Quantitative assessments in evaluating the effectiveness of arterial hypertension treatment: new technologies

Abstract: Background. In the practice of clinical research, it is traditionally accepted to evaluate parameters that characterize the degree of impairment or loss of the function of an organ or system, and not their preservation. A fundamental change in the approach distinguishes a new trend in modern medicine, which makes it possible to assess the degree of preservation of functional resources, which was the basis of this study.Study purpose: To develop a method for dynamic quantitative assessment of the severity of arterial hypertension and evaluate the relationship between a qualitative indicator of arterial hypertension and a quantitative indicator.Instruments and Data Collection Procedure. Index of adaptive aptitude (IAA) (patent for invention No. 2342900 "Method for eavaluation of the functional reserves of the body", author - Kurnikova I. A.). using automated assessment (certificates of official registration No. 2007614560 and No. 2007613898).IAA=0.011(P-P*)+0.014(S-S*)+0.008(D-D*)+0.009(W-W*),Where: P - actual heart rate (b/min.); P* - ideal pulse rate (beats/ min.); S - systolic blood pressure, actual average per day (mm Hg); S* – ideal systolic blood pressure (mm Hg); D - diastolic blood pressure, actual average per day (mm Hg); D* - ideal diastolic blood pressure (mm/Hg); W - body weight at the time of examination (kg); W* - ideal body weight (kg); H - patient's height at the time of examination (cm).Assessment of daily heart rate variability on the Valenta system, equipped with a program for computer processing of spectral analysis indicators.Results:- 143 patients with arterial hypertension (AH) were examined. The relationship between a qualitative indicator - the severity of AH and quantitative indicators - rehabilitation potential, the numerical value of which is PAS, the circadian index (CI) as an indicator of increased sensitivity of the heart rate to sympathetic stimulation, and the LF/HF vago sympathetic balance coefficient, which increases with hypersympathatic tone, was considered. Statistical analysis of the surface plot using the weighted least squares distance allowed this relationship to be clearly demonstrated. Quantitative analogue of the Framingham arterial hypertension severity scale (AHSS) in a specific patient (certificate for invention №. 201152181)AHSS = 119,31 + 2,22× (CI) - 2,03× (IAA) - 1,33×(2×(CI)) + 2,72×(CI)× (IAA) + 7,06×(IAA)where: AHSS less than 120 - normal. Mild AHSS = 121 – 130 points; average severity of AHSS = 131 – 140 points; severe AHSS - 141 points or more. The effectiveness of rehabilitation is good with AHSS less than 120, satisfactory - with 121 - 130; unsatisfactory - more than 131.For illustration, the data of 54 patients are presented. Observation group "1" - patients with AH (BMI<25), mean age - 49±1.9 years (19 people). Observation group "2" - patients with metabolic syndrome (BMI>25; HOMA index> 2.5), mean age - 50±1.7 (35 people). All patients were assessed for the severity of hypertension according to the WHO criteria and the AHSS index at the beginning of the study. Normal value was achieved in 41.8% in 1st group during treatment, in 47.1% there was a decrease in the severity of AH according to AHSS. In group 2, in patients with metabolic syndrome during treatment, it was possible to normalize blood pressure in 55.8%, and to obtain satisfactory results in 35.9%.Conclusion. Developed mathematical modeling methods, a quantitative analogue indicator of the severity of arterial hypertension - AHSS allows you to dynamically monitor the effectiveness of treatment and evaluate the achieved result based on a quantitative assessment within the severity indicated by the classification. The effectiveness of the rehabilitation of patients with hypertension is considered sufficient if the AHSS decreases below the value of 120 units or one level from the baseline

Keywords: arterial hypertension, Index of adaptive aptitude, vegetative dysfunction, adaptation reserves, automated assessment methods

DOI: 10.54941/ahfe1002959

Cite this paper:

​