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INDIVIDUAL PREDICTION OF THE DEVELOPMENT OF COMPLICATIONS OF DENTAL IMPLANTATION BASED ON THE ASSESSMENT OF CLINICAL RISK FACTORS

Authors: Zaitxanov Askar Anvarovich; Bekjanova Olga Yesenovna;

INDIVIDUAL PREDICTION OF THE DEVELOPMENT OF COMPLICATIONS OF DENTAL IMPLANTATION BASED ON THE ASSESSMENT OF CLINICAL RISK FACTORS

Abstract

A clinical method has been developed for individual prediction of the development of complications of dental implantation based on the assessment of clinical risk factors. During the statistical processing of data obtained as a result of a clinical examination, we studied the features of the clinical course and the severity of the manifestation of individual clinical indicators of general health, oral hygiene, periodontal condition, patient age, the number of implants placed, the presence of bad habits and the anatomical and topographic location of implants in dentition. The resulting logical regression equation and the model were the material basis for predicting possible complications of dental implantation based on reasonable clinical risk factors. As a result of the analysis, a multiple logical regression equation was obtained, which makes it possible to calculate the probability of developing inflammatory complications of dental implantation.

Keywords

dental implantation, linear regression equation, individual prediction of complications, risk factors.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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