O013 The pathogenesis of obstructive sleep apnea in individuals with comorbid insomnia and obstructive sleep apnoea (COMISA)

Obstructive sleep apnea (OSA) and Insomnia are prevalent sleep disorders which are highly comorbid. This frequent co-occurrence suggests a shared etiology may exist. OSA is caused by the interaction of four pathophysiological traits: a highly collapsible upper airway, elevated loop gain, a low arousal threshold, and poor muscle compensation. No study has ascertained whether these traits are influenced by insomnia. We aimed to quantify the four traits which contribute to OSA in individuals diagnosed with comorbid insomnia and OSA (COMISA). We non-invasively determined these traits in 52 COMISA patients (Age: 56±14 years) with mild-to-severe OSA (AHI=21.2±10.63 events/h) using polysomnography. Our results indicated that 83% of COMISA patients had a low arousal threshold and only 2% of patients exhibited a highly collapsible airway using previously defined thresholds. Multiple linear regression revealed the arousal threshold (b=0.24, 95%CI[0.11, 0.37], β=0.47, p<0.001) and loop gain (b=23.6, 95%CI[7.02, 40.18], β=0.33, p<0.01) were the strongest predictors of OSA severity in our sample. There was no significant relationship between the arousal threshold and insomnia severity measured by the insomnia severity index (ISI). Further work is being performed to compare these findings with a matched sample of OSA only participants. Our preliminary findings demonstrate OSA in COMISA is characterized by a mildly collapsible airway/low arousal threshold phenotype and is largely driven by non-anatomical factors including a low arousal threshold and high loop gain. OSA treatments which are effective in patients with mild anatomical compromise and raise the arousal threshold may provide therapeutic benefit in COMISA patients.

P002 Targeted non-CPAP combination therapy resolves obstructive sleep apnoea

Introduction Mandibular advancement splint (MAS) therapy is an effective alternative to CPAP for many people with obstructive sleep apnoea (OSA) but ~50% have residual OSA. This study aimed to resolve OSA in these individuals by combining MAS with other targeted therapies based on OSA endotype characterisation. Methods Eleven people with OSA (apnoea-hypopnoea index (AHI): 35±13 events/h), not fully resolved with MAS alone (AHI>10 events/h) were recruited. Initially, OSA endotypes were assessed via a detailed physiology night. Step one of combination therapy focused on anatomical interventions including MAS plus an oral expiratory positive airway pressure valve (EPAP) and a supine-avoidance device. Participants with residual OSA (AHI>10 events/h) following the anatomical combination therapy night, were then given one or more targeted non-anatomical therapies according to endotype characterisation. This included oxygen (4L/min) to reduce unstable respiratory control (high loop gain), 10mg zolpidem to increase arousal threshold, or 80/5mg atomoxetine-oxybutynin (ato-oxy) for poor pharyngeal muscle responsiveness. Results OSA was successfully treated (AHI<10 events/h) in all participants with combination therapy. MAS combined with EPAP and supine-avoidance therapy resolved OSA in ~65% of participants (MAS alone vs. combination therapy: 17±4 vs. 5±3, events/h, n=7). For the remaining participants, OSA resolved with the addition of oxygen (n=2), one with 80/5mg ato-oxy and another required both oxygen and 80/5mg ato-oxy. Discussion Targeted combination therapy may be a viable treatment alternative for people with OSA who cannot tolerate CPAP or for those who have an incomplete therapeutic response with monotherapy.

