Varela Iván, Fernández-Feijoo Javier, García Eliane, Diniz-Freitas Márcio, Martínez Isabel, Roca Javier, Diz Pedro, Limeres Jacobo
Medical-Surgical Dentistry Research Group (OMEQUI), Health Research Institute of Santiago de Compostela (IDIS), University of Santiago de Compostela (USC), Santiago de Compostela, Spain.
Medical-Surgical Dentistry Research Group (OMEQUI), Health Research Institute of Santiago de Compostela (IDIS), University of Santiago de Compostela (USC), Santiago de Compostela, Spain.
Disabil Health J. 2022 Apr;15(2):101229. doi: 10.1016/j.dhjo.2021.101229. Epub 2021 Nov 9.
The dental treatment of individuals with intellectual disability can represent a considerable professional challenge.
To develop a model for predicting the behavior of patients with intellectual disability in the dental office.
The study group comprised 250 patients with Down syndrome (DS), autism spectrum disorder (ASD), cerebral palsy (CP), idiopathic cognitive impairment or rare disorders. We collected their demographic, medical, social and behavioral information and identified potential predictors (chi-squared test). We developed stratified models (Akaike information criterion) to anticipate the patients'behavior during intraoral examinations and to discern whether the dental treatment should be performed under general anesthesia. These models were validated in a new study group consisting of 80 patients. Goodness of fit was quantified with sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic curve (AUC). We developed a mathematical algorithm for executing the models and developed software for its practical implementation (PREdictors of BEhavior in Dentistry, "PREBED").
For patients with DS, ASD and CP, the model predicting the need for physical restraint during examination achieved a PPV of 0.90, 0.85 and 1.00, respectively, and an NPV of 0.66, 0.76 and 1.00, respectively. The model predicting the need for performing treatment under general anesthesia achieved a PPV of 0.63, 1.00 and 1.00, respectively, and an NPV of 1.00, 1.00 and 0.73, respectively. However, when validating the stratified models, the percentage of poorly classified individuals (false negatives + false positives) ranged from 24% to 46.6%.
The results of the PREBED tool open the door to establishing new models implementing other potentially predictive variables.
为智障人士提供牙科治疗对专业人员来说可能是一项巨大的挑战。
建立一个预测智障患者在牙科诊所行为的模型。
研究组包括250名患有唐氏综合征(DS)、自闭症谱系障碍(ASD)、脑瘫(CP)、特发性认知障碍或罕见疾病的患者。我们收集了他们的人口统计学、医学、社会和行为信息,并确定了潜在的预测因素(卡方检验)。我们开发了分层模型(赤池信息准则),以预测患者在口腔检查期间的行为,并判断是否应在全身麻醉下进行牙科治疗。这些模型在一个由80名患者组成的新研究组中得到了验证。通过敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)和受试者工作特征曲线下面积(AUC)对拟合优度进行量化。我们开发了一种执行模型的数学算法,并开发了用于实际应用的软件(牙科行为预测器,“PREBED”)。
对于患有DS、ASD和CP的患者,预测检查期间需要身体约束的模型的PPV分别为0.90、0.85和1.00,NPV分别为0.66、0.76和1.00。预测需要在全身麻醉下进行治疗的模型的PPV分别为0.63、1.00和1.