Bühling Sarah, Thedens Cedric, Eslami Sara, Dahmer Iulia, Sayahpour Babak, Plein Nicolas, Seifert Lukas Benedikt, Sader Robert, Kopp Stefan
Department of Orthodontics, Johann-Wolfgang Goethe University, Frankfurt, Germany.
Faculty of Medicine, Institute of Biostatistics and Mathematical Modelling, Johann-Wolfgang Goethe University, Frankfurt, Germany.
Clin Oral Investig. 2025 May 26;29(6):312. doi: 10.1007/s00784-025-06378-2.
The aim of the study was to identify the best prediction model for the growth pattern of the maxillary segments of infants with unilateral cleft lip and palate post birth and prior to the primary surgical cleft closure.
195 digital maxillary models of 50 infants with unilateral cleft lip and palate were collected during their preoperative alveolar molding therapy period. Intraoral scans were taken shortly after birth, at the monthly checkups and just before the surgical cleft closure at approximately 6 months of age. Surface measurements of maxillary segments were conducted using the diagnostic program OnyxCeph³™. For identifying the best fit for the growth pattern, mixed-effects regression models (fractional polynomials and B-splines) with the surface measurement as dependent variable, patient age (days) as predictor and the patient as random effect were fitted to the data. The best fit was selected according to the Akaike Information Criterium. A likelihood ratio test was performed for comparing the selected model with the intercept-only model.
The linear regression with mixed effects model showed the best fit for the total area, the area of the large segment and the area of the small segment. A highly significant association between the surface area and patient age was observed (p < 0.001). An increase of the area with time was estimated at 2.88 mm per day for the total area, 1.62 mm per day for the area of the large segment and 1.25 mm per day for the area of the small segment. The likelihood ratio tests indicated that the linear regression models were significantly better than the intercept-only models for all the measured areas (p < 0.01).
The growth pattern for the maxillary segments of patients with unilateral cleft lip and palate in the preoperative period can be best predicted by using a linear regression model. The growth curve model developed by the present study can be used in future treatment planning of patients with unilateral cleft lip and palate.
本研究旨在确定单侧唇腭裂婴儿出生后至初次腭裂修复术前上颌骨段生长模式的最佳预测模型。
收集了50名单侧唇腭裂婴儿在术前牙槽骨塑形治疗期间的195个数字化上颌模型。在出生后不久、每月检查时以及大约6个月龄手术腭裂修复术前进行口腔内扫描。使用诊断程序OnyxCeph³™对上颌骨段进行表面测量。为了确定最适合的生长模式，将以表面测量为因变量、患者年龄（天）为预测变量且患者为随机效应的混合效应回归模型（分数多项式和B样条）拟合到数据中。根据赤池信息准则选择最佳拟合。进行似然比检验以比较所选模型与仅含截距的模型。
混合效应线性回归模型对总面积、大段面积和小段面积显示出最佳拟合。观察到表面积与患者年龄之间存在高度显著的关联（p < 0.001）。估计总面积每天增加2.88毫米，大段面积每天增加1.62毫米，小段面积每天增加1.25毫米。似然比检验表明，对于所有测量区域，线性回归模型显著优于仅含截距的模型（p < 0.01）。
使用线性回归模型可以最好地预测单侧唇腭裂患者术前上颌骨段的生长模式。本研究建立的生长曲线模型可用于未来单侧唇腭裂患者的治疗规划。