O001 Reboxetine reduces obstructive sleep apnea severity: a randomized trial

Introduction Noradrenergic and muscarinic processes are crucial for pharyngeal muscle control during sleep. Selective norepinephrine reuptake inhibitors (SNRIs) such as reboxetine combined with an antimuscarinic reduce obstructive sleep apnea (OSA) severity. The effects of reboxetine alone on OSA severity are unknown. Methods Double-blind, placebo-controlled, three-way crossover trial in 16 people with OSA. Each participant completed three overnight polysomnograms (~1-week washout). Single doses of reboxetine 4mg, placebo, or reboxetine+oxybutynin 5mg were administered before sleep (randomized order). The primary outcome was apnea-hypopnea index (AHI). Secondary outcomes included other polysomnography parameters, next day sleepiness and alertness. Endotyping analysis was performed to determine the medications’ effects on OSA pathophysiological mechanisms. Results Reboxetine reduced the AHI by 5.4 [95% CI -10.4 to -0.3] events/h, P=0.03 (men: -24±27%; women: -0.7±32%). The addition of oxybutynin did not further reduce AHI. Reboxetine alone and reboxetine+oxybutynin reduced overnight hypoxemia versus placebo (e.g. 4% oxygen desaturation index 10.4±12.8 vs. 10.6±12.8 vs. 15.7±14.7 events/h, P=0.02). Mechanistically, reboxetine and reboxetine+oxybutynin improved pharyngeal collapsibility and respiratory control stability. Men had higher baseline loop gain. Larger reductions in AHI with reboxetine occurred in those with high loop gain. Neither drug intervention changed next day sleepiness or alertness. Discussion A single 4mg dose of reboxetine modestly reduces OSA severity without further improvement with the addition of an antimuscarinic. Reboxetine increases breathing stability via improvements in pharyngeal collapsibility and respiratory control. These findings provide new insight into the role of SNRIs on upper airway stability during sleep and have important implications for pharmacotherapy development for OSA.

O027 The combination of mandibular advancement devices (MAD) and supplemental oxygen dramatically improves OSA severity: preliminary results from the MADOX trial

Introduction Patients with obstructive sleep apnoea (OSA) considered ‘non-responders’ to mandibular advancement device (MAD) therapy, typically have a high loop gain contributing to their OSA physiology. While MAD does not improve loop gain, other treatments such as supplemental oxygen can have a strong effect on this pathogenic trait. Therefore, we conducted a randomised controlled trial (RCT) to determine whether the administration of supplemental oxygen in combination with a MAD, was associated with greater improvements in OSA severity compared to MAD therapy alone. Methods Patients recently diagnosed with OSA underwent an initial screening sleep study to confirm the presence of moderate-severe OSA (Apnoea-hypopnoea index [AHI]>20events/hr). Eligible patients were then enrolled in a randomised single-blind cross-over trial involving 4 sleep studies with the following treatments; MAD, oxygen (4L/min), MAD+oxygen and room-air/sham (control). The primary outcome was the reduction in AHI (%baseline). Results Of the 57 participants screened, 35 met the eligibility criteria (Baseline/Screening AHI = 52±22 events/hr). Compared to the sham night, all treatments significantly reduced the AHI; a 35% [CI: 18–48] was seen with oxygen (p<0.0002), a 53% [CI: 40–64] was seen with MAD (p<0.0001) and a 67% [CI: 56–76] was seen with MAD+oxygen (p<0.0001). Importantly, the combination of MAD+oxygen was associated with a significant reduction in AHI relative to MAD alone (15% [CI:4–24] p=0.01). Discussion In a population with moderate-severe OSA, preliminary analyses from this trial suggests that the addition of supplemental oxygen in combination with MAD therapy provided greater reductions in OSA severity than either treatment alone.

475 Automatic detection of self-similarity and prediction of CPAP failure

Introduction Sleep disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. Tolerance and efficacy of continuous positive airway pressure (CPAP), the primary form of therapy for sleep apnea, is often poor. High loop gain (HLG) is a driving mechanism of central sleep apnea or periodic breathing. The current study aimed to develop a computational approach to detect HLG based on self-similarity in respiratory oscillations during sleep solely using breathing patterns, measured via Respiratory Inductance Plethysmography (RIP). To quantify the potential utility of the developed similarity metric, the presented algorithm was used to predict acute CPAP failure. Methods We developed an algorithm for detecting apneas as periods with reduced breathing effort, manifested in the RIP signal as low signal amplitude. Our algorithm calculates self-similarity in breathing patterns between consecutive periods of apnea or hypopnea. Working under the assumption that high loop gain induces self-similar respiratory oscillations and increases the risk of failure during CPAP, the full night similarity, computed during diagnostic non-CPAP polysomnography (PSG), was used to predict failure of CPAP, which we defined as titration central apnea index (CAI)>10. Central apnea labels are obtained both from manual scoring by sleep technologists, and from an automated algorithm developed for this study. The Massachusetts General Hospital (MGH) sleep database was used, including 2466 PSG pairs of diagnostic and CPAP titration PSG recordings. Results Diagnostic CAI based on technologist labels predicted failure of CPAP with an AUC of 0.82 ±0.03. Based on automatically generated labels, the combination of full night similarity and automatically generated CAI resulted in an AUC of 0.85 ±0.02. A subanalysis was performed on a population with technologist labeled diagnostic CAI>5. Full night similarity predicted failure with an AUC of 0.57 ±0.07 for manual and 0.65 ±0.06 for automated labels. Conclusion This study showed that central apnea labels can be derived in an automated way. The proposed self-similarity feature, as a surrogate estimate of expressed respiratory high loop gain and computed from easily accessible effort signals, can detect periodic breathing regardless of admixed obstructive features such as flow-limitation, and can aid prediction of CPAP failure or success. Support (if any):

