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Construction and Validation of a Risk Prediction Model for Enamel Demineralization in Orthodontic Patients
Zhaolan Guan, Xiaoqing Yin, Xiaoyan Cai, Danyan Hu, Mengnan Zhang, Luwei Liu, Hongmei Wu
2024, 27(2):
117-123.
DOI: 10.12337/zgkqjxjyzz.2024.02.001
Objective: To investigate the factors affecting enamel demineralization in orthodontic patients and to establish a logistic regression prediction model. Methods: A total of 1934 orthodontic patients were selected from three hospitals in Nanjing from December 2019 to December 2022 as the research subjects. The risk factors between the demineralization group (n=226) and the non-demineralization group (n=1708) were compared. Logistic regression analysis was used to establish a risk prediction model, and the prediction effect of the model was evaluated by ROC curve. Additionally, 828 patients who met the criteria from January to June 2023 were selected for model prediction effect validation. Results: Seven independent risk factors including caries, dental plaque, tooth surface erosion, preference for soft food, brushing frequency, fluoride toothpaste and orthodontic treatment duration were included to construct the risk prediction model. The area under the ROC curve of this model was 0.849, with the sensitivity, the specificity and the Youden index were 0.771, 0.723, and 0.494, respectively. The model validation results showed the sensitivity of 0.813, the specificity of 0.733, and the accuracy of 74.09%. Conclusions: The model is effective in predicting the risk of enamel demineralization, and can provide reference for healthcare professionals to implement timely preventive management measures.
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