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A method for measuring and modeling the physiological traits causing obstructive sleep apnea.

ABSTRACT: 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.

SUBMITTER: Wellman A

PROVIDER: S-EPMC3119134 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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A method for measuring and modeling the physiological traits causing obstructive sleep apnea.

Wellman Andrew A Eckert Danny J DJ Jordan Amy S AS Edwards Bradley A BA Passaglia Chris L CL Jackson Andrew C AC Gautam Shiva S Owens Robert L RL Malhotra Atul A White David P DP

Journal of applied physiology (Bethesda, Md. : 1985) 20110324 6

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 airwa ...[more]

PMID: 21436459

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Project description:Current evidence suggests that the pathological mechanisms underlying obstructive sleep apnea (OSA) are altered with age. However, previous studies examining individual physiological traits known to contribute to OSA pathogenesis have been assessed in isolation, primarily in healthy individuals.We assessed the four physiological traits responsible for OSA in a group of young and old patients with OSA.Sleep research laboratory.Ten young (20-40 y) and old (60 y and older) patients with OSA matched by body mass index and sex.Pharyngeal anatomy/collapsibility, loop gain (LG), upper airway muscle responsiveness/gain (UAG) and the respiratory arousal threshold were determined using multiple 2- to 3-min decreases or drops in continuous positive airway pressure (CPAP). Passive pharyngeal anatomy/collapsibility was quantified as the ventilation at CPAP = 0 cmH2O immediately after the CPAP drop. LG was defined as the ratio of the ventilatory overshoot to the preceding reduction in ventilation. UAG was taken as the ratio of the increase in ventilation to the increase in ventilatory drive across the pressure drop. Arousal threshold was estimated as the ventilatory drive that caused arousal. Veupnea was quantified as the mean ventilation prior to the pressure drop. In comparison with younger patients with OSA, older patients had a more collapsible airway (ventilation at 0 cmH2O = 3.4 ± 0.9 versus 1.5 ± 0.7 L/min; P = 0.05) but lower Veupnea (8.2 ± 0.5 versus 6.1 ± 0.4 L/min; P < 0.01) and a lower LG (5.0 ± 0.7 versus 2.9 ± 0.5; P < 0.05). The remaining traits were similar between groups.Our data suggest that airway anatomy/collapsibility plays a relatively greater pathogenic role in older adults, whereas a sensitive ventilatory control system is a more prominent trait in younger adults with obstructive sleep apnea.Edwards BA, Wellman A, Sands SA, Owens RL, Eckert DJ, White DP, Malhotra A. Obstructive sleep apnea in older adults is a distinctly different physiological phenotype.

Project description:STUDY OBJECTIVES:To test whether the integration of both anatomical and nonanatomical parameters (ventilatory control, arousal threshold, muscle responsiveness) in a physiology-based model will improve the ability to predict outcomes after upper airway surgery for obstructive sleep apnea (OSA). METHODS:In 31 patients who underwent upper airway surgery for OSA, loop gain and arousal threshold were calculated from preoperative polysomnography (PSG). Three models were compared: (1) a multiple regression based on an extensive list of PSG parameters alone; (2) a multivariate regression using PSG parameters plus PSG-derived estimates of loop gain, arousal threshold, and other trait surrogates; (3) a physiological model incorporating selected variables as surrogates of anatomical and nonanatomical traits important for OSA pathogenesis. RESULTS:Although preoperative loop gain was positively correlated with postoperative apnea-hypopnea index (AHI) (P = .008) and arousal threshold was negatively correlated (P = .011), in both model 1 and 2, the only significant variable was preoperative AHI, which explained 42% of the variance in postoperative AHI. In contrast, the physiological model (model 3), which included AHIREM (anatomy term), fraction of events that were hypopnea (arousal term), the ratio of AHIREM and AHINREM (muscle responsiveness term), loop gain, and central/mixed apnea index (control of breathing terms), was able to explain 61% of the variance in postoperative AHI. CONCLUSIONS:Although loop gain and arousal threshold are associated with residual AHI after surgery, only preoperative AHI was predictive using multivariate regression modeling. Instead, incorporating selected surrogates of physiological traits on the basis of OSA pathophysiology created a model that has more association with actual residual AHI. COMMENTARY:A commentary on this article appears in this issue on page 1023. CLINICAL TRIAL REGISTRATION:ClinicalTrials.Gov; Title: The Impact of Sleep Apnea Treatment on Physiology Traits in Chinese Patients With Obstructive Sleep Apnea; Identifier: NCT02696629; URL: https://clinicaltrials.gov/show/NCT02696629.

Dataset Information

A method for measuring and modeling the physiological traits causing obstructive sleep apnea.

Publications

A method for measuring and modeling the physiological traits causing obstructive sleep apnea.

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