The impact of alcohol consumption on commercial eye blink drowsiness detection technology.

INTRODUCTION: Driver drowsiness detection technology that assesses eye blinks is increasingly being used as a safety intervention in the transport industry. It is unclear how alcohol consumption to common legal driving limits impacts upon this technology. The aim of the study was to assess the impact of a blood alcohol content (BAC) of 0.05% and of 0.08% on drowsiness detection technology during simulated driving. METHODS: Participants completed a 60-min driving simulation and sleepiness questionnaire under three conditions: 1-0.00% BAC, 2-0.05% BAC and 3-0.08% BAC. During the driving simulation task participants wore a commercial eye blink drowsiness detection technology (Optalert) with the drowsiness alarms silenced. RESULTS: Twelve participants (3 female) completed all alcohol conditions. Relative to baseline, all eye blink parameters were affected at 0.08% BAC (all p < 0.05), whereas 0.05% BAC only affected the composite eye blink drowsiness measure (the Johns Drowsiness Scale). CONCLUSIONS: Alcohol consumption to 0.08% BAC impaired eye blink measures to a level that would be considered a moderate drowsiness risk. Therefore, employers should be aware that drowsiness alerts from these technologies may increase after alcohol consumption.

A brief assessment of eye blink drowsiness immediately prior to or following driving detects drowsiness related driving impairment.

Drowsy driving is a major cause of fatal and serious injury motor vehicle accidents. The inability objectively to assess drowsiness has hindered the assessment of fitness to drive and the development of drowsy driving regulations. This study evaluated whether spontaneous eye blink parameters measured briefly pre- and post-drive could be used to detect drowsy driving impairment. Twelve healthy participants (6 female) drove an instrumented vehicle for 2 h on a closed-loop track during a rested (8-10 h awake) and an extended wake condition (32-34 h awake). Pre- and post-drive, the participants completed a 5 min eye blink task, a psychomotor vigilance task (PVT), and the Karolinska sleepiness scale (KSS). Whole drive impairment was defined as >3.5 lane departures per hour. Severe end of drive impairment was defined as ≥2 lane departures in the last 15 min. The pre-drive % of time with eyes closed best predicted the whole drive impairment (area under the curve [AUC] 0.87). KSS had similar prediction ability (AUC 0.85), while PVT reaction time (AUC 0.72) was less accurate. The composite eye blink parameter, the Johns drowsiness scale was the best retrospective detector of severe end of drive impairment (AUC 0.99). The PVT reaction time (AUC 0.92) and the KSS (AUC 0.93) were less accurate. Eye blink parameters detected drowsy driving impairment with an accuracy that was similar to, or marginally better than, PVT and KSS. As eye blink measures are simple to measure, are objective and have high accuracy, they present an ideal option for the assessment of fitness for duty and roadside drowsiness.

The impact of break duration, time of break onset, and prior shift duration on the amount of sleep between shifts in heavy vehicle drivers.

This study aimed to examine the impact of break duration between consecutive shifts, time of break onset, and prior shift duration on total sleep time (TST) between shifts in heavy vehicle drivers (HVDs), and to assess the interaction between break duration and time of break onset. The sleep (actigraphy and sleep diaries) and work shifts (work diaries) of 27 HVDs were monitored during their usual work schedule for up to 9 weeks. Differences in TST between consecutive shifts and days off were assessed. Linear mixed models (followed by pairwise comparisons) assessed whether break duration, prior shift duration, time of break onset, and the interaction between break duration and break onset were related to TST between shifts. Investigators found TST between consecutive shifts (mean [SD] 6.38 [1.38] h) was significantly less than on days off (mean [SD] 7.63 [1.93] h; p < 0.001). Breaks starting between 12:01 and 8:00 a.m. led to shorter sleep (p < 0.05) compared to breaks starting between 4:01 and 8:00 p.m. Break durations up to 7, 9, and 11 h (Australian and European minimum break durations) resulted in a mean (SD) of 4.76 (1.06), 5.66 (0.77), and 6.41 (1.06) h of sleep, respectively. The impact of shift duration prior to the break and the interaction between break duration and time of break were not significant. HVDs' sleep between workdays is influenced independently by break duration and time of break onset. This naturalistic study provides evidence that current break regulations prevent sufficient sleep duration in this industry. Work regulations should evaluate appropriate break durations and break onset times to allow longer sleep opportunities for HVDs.

