Mazzilli Luiz Eugenio Nigro, Melani Rodolfo Francisco Haltenhoff, Lascala Cesar Angelo, Palacio Luz Andrea Velandia, Cameriere Roberto
Department of Community Dentistry, School of Dentistry, University of São Paulo, OFLab (anthropology and Forensic Dentistry Laboratory), Brazil.
Department of Radiology, School of Dentistry, University of São Paulo, Brazil.
J Forensic Leg Med. 2018 Aug;58:164-168. doi: 10.1016/j.jflm.2018.06.006. Epub 2018 Jun 28.
Age estimation plays an important role in clinical and forensic dentistry. Cameriere's 2007 open apices method for age estimation was applied in a sample of 612 digital panoramic orthopantomographs from Brazilian subadult individuals of known age and sex. The sample was composed of 290 males and 322 females individuals aged between four and 16 years of age from São Paulo metropolitan area who had undertaken radiographs for clinical purposes. Participant's ethnicity data was not available. An open code computer-aided drafting software (ImageJ) was used to measure the variables according to the author's published guidelines. Subjects' age was firstly estimated under the application of the European formula (2007) showing under-estimation (-1.24yr). On the other hand, the linear regression analysis modeled for this specific population was able to explain 91.2% of the chronological age variation with a standard error of 0.91yr. Residual analyses confirmed independent errors and a normal distribution. In conclusion, the present results support Cameriere's method for age estimation in Brazilian subadults to be a reliable method, although correlations may vary between specific groups and, hence, specific formulae may be useful for an accurate prediction.
年龄估计在临床牙科和法医牙科学中起着重要作用。卡梅里埃2007年提出的用于年龄估计的根尖孔开放法应用于来自巴西已知年龄和性别的612例亚成年人的数字全景曲面断层片样本。该样本由来自圣保罗大都市区年龄在4至16岁之间的290名男性和322名女性组成,他们因临床目的接受了X光检查。参与者的种族数据不可用。根据作者发表的指南,使用开源计算机辅助绘图软件(ImageJ)来测量变量。首先应用欧洲公式(2007)对受试者的年龄进行估计,结果显示存在低估(-1.24岁)。另一方面,针对该特定人群建立的线性回归分析能够解释91.2%的实际年龄变化,标准误差为0.91岁。残差分析证实了独立误差和正态分布。总之,目前的结果支持卡梅里埃的方法在巴西亚成年人年龄估计中是一种可靠的方法,尽管不同特定群体之间的相关性可能有所不同,因此特定公式可能有助于进行准确预测。