Assessing Cerebral Autoregulation Impairment Via Short-Time Correlation-Based Markers Derived from Transcranial Doppler and Near-Infrared Spectroscopy Signals During General Anesthesia in Cardiac Surgery.

Background. Cerebral autoregulation (CA) is estimated by assessing the association between variations of mean cerebral blood velocity (MCBv) and mean arterial pressure (MAP). Recently, regional oxygen saturation (rSO2) has been tested as an alternative to MCBv for CA estimation.Objective. We propose a correlation-based method iterating the computation of the Pearson correlation coefficientrover short windows of MAP, MCBv and rSO2and testing on an individual basis the significance of the positive MCBv-MAP and rSO2-MAP association.Analysis. The rejection of the null hypothesis of zero or negative correlation was performed using a fast approach based on the classical t-test applied to the Pearson correlation coefficient and via a time-consuming approach based on surrogate series generation. The median ofrcomputed over segments rejecting the null hypothesis and their percentage was computed in 53 patients (age: 62 ± 11 years, 39 males, 14 females) scheduled for cardiac surgery acquired before (BASAL) and after induction of propofol-based general anesthesia (ANESTH). The method was compared to more traditional time-domain techniques.Main results.The percentage of positively correlated sequences and theirrdecreased during ANESTH and this result was valid regardless of the method utilized to reject the null hypothesis and the use of MCBv or rSO2. Since markers computed using MCBv and rSO2were uncorrelated, two approaches might unveil different CA aspects. Only results based on MCBv were significantly correlated with traditional time-domain indexes.Significance.The method should be considered for applications of CA monitoring in practical settings.