The impact of aging on driving performance in patients with untreated obstructive sleep apnea.

OBJECTIVE: To determine the influence of age on sleepiness-related driving performance in individuals with obstructive sleep apnea (OSA). DESIGN: Extended wakefulness protocol comparing simulated driving performance in younger and older individuals with OSA. PARTICIPANTS: Fifty-two individuals with OSA (15 female) were median split into younger (≤55 years, n = 26) and older (>55 years, n = 26) groups. MEASUREMENTS: Participants underwent polysomnography to derive sleep parameters and confirm OSA diagnosis. One-to-2 weeks following polysomnography, participants completed a 60-minute driving simulation 4 hours prior to their habitual bedtime. Participants remained awake to 3 hours post habitual bedtime before repeating the task. RESULTS: Median age was 44.5 years (25th, 75th centiles = 37.0, 48.0) for the younger group and 64.5 years (60.0, 70.0) for the older group. When comparing the performance change between baseline and extended wakefulness, the younger patients had greater deterioration on all driving simulator parameters (crashes, standard deviation of lateral position, speed deviation and braking reaction time, all p < .05), compared to the older group. Linear regression found a 10-year age increase was associated with an a ∼30%-41% reduction in crash occurrence when accounting for covariates (p = .023). Age also predicted standard deviation of lateral position deviation, but not when sleep efficiency and self-reported sleepiness were included as covariates. CONCLUSION: Older participants with OSA were less vulnerable than younger participants to sleepiness-related driving simulator impairment when assessed at night-time following extended wakefulness. Future work should assess naturalistic on-road driving to determine if this extends to a variety of challenging driving scenarios.

An evaluation and comparison of commercial driver sleepiness detection technology: a rapid review.

Objective. Sleepiness-related motor vehicle crashes, caused by lack of sleep or driving during night-time hours, often result in serious injury or fatality. Sleepiness detection technology is rapidly emerging as a sleepiness risk mitigation strategy for drivers. Continuous monitoring technologies assess and alert to driver sleepiness in real-time, while fit for duty technologies provide a single assessment of sleepiness state. The aim of this rapid review was to evaluate and compare sleepiness detection technologies in relation to specifications, cost, target consumer group and validity.Approach. We evaluated a range of sleepiness detection technologies suitable for consumer groups ranging from regular drivers in private vehicles through to work-related drivers within large businesses.Main results. Continuous monitoring technologies typically ranged between $100 and $3000 AUD and had ongoing monthly costs for telematics functionality and manager alerts. Fit for duty technologies had either a one-off purchase cost or a monthly subscription cost. Of concern, the majority of commercial continuous monitoring technologies lacked scientific validation. While some technologies had promising findings in terms of their ability to detect and reduce driver sleepiness, further validation work is required. Field studies that evaluate the sensitivity and specificity of technology alerts under conditions that are regularly experienced by drivers are necessary. Additionally, there is a need for longitudinal naturalistic driving studies to determine whether sleepiness detection technologies actually reduce sleepiness-related crashes or near-crashes.Significance. There is an abundance of sleepiness detection technologies on the market, but a majority lacked validation. There is a need for these technologies and their validation to be regulated by a driver safety body. Otherwise, consumers will base their technology choices on cost and features, rather than the ability to save lives.

The impact of 7-hour and 11-hour rest breaks between shifts on heavy vehicle truck drivers' sleep, alertness and naturalistic driving performance.