446 Acute effect of acetazolamide in high loop gain sleep apnea

Introduction Obstructive sleep apnea is a disease with different driver phenotypes, including high loop gain (HLG). Acetazolamide (AZT) reduces HLG through multiple mechanisms. The acute effect of AZT used during titration polysomnography in HLG sleep apnea (HLGSA, predominantly obstructive) is described here. HLGSA is a NREM-dominant disease. Methods HLGSA was identified by one or more of the following: 1) baseline or titration CAHI of 5 or more, baseline or titration periodic breathing, or high residual apnea on CPAP in the absence of large leak. Retrospective analysis of polysomnograms from patients with HLGSA who underwent a PAP titration study and took ATZ (125 or 250 mg) after a baseline component of PAP titration. A responder was defined as a minimum reduction of the AHI3% of 50%. Multivariable logistic regression model estimated responder predictors. Results Two hundred and thirty-six patients with a median age of 60 (50.25–68) years and 189 (80.1%) males, were included. 69 patients were given 125 mg ATZ and 157 patients took 250 mg after about 3 hours of initial drug-free titration. Compared to PAP alone, PAP plus ATZ reduced the breathing related arousal index (8.45[3.03–15.60] vs. 4.8[2.1–10.15], p<0.001), AHI3% (19.09[7.34–37.28] vs. 10.63[4.46–20.56], p<0.001), AHI4% (1.89[0.23–8.58] vs. 1.19 [0.42–4.70], p=0.001), RDI (24.01[10.55–41.46] vs. 13.55[7.24–25.66], p<0.001). ATZ minimally improved the Min SpO2 (90[87–92] vs. 91[88–92], p=0.014). 101 patients were responders. Multiple logistic regression analysis showed that the NREM AHI3% was the only predictor for responder status with ATZ exposure (OR 1.022, 95%CI [1.004–1.041], p=0.018) Conclusion ATZ acutely improves PAP efficacy in HLGSA. The NREM AHI3% is a predictor for the ATZ responders. Support (if any) This study was supported by American Academy of Sleep Medicine Foundation, category-I award to RJT

A three-point form factor through five loops

We bootstrap the three-point form factor of the chiral part of the stress­tensor supermultiplet in planar $$ \mathcal{N} $$ N = 4 super-Yang-Mills theory, obtaining new results at three, four, and five loops. Our construction employs known conditions on the first, second, and final entries of the symbol, combined with new multiple-final-entry conditions, “extended-Steinmann-like” conditions, and near-collinear data from the recently-developed form factor operator product expansion. Our results are expected to give the maximally transcendental parts of the gg → Hg and H → ggg amplitudes in the heavy-top limit of QCD. At two loops, the extended-Steinmann-like space of functions we describe contains all transcendental functions required for four-point amplitudes with one massive and three massless external legs, and all massless internal lines, including processes such as gg → Hg and γ* → $$ q\overline{q}g $$ q q ¯ g . We expect the extended-Steinmann-like space to contain these amplitudes at higher loops as well, although not to arbitrarily high loop order. We present evidence that the planar $$ \mathcal{N} $$ N = 4 three-point form factor can be placed in an even smaller space of functions, with no independent ζ values at weights two and three.

