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A network physiology approach to oxygen saturation variability during normobaric hypoxia
Author(s) -
Jiang Yuji,
Costello Joseph T.,
Williams Thomas B.,
Panyapiean Nawamin,
Bhogal Amar S.,
Tipton Michael J.,
Corbett Jo,
Mani Ali R.
Publication year - 2020
Publication title -
experimental physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.925
H-Index - 101
eISSN - 1469-445X
pISSN - 0958-0670
DOI - 10.1113/ep088755
Subject(s) - hypoxia (environmental) , transfer entropy , conditional entropy , respiratory system , cardiorespiratory fitness , respiratory physiology , tidal volume , heart rate , cardiology , medicine , anesthesia , oxygen , chemistry , mathematics , blood pressure , statistics , organic chemistry , principle of maximum entropy
New FindingsWhat is the central question of this study? What is the physiological interpretation of S p O 2fluctuations observed during normobaric hypoxia in healthy individuals?What is the main finding and its importance? There is a significant flow of information between S p O 2and other cardio‐respiratory time series during graded hypoxia. Analysis of the pattern of S p O 2variations has potential for non‐invasive assessment of the engagement of respiratory control system in health and disease.Abstract Peripheral capillary oxygen saturation ( S p O 2) exhibits a complex pattern of fluctuations during hypoxia. The physiological interpretation of S p O 2variability is not well understood. In this study, we tested the hypothesis that S p O 2fluctuation 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 ( F I O 2): 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 ( S p O 2, respiratory frequency, tidal volume, minute ventilation, heart rate, end‐tidal pressure of O 2 and CO 2 ) were analysed using transfer entropy. Normobaric hypoxia was associated with a significant increase in entropy of the S p O 2time series. The transfer entropy analysis showed that, particularly at F I O 20.145 and 0.12, the flow of information between S p O 2and other physiological variables exhibits a bidirectional relationship. While reciprocal interactions were observed between different cardio‐respiratory parameters during hypoxia, S p O 2remained the main hub of this network. S p O 2fluctuations during graded hypoxia exposure carry information about cardio‐respiratory control. Therefore, S p O 2entropy analysis has the potential for non‐invasive assessment of the functional connectivity of respiratory control system in various healthcare settings.