Predicting the results of periodontal treatment in patients with generalized periodontitis - Viyun А. (Actual Dentistry, 2018)
Background. In the time of evidence-based medicine and the information-legal space, the patients are demanding the long-term results of treatment, which makes doctors clearly predict long-term results. Existing methods and the tools for determining predictions, although they allow accurately predict the course of the disease, still remain complex and not integrated into practical activities. Therefore, it is important to develop the universal principles, which would be convenient, quickly and accurately determine the further tactics for teeth affected by periodontitis. Purpose. To analyze the results of the treatment of the patients with generalized periodontitis and to determine local clinical prognostic factors. Materials and methods. 163 patients with a diagnosis of generalized periodontitis of the I-III degree of severity. Many parametric linear regression models were used to determine the most prognostic factors. The adequacy of the proposed forecasting model was verified using a plurality of correlation coefficient, R-square and normalized R-square, and statistical significance by Fisher’s criterion. Results. The dispersion analysis showed that there is a significant effect on the outcome of the treatment initial LEA (loss of epithelial attachment) – significance level = 0.0053, DPP (depth of periodontal pockets) – p = 0.00415, and % ВОР (bleeding of probing) – p = 0.0305, % plaque – p = 0.0609. Measures such as age and tooth loss with 12 months after treatment were not include into the prognostic model due to low levels of significance. Conclusions. The following clinical factors have the greatest impact on the treatment outcomes: initial LEA, DPP and BOP. Therefore, the model based on these clinical prognostic factors has been proposed, which allows a high degree of accuracy to predict the results of treatment. Key words: periodontitis, prognosis of treatment outcomes, prognostic factors.