of on-call work on the physiological stress response.

Quantitative electroencephalography measures in rapid eye movement and nonrapid eye movement sleep are associated with apnea–hypopnea index and nocturnal hypoxemia in men

Study Objectives

Quantitative electroencephalography (EEG) measures of sleep may identify vulnerability to obstructive sleep apnea (OSA) sequelae, however, small clinical studies of sleep microarchitecture in OSA show inconsistent alterations. We examined relationships between quantitative EEG measures during rapid eye movement (REM) and non-REM (NREM) sleep and OSA severity among a large population-based sample of men while accounting for insomnia.

Methods

All-night EEG (F4-M1) recordings from full in-home polysomnography (Embletta X100) in 664 men with no prior OSA diagnosis (age ≥ 40) were processed following exclusion of artifacts. Power spectral analysis included non-REM and REM sleep computed absolute EEG power for delta, theta, alpha, sigma, and beta frequency ranges, total power (0.5–32 Hz) and EEG slowing ratio.

Results

Apnea–hypopnea index (AHI) ≥10/h was present in 51.2% (severe OSA [AHI ≥ 30/h] 11.6%). In mixed effects regressions, AHI was positively associated with EEG slowing ratio and EEG power across all frequency bands in REM sleep (all p < 0.05); and with beta power during NREM sleep (p = 0.06). Similar associations were observed with oxygen desaturation index (3%). Percentage total sleep time with oxygen saturation <90% was only significantly associated with increased delta, theta, and alpha EEG power in REM sleep. No associations with subjective sleepiness were observed.

Conclusions

In a large sample of community-dwelling men, OSA was significantly associated with increased EEG power and EEG slowing predominantly in REM sleep, independent of insomnia. Further study is required to assess if REM EEG slowing related to nocturnal hypoxemia is more sensitive than standard PSG indices or sleepiness in predicting cognitive decline.

Slow-wave activity surrounding stage N2 K-complexes and daytime function measured by psychomotor vigilance test in obstructive sleep apnea

STUDY OBJECTIVE

To better understand the inter-individual differences in neurobehavioral impairment in obstructive sleep apnea (OSA) and its treatment with continuous positive airway pressure (CPAP), we examined how changes in sleep electroencephalography (EEG) slow waves were associated with next-day psychomotor vigilance test (PVT) performance.

METHODS

Data from 28 OSA subjects (Apnea-Hypopnea Index with 3% desaturation and/or with an associated arousal [AHI3A] > 15/hour; AHI3A = sum of all apneas and hypopneas with 3% O2 desaturation and/or an EEG arousal, divided by total sleep time [TST]), who underwent three full in-lab nocturnal polysomnographies (NPSGs: chronic OSA, CPAP-treated OSA, and acute OSA), and 19 healthy sleepers were assessed. Four 20-minute PVTs were performed after each NPSG along with subjective and objective assessment of sleepiness. Three EEG metrics were calculated: K-complex (KC) Density (#/minute of N2 sleep), change in slow-wave activity in 1-second envelopes surrounding KCs (ΔSWAK), and relative frontal slow-wave activity during non-rapid eye movement (NREM) (%SWA).

RESULTS

CPAP treatment of OSA resulted in a decrease in KC Density (chronic: 3.9 ± 2.2 vs. treated: 2.7 ± 1.1; p < 0.01; mean ± SD) and an increase in ΔSWAK (chronic: 2.6 ± 2.3 vs. treated: 4.1 ± 2.4; p < 0.01) and %SWA (chronic: 20.9 ± 8.8 vs. treated: 26.6 ± 8.6; p < 0.001). Cross-sectionally, lower ΔSWAK values were associated with higher PVT Lapses (chronic: rho = -0.55, p < 0.01; acute: rho = -0.46, p = 0.03). Longitudinally, improvement in PVT Lapses with CPAP was associated with an increase in ΔSWAK (chronic to treated: rho = -0.48, p = 0.02; acute to treated: rho = -0.5, p = 0.03). In contrast, OSA severity or global sleep quality metrics such as arousal index, NREM, REM, or TST were inconsistently associated with PVT Lapses.

CONCLUSION

Changes in EEG slow waves, in particular ∆SWAK, explain inter-individual differences in PVT performance better than conventional NPSG metrics, suggesting that ΔSWAK is a night-time correlate of next-day vigilance in OSA.

Intra-individual stability of NREM sleep quantitative EEG measures in obstructive sleep apnea

Electroencephalography is collected routinely during clinical polysomnography, but is often utilised to simply determine sleep time to calculate apnea-hypopnea indices. Quantitative analysis of these data (quantitative electroencephalogram) may provide trait-like information to predict patient vulnerability to sleepiness. Measurements of trait-like characteristics need to have high test-retest reliability. We aimed to investigate the intra-individual stability of slow-wave (delta power) and spindle frequency (sigma power) activity during non-rapid eye movement sleep in patients with obstructive sleep apnea. We recorded sleep electroencephalograms during two overnight polysomnographic recordings in 61 patients with obstructive sleep apnea (median days between studies 47, inter-quartile range 53). Electroencephalograms recorded at C3-M2 derivation were quantitatively analysed using power spectral analysis following artefact removal. Relative delta (0.5-4.5 Hz) and sigma (12-15 Hz) power during non-rapid eye movement sleep were calculated. Intra-class correlation coefficients and Bland-Altman plots were used to assess agreement between nights. Intra-class correlation coefficients demonstrated good-to-excellent agreement in the delta and sigma frequencies between nights (intra-class correlation coefficients: 0.84, 0.89, respectively). Bland-Altman analysis of delta power showed a mean difference close to zero (-0.4, 95% limits of agreement -9.4, 8.7) and no heteroscedasticity with increasing power. Sigma power demonstrated heteroscedasticity, with reduced stability as sigma power increased. The mean difference of sigma power between nights was close to zero (0.1, 95% limits -1.6, 1.8). We have demonstrated the stability of slow-wave and spindle frequency electroencephalograms during non-rapid eye movement sleep within patients with obstructive sleep apnea. The electroencephalogram profile during non-rapid eye movement sleep may be a useful biomarker for predicting vulnerability to daytime impairment in obstructive sleep apnea and responsiveness to treatment.

