Modeling Brain–Heart Crosstalk Information in Patients with Traumatic Brain Injury
Giovanna Maria Dimitri, Erta Beqiri, Michał M. Placek, Marek Czosnyka, Nino Stocchetti, Ari Ercole, Peter Smielewski, Píetro Lió, Audny Anke, Ronny Beer, Bo‐Michael Bellander, Erta Beqiri, András Büki, Manuel Cabeleira, Marco Carbonara, Arturo Chieregato, Giuseppe Citerio, Hans Clusmann, Endre Czeiter, Marek Czosnyka, Bart Depreitere, Ari Ercole, Shirin Frisvold, Raimund Helbok, Stefan Jankowski, Daniel Kondziella, Lars‐Owe Koskinen, Ana Kowark, David K. Menon, Geert Meyfroidt, Kirsten Moeller, David Nelson, Anna Piippo-Karjalainen, Andreea Rădoi, Arminas Ragauskas, Rahul Raj, Jonathan R. Rhodes, Saulius Ročka, Rolf Rossaint, Juan Sahuquillo, Oliver Sakowitz, Peter Smielewski, Nino Stocchetti, Nina Sundström, Riikka Takala, Tomas Tamošuitis, Olli Tenovuo, Andreas Unterberg, Peter Vajkoczy, Alessia Vargiolu, Rimantas Vilcinis, Stefan Wolf, Alexander Younsi, Frederick A. Zeiler
Abstract
Abstract Background Traumatic brain injury (TBI) is an extremely heterogeneous and complex pathology that requires the integration of different physiological measurements for the optimal understanding and clinical management of patients. Information derived from intracranial pressure (ICP) monitoring can be coupled with information obtained from heart rate (HR) monitoring to assess the interplay between brain and heart. The goal of our study is to investigate events of simultaneous increases in HR and ICP and their relationship with patient mortality.. Methods In our previous work, we introduced a novel measure of brain–heart interaction termed brain–heart crosstalks ( ct np ), as well as two additional brain–heart crosstalks indicators [mutual information ( $$mi_{ct}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>m</mml:mi> <mml:msub> <mml:mi>i</mml:mi> <mml:mrow> <mml:mi>ct</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> ) and average edge overlap ( ω ct )] obtained through a complex network modeling of the brain–heart system. These measures are based on identification of simultaneous increase of HR and ICP. In this article, we investigated the relationship of these novel indicators with respect to mortality in a multicenter TBI cohort, as part of the Collaborative European Neurotrauma Effectiveness Research in TBI high-resolution work package. Results A total of 226 patients with TBI were included in this cohort. The data set included monitored parameters (ICP and HR), as well as laboratory, demographics, and clinical information. The number of detected brain–heart crosstalks varied (mean 58, standard deviation 57). The Kruskal–Wallis test comparing brain–heart crosstalks measures of survivors and nonsurvivors showed statistically significant differences between the two distributions ( p values: 0.02 for $$mi_{ct}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>m</mml:mi> <mml:msub> <mml:mi>i</mml:mi> <mml:mrow> <mml:mi>ct</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , 0.005 for ct np and 0.006 for ω ct ). An inverse correlation was found, computed using the point biserial correlation technique, between the three new measures and mortality: − 0.13 for ct np ( p value 0.04), − 0.19 for ω ct ( p value 0.002969) and − 0.09 for $$mi_{ct}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>m</mml:mi> <mml:msub> <mml:mi>i</mml:mi> <mml:mrow> <mml:mi>ct</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> ( p value 0.1396). The measures were then introduced into the logistic regression framework, along with a set of input predictors made of clinical, demographic, computed tomography (CT), and lab variables. The prediction models were obtained by dividing the original cohort into four age groups (16–29, 30–49, 50–65, and 65–85 years of age) to properly treat with the age confounding factor. The best performing models were for age groups 16–29, 50–65, and 65–85, with the deviance of ratio explaining more than 80% in all the three cases. The presence of an inverse relationship between brain–heart crosstalks and mortality was also confirmed. Conclusions The presence of a negative relationship between mortality and brain–heart crosstalks indicators suggests that a healthy brain–cardiovascular interaction plays a role in TBI.