›› 2016, Vol. 36 ›› Issue (12): 1083-1086.

• 临床研究 • 上一篇    下一篇

种植修复基台就位疼痛的VAS评测及其临床影响因素初探

邵水易,虞颖娟,邱憬   

  1. 江苏省口腔医院
  • 收稿日期:2016-06-13 修回日期:2016-07-16 出版日期:2016-12-28 发布日期:2016-12-20
  • 通讯作者: 邱憬 E-mail:qiujing@njmu.edu.cn
  • 基金资助:
    氟暴露在钛腐蚀行为中的作用机制及其对种植体骨整合的影响;牙龈卟啉单胞菌协同钛腐蚀行为在种植体周围炎发生发展中的作用机理研究

A pilot study of pain scored using VAS and involved clinical factors during seating dental implant restoration abutments

  • Received:2016-06-13 Revised:2016-07-16 Online:2016-12-28 Published:2016-12-20

摘要: 目的 初步探索种植修复基台就位疼痛的临床影响因素,并建立多元线性回归模型。 方法 收集2015年10月至2016年3月于南京医科大学附属口腔医院种植科就诊的登腾种植修复病例。应用视觉模拟评分(VAS)对研究对象的基台就位疼痛进行评测,并测量、记录相关临床因素,包括种植体所在颌位、前后牙区、牙龈袖口深度以及二期手术至戴牙间隔时间,再通过多元线性回归分析临床因素与基台就位疼痛的相关性,建立多元线性回归模型。 结果 38例共82枚登腾种植体被纳入本研究。牙龈袖口深度、二期手术至戴冠间隔时间与基台就位疼痛存在显著相关性,被纳入多元线性回归模型。而种植体所在颌位、前后牙区与基台就位疼痛无显著相关性。建立的多元线性回归模型中,相关变量之间无共线性,无样本强影响点,且残差分布具有正态性和等方差性。 结论 牙龈袖口深度与二期手术至戴牙间隔时间是基台就位疼痛的相关影响因素,由此建立的多元线性回归模型具有较高的可信度。

关键词: 口腔种植, 基台, 就位, 疼痛, 视觉模拟评分, 多元线性回归

Abstract: Objective To explore the pain involved clinical factors during seating dental implant restoration abutments and establish a multivariable linear regression model. Methods Patients of Dentium implant restoration were collected at the Department of Implantology of Affiliated Hospital of Stomatology of Nanjing Medical University from October 2015 to March 2016. Visual analog scale (VAS) was used to score pain intensity during seating dental implant restoration abutments. The clinical factors related to the pain intensity were measured and recorded, including the implant location of maxilla or mandibular (Max-Man) and anterior or posterior tooth area (A-P), the depth of gingival cuff (DC) and the interval time between secondary operation and final restoration (TI). Correlations between these factors and pain intensity were explored by linear regression analysis and a multivariable linear regression model was established. Results 38 patients with 82 Dentium implants were included in this study. DC and TI had statistically significant correlation with the pain intensity and were introduced to establish a multivariable linear regression model. Max-Man and A-P had no statistically significant correlation with the pain intensity. In the established multivariable linear regression model, the predictors had no collinearity; sample influential points were absent, and the residual distribution had normality and equal variances. Conclusion DC and TI have significant association with the pain intensity during seating implant abutments. Thus, the established multivariable linear regression model is reliable.

Key words: Dental implant, Abutment, Seating, Pain, Visual analog scale, Multivariable liner regression

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