Neuro-endocrine correlates and predictors of electrokinetic index changes in buccal epithelium during rehabilitation treatment: a multivariate analysis

Abstract

Abstract. Background. Earlier we showed that qualitative-quantitative clusters of blood pressure (BP) are very clearly different from each other by age, sex and the constellation of neuro-endocrine, immune and metabolic variables, which we called the tensioregulome. The tensioregulome also included the electrokinetic index (EKI) of the buccal epithelium, which cannot formally be attributed to either neuro-endocrine-immune or metabolic constellations. The aim of the study is to determine how changes in EKI levels correlate with changes in brain electrical activity, heart rate variability (HRV) and adaptation hormones levels in individuals with maladaptation. Materials and methods. Under observation, there were 42 men (49 ± 15 years old) and 30 women (51 ± 13 years old) without clinical diagnosis or with chronic pyelonephritis in the phase of remission (23 men), but with deviations in individual parameters of the neuro-endocrine-immune complex as a manifestation of maladaptation. Upon admission, we determined EKI, as well as BP and neuro-endocrine parameters. After three rehabilitation treatment regimens, all tests were repeated. Results. The EKI initial levels were in the range of 20 71.4 %. Their changes in the range of 2.5 % considered as insignificant were reported in 49 cases. However, in 17 patients, EKI levels increased significantly, and in 6 patients decreased. The response of EKI to the application of adaptogenic factors did not depend on its initial levels. Neither the directionality nor the magnitude of EKI responses, nor their absence depended on the nature of treatment regimens. There were both linear (direct and inverse) and nonlinear correlations between changes in EKI and 32 neuro-endocrine variables. Nineteen variables were selected for the regression model: aldosterone; 5 parameters of beta, 4 alpha, 2 delta and 2 theta EEG rhythms, SPD entropy in T3 locus; 3 parameters of HRV, BPS2/BPS1 ratio. Changes in this constellation of variables explain 72 % of the variability in EKI changes. The forward stepwise program included in the discriminant model only 24 variables as characteristic. On the other hand, the discriminant analysis method revealed 35 initial variables as predictors of individual EKI responses (classification accuracy 98.6 %). It turned out that using the regression model, it is possible to reliably predict not only the direction/quality of the EKI response, but also its actual value (the standard error for estimation is 2.5 %). Conclusions. The electrokinetic index response to adaptogenic factors are ambiguous and correlate with changes in EEG and HRV variables and aldosterone levels in individuals with maladaptation. Both quality and magnitude of the EKI response are independent of its initial level or the nature of adaptogenic factors, but can be reliably predicted (accuracy 98.6 %) by the constellation of 35 initial neuro-endocrine variables, including 23 EEG and 7 heart rate variables, triiodothyronine, aldosterone and diastolic BP levels, as well as Kerd vegetative index (KVI) and Popovych adaptation index. These findings suggest that EKI may serve as an integrative biomarker of neuro-endocrine regulation and could be useful for personalized rehabilitation program planning.