■使用回归改变的年龄估计,如根牙本质半透明,PDL附件,和减员是预测年龄的简单而可靠的方法。然而,尚未产生广泛的和针对特定人群的公式。此尝试是评估这些改变与年龄的相关性,并生成线性回归公式,具体到这个群体。
■评估了三种改变,例如牙齿磨损,根牙本质半透明,和拔牙的牙周附着水平。使用Johanson\s和Li和Ji标准测量牙齿磨耗。使用Johanson方法和Lamendin方法测量PDL附着水平和根牙本质半透明性。
■SPSS软件(版本27),皮尔逊相关性检验,并采用线性回归分析。
■我们的结果显示了所有三个因素/参数,如损耗,牙周膜,和半透明与年龄有很好的相关性,相关系数r值在0.6到0.8之间。所有参数均与P值<0.005具有统计学上的显着相关性。其中,JohansonG法的根牙本质半透明性与r=0.83表现出良好的相关性,其次是JohansonG法的PDL附着,r=0.702。
■回归变化,如牙本质半透明,卡纳塔克邦海岸的PDL依恋和磨耗与年龄有很好的相关性。其中,JohansonG方法的牙本质半透明性与标准误差估计(SEE)具有最佳相关性。我们的研究结果表明,所有这些参数[半透明,PDL附件,和减员]可以用于年龄估计。
UNASSIGNED: Age estimation using regressive alterations such as root dentin translucency, PDL attachment, and attrition are easy and reliable way of predicting the age. However, extensive and population-specific formula has not been generated. This attempt was to assess the correlation of these alterations with age and to generate a Linear regressive formula, specific to this population.
UNASSIGNED: Three alterations were assessed such as dental attrition, root dentin translucency, and periodontal attachment level from the extracted teeth. Dental attrition was measured using Johanson\'s and Li and Ji criteria. PDL attachment level and root dentin translucency was measured using the Johanson method and the Lamendin method.
UNASSIGNED: SPSS software (Version 27), Pearson correlation test, and Linear regressive analysis were used.
UNASSIGNED: Our results showed all three factors/parameters such as attrition, periodontal ligament, and translucency having a very good correlation with age and correlation coefficient r value ranging from 0.6 to 0.8. All the parameters were having statistically significant correlation with P value <0.005. Among them, root dentin translucency with Johanson G method showed excellent correlation with r = 0.83 followed by PDL attachment by Johanson G method with r = 0.702.
UNASSIGNED: Regressive changes such as Dentin translucency, PDL attachment and attrition on Coastal Karnataka showed a very good correlation with age. Among them, Dentin translucency by Johanson G method had the best correlation with the a standard error of estimate (SEE). Results of our study indicates that all these parameters [Translucency, PDL attachment, and attrition] can be utilized in age estimation.