BACKGROUND: An inadequate rest break between shifts may contribute to driver sleepiness. This study assessed whether extending the major rest break between shifts from 7-hours (Australian industry standard) to 11-hours, improved drivers' sleep, alertness and naturalistic driving performance. METHODS: 17 heavy vehicle drivers (16 male) were recruited to complete two conditions. Each condition comprised two 13-hour shifts, separated by either a 7- or 11-hour rest break. The initial 13-hour shift was the drivers' regular work. The rest break and following 13-hour shift were simulated. The simulated shift included 5-hours of naturalistic driving with measures of subjective sleepiness, physiological alertness (ocular and electroencephalogram) and performance (steering and lane departures). RESULTS: 13 drivers provided useable data. Total sleep during the rest break was greater in the 11-hour than the 7-hour condition (median hours [25th to 75th percentile] 6.59 [6.23, 7.23] vs. 5.07 [4.46, 5.38], p = 0.008). During the simulated shift subjective sleepiness was marginally better for the 11-hour condition (mean Karolinska Sleepiness Scale [95th CI] = 4.52 [3.98, 5.07] vs. 5.12 [4.56, 5.68], p = 0.009). During the drive, ocular and vehicle metrics were improved for the 11-hour condition (p<0.05). Contrary to expectations, mean lane departures p/hour were increased during the 11-hour condition (1.34 [-0.38,3.07] vs. 0.63 [-0.2,1.47], p = 0.027). CONCLUSIONS: Extending the major rest between shifts substantially increases sleep duration and has a modest positive impact on driver alertness and performance. Future work should replicate the study in a larger sample size to improve generalisability and assess the impact of consecutive 7-hour major rest breaks.

Eye blink parameters to indicate drowsiness during naturalistic driving in participants with obstructive sleep apnea: A pilot study.

OBJECTIVES: To determine whether continuous eye blink measures could identify drowsiness in patients with obstructive sleep apnea (OSA) during a week of naturalistic driving. DESIGN: Observational study comparing OSA patients and healthy controls. SETTING: Regular naturalistic driving across one week. PARTICIPANTS: Fifteen untreated moderate to severe OSA patients and 15 age (± 5 years) and sex (female = 6) matched healthy controls. MEASUREMENTS: Participants wore an eye blink drowsiness recording device during their regular driving for one week. RESULTS: During regular driving, the duration of time with no ocular movements (quiescence), was elevated in the OSA group by 43% relative to the control group (mean [95% CI] 0.20[0.17, 0.25] vs 0.14[0.12, 0.18] secs, P = .011). During long drives only, the Johns Drowsiness Scale was also elevated and increased by 62% in the OSA group relative to the control group (1.05 [0.76, 1.33] vs 0.65 [0.36, 0.93], P = .0495). Across all drives, critical drowsiness events (defined by a Johns Drowsiness Scale score ≥2.6) were twice as frequent in the OSA group than the control group (rate ratio [95% CI] =1.93 [1.65, 2.25], P ≤ .001). CONCLUSIONS: OSA patients were drowsier than healthy controls according to some of the continuous real time eye blink drowsiness measures. The findings of this pilot study suggest that there is potential for eye blink measures to be utilized to assess fitness to drive in OSA patients. Future work should assess larger samples, as well as the relationship of eye blink measures to conventional fitness to drive assessments and crash risk.

An assessment of a simple clinical technique to estimate pharyngeal collapsibility in people with obstructive sleep apnea.

STUDY OBJECTIVES: Quantification of upper airway collapsibility in obstructive sleep apnea (OSA) could help inform targeted therapy decisions. However, current techniques are clinically impractical. The primary aim of this study was to assess if a simple, novel technique could be implemented as part of a continuous positive airway pressure (CPAP) titration study to assess pharyngeal collapsibility. METHODS: A total of 35 participants (15 female) with OSA (mean ± SD apnea-hypopnea index = 35 ± 19 events/h) were studied. Participants first completed a simple clinical intervention during a routine CPAP titration, where CPAP was transiently turned off from the therapeutic pressure for ≤5 breaths/efforts on ≥5 occasions during stable non-rapid eye movement (non-REM) sleep for quantitative assessment of airflow responses (%peak inspiratory flow [PIF] from preceding 5 breaths). Participants then underwent an overnight physiology study to determine the pharyngeal critical closing pressure (Pcrit) and repeat transient drops to zero CPAP to assess airflow response reproducibility. RESULTS: Mean PIF of breaths 3-5 during zero CPAP on the simple clinical intervention versus the physiology night were similar (34 ± 29% vs. 28 ± 30% on therapeutic CPAP, p = 0.2; range 0%-90% vs. 0%-95%). Pcrit was -1.0 ± 2.5 cmH2O (range -6 to 5 cmH2O). Mean PIF during zero CPAP on the simple clinical intervention and the physiology night correlated with Pcrit (r = -0.7 and -0.9, respectively, p < 0.0001). Receiver operating characteristic curve analysis indicated significant diagnostic utility for the simple intervention to predict Pcrit < -2 and < 0 cmH2O (AUC = 0.81 and 0.92), respectively. CONCLUSIONS: A simple CPAP intervention can successfully discriminate between patients with and without mild to moderately collapsible pharyngeal airways. This scalable approach may help select individuals most likely to respond to non-CPAP therapies.

