PREDICTION OF STOMATITIS DEVELOPMENT IN PATIENTS AFTER ACRYLIC DENTURE TREATMENT

Abstract

In 72 % of cases, acrylic plastics are used for the manufacture of dentures, despite the fact that it can cause the denture stomatitis, among which the inflammatory reactions of allergic genesis are most relevant. The results of various studies indicate that allergic intolerance to denture materials is growing every year, and now the prevalence of denture stomatitis reaches 40 %. In order to create a mathematical model for calculating the risk of developing stomatitis on removable acrylic dentures, 54 patients aged 42 to 88 years were examined. The symptoms of stomatitis were recorded 1 month after the installation of the denture. Immediately prior the denture treatment, an anamnesis was studied and laboratory testing was performed. Oral fluid (IL-4, TNF-a and sIgA) and blood serum (IL-4, TNF-a, sIgA, total IgE, total IgG4) were studied. Allergological diagnostics included the determination of IgE and IgG classes specific for acrylic antibodies, as well as the performance of RTML with methyl methacrylate monomer. For statistical data processing, the methods of rank correlation of Kendall and binary logistic regression were used. 1 month after prosthetics, the symptoms of stomatitis were identified in 29.6% of cases. The development of denture stomatitis depended (p <0.05) on the presence of an allergic disease in patients (t = 0.32), thyroid pathology ( t = 0.20), chemical adverse factors in the workplace (t = 0.20), and on the initial concentrations of IL-4 (t = 0.31) and total IgE ( t = 0.24) in blood serum. The mathematical model for calculating the risk of denture stomatitis, created using the method of binary logistic regression, includes the use of allergy history and IL-4 concentrations in blood serum as predictors. The total share of correctly predicted results using the developed model is 78.4 %. The obtained data should be used in practical public health to predict the development of denture stomatitis. Ключевые Variables in the binary logistic regression equation to describe the likelihood prosthetic stomatitis