A network physiology approach to oxygen saturation variability during normobaric hypoxia
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A network physiology approach to oxygen saturation variability during normobaric hypoxia. / Jiang, Yuji; Costello, Joseph T.; Williams, Thomas B.; Panyapiean, Nawamin; Bhogal, Amar S.; Tipton, Michael J.; Corbett, Jo; Mani, Ali R.
In: Experimental Physiology, Vol. 106, 01.01.2021, p. 151-159.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - A network physiology approach to oxygen saturation variability during normobaric hypoxia
AU - Jiang, Yuji
AU - Costello, Joseph T.
AU - Williams, Thomas B.
AU - Panyapiean, Nawamin
AU - Bhogal, Amar S.
AU - Tipton, Michael J.
AU - Corbett, Jo
AU - Mani, Ali R.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Peripheral capillary oxygen saturation (SpO2 ) exhibits a complex pattern of fluctuations during hypoxia. The physiological interpretation of SpO2 variability is not well understood. In this study, we tested the hypothesis that SpO2 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 (FIO2 ): 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 (SpO2 , 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 SpO2 time series. The transfer entropy analysis showed that, particularly at FIO2 0.145 and 0.12, the flow of information between SpO2 and other physiological variables exhibits a bidirectional relationship. While reciprocal interactions were observed between different cardio-respiratory parameters during hypoxia, SpO2 remained the main hub of this network. SpO2 fluctuations during graded hypoxia exposure carry information about cardio-respiratory control. Therefore, SpO2 entropy analysis has the potential for non-invasive assessment of the functional connectivity of respiratory control system in various healthcare settings.
AB - Peripheral capillary oxygen saturation (SpO2 ) exhibits a complex pattern of fluctuations during hypoxia. The physiological interpretation of SpO2 variability is not well understood. In this study, we tested the hypothesis that SpO2 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 (FIO2 ): 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 (SpO2 , 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 SpO2 time series. The transfer entropy analysis showed that, particularly at FIO2 0.145 and 0.12, the flow of information between SpO2 and other physiological variables exhibits a bidirectional relationship. While reciprocal interactions were observed between different cardio-respiratory parameters during hypoxia, SpO2 remained the main hub of this network. SpO2 fluctuations during graded hypoxia exposure carry information about cardio-respiratory control. Therefore, SpO2 entropy analysis has the potential for non-invasive assessment of the functional connectivity of respiratory control system in various healthcare settings.
KW - altitude
KW - hypoxic
KW - sample entropy
KW - SpO2
KW - transfer entropy
UR - https://onlinelibrary.wiley.com/doi/abs/10.1113/EP088755
U2 - 10.1113/EP088755
DO - 10.1113/EP088755
M3 - Article
VL - 106
SP - 151
EP - 159
JO - Experimental Physiology
JF - Experimental Physiology
SN - 0958-0670
ER -
ID: 21954001