Effect of general anesthesia on non linear indexes of HRV during abdominal surgery

The Heart Rate Varibility(HRV) signal contains mass information, which concerns the cardiovascular nervous system and the analysis of the HRV signal is one of the key techniques for the clinical studying and diagnosing the cardiovascular diseases. Newer HRV measures are model independent, suitable for nonlinear processes, and measure aspects of HRV different from the traditional methods . The aim of this study was to evaluate the effects of deep general anesthesia on the the HRV using non linear analysis in patients undergone to abdominal surgery. Materials and Methods. We studied 7 subjects of both sexes (5 women) with a mean age of 54.4 ± 5.8 years with digestive diseases. None of the patients used drugs or was suffering from cardiovascular or metabolic disease. The patient was anesthetized after endotracheal intubation. The recording was performed before anesthesia induction and after 5 minutes after the start of maintenance. The third measurement was performed at 24 hours after surgery. ECG signal recording, lasting 5 minutes each, were made using a digital ECG with dedicated software (Xai-Medica) for PC storage and off-line analysis (Kubios HRV). Nonlinear Methods: Poincarè Plots: Two-dimensional vector analysis was used to quantify the shape of the plots. In this quantitative method, short-term (SD1) and long-term R-R interval variability (SD2) and the ellipse area of the plot are separately quantified. The Detrended fluctuation analysis (DFA) was used to quantify the fractal scaling properties of short- and intermediate-term R-R interval time series. The HR correlations were defined separately for short-term (<11 beats, 1) and longer-term (>11 beats, 2) R-R interval data. Thus, fractal analysis can be considered as an improvement of spectral analysis, without any interference of environmental and physiological changes, such as respiration and physical activity. Finally we analyzed the ApproximativeEntropy (ApEn) that is another nonlinear method for to quantifie the amount of complexity in the time series data. Lower ApEn values indicate a more regular (less complex) signal; higher values indicate more irregularity (greater complexity). Results: Our data indicate, during deep anesthesia, a significant reduction of LF/HF ratio, and SD1 index of the Poincarè plots. Also the 2 index of DFA shows a significant reduction. The Entropy expressed as Approximative Entropy shows a significant reduction of the signal complexity. Because it has been suggested that the sympathetic modulation on the HRV is reduced by deep anesthesia, maybe the same results is possible to see using nonlinear methods.