0000000000537294
AUTHOR
Marco Ranucci
Exploring metrics for the characterization of the cerebral autoregulation during head-up tilt and propofol general anesthesia
Techniques grounded on the simultaneous utilization of Tiecks' second order differential equations and spontaneous variability of mean arterial pressure (MAP) and mean cerebral blood flow velocity (MCBFV), recorded from middle cerebral arteries through a transcranial Doppler device, provide a characterization of cerebral autoregulation (CA) via the autoregulation index (ARI). These methods exploit two metrics for comparing the measured MCBFV series with the version predicted by Tiecks' model: normalized mean square prediction error (NMSPE) and normalized correlation rho. The aim of this study is to assess the two metrics for ARI computation in 13 healthy subjects (age: 27 & PLUSMN; 8 yr…
Categorizing the Role of Respiration in Cardiovascular and Cerebrovascular Variability Interactions
Objective: Respiration disturbs cardiovascular and cerebrovascular controls but its role is not fully elucidated. Methods: Respiration can be classified as a confounder if its observation reduces the strength of the causal relationship from source to target. Respiration is a suppressor if the opposite situation holds. We prove that a confounding/suppression (C/S) test can be accomplished by evaluating the sign of net redundancy/synergy balance in the predictability framework based on multivariate autoregressive modelling. In addition, we suggest that, under the hypothesis of Gaussian processes, the C/S test can be given in the transfer entropy decomposition framework as well. Experimental p…
Multiscale Decomposition of Cardiovascular and Cardiorespiratory Information Transfer under General Anesthesia∗
The analysis of short-term cardiovascular and cardiorespiratory regulation during altered conscious states, such as those induced by anesthesia, requires to employ time series analysis methods able to deal with the multivariate and multiscale nature of the observed dynamics. To meet this requirement, the present study exploits the extension to multiscale analysis of recently proposed information decomposition methods which allow to quantify, from short realizations, the amounts of joint, unique, redundant and synergistic information transferred within multivariate time series. These methods were applied to the spontaneous variability of heart period (HP), systolic arterial pressure (SAP) an…