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Testing the accuracy of Bedek et al’s new models based on 1-to-7 mandibular teeth for age estimation in 7-15 year old south Indian children
- Source :
- J Forensic Odontostomatol
- Publication Year :
- 2020
- Publisher :
- International Organization for Forensic Odonto-Stomatology, 2020.
-
Abstract
- The goal of long term research on age assessment is to focus on the strengths and weaknesses of existing reliable methods of age estimation. In cases of age estimation when all teeth are present, maximum accuracy can be obtained using a 7 tooth model. Demirjian’s system and Willems models require all seven mandibular teeth in the lower left quadrant for age assessment. Unfortunately, these methods cannot be applied in children with hypodontia. In 2019, Bedek et al., from Croatia, developed new models of age estimation based on a combination of one to seven mandibular teeth. In the present study, we tested the accuracy of the newly developed models for age estimation in South Indian children. Tested in parallel with Willems models, the accuracy of the new models was tested in terms of mean difference, mean absolute error (MAE) and percentage of correct estimations within intervals of +0.5 and +1 years. In terms of mean difference between chronological age (CA) and estimated dental age (DA), all models along with Willems models have underestimated the CA except Bedek et al’s 6 tooth model where overestimation of CA was seen in boys. For MAE and percentage of correct estimations, the new models performed better than Willems models. With regards to our results, it can be concluded that the new models for dental age calculation are accurate and suitable. Therefore, we may encourage their use for age estimation in South Indian children, particularly in individuals with hypodontia or when multiple teeth are missing.
- Subjects :
- stomatognathic diseases
stomatognathic system
Original Articles
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- J Forensic Odontostomatol
- Accession number :
- edsair.pmc...........1cf8ff01fad8983ce44b1a204fbd94e7