A review of supine position related obstructive sleep apnea: Classification, epidemiology, pathogenesis and treatment.

Supine related obstructive sleep apnea (OSA) is the most common clinical and physiological phenotype of OSA. This condition is recognizable by patients, their families and through polysomnographic recordings. Commonly used definitions distinguish the presence of supine related OSA when respiratory events occur at twice the frequency when the patient lies in the supine compared to non-supine sleeping positions. Recent physiology studies have demonstrated that airway obstruction arises more commonly in the supine position particularly at the level of the soft palate and epiglottis. Increased airway collapsibility is reliability observed supine relative to lateral position. To a lesser extent, changes in control of breathing favour less stable ventilation when the supine sleeping posture is adopted. Many treatments have been developed and trialled to help patients avoid sleeping on their back. The last 10 years has seen the emergence of vibrotactile warning devices that are worn on the patients' neck or chest. High quality randomized controlled trial data is accumulating on the efficacy and common pitfalls of the application of these treatments.

Oronasal vs Nasal Masks: The Impact of Mask Type on CPAP Requirement, Pharyngeal Critical Closing Pressure (Pcrit), and Upper Airway Cross-Sectional Areas in Patients With OSA.

BACKGROUND: CPAP delivered via an oronasal mask is associated with lower adherence, higher residual apnea-hypopnea index (AHI), and increased CPAP therapeutic pressure compared with nasal masks. However, the mechanisms underlying the increased pressure requirements are not well understood. RESEARCH QUESTION: How do oronasal masks affect upper airway anatomy and collapsibility? STUDY DESIGN AND METHODS: Fourteen patients with OSA underwent a sleep study with both a nasal and oronasal mask, each for one-half of the night (order randomized). CPAP was manually titrated to determine therapeutic pressure. Upper airway collapsibility was assessed using the pharyngeal critical closing pressure (Pcrit) technique. Cine MRI was done to dynamically assess the cross-sectional area of the retroglossal and retropalatal airway throughout the respiratory cycle with each mask interface. Scans were repeated at 4 cm H2O and at the nasal and oronasal therapeutic pressures. RESULTS: The oronasal mask was associated with higher therapeutic pressure requirements (ΔM ± SEM; +2.6 ± 0.5; P < .001) and higher Pcrit (+2.4 ± 0.5 cm H2O; P = .001) compared with the nasal mask. The change in therapeutic pressure between masks was strongly correlated with the change in Pcrit (r2 = 0.73; P = .003). Increasing CPAP increased both the retroglossal and retropalatal airway dimensions across both masks. After controlling for pressure and breath phase, the retropalatal cross-sectional area was moderately larger when using a nasal vs an oronasal mask (+17.2 mm2; 95% CI, 6.2-28.2, P < .001) while nasal breathing. INTERPRETATION: Oronasal masks are associated with a more collapsible airway than nasal masks, which likely contributes to the need for a higher therapeutic pressure.

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.

A single dose of noradrenergic/serotonergic reuptake inhibitors combined with an antimuscarinic does not improve obstructive sleep apnoea severity.

Previous trials have demonstrated that the combination of noradrenergic reuptake inhibitors with an antimuscarinic can substantially reduce the apnoea-hypopnoea index (AHI) and improve airway collapsibility in patients with obstructive sleep apnoea (OSA). However, some studies have shown that when administered individually, neither noradrenergic or serotonergic agents have been effective at alleviating OSA. This raises the possibility that serotonergic agents (like noradrenergic agents) may also need to be delivered in combination to be efficacious. Therefore, we investigated the effect of an antimuscarinic (oxybutynin) on OSA severity when administered with either duloxetine or milnacipran, two dual noradrenergic/serotonergic reuptake inhibiters. A randomized, double-blind, 4 way cross-over, placebo-controlled trial in ten OSA patients was performed. Patients received each drug condition separately across four overnight in-lab polysomnography (PSG) studies ~1-week apart. The primary outcome measure was the AHI. In addition, the four key OSA endotypes (collapsibility, muscle compensation, arousal threshold, loop gain) were measured non-invasively from the PSGs using validated techniques. There was no significant effect of either drug combinations on reducing the total AHI or improving any of the key OSA endotypes. However, duloxetine+oxybutynin did significantly increase the fraction of hypopnoeas to apnoeas (FHypopnoea ) compared to placebo (p = 0.02; d = 0.54). In addition, duloxetine+oxybutynin reduced time in REM sleep (p = 0.009; d = 1.03) which was positively associated with a reduction in the total AHI (R2  = 0.62; p = 0.02). Neither drug combination significantly improved OSA severity or modified the key OSA endotypes when administered as a single dose to unselected OSA patients.

