Rationale: A low respiratory arousal threshold (ArTH) is one of several traits involved in obstructive sleep apnea pathogenesis and may be a therapeutic target; however, there is no simple way to identify patients without invasive measurements. Objectives: To determine the physiologic determinates of the ArTH and develop a clinical tool that can identify patients with low ArTH. Methods: Anthropometric data were collected in 146 participants who underwent overnight polysomnography with an epiglottic catheter to measure the ArTH (nadir epiglottic pressure before arousal). The ArTH was measured from up to 20 non-REM and REM respiratory events selected randomly. Multiple linear regression was used to determine the independent predictors of the ArTH. Logistic regression was used to develop a clinical scoring system. Measurements and Main Results: Nadir oxygen saturation as measured by pulse oximetry, apnea-hypopnea index, and the fraction of events that were hypopneas (Fhypopneas) were independent predictors of the ArTH (r2 = 0.59; P < 0.001). Using this information, we used receiver operating characteristic analysis and logistic regression to develop a clinical score to predict a low ArTH, which allocated a score of 1 to each criterion that was satisfied: (apnea-hypopnea index, 82.5%) + (Fhypopneas >58.3%). A score of 2 or above correctly predicted a low arousal threshold in 84.1% of participants with a sensitivity of 80.4% and a specificity of 88.0%, a finding that was confirmed using leave-one-out cross-validation analysis. Conclusions: Our results demonstrate that individuals with a low ArTH can be identified from standard, clinically available variables. This finding could facilitate larger interventional studies targeting the ArTH.

Rationale: Therapies for obstructive sleep apnea (OSA) could be administered on the basis of a patient’s own phenotypic causes (“traits”) if a clinically applicable approach were available. Objectives: Here we aimed to provide a means to quantify two key contributors to OSA—pharyngeal collapsibility and compensatory muscle responsiveness—that is applicable to diagnostic polysomnography. Methods: Based on physiological definitions, pharyngeal collapsibility determines the ventilation at normal (eupneic) ventilatory drive during sleep, and pharyngeal compensation determines the rise in ventilation accompanying a rising ventilatory drive. Thus, measuring ventilation and ventilatory drive (e.g., during spontaneous cyclic events) should reveal a patient’s phenotypic traits without specialized intervention. We demonstrate this concept in patients with OSA (N = 29), using a novel automated noninvasive method to estimate ventilatory drive (polysomnographic method) and using “gold standard” ventilatory drive (intraesophageal diaphragm EMG) for comparison. Specialized physiological measurements using continuous positive airway pressure manipulation were employed for further comparison. The validity of nasal pressure as a ventilation surrogate was also tested (N = 11). Measurements and Main Results: Polysomnography-derived collapsibility and compensation estimates correlated favorably with those quantified using gold standard ventilatory drive (R = 0.83, P < 0.0001; and R = 0.76, P < 0.0001; respectively) and using continuous positive airway pressure manipulation (R = 0.67, P < 0.0001; and R = 0.64, P < 0.001; respectively). Polysomnographic estimates effectively stratified patients into high versus low subgroups (accuracy, 69–86% vs. ventilatory drive measures; P < 0.05). Traits were near-identical using nasal pressure versus pneumotach (N = 11, R ≥ 0.98, both traits; P < 0.001). Conclusions: Phenotypes of pharyngeal dysfunction in OSA are evident from spontaneous changes in ventilation and ventilatory drive during sleep, enabling noninvasive phenotyping in the clinic. Our approach may facilitate precision therapeutic interventions for OSA.

We sought to provide an updated systematic review and meta-analysis of studies investigating the effect of positive airway pressure (PAP) treatment for obstructive sleep apnea (OSA) on systolic and diastolic blood pressure (SBP, DBP). Two independent investigators undertook a systematic search of the PubMed database (1980-2012) to identify randomized controlled trials comparing therapeutic PAP to sham-PAP, pill placebo, or standard care over at least one week in adult OSA patients without major comorbidities. The mean, variance, and sample size for diurnal and nocturnal SBP and DBP data were also extracted independently from each study. Random effects meta-analyses were conducted, followed by pre-specified subgroup and meta-regression analyses. 32 studies were identified, with data available from 28 studies representing n = 1,948 patients. The weighted mean difference in diurnal SBP (-2.58 mm Hg, 95% CI -3.57 to -1.59 mm Hg) and DBP (-2.01 mm Hg, 95% CI -2.84 to -1.18 mm Hg) both significantly favored PAP treatment over control arms, with similar results seen in nocturnal readings. Statistically significant reductions in BP were seen in studies whose patients were younger, sleepier, had more severe OSA, and exhibited greater PAP adherence. Meta-regression indicated that the reductions in DBP with PAP were predicted by mean baseline BP (β = -0.22, p = 0.02) and Epworth Sleepiness Scale scores (β = -0.27, p = 0.04). PAP treatment for OSA is associated with modest but significant reductions in diurnal and nocturnal SBP and DBP. Future research should be directed towards identifying subgroups likely to reap greater treatment benefits as well as other therapeutic benefits provided by PAP therapy.

There is not a clinically available technique for measuring the physiological traits causing obstructive sleep apnea (OSA). Therefore, it is often difficult to determine why an individual has OSA or to what extent the various traits contribute to the development of OSA. In this study, we present a noninvasive method for measuring four important physiological traits causing OSA: 1) pharyngeal anatomy/collapsibility, 2) ventilatory control system gain (loop gain), 3) the ability of the upper airway to dilate/stiffen in response to an increase in ventilatory drive, and 4) arousal threshold. These variables are measured using a single maneuver in which continuous positive airway pressure (CPAP) is dropped from an optimum to various suboptimum pressures for 3- to 5-min intervals during sleep. Each individual's set of traits is entered into a physiological model of OSA that graphically illustrates the relative importance of each trait in that individual. Results from 14 subjects (10 with OSA) are described. Repeatability measurements from separate nights are also presented for four subjects. The measurements and model illustrate the multifactorial nature of OSA pathogenesis and how, in some individuals, small adjustments of one or another trait (which might be achievable with non-CPAP agents) could potentially treat OSA. This technique could conceivably be used clinically to define a patient's physiology and guide therapy based on the traits.

Elevated loop gain, consequent to hypersensitive ventilatory control, is a primary nonanatomical cause of obstructive sleep apnoea (OSA) but it is not possible to quantify this in the clinic. Here we provide a novel method to estimate loop gain in OSA patients using routine clinical polysomnography alone. We use the concept that spontaneous ventilatory fluctuations due to apnoeas/hypopnoeas (disturbance) result in opposing changes in ventilatory drive (response) as determined by loop gain (response/disturbance). Fitting a simple ventilatory control model (including chemical and arousal contributions to ventilatory drive) to the ventilatory pattern of OSA reveals the underlying loop gain.Following mathematical-model validation, we critically tested our method in patients with OSA by comparison with a standard (continuous positive airway pressure (CPAP) drop method), and by assessing its ability to detect the known reduction in loop gain with oxygen and acetazolamide.Our method quantified loop gain from baseline polysomnography (correlationversusCPAP-estimated loop gain: n=28; r=0.63, p<0.001), detected the known reduction in loop gain with oxygen (n=11; mean±semchange in loop gain (ΔLG) −0.23±0.08, p=0.02) and acetazolamide (n=11; ΔLG −0.20±0.06, p=0.005), and predicted the OSA response to loop gain-lowering therapy.We validated a means to quantify the ventilatory control contribution to OSA pathogenesis using clinical polysomnography, enabling identification of likely responders to therapies targeting ventilatory control.