Early and 1-year postsurgical stability and its factors in patients with complicated skeletal Class Ⅲ malocclusion treated by conventional and surgery-first approach: A prospective cohort study.

Introduction: This study aimed to compare postsurgical stability between conventional (CSA) and surgery-first (SFA) approaches and investigate its prognostic factors in patients with a skeletal Class Ⅲ extraction.
Methods: Twenty and 19 patients treated with LeFort I osteotomy and bilateral sagittal split ramus osteotomy (BSSRO) with premolar extraction were enrolled in SFA and CSA groups, respectively. Serial cone-beam computed tomography images obtained before surgery, immediately after surgery (T1), 3 months after surgery, and 12 months after surgery were used for 3-dimensional quantitative analysis. The condyle was segmented for analyzing volumetric changes. Repeated measures analysis of variance, independent t test, and chi-square test were used to compare time-course and intergroup differences. Pearson and Kendall correlation and multivariate linear regression analyses were used to explore prognostic factors affecting skeletal stability.
Results: In both CSA and SFA, postsurgical relapse mainly occurred in the mandible sagittal and vertical dimensions and during the first 3 months after surgery. Stability in SFA was significantly less than that in CSA. Intraoperatively, inferolateral condylar displacement with proximal segment inwards, clockwise rotation, and return movements after surgery were observed regardless of the treatment approach. The condylar volume remained stable over time. Multivariate regression analysis showed that posterior vertical dimension (VD) at T1 (-1.63 mm), surgical amount of mandibular setback (-10.33 mm), surgical condylar downwards displacement (-1.28 mm), and anterior overjet at T1 (6.43 mm) were the most important predictors of early mandibular relapse (r ²  = 0.593).
Conclusions: The risk of early relapse could be reduced by controlling the anterior, middle, and posterior constraints provided by the prediction model.
(Copyright © 2023 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.)