A network physiology approach to oxygen saturation variability during normobaric hypoxia

What is the central question of this study? What is the physiological interpretation of $$ fluctuations observed during normobaric hypoxia in healthy individuals? What is the main finding and its importance? There is a significant flow of information between $$ and other cardio-respiratory time series during graded hypoxia. Analysis of the pattern of $$ variations has potential for non-invasive assessment of the engagement of respiratory control system in health and disease.

Peripheral capillary oxygen saturation ( $$ ) exhibits a complex pattern of fluctuations during hypoxia. The physiological interpretation of $$ variability is not well understood. In this study, we tested the hypothesis that $$ fluctuation carries information about integrated cardio-respiratory control in healthy individuals using a network physiology approach. We explored the use of transfer entropy in order to compute the flow of information between cardio-respiratory signals during hypoxia. Twelve healthy males (mean (SD) age 22 (4) years) were exposed to four simulated environments (fraction of inspired oxygen ( $$ ): 0.12, 0.145, 0.17, and 0.2093) for 45 min, in a single blind randomized controlled design. The flow of information between different physiological parameters ( $$ , respiratory frequency, tidal volume, minute ventilation, heart rate, end-tidal pressure of O₂ and CO₂ ) were analysed using transfer entropy. Normobaric hypoxia was associated with a significant increase in entropy of the $$ time series. The transfer entropy analysis showed that, particularly at $$ 0.145 and 0.12, the flow of information between $$ and other physiological variables exhibits a bidirectional relationship. While reciprocal interactions were observed between different cardio-respiratory parameters during hypoxia, $$ remained the main hub of this network. $$ fluctuations during graded hypoxia exposure carry information about cardio-respiratory control. Therefore, $$ entropy analysis has the potential for non-invasive assessment of the functional connectivity of respiratory control system in various healthcare settings.