Model for Predicting Temporomandibular Dysfunction: Use of Classification Tree Analysis

• Published in: Brazilian dental journal 2020-08, Vol.31 (4), p.360-367
• Main Authors: Waked, Jorge P, Canuto, Mariana P. L. de A. M., Gueiros, Maria Cecilia S. N., Aroucha, João Marcílio C. N. L., Farias, Cleysiane G., Caldas Jr, Arnaldo de F.
• Format: Article
• Language: English
• ISSN: 0103-6440; 1806-4760
• DOI: 10.1590/0103-6440202003279

Abstract The aim of this study was to construct a predictive model that uses classification tree statistical analysis to predict the occurrence of temporomandibular disorder, by dividing the sample into groups of high and low risk for the development of the disease. The use of predictive statistical approaches that facilitate the process of recognizing and/or predicting the occurrence of temporomandibular disorder is of interest to the scientific community, for the purpose of providing patients with more adequate solutions in each case. This was a cross-sectional analytical population-based study that involved a sample of 776 individuals who had sought medical or dental attendance at the Family Health Units in Recife, PE, Brazil. The sample was submitted to anamnesis using the instrument Research Diagnostic Criteria for Temporomandibular Disorders. The data were inserted into the software Statistical Package for the Social Sciences 20.0 and analyzed by the Pearson Chi-square test for bivariate analysis, and by the classification tree method for the multivariate analysis. Temporomandibular disorder could be predicted by orofacial pain, age and depression. The high-risk group was composed of individuals with orofacial pain, those between the ages of 25 and 59 years and those who presented depression. The low risk group was composed of individuals without orofacial pain. The authors were able to conclude that the best predictor for temporomandibular disorder was orofacial pain, and that the predictive model proposed by the classification tree could be applied as a tool for simplifying decision making relative to the occurrence of temporomandibular disorder. Resumo O objetivo deste estudo foi construir um modelo preditivo que utiliza a análise estatística de árvore de classificação para predizer a ocorrência de disfunção temporomandibular, dividindo a amostra em grupos de alto e baixo risco para o desenvolvimento da doença. A utilização de abordagens estatísticas preditivas que facilitem o processo de reconhecimento e / ou previsão da ocorrência de disfunção temporomandibular é de interesse da comunidade científica, com o objetivo de fornecer aos pacientes soluções mais adequadas a cada caso. Trata-se de um estudo transversal analítico de base populacional que envolveu uma amostra de 776 indivíduos que procuraram atendimento médico ou odontológico nas Unidades de Saúde da Família de Recife, PE, Brasil. A amostra foi submetida à anamnese por meio do instrumento