A simplified method for determining phenotypic traits in patients with obstructive sleep apnea

J Appl Physiol (1985). 2013 Apr;114(7):911-22. doi: 10.1152/japplphysiol.00747.2012. Epub 2013 Jan 24.

Abstract

We previously published a method for measuring several physiological traits causing obstructive sleep apnea (OSA). The method, however, had a relatively low success rate (76%) and required mathematical modeling, potentially limiting its application. This paper presents a substantial revision of that technique. To make the measurements, continuous positive airway pressure (CPAP) was manipulated during sleep to quantify 1) eupneic ventilatory demand, 2) the level of ventilation at which arousals begin to occur, 3) ventilation off CPAP (nasal pressure = 0 cmH(2)O) when the pharyngeal muscles are activated during sleep, and 4) ventilation off CPAP when the pharyngeal muscles are relatively passive. These traits could be determined in all 13 participants (100% success rate). There was substantial intersubject variability in the reduction in ventilation that individuals could tolerate before having arousals (difference between ventilations #1 and #2 ranged from 0.7 to 2.9 liters/min) and in the amount of ventilatory compensation that individuals could generate (difference between ventilations #3 and #4 ranged from -0.5 to 5.5 liters/min). Importantly, the measurements accurately reflected clinical metrics; the difference between ventilations #2 and #3, a measure of the gap that must be overcome to achieve stable breathing during sleep, correlated with the apnea-hypopnea index (r = 0.9, P < 0.001). An additional procedure was added to the technique to measure loop gain (sensitivity of the ventilatory control system), which allowed arousal threshold and upper airway gain (response of the upper airway to increasing ventilatory drive) to be quantified as well. Of note, the traits were generally repeatable when measured on a second night in 5 individuals. This technique is a relatively simple way of defining mechanisms underlying OSA and could potentially be used in a clinical setting to individualize therapy.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Diagnosis, Computer-Assisted / methods*
  • Female
  • Humans
  • Lung / physiopathology*
  • Male
  • Middle Aged
  • Polysomnography / methods*
  • Respiratory Function Tests / methods*
  • Respiratory Mechanics*
  • Sleep Apnea, Obstructive / diagnosis*
  • Sleep Apnea, Obstructive / physiopathology*