Opportunities for utilizing polysomnography signals to characterize obstructive sleep apnea subtypes and severity

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder with many pathophysiological pathways to disease. Currently, the diagnosis and classification of OSA is based on the apnea-hypopnea index, which poorly correlates to underlying pathology and clinical consequences. A large number of in-laboratory sleep studies are performed around the world every year, already collecting an enormous amount of physiological data within an individual. Clinically, we have not yet fully taken advantage of this data, but combined with existing analytical approaches, we have the potential to transform the way OSA is managed within an individual patient. Currently, respiratory signals are used to count apneas and hypopneas, but patterns such as inspiratory flow signals can be used to predict optimal OSA treatment. Electrocardiographic data can reveal arrhythmias, but patterns such as heart rate variability can also be used to detect and classify OSA. Electroencephalography is used to score sleep stages and arousals, but specific patterns such as the odds-ratio product can be used to classify how OSA patients responds differently to arousals.

OBJECTIVE

In this review, we examine these and many other existing computer-aided polysomnography signal processing algorithms and how they can reflect an individual's manifestation of OSA.

SIGNIFICANCE

Together with current technological advance, it is only a matter of time before advanced automatic signal processing and analysis is widely applied to precision medicine of OSA in the clinical setting.

EEG characteristic analysis of coach bus drivers based on brain connectivity as revealed via a graph theoretical network

This study describes the detection of driving fatigue using the characteristics of brain networks in a real driving environment. First, the θ, β and 36–44 Hz rhythm from the EEG signals of drivers were extracted using wavelet packet decomposition (WPD). The correlation between EEG channels was calculated using a Pearson correlation coefficient and subsequently, the brain networks were built. Furthermore, the clustering coefficient (C) and global efficiency (G) of the complex brain networks were calculated to analyze the functional differences in the brains of drivers over time. Combined with the relative power spectrum ratio (β/θ) of EEG signals and the mean value from questionnaires, the correlation of data characteristics between brain networks and subjective and objective data was analyzed. The results show that changes in the fatigue state of drivers can be effectively detected by calculating the data characteristics of brain networks in a real driving environment.

This study describes the detection of driving fatigue using the characteristics of brain networks in a real driving environment.

Effects of Habenular Stimulation Frequencies on Obstructive Sleep Apnea Induced by Stimulation of Insular Cortex

Objective

To investigate the effects of high-frequency stimulation of the habenula (Hb) on obstructive sleep apnea (OSA) induced by stimulation of the insular cortex Method. After OSA was induced by stimulating the insular cortex (Ic) with concentric stimulating electrodes at 100 Hz in rats, the Hb was stimulated at different frequencies (50 Hz, 120 Hz, 130 Hz, and 280 Hz). The changes of apnea events and electromyography (EMG) of the genioglossus were compared before and after stimulation of the Hb.

Results

With stimulation of the Ic at 100 Hz, apnea events were successfully induced with disappearance of EMG of the genioglossus. After stimulation of the Hb at 130 Hz, apnea events disappeared with significantly increased genioglossal EMG. However, such a change failed to be found at the stimulation frequencies of 50 Hz, 120 Hz, and 280 Hz.

Conclusion

Stimulation of the Hb at the frequency of 130 Hz could effectively inhibit OSA events induced by stimulation of the Ic.

Real-Time ECG-Based Detection of Fatigue Driving Using Sample Entropy

In present work, the heart rate variability (HRV) characteristics, calculated by sample entropy (SampEn), were used to analyze the driving fatigue state at successive driving stages. Combined with the relative power spectrum ratio β/(θ + α), subjective questionnaire, and brain network parameters of electroencephalogram (EEG) signals, the relationships between the different characteristics for driving fatigue were discussed. Thus, it can conclude that the HRV characteristics (RR SampEn and R peaks SampEn), as well as the relative power spectrum ratio β/(θ + α) of the channels (C3, C4, P3, P4), the subjective questionnaire, and the brain network parameters, can effectively detect driving fatigue at various driving stages. In addition, the method for collecting ECG signals from the palm part does not need patch electrodes, is convenient, and will be practical to use in actual driving situations in the future.

Sleep apnea and its role in transportation safety

Obstructive sleep apnea (OSA) is a main cause of excessive daytime sleepiness and increases the risk for driving accidents, which can be normalized by treatment with continuous positive airway pressure ventilation. Since it is estimated that OSA is not diagnosed in about 80% of cases, recognition of patients at risk for driving accidents is a problem from both medical and societal points of view. Strategies to screen and identify subjects at high risk for driving accidents are under study in order to improve safety on the road, especially for commercial drivers, who show a high prevalence of OSA.