Abstract. Background and aim. Standards and gradations of blood pressure (BP) levels are still the object of debate. The existing classifications do not account for isolated forms of hypertension as independent clinical entities and do not reflect the natural distribution of BP levels in the population. The aim of the present study was to identify 7 natural quantitative-qualitative clusters of BP and to determine their neuro-endocrine accompaniment in patients with chronic pyelonephritis in remission undergoing balneotherapy at Truskavets’ Spa.

Materials and methods. A total of 44 patients (34 men aged 23–70 years and 10 women aged 33–76 years) with chronic pyelonephritis in remission were examined. Testing was performed twice — on admission and after 7–10 days of standard balneotherapy (drinking of Naftussya bioactive water, applications of ozokerite, mineral pools). Systolic and diastolic blood pressure was measured three times consecutively with calculation of BP response ratios and Kerdö Vegetative Index. Heart rate variability (HRV) was assessed by 7-minute ECG recording with analysis of Baevsky's parameters, time domain, frequency domain and nonlinear parameters. EEG was recorded monopolarly in 16 loci by the 10–20 international system with analysis of absolute and relative power spectral density of β-, α-, θ- and δ-rhythms, amplitude, frequency, asymmetry and entropy parameters. Serum levels of cortisol, aldosterone, testosterone, triiodothyronine, calcitonin and PTH were determined by ELISA. Clustering was performed by iterative k-means method. Discriminant analysis was performed using forward stepwise algorithm with calculation of Wilks' Λ, canonical roots, standardized and raw coefficients, classification functions and Mahalanobis distances.

Results. Using iterative k-means clustering, 7 natural BP clusters were identified: low normal (n = 15), normal (n = 19), high normal (n = 16), isolated diastolic AH I (n = 5), AH I (n = 19), isolated systolic AH I (n = 8), and AH II (n = 6). Discriminant analysis identified 35 neuro-endocrine parameters that statistically significantly differentiate these 7 clusters (Wilks’ Λ = 0.00012; approx. F(210) = 4.9; p < 10 –6 ).

Classification accuracy reached 98.9 %.

Conclusions. The natural clustering of BP into 7 quantitative-qualitative groups reflects distinct neuro-endocrine regulatory mechanisms. The identified tensioregulome for each BP cluster confirms the complex multilevel nature of BP regulation involving central cortical, autonomic and endocrine components.

Keywords: blood pressure, clustering, neuro-endocrine regulation, heart rate variability, electroencephalography, adaptation hormones, balneotherapy, Truskavets’, tensioregulome, discriminant analysis

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