AUTHOR=Schirato Sergio Rhein , El-Dash Ingrid , El-Dash Vivian , Bizzarro Bruna , Marroni Alessandro , Pieri Massimo , Cialoni Danilo , Chaui-Berlinck José Guilherme 

TITLE=Association Between Heart Rate Variability and Decompression-Induced Physiological Stress

JOURNAL=Frontiers in Physiology

VOLUME=11

YEAR=2020

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2020.00743

DOI=10.3389/fphys.2020.00743

ISSN=1664-042X

ABSTRACT=<p>The purpose of this study was to analyze the correlation between decompression-related physiological stress markers, given by inflammatory processes and immune system activation and changes in Heart Rate Variability, evaluating whether Heart Rate Variability can be used to estimate the physiological stress caused by the exposure to hyperbaric environments and subsequent decompression. A total of 28 volunteers participated in the experimental protocol. Electrocardiograms were performed; blood samples were obtained for the quantification of red cells, hemoglobin, hematocrit, neutrophils, lymphocytes, platelets, aspartate transaminase (AST), alanine aminotransferase (ALT), and for immunophenotyping and microparticles (MP) research through Flow Cytometry, before and after each experimental protocol from each volunteer. Also, myeloperoxidase (MPO) expression and microparticles (MPs) deriving from platelets, neutrophils and endothelial cells were quantified. Negative associations between the standard deviation of normal-to-normal intervals (SDNN) in the time domain, the High Frequency in the frequency domain and the total number of circulating microparticles was observed (<italic>p</italic>-value = 0.03 and <italic>p</italic>-value = 0.02, respectively). The pre and post exposure ratio of variation in the number of circulating microparticles was negatively correlated with SDNN (<italic>p</italic>-value = 0.01). Additionally, a model based on the utilization of Radial Basis Function Neural Networks (RBF-NN) was created and was able to predict the SDNN ratio of variation based on the variation of specific inflammatory markers (RMSE = 0.06).</p>