Orofacial Myofunctional Therapy in Obstructive Sleep Apnea Syndrome: A Pathophysiological Perspective

Obstructive sleep apnea (OSA) syndrome is a multi-factorial disorder. Recently identified pathophysiological contributing factors include airway collapsibility, poor pharyngeal muscle responsiveness, a low arousal threshold, and a high loop gain. Understanding the pathophysiology is of pivotal importance to select the most effective treatment option. It is well documented that conventional treatments (continuous positive airway pressure (CPAP), upper airway surgery, and dental appliance) may not always be successful in the presence of non-anatomical traits, especially in mild to moderate OSA. Orofacial myofunctional therapy (OMT) consists of isotonic and isometric exercises targeted to oral and oropharyngeal structures, with the aim of increasing muscle tone, endurance, and coordinated movements of pharyngeal and peripharyngeal muscles. Recent studies have demonstrated the efficacy of OMT in reducing snoring, apnea–hypopnea index, and daytime sleepiness, and improving oxygen saturations and sleep quality. Myofunctional therapy helps to reposition the tongue, improve nasal breathing, and increase muscle tone in pediatric and adult OSA patients. Studies have shown that OMT prevents residual OSA in children after adenotonsillectomy and helps adherence in CPAP-treated OSA patients. Randomized multi-institutional studies will be necessary in the future to determine the effectiveness of OMT in a single or combined modality targeted approach in the treatment of OSA. In this narrative review, we present up-to-date literature data, focusing on the role of OSA pathophysiology concepts concerning pharyngeal anatomical collapsibility and muscle responsiveness, underlying the response to OMT in OSA patients.

Multicomponent Analysis of Sleep Using Electrocortical, Respiratory, Autonomic and Hemodynamic Signals Reveals Distinct Features of Stable and Unstable NREM and REM Sleep

A new concept of non-rapid eye movement (NREM) and rapid eye movement (REM) sleep is proposed, that of multi-component integrative states that define stable and unstable sleep, respectively, NREMS, NREMUS REMS, and REMUS. Three complementary data sets are used: obstructive sleep apnea (20), healthy subjects (11), and high loop gain sleep apnea (50). We use polysomnography (PSG) with beat-to-beat blood pressure monitoring, and electrocardiogram (ECG)-derived cardiopulmonary coupling (CPC) analysis to demonstrate a bimodal, rather than graded, characteristic of NREM sleep. Stable NREM (NREMS) is characterized by high probability of occurrence of the <1 Hz slow oscillation, high delta power, stable breathing, blood pressure dipping, strong sinus arrhythmia and vagal dominance, and high frequency CPC. Conversely, unstable NREM (NREMUS) has the opposite features: a fragmented and discontinuous <1 Hz slow oscillation, non-dipping of blood pressure, unstable respiration, cyclic variation in heart rate, and low frequency CPC. The dimension of NREM stability raises the possibility of a comprehensive integrated multicomponent network model of NREM sleep which captures sleep onset (e.g., ventrolateral preoptic area-based sleep switch) processes, synaptic homeostatic delta power kinetics, and the interaction of global and local sleep processes as reflected in the spatiotemporal evolution of cortical “UP” and “DOWN” states, while incorporating the complex dynamics of autonomic-respiratory-hemodynamic systems during sleep. Bimodality of REM sleep is harder to discern in health. However, individuals with combined obstructive and central sleep apnea allows ready recognition of REMS and REMUS (stable and unstable REM sleep, respectively), especially when there is a discordance of respiratory patterns in relation to conventional stage of sleep.

Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during continuous positive airway pressure

Study Objectives Sleep-disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. High loop gain (HLG) is a driving mechanism of central sleep apnea or periodic breathing. This study presents a computational approach that identifies “expressed/manifest” HLG via a cyclical self-similarity feature in effort-based respiration signals. Methods Working under the assumption that HLG increases the risk of residual central respiratory events during continuous positive airway pressure (CPAP), the full night similarity, computed during diagnostic non-CPAP polysomnography (PSG), was used to predict residual central events during CPAP (REC), which we defined as central apnea index (CAI) higher than 10. Central apnea labels are obtained both from manual scoring by sleep technologists and from an automated algorithm developed for this study. The Massachusetts General Hospital sleep database was used, including 2466 PSG pairs of diagnostic and CPAP titration PSG recordings. Results Diagnostic CAI based on technologist labels predicted REC with an area under the curve (AUC) of 0.82 ± 0.03. Based on automatically generated labels, the combination of full night similarity and automatically generated CAI resulted in an AUC of 0.85 ± 0.02. A subanalysis was performed on a population with technologist-labeled diagnostic CAI higher than 5. Full night similarity predicted REC with an AUC of 0.57 ± 0.07 for manual and 0.65 ± 0.06 for automated labels. Conclusions The proposed self-similarity feature, as a surrogate estimate of expressed respiratory HLG and computed from easily accessible effort signals, can detect periodic breathing regardless of admixed obstructive features such as flow limitation and can aid the prediction of REC.