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 (rSO 2 ) 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 coefficient r over short windows of MAP, MCBv and rSO 2 and testing on an individual basis the significance of the positive MCBv-MAP and rSO 2 -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 of r computed 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 their r decreased during ANESTH and this result was valid regardless of the method utilized to reject the null hypothesis and the use of MCBv or rSO 2 . Since markers computed using MCBv and rSO 2 were 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.