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安氏Ⅱ类1分类错病例前磨牙拔除模式的选择 被引量:3

Choice of premolar extraction patterns in class Ⅱ division 1 patients
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摘要 目的:对拔除4个第一前磨牙(44/44)或拔除双侧上颌第一前磨牙和下颌第二前磨牙(44/55)的安氏II1错畸形病例,进行治疗前颌面部软硬组织的比较,探寻影响前磨牙拔除模式的因素,为临床矫治设计提供参考。方法:选取疗效满意、非骨性错的安氏II1病例50例,分为两组,其中拔除44/44 25例,拔除44/55 25例。对两组治疗前的头颅侧位X线片进行测量分析,组间比较,选取其中有统计学差别的指标进行逐步判别分析。结果:L1-AP、TLL-E、拥挤度、Pos-NFL、L1-MP 5个测量项目进入Logistic回归方程,得出Logistic回归方程LogitP=0.056+0.0037L1-MP+0.125 L1-AP(mm)-0.022 Pos-NFL+0.056 TLL-E+0.052拥挤度,概率大于0.5,选择44/44拔牙模式;概率小于0.5,选择44/55拔牙模式。结论:在进行安氏II1错畸形矫治设计上,下切牙突度、下唇突度、拥挤度、下颌软组织颏部位置、下切牙唇舌向倾斜度共同决定了拔牙模式的选择。 Objective: To find the pretreatment factor influencing the premolar extraction pattern and provide some clinical reference for the choice of premolar extraction pattern.Methods : In the study,there were 25 patients involved the extraction of four first premolars and 25 patients involved the extraction of two first maxillary premolars and two second mandibular premolars.The lateral cephalometer with X-ray were taken before and after treatment.46 typical values of hard and soft tissue were measured and analyzed,collected the statistically different index,stepwise discriminant analysis was applied to identify the key factors for discriminating the two groups.Results : L1-AP(mm),TLL-E,congestion,Pos-NFL,L1-MP,the five measurements were collected into the Logistic regression equation.The Logistic regression equation was derived: LogitP=0.056+0.0037L1-MP+0.125L1-AP(mm)-0.022Pos-NFL+0.056TLL-E+0.052 congestion.The probability of greater than 0.5,the extraction model 44/44 was collected.Probability of less than 0.5,the 44/55 tooth extraction mode was selected.Conclusion : During the class Ⅱ division 1 malocclusion deformity correction combine design,the lower incisors protrusion,lower lip protrusion,congestion,jaw and soft tissue chin,lower incisor inclination to the tongue are closely contact with the choice of extraction model.
出处 《天津医科大学学报》 2012年第1期109-111,共3页 Journal of Tianjin Medical University
关键词 安氏Ⅱ类1分类 拔牙模式 头影测量 LOGISTIC回归分析 classⅡ division 1 extraction pattern cephalometrics Logistic regression analysis
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