A network physiology approach to oxygen saturation variability during normobaric hypoxia.

New Findings: 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.

Abstract: Peripheral capillary oxygen saturation ( ) exhibits a complex pattern of fluctuations during hypoxia.

Effects of Normobaric Hypoxia on Oxygen Saturation Variability.

The study is the first to evaluate the effects of graded normobaric hypoxia on SpO variability in healthy individuals. Twelve healthy males (mean [standard deviation] age 22 [4] years) were exposed to four simulated environments (fraction of inspired oxygen [O]: 0.12, 0.

Which heart rate variability index is an independent predictor of mortality in cirrhosis?

Background: Liver cirrhosis is associated with reduced heart rate variability (HRV), which indicates impaired integrity of cardiovascular control in this patient population. There are several different indices for HRV quantification. The present study was designed to: 1) determine which of the HRV indices is best at predicting mortality in patients with cirrhosis; 2) verify if such ability to predict mortality is independent of the severity of hepatic failure.

Pattern Analysis of Oxygen Saturation Variability in Healthy Individuals: Entropy of Pulse Oximetry Signals Carries Information about Mean Oxygen Saturation.

Pulse oximetry is routinely used for monitoring patients' oxygen saturation levels with little regard to the variability of this physiological variable. There are few published studies on oxygen saturation variability (OSV), with none describing the variability and its pattern in a healthy adult population. The aim of this study was to characterize the pattern of OSV using several parameters; the regularity (sample entropy analysis), the self-similarity [detrended fluctuation analysis (DFA)] and the complexity [multiscale entropy (MSE) analysis].