Vehicle and Highway Adaptations to Compensate for Sleepy Drivers.

Sleepiness remains a major contributor to road crashes. Driver monitoring systems identify early signs of sleepiness and alert drivers, using real-time analysis of eyelid movements, EEG activity, and steering control. Other vehicle adaptations warn drivers of lane departures or collision hazards, with higher vehicle automation actively taking over vehicle control to prevent run off the road incidents and institute emergency braking. Similarly, road adaptations warn drivers (rumble strips) or mitigate crash severity (barriers). Infrastructure to encourage drivers to use countermeasures, such as rest stops for napping, is also important. The effectiveness of adaptations varies for different road users.

Genioglossus muscle responses to resistive loads in severe OSA patients and healthy control subjects.

This study aimed to determine whether there is impairment of genioglossus neuromuscular responses to small negative pressure respiratory stimuli, close to the conscious detection threshold, in obstructive sleep apnea (OSA). We compared genioglossus electromyogram (EMGgg) responses to midinspiratory resistive loads of varying intensity (≈1.2-6.2 cmH2O·L-1·s), delivered via a nasal mask, between 16 severe OSA and 17 control participants while the subjects were awake and in a seated upright position. We examined the relationship between stimulus intensity and peak EMGgg amplitude in a 200-ms poststimulus window and hypothesized that OSA patients would have an increased activation threshold and reduced sensitivity in the relationship between EMGgg activation and stimulus intensity. There was no significant difference between control and OSA participants in the threshold (P = 0.545) or the sensitivity (P = 0.482) of the EMGgg amplitude vs. stimulus intensity relationship, where change in epiglottic pressure relative to background epiglottic pressure represented stimulus intensity. These results do not support the hypothesis that deficits in neuromuscular response to negative upper airway pressure exist in OSA during wakefulness; however, the results are likely influenced by a counterintuitive and novel genioglossus muscle suppression response observed in a significant proportion of both OSA and healthy control participants. This suppression response may relate to the inhibition seen in inspiratory muscles such as the diaphragm in response to sudden-onset negative pressure, and its presence provides new insight into the upper airway neuromuscular response to the collapsing force of negative pressure.NEW & NOTEWORTHY Our study used a novel midinspiratory resistive load stimulus to study upper airway neuromuscular responses to negative pressure during wakefulness in obstructive sleep apnea (OSA). Although no differences were found between OSA and healthy groups, the study uncovered a novel and unexpected suppression of neuromuscular activity in a large proportion of both OSA and healthy participants. The unusual response provides new insight into the upper airway neuromuscular response to the collapsing force of negative pressure.

Eye-Blink Parameters Detect On-Road Track-Driving Impairment Following Severe Sleep Deprivation.

