Information-predictive approach to evaluation of the efficiency of treatment of chronic generalized periodontitis using non-drug technologies ABSTRACT

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Abstract

BACKGROUND: The information-predictive approach can be used for determining biomarkers as predictors that allow predicting the effectiveness of the treatment of chronic generalized periodontitis using the combined use of ozone and transcranial magnetotherapy.

AIMS: Determination of the set of initial morphometric parameters that have predictive significance, as well as the development of a method for the integral assessment of the clinical effectiveness of the combined use of ozone and transcranial magnetotherapy in patients with chronic generalized periodontitis.

MATERIALS AND METHODS: A multiple regression model was built, which establishes the relationship between the dependent variable (effective sign — treatment effectiveness) and the value of independent variables (factors characterizing the initial state of patients).

RESULTS: It has been established that the technology of combined use of ozone and transcranial magnetotherapy is most effective in the initial clinical manifestations of chronic generalized periodontitis and minimal values of other pathogenetically significant parameters (microcirculation, oxygen metabolism, lipid peroxidation disorders) in the initial state.

CONCLUSION: The clinical and laboratory cluster identified as a result of mathematical analysis — the index of bleeding of the gingival sulcus, the volume of nutritive blood flow, the fluorescent indicator of oxygen consumption, the quality of life according to the Daily Life domain generalized periodontitis, determining the indications and contraindications for the use of this treatment regimen for inflammatory periodontal diseases.

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About the authors

Olga I. Ryabtsun

LLC "Belta"

Author for correspondence.
Email: drnag@mail.ru
ORCID iD: 0000-0003-4208-8074
Russian Federation, Moscow

Sergey N. Nagornev

Center for Strategic Planning and Management of Biomedical Health Risks

Email: drnag@mail.ru
ORCID iD: 0000-0002-1190-1440
SPIN-code: 2099-3854

Dr. Sci. (Med.), Professor

Russian Federation, Moscow

Valery K. Frolkov

Center for Strategic Planning and Management of Biomedical Health Risks

Email: drnag@mail.ru
ORCID iD: 0000-0002-1277-5183
SPIN-code: 3183-0883

Dr. Sci. (Biol.), Professor

Russian Federation, Moscow

Elena V. Gusakova

Central State Medical Academy of Department of Presidential Affairs

Email: drnag@mail.ru
ORCID iD: 0000-0003-3254-0354
SPIN-code: 5913-9674

Dr. Sci. (Med.)

Russian Federation, Moscow

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