Predictors of effectiveness in the implementation of personalized use of therapeutic physical factors in patients with metabolic syndrome
Authors: Benkov Andrey A. , Nagornev Sergey N. , Mamedova Sabina S. , Shabanova Amalia S. 
Published: August 2023

BACKGROUND: A personalized approach to the use of therapeutic physical factors should take into account individual predictor biomarkers, which are predictive information regarding the effectiveness of the treatment, taking into account the initial state of the patient's reserve capabilities. The metabolic syndrome was defined as a model of a pathological condition characterized by reduced functional reserves. Previous studies have shown that transcranial magnetotherapy (TMT) and pulsed low-frequency exposure to an electrostatic field (INESP) have potential effectiveness in relation to the pathogenetic manifestations of the metabolic syndrome.
AIM: The purpose of the study is to determine the predictors of effectiveness in the implementation of personalized combined use of TMT and INESP in patients with metabolic syndrome.
MATERIALS AND METHODS: The study involved 100 patients with a diagnosis of metabolic syndrome established in accordance with clinical guidelines. All patients were divided into four groups of 25 by simple fixed randomization. The first group (control) received a placebo effect (imitation of physiotherapeutic effects with the device turned off) for 10 days of observation. Patients of the second group (comparison group 1) were exposed to a low frequency electrostatic field (INESP). The third group (comparison group 2) received transcranial magnetic therapy with a traveling magnetic field (TMT). Patients of the fourth group (main) were subjected to a combined effect of INESP and TMT. All patients before and after a course of physiotherapy underwent a comprehensive examination using functional, biochemical and hormonal methods. Statistical processing of the obtained results was carried out using the Statistica 12.6 software package using the algorithms of correlation and regression analyses.
RESULTS: The analysis performed using the multiple regression algorithm made it possible to identify a cluster of independent variables in the form of an autonomic balance index, microcirculation index, body mass index and catalase activity, determined in the initial value of patients. The high efficiency of the combined use of TMT and INESP is achieved with a probability of at least 95% in patients with metabolic syndrome, the initial state of which is characterized by a level of the autonomic balance index below 1.7 conventional units. units, tissue perfusion parameter more than 14 perf. units, BMI value below 29 c.u. units and catalase activity above 90 units. аct. The results of the verification of the constructed information model convincingly prove its adequacy and objectively confirm compliance with the stated forecast requirements.
CONCLUSION: It is concluded that the identified constellation of phenotypic patterns, which characterizes the state of the pathological process, reflects the main pathogenetic mechanisms that determine the severity of clinical and functional manifestations of metabolic syndrome. Evaluation of the initial values of the autonomic balance index, microcirculation index, body mass index and catalase activity in patients with metabolic syndrome makes it possible to predict the expected effectiveness of the course combined use of TMT and INESP.