STUDY OBJECTIVES: Drowsiness leads to 20% of fatal road crashes, while inability to assess drowsiness has hampered drowsiness interventions. This study examined the accuracy of eye-blink parameters for detecting drowsiness related driving impairment in real time. METHODS: Twelve participants undertook two sessions of 2-hour track-driving in an instrumented vehicle following a normal night's sleep or 32 to 34 hours of extended wake in a randomized crossover design. Eye-blink parameters and lane excursion events were monitored continuously. RESULTS: Sleep deprivation increased the rates of out-of-lane driving events and early drive terminations. Episodes of prolonged eyelid closures, blink duration, the ratio of amplitude to velocity of eyelid closure, and John's Drowsiness Score (JDS, a composite score) were also increased following sleep deprivation. A time-on-task (drive duration) effect was evident for out-of-lane events rate and most eye-blink parameters after sleep deprivation. The JDS demonstrated the strongest association with the odds of out-of-lane events in the same minute, whereas measures of blink duration and prolonged eye closure were stronger indicators of risk for out-of-lane events over longer periods of 5 minutes and 15 minutes, respectively. Eye-blink parameters also achieved moderate accuracies (specificities from 70.12% to 84.15% at a sensitivity of 50%) for detecting out-of-lane events in the same minute, with stronger associations over longer timeframes of 5 minutes to 15 minutes. CONCLUSIONS: Eyelid closure parameters are useful tools for monitoring and predicting drowsiness-related driving impairment (out-of-lane events) that could be utilized for monitoring drowsiness and assessing the efficacy of drowsiness interventions. CLINICAL TRIAL REGISTRATION: This study is registered with the Australian New Zealand Clinical Trial Registry (ANCTR), http://www.anzctr.org.au/TrialSearch.aspx ACTRN12612000102875. CITATION: Shekari Soleimanloo S, Wilkinson VE, Cori JM,Westlake J, Stevens B, Downey LA, Shiferaw BA, Rajaratnam SMW, Howard ME. Eye-blink parameters detect on-road track-driving impairment following severe sleep deprivation. J Clin Sleep Med. 2019;15(9):1271-1284.

Narrative review: Do spontaneous eye blink parameters provide a useful assessment of state drowsiness?

Most objective drowsiness measures have limited ability to provide continuous, accurate assessment of drowsiness state in operational settings. Spontaneous eye blink parameters are ideal for drowsiness assessment as they are objective, non-invasive, and can be recorded continuously during regular activities. Studies that have assessed the spontaneous eye blink as a drowsiness measure are diverse, varying greatly in respect to study design, eye blink acquisition technology and eye blink parameters assessed. The purpose of this narrative review is to collate these studies to determine 1) which eye blink parameters provide the best state drowsiness measures; 2) how well eye blink parameters relate to and predict conventional drowsiness measures and 3) whether eye blink parameters can identify drowsiness impairment in obstructive sleep apnoea (OSA) - a highly prevalent disorder associated with excessive sleepiness and increased accident risk. In summary, almost all eye blink parameters varied consistently with drowsiness state, with blink duration and percentage of eye closure the most robust. All eye blink parameters were associated with and predicted conventional drowsiness measures, with generally fair to good accuracy. Eye blink parameters also showed utility for identifying OSA patients and treatment response, suggesting these parameters may identify drowsiness impairment in this group.

Randomised controlled trial of polysomnographic titration of noninvasive ventilation.

Noninvasive ventilation (NIV) settings determined during wakefulness may produce patient-ventilator asynchrony (PVA) during sleep, causing sleep disruption and limiting tolerance. This study investigated whether NIV titrated with polysomnography (PSG) is associated with less PVA and sleep disruption than therapy titrated during daytime alone.Treatment-naive individuals referred for NIV were randomised to control (daytime titration followed by sham polysomnographic titration) or PSG (daytime titration followed by polysomnographic titration) groups. Primary outcomes were PVA and arousal indices on PSG at 10 weeks. Secondary outcomes included adherence, gas exchange, symptoms and health-related quality of life (HRQoL).In total, 60 participants were randomised. Most (88.3%) had a neuromuscular disorder and respiratory muscle weakness but minor derangements in daytime arterial blood gases. PVA events were less frequent in those undergoing polysomnographic titration (median (interquartile range (IQR)): PSG 25.7 (12-68) events·h-1 versus control 41.0 (28-182) events·h-1; p=0.046), but arousals were not significantly different (median (IQR): PSG 11.4 (9-19) arousals·h-1 versus control 14.6 (11-19) arousals·h-1; p=0.258). Overall adherence was not different except in those with poor early adherence (<4 h·day-1) who increased their use after polysomnographic titration (mean difference: PSG 95 (95% CI 29-161) min·day-1 versus control -23 (95% CI -86-39) min·day-1; p=0.01). Arterial carbon dioxide tension, somnolence and sleep quality improved in both groups. There were no differences in nocturnal gas exchange or overall measures of HRQoL.NIV titrated with PSG is associated with less PVA but not less sleep disruption when compared with therapy titrated during daytime alone.

