Characterizing Fluctuations of Arterial and Cerebral Tissue Oxygenation in Preterm Neonates by Means of Data Analysis Techniques for Nonlinear Dynamical Systems

Abstract

The cerebral autoregulatory state as well as fluctuations in arterial (SpO2) and cerebral tissue oxygen saturation (StO2) are potentially new relevant clinical parameters in preterm neonates. The aim of the present study was to test the investigative capabilities of data analysis techniques for nonlinear dynamical systems, looking at fluctuations and their interdependence. StO2, SpO2 and the heart rate (HR) were measured on four preterm neonates for several hours. The fractional tissue oxygenation extraction (FTOE) was calculated. To characterize the fluctuations in StO2, SpO2, FTOE and HR, two methods were employed: (1) phase-space modeling and application of the recurrence quantification analysis (RQA), and (2) maximum entropy spectral analysis (MESA). The correlation between StO2 and SpO2 as well as FTOE and HR was quantified by (1) nonparametric nonlinear regression based on the alternating conditional expectation (ACE) algorithm, and (2) the maximal information-based nonparametric exploration (MINE) technique. We found that (1) each neonate showed individual characteristics, (2) a ~60 min oscillation was observed in all of the signals, (3) the nonlinear correlation strength between StO2 and SpO2 as well as FTOE and HR was specific for each neonate and showed a high value for a neonate with a reduced health status, possibly indicating an impaired cerebral autoregulation. In conclusion, our data analysis framework enabled novel insights into the characteristics of hemodynamic and oxygenation changes in preterm infants. To the best of our knowledge, this is the first application of RQA, MESA, ACE and MINE to human StO2 data measured with near-infrared spectroscopy (NIRS).

Non-neuronal evoked and spontaneous hemodynamic changes in the anterior temporal region of the human head may lead to misinterpretations of functional near-infrared spectroscopy signals

“…For the resting-state dataset, we computed the channel-wise correlation as a metric to assess the global influence of expected spontaneous vascular and metabolic fluctuations that are present in both task and resting states 33 , 34 . As the primary analysis goal was to evaluate the presence of global fluctuations, we did not apply any further correction (e.g., principal component analysis 35 , 36 ).…”

Newer indications for neuromonitoring in critically ill neonates

“…It is important to consider that previous studies, mostly conducted in experimental settings, suggest that the neonatal sensor linearly correlates and reads ∼10% higher than the adult sensor. This information must be considered when analyzing cut-offs values for hypoxia and hyperoxia (21)(22)(23). The combination of low rScO 2 and abnormal electrocortical activity likely reflects decreased cerebral oxygen delivery or cerebral blood flow and should alert the clinician to the risk for brain injury.…”

Synchronized Oscillations of Arterial Oxygen Saturation, Cerebral Tissue Oxygenation and Heart Rate in Preterm Neonates: Investigation of Long-Term Measurements with Multiple Einstein’s Cross Wavelet Analysis

“…The measurements were approved by the local ethics committee, and written informed consent was obtained from the parents before the study. The datasets used are the same as those analyzed by our previous study investigating another signal processing and data analysis framework [6].…”

“…Long-term (i.e., several hours) monitoring of changes in SpO2 and StO2 offers insights into tissue oxygenation and the regulation of hemodynamics. In a previous study in preterm neonates [6] we found that the fluctuations in SpO2, SaO2, heart rate (HR) and fractional tissue-oxygen extraction, measured over several hours, showed properties (i.e. coupling of the signals and oscillations present) dependent on the individual subject.…”

“…Low-frequency oscillations in the coupling were observed, indicating that the cerebral and systemic hemodynamic state is especially synchronized in the low-frequency region (i.e., with period lengths of >20 min). As already indicated in our previous publication [6], analysis of spontaneous fluctuations of cerebral and systemic hemodynamic signals and their synchronization offer novel insights into the physiological state of the neonate investigated which are not assessed routinely. The present approach could be extended by also adding the arterial carbon dioxide pressure (PaCO2) signal to the input signals for MECWA since fluctuations in PaCO2 are also relevant for hemodynamic state in preterm neonates [13].…”