Allan Pau1, Keshav P Viswanath, Ray Croucher. 1. Oral Health Services Research & Dental Public Health, King's College London Dental Institute, London, UK. allan.pau@nhs.net
Abstract
AIMS: To assess the validity of modified DePaQ items in correctly classifying dental pain patients into three groups of common dental conditions when compared against clinically-determined classification; generate a model of classification equations from a sub-population of the sample; and assess the validity of the model in predicting group membership of new dental pain cases. METHODS: Consecutive adult hospital dental patients aged 18 years and older attending with a dental pain complaint were diagnosed by a dentist. Before treatment commenced a self-complete questionnaire was completed. The examining dentist was blinded to the questionnaire responses. The sample was randomly split into two groups (RS1 and RS2). Discriminant analysis was carried out on RS1 to develop a model for classifying new dental pain cases into three groups. This model was used to classify dental pain cases in RS2. RESULTS: Of the 311 questionnaires distributed, 306 (98.4%) were returned. Of the 205 Group 1 cases diagnosed clinically 186 (90.7%) were correctly predicted as belonging to that group by M-DePaQ. For 54 clinically diagnosed Group 2 cases 44 (81.5%) were correctly predicted, and for 32 Group 3 cases, 26 (81.3%) were correctly predicted. The model of classification equations derived from RS1 were capable of correctly classifying 85%, 82% and 79% of clinically-derived classification for Group 1, 2 and 3 respectively. CONCLUSIONS: This study has demonstrated that the M-DePaQ is valid in classifying dental pain patients into three groups of common dental conditions. Classification equations generated from a sub-group of the sample provided a valid statistical model for classifying dental pain cases from the same setting.
AIMS: To assess the validity of modified DePaQ items in correctly classifying dental painpatients into three groups of common dental conditions when compared against clinically-determined classification; generate a model of classification equations from a sub-population of the sample; and assess the validity of the model in predicting group membership of new dental pain cases. METHODS: Consecutive adult hospital dental patients aged 18 years and older attending with a dental pain complaint were diagnosed by a dentist. Before treatment commenced a self-complete questionnaire was completed. The examining dentist was blinded to the questionnaire responses. The sample was randomly split into two groups (RS1 and RS2). Discriminant analysis was carried out on RS1 to develop a model for classifying new dental pain cases into three groups. This model was used to classify dental pain cases in RS2. RESULTS: Of the 311 questionnaires distributed, 306 (98.4%) were returned. Of the 205 Group 1 cases diagnosed clinically 186 (90.7%) were correctly predicted as belonging to that group by M-DePaQ. For 54 clinically diagnosed Group 2 cases 44 (81.5%) were correctly predicted, and for 32 Group 3 cases, 26 (81.3%) were correctly predicted. The model of classification equations derived from RS1 were capable of correctly classifying 85%, 82% and 79% of clinically-derived classification for Group 1, 2 and 3 respectively. CONCLUSIONS: This study has demonstrated that the M-DePaQ is valid in classifying dental painpatients into three groups of common dental conditions. Classification equations generated from a sub-group of the sample provided a valid statistical model for classifying dental pain cases from the same setting.
Authors: José Obed García-Cortés; Jairo Mariel-Cárdenas; Ricardo Martinez-Rider; Rosalina Islas-Zarazúa; Rubén de la Rosa-Santillana; José de Jesús Navarrete-Hernández; Carlo Eduardo Medina-Solís; Gerardo Maupomé Journal: Int Dent J Date: 2020-07-31 Impact factor: 2.607