Comparison of Linear and Nonlinear Algorithms for Detection of Cardiorespiratory Uncoupling in Endotoxemic Rats

Abstract

Previous studies have shown that LPS-induced endotoxemia causes a cardiorespiratory (CRP) uncoupling owing to the physiological effects of systemic inflammation. Also, it is known that oxytocin has anti-inflammatory effects and cardioprotective properties; however, it is unknown whether it can modify the CRP coupling. This study aimed to compare different linear and nonlinear mathematics methods for the detection of cardiorespiratory uncoupling between cardiac and respiratory time series. The R-R time series of electrocardiograms of male rodents that were administered with saline solution (V); lipopolysaccharide (LPS); oxytocin (O) and LPS + oxytocin (LPS + Ox) were studied. We tested the R-R and respiratory series derived from the electrocardiogram (EDR) for the four groups to quantify the degree of coupling with cross-correlation; cross sample entropy; conditional entropy; mutual infor-mation; and Rényi’s mutual information. We found that oxytocin does not seem to favor the CRP coupling during endotoxemia induced by LPS. Finally, we observed that the cross-sample entropy and the conditional entropy pre-sented the highest statistical differences to identify the CRP uncoupling produced by LPS.