Sleeping tongue: current perspectives of genioglossus control in healthy individuals and patients with obstructive sleep apnea.

The focus of this review was on the genioglossus (GG) muscle and its role in maintaining upper airway patency in both healthy individuals and obstructive sleep apnea (OSA) patients. This review provided an overview of GG anatomy and GG control and function during both wakefulness and sleep in healthy individuals and in those with OSA. We reviewed evidence for the role of the GG in OSA pathogenesis and also highlighted abnormalities in GG morphology, responsiveness, tissue movement patterns and neurogenic control that may contribute to or result from OSA. We summarized the different methods for improving GG function and/or activity in OSA and their efficacy. In addition, we discussed the possibility that assessing the synergistic activation of multiple upper airway dilator muscles may provide greater insight into upper airway function and OSA pathogenesis, rather than assessing the GG in isolation.

The Differential Effects of Regular Shift Work and Obstructive Sleep Apnea on Sleepiness, Mood and Neurocognitive Function.

STUDY OBJECTIVES: To assess whether poor sleep quality experienced by regular shift workers and individuals with obstructive sleep apnea (OSA) affects neurobehavioral function similarly, or whether the different etiologies have distinct patterns of impairment. METHODS: Thirty-seven shift workers (> 24 hours after their last shift), 36 untreated patients with OSA, and 39 healthy controls underwent assessment of sleepiness (Epworth Sleepiness Scale [ESS]), mood (Beck Depression Index, State Trait Anxiety Inventory [STAI], Profile of Mood States), vigilance (Psychomotor Vigilance Task [PVT], Oxford Sleep Resistance Test [OSLER], driving simulation), neurocognitive function (Logical Memory, Trails Making Task, Digit Span Task, Victoria Stroop Test) and polysomnography. RESULTS: Sleepiness (ESS score; median, interquartile range) did not differ between the OSA (10.5, 6.3-14) and shift work (7, 5-11.5) groups, but both had significantly elevated scores relative to the control group (5, 3-6). State anxiety (STAI-S) was the only mood variable that differed significantly between the OSA (35, 29-43) and shift work (30, 24-33.5) groups, however both demonstrated several mood deficits relative to the control group. The shift work and control groups performed similarly on neurobehavioral tasks (simulated driving, PVT, OSLER and neurocognitive tests), whereas the OSA group performed worse. On the PVT, lapses were significantly greater for the OSA group (3, 2-6) than both the shift work (2, 0-3.5) and control (1, 0-4) groups. CONCLUSIONS: Shift workers and patients with OSA had similar sleepiness and mood deficits relative to healthy individuals. However, only the patients with OSA showed deficits on vigilance and neurocognitive function relative to healthy individuals. These findings suggest that distinct causes of sleep disturbance likely result in different patterns of neurobehavioral dysfunction.

The Effects of Experimental Sleep Fragmentation and Sleep Deprivation on the Response of the Genioglossus Muscle to Inspiratory Resistive Loads.

STUDY OBJECTIVES: Poor upper airway dilator muscle function may contribute to obstructive sleep apnea (OSA). Sleep deprivation reduces dilator muscle responsiveness, but sleep fragmentation, which is most characteristic of OSA, has not been assessed. This study compared the effects of sleep deprivation and fragmentation on dilator muscle responsiveness during wakefulness. METHODS: Twenty-four healthy individuals (10 female) participated in two consecutive overnight polysomnography (PSG) sessions. The first was an adaptation PSG of normal sleep. The second was an experimental PSG, where participants were allocated to groups of either normal sleep, no sleep, or fragmented sleep. Inspiratory resistive loading assessment occurred the morning following each PSG. Four 10 cmH2O and four 20 cmH2O loads were presented in random order for 60 seconds while participants were awake and supine. Sleep (electroencephalogram, electrooculogram, electromyogram [EMG]), intramuscular genioglossus activity (EMGGG), and ventilation were measured throughout the loading sessions. RESULTS: Five controls, seven sleep deprivation participants, and seven sleep fragmentation participants provided data. Contrary to expectations, neither EMGGG nor ventilation showed significant interaction effects (group × session × load) during resistive loading. There was a main effect of load, with peak EMGGG (mean % max ± standard error) significantly higher for the 20 cmH2O load (4.1 ± 0.6) than the 10 cmH2O load (3.3 ± 0.6) across both sessions and all groups. Similar results were observed for peak inspiratory flow, duty cycle, and mask pressure. CONCLUSIONS: Upper airway function was not affected by 1 night of no sleep or poor-quality sleep. This raises doubt as to whether fragmented sleep in OSA increases disorder severity via reduced upper airway dilator responses.