Examining the impact of multilevel upper airway surgery on the obstructive sleep apnoea endotypes and their utility in predicting surgical outcomes.

BACKGROUND AND OBJECTIVE: Upper airway surgery for obstructive sleep apnoea (OSA) is an alternative treatment for patients who are intolerant of continuous positive airway pressure (CPAP). However, upper airway surgery has variable treatment efficacy with no reliable predictors of response. While we now know that there are several endotypes contributing to OSA (i.e., upper airway collapsibility, airway muscle response/compensation, respiratory arousal threshold and loop gain), no study to date has examined: (i) how upper airway surgery affects all four OSA endotypes, (ii) whether knowledge of baseline OSA endotypes predicts response to surgery and (iii) whether there are any differences when OSA endotypes are measured using the CPAP dial-down or clinical polysomnographic (PSG) methods. METHODS: We prospectively studied 23 OSA patients before and ≥3 months after multilevel upper airway surgery. Participants underwent clinical and research PSG to measure OSA severity (apnoea-hypopnoea index [AHI]) and endotypes (measured in supine non-rapid eye movement [NREM]). Values are presented as mean ± SD or median (interquartile range). RESULTS: Surgery reduced the AHITotal (38.7 [23.4 to 79.2] vs. 22.0 [13.3 to 53.5] events/h; p = 0.009). There were no significant changes in OSA endotypes, however, large but variable improvements in collapsibility were observed (CPAP dial-down method: ∆1.9 ± 4.9 L/min, p = 0.09, n = 21; PSG method: ∆3.4 [-2.8 to 49.0]%Veupnoea , p = 0.06, n = 20). Improvement in collapsibility strongly correlated with improvement in AHI (%∆AHISupineNREM vs. ∆collapsibility: p < 0.005; R2  = 0.46-0.48). None of the baseline OSA endotypes predicted response to surgery. CONCLUSION: Surgery unpredictably alters upper airway collapsibility but does not alter the non-anatomical endotypes. There are no baseline predictors of response to surgery.

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.

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.

Assessing the Physiologic Endotypes Responsible for REM- and NREM-Based OSA.

BACKGROUND: Patients with OSA can have the majority of their respiratory events in rapid eye movement (REM) sleep or in non-rapid eye movement (NREM) sleep. No previous studies have linked the different physiologic conditions in REM and NREM sleep to the common polysomnographic patterns seen in everyday clinical practice, namely REM predominant OSA (REMOSA) and NREM predominant OSA (NREMOSA). RESEARCH QUESTION: (1) How does OSA physiologic condition change with sleep stage in patients with NREMOSA and REMOSA? (2) Do patients with NREMOSA and REMOSA have different underlying OSA pathophysiologic conditions? STUDY DESIGN AND METHODS: We recruited patients with three polysomnographic patterns. (1) REMOSA: twice as many respiratory events in REM sleep, (2) NREMOSA: twice as many events in NREM sleep, and (3) uniform OSA: equal number of events in NREM/REM sleep. We deployed a noninvasive phenotyping method to determine OSA endotype traits (Vpassive, Vactive, loop gain, arousal threshold) in NREM sleep, REM sleep, and total night sleep in each group of patients (NREMOSA, REMOSA, uniform OSA). RESULTS: Patients with NREMOSA have significantly worse ventilatory control stability in NREM sleep compared with REM sleep (loop gain, 0.546 [0.456,0.717] in NREM vs 0.365 [0.238,0.459] in REM sleep; P = .0026). Patients with REMOSA displayed a significantly more collapsible airway (ie, lower Vpassive) in REM compared with NREM sleep (98.4 [97.3,99.2] %Veupnea in NREM vs 95.9 [86.4,98.9] %Veupnea in REM sleep; P < .0001). The major between-group difference across the whole night was a significantly higher loop gain in the NREMOSA group (0.561 [0.429,0.675]) compared with the REMOSA group (0.459 [0.388,0.539]; P = .0033). INTERPRETATION: This study is the first to link long-recognized polysomnographic patterns of OSA to underlying physiologic differences. Patients with NREMOSA have a higher loop gain in NREM sleep; patients with REMOSA have a worsening of Vpassive in REM sleep.

