Department of Periodontology, University of Florence, Italy.
Am J Orthod Dentofacial Orthop. 2010 Jun;137(6):755-62. doi: 10.1016/j.ajodo.2008.08.028.
The aim of this study was to apply Bayesian networks to evaluate the relative role and possible causal relationships among various factors affecting the diagnosis and final treatment outcome of impacted maxillary canines.
A total of 168 patients with infraosseous impacted maxillary canines had a combined surgical-orthodontic approach aimed to guide the impacted tooth to the center of the alveolar ridge. Demographic, orthodontic, and periodontal variables were recorded and analyzed by means of Bayesian network analysis.
All 168 impacted canines were successfully moved and aligned in the dental arches with healthy periodontiums. According to the Bayesian network analysis, bilateral impaction was associated with palatal impaction and longer treatment; the pretreatment alpha-angle was a determinant for the duration of orthodontic traction, also because of the associations between greater angulation of impacted canines with more severe tooth displacement and with greater distance of the impacted canine from the occlusal plane; the posttreatment periodontal outcome was not related to the pretreatment radiographic variables.
Bayesian network analysis was useful to identify possible relationships among the variables considered for diagnosis and treatment of impacted canines.
本研究旨在应用贝叶斯网络评估影响上颌埋伏尖牙诊断和最终治疗结果的各种因素的相对作用和可能的因果关系。
共有 168 例上颌埋伏尖牙患者采用联合外科-正畸方法,旨在将埋伏牙引导至牙槽嵴中心。记录人口统计学、正畸和牙周变量,并通过贝叶斯网络分析进行分析。
所有 168 颗埋伏的尖牙均成功移动并排列在具有健康牙周组织的牙弓中。根据贝叶斯网络分析,双侧埋伏与腭侧埋伏和更长的治疗时间有关;治疗前的 α 角是正畸牵引持续时间的决定因素,这也是由于埋伏牙的角度越大,牙齿移位越严重,与咬合平面的距离越大;治疗后的牙周状况与治疗前的放射学变量无关。
贝叶斯网络分析可用于确定诊断和治疗埋伏尖牙时考虑的变量之间可能存在的关系。