[Analysis of influencing factors on orthodontic efficacy in adolescent patients and construction of logistic regression model].

چکیده اصلی

PURPOSE: To analyze the influencing factors of orthodontic efficacy in adolescent patients and construct a logistic regression model. METHODS: A total of 260 adolescent orthodontic patients treated from January 2019 to December 2023 were selected. The therapeutic effect was evaluated using the peer assessment rating (PAR) index. At the 2-year follow-up after treatment completion, patients with a reduction of more than 5 points in the PAR index compared with immediately post-treatment were assigned to the poor efficacy group (n=53), and the remaining patients were assigned to the favorable efficacy group (n=207). Binary logistic regression was used to analyze the risk factors for poor efficacy in adolescent orthodontic patients, and logistic regression model was constructed based on the risk factors. RESULTS: The binary logistic regression analysis showed that anxiety (OR=8.467, 95%CI=2.800-25.609, P＜0.001), Angle Class Ⅱ malocclusion (OR=9.624, 95%CI=2.504-36.990, P=0.001), Angle Class Ⅲ malocclusion (OR=4.210, 95%CI=1.146-15.467, P=0.030), root morphology abnormalities (OR=5.927, 95%CI=2.276-15.435, P＜0.001), poor oral hygiene (OR=2.943, 95%CI=1.139-7.604, P=0.026) and poor patient compliance (OR=9.620, 95%CI =3.047-30.376, P＜0.001) were risk factors for poor treatment outcome in adolescent orthodontic patients, while retainer wearing time (OR=0.773, 95%CI=0.69-0.864, P＜0.001) was a protective factor. A logistic regression model was constructed using the risk factors. The Hosmer-Lemeshow goodness-of-fit test showed that P=0.575. The area under the curve (AUC) of the model for predicting poor treatment outcomes in adolescent orthodontic patients was 0.939, with a 95%CI of 0.908-0.971. The sensitivity and specificity were 92.5% and 83.6%, respectively, and the practical application accuracy was 89.2%. CONCLUSIONS: The orthodontic efficacy of adolescent orthodontic patients is related to anxiety, types of malocclusions, abnormal root morphology, oral hygiene, compliance and duration of retainer wearing. A logistic regression model constructed through risk factors has high predictive value.

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