A randomized controlled trial of oxygen therapy for patients who do not respond to upper airway surgery for obstructive sleep apnea.

STUDY OBJECTIVES: We aimed to determine whether patients diagnosed with obstructive sleep apnea (OSA) who fail to respond to upper airway surgery may be successfully treated with supplemental oxygen and whether we could identify baseline physiologic endotypes (ie, collapsibility, loop gain, arousal threshold, and muscle compensation) that predict response to oxygen therapy. METHODS: We conducted a single night, randomized double-blinded cross over trial in which patients with OSA who failed to respond to upper airway surgery were treated on separate nights with oxygen therapy (4 L/min) or placebo (medical air). Effect of oxygen/air on OSA on key polysomnography outcomes were assessed: apnea-hypopnea index (AHI), AHI without desaturation (ie, flow-based AHI), arousal index, and morning blood pressure. OSA endotypes were estimated from the polysomnography signals to determine whether baseline OSA physiology could be used to predict response to oxygen therapy. RESULTS: There was a statistically significant reduction in AHI and flow-based AHI on oxygen vs placebo (flow-based AHI: 42.4 ± 21.5 vs 30.5 ± 17.1 events/h, P = .008). Arousal index was also reduced on oxygen vs placebo (41.1 ± 19.5 vs 33.0 ± 15.3 events/h, P = .006). There was no significant difference in morning blood pressure between oxygen and placebo. Although 7 of 20 individuals experienced a 50% reduction or greater in flow-based AHI on oxygen (responders), there was no difference in the baseline OSA endotypes (or clinical characteristics) between responders and nonresponders. CONCLUSIONS: Our findings demonstrate that a proportion of patients who fail to respond to upper airway surgery for OSA respond acutely to treatment with supplemental oxygen. CLINICAL TRIAL REGISTRATION: Registry: Australian New Zealand Clinical Trials Registry; Name: Oxygen therapy for treating patients with residual obstructive sleep apnea following upper airway surgery; URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373566; Identifier: ACTRN12617001361392.

The impact of structured sleep schedules prior to an in-laboratory study: Individual differences in sleep and circadian timing.

INTRODUCTION: Many sleep and circadian studies require participants to adhere to structured sleep-wake schedules designed to stabilize sleep outcomes and circadian phase prior to in-laboratory testing. The effectiveness of this approach has not been rigorously evaluated, however. We therefore investigated the differences between participants' unstructured and structured sleep over a three-week interval. METHODS: Twenty-three healthy young adults completed three weeks of sleep monitoring, including one week of unstructured sleep and two weeks of structured sleep with consistent bed and wake times. Circadian phase was assessed via salivary dim light melatonin onset (DLMO) during both the unstructured and structured sleep episodes. RESULTS: Compared to their unstructured sleep schedule, participants' bed- and wake times were significantly earlier in their structured sleep, by 34 ± 44 mins (M ± SD) and 44 ± 41 mins, respectively. During structured sleep, circadian phase was earlier in 65% of participants (40 ± 32 mins) and was later in 35% (41 ± 25 mins) compared to unstructured sleep but did not change at the group level. While structured sleep reduced night-to-night variability in sleep timing and sleep duration, and improved the alignment (phase angle) between sleep onset and circadian phase in the most poorly aligned individuals (DLMO < 1h or > 3h before sleep onset time; 25% of our sample), sleep duration and quality were unchanged. CONCLUSION: Our results show adherence to a structured sleep schedule results in more regular sleep timing, and improved alignment between sleep and circadian timing for those individuals who previously had poorer alignment. Our findings support the use of structured sleep schedules prior to in-laboratory sleep and circadian studies to stabilize sleep and circadian timing in healthy volunteers.