The Influence of CO2 on Genioglossus Muscle After-Discharge Following Arousal From Sleep.

Objectives: Ventilatory after-discharge (sustained elevation of ventilation following stimulus removal) occurs during sleep but not when hypocapnia is present. Genioglossus after-discharge also occurs during sleep, but CO2 effects have not been assessed. The relevance is that postarousal after-discharge may protect against upper airway collapse. This study aimed to determine whether arousal elicits genioglossus after-discharge that persists into sleep, and whether it is influenced by CO2. Methods: Twenty-four healthy individuals (6 female) slept with a nasal mask and ventilator. Sleep (EEG, EOG, EMG), ventilation (pneumotachograph), end-tidal CO2 (PETCO2), and intramuscular genioglossus EMG were monitored. NREM eucapnia was determined during 5 minutes on continuous positive airway pressure (4 cmH2O). Inspiratory pressure support was increased until PETCO2 was ≥2 mm Hg below NREM eucapnia. Supplemental CO2 was added to reproduce normocapnia, without changing ventilator settings. Arousals were induced by auditory tones and genioglossus EMG compared during steady-state hypocapnia and normocapnia. Results: Eleven participants (4 female) provided data. Prearousal PETCO2 was less (p < .05) during hypocapnia (40.74 ± 2.37) than normocapnia (43.82 ± 2.89), with differences maintained postarousal. After-discharge, defined as an increase in genioglossus activity above prearousal levels, occurred following the return to sleep. For tonic activity, after-discharge lasted four breaths irrespective of CO2 condition. For peak activity, after-discharge lasted one breath during hypocapnia and 6 breaths during normocapnia. However, when peak activity following the return to sleep was compared between CO2 conditions no individual breath differences were observed. Conclusions: Postarousal genioglossal after-discharge may protect against upper airway collapse during sleep. Steady-state CO2 levels minimally influence postarousal genioglossus after-discharge.

Arousal-Induced Hypocapnia Does Not Reduce Genioglossus Activity in Obstructive Sleep Apnea.

Study Objectives: To determine whether arousals that terminate obstructive events in obstructive sleep apnea (OSA) (1) induce hypocapnia and (2) subsequently reduce genioglossus muscle activity following the return to sleep. Methods: Thirty-one untreated patients with OSA slept instrumented with sleep staging electrodes, nasal mask and pneumotachograph, end-tidal CO2 monitoring, and intramuscular genioglossus electrodes. End-tidal CO2 was monitored, and respiratory arousals were assigned an end-arousal CO2 change value (PETCO2 on the last arousal breath minus each individual's wakefulness PETCO2). This change value, in conjunction with the normal sleep related increase in PETCO2, was used to determine whether arousals induced hypocapnia and whether the end-arousal CO2 change was associated with genioglossus muscle activity on the breaths following the return to sleep. Results: Twenty-four participants provided 1137 usable arousals. Mean ± SD end-arousal CO2 change was -0.2 ± 2.4 mm Hg (below wakefulness) indicating hypocapnia typically developed during arousal. Following the return to sleep, genioglossus muscle activity did not fall below prearousal levels and was elevated for the first two breaths. End-arousal CO2 change and genioglossus muscle activity were negatively associated such that a 1 mm Hg decrease in end-arousal CO2 was associated with an ~2% increase in peak and tonic genioglossus muscle activity on the breaths following the return to sleep. Conclusions: Arousal-induced hypocapnia did not result in reduced dilator muscle activity following return to sleep, and thus hypocapnia may not contribute to further obstructions via this mechanism. Elevated dilator muscle activity postarousal is likely driven by non-CO2-related stimuli.