%0 Journal Article
%T Risk prediction model of impacted supernumerary tooth-associated root resorption in children based on cone-beam computed tomography analysis: a case control study.
%A Li Y
%A Zhang Y
%A Gao L
%A Lyu M
%A Zheng B
%A Zhang F
%A Xu J
%J BMC Oral Health
%V 24
%N 1
%D 2024 Aug 9
%M 39123166
%F 3.747
%R 10.1186/s12903-024-04493-2
%X BACKGROUND: External surface resorption is pressure-induced resorption and occurs on the external surface of the root, pressure exerted by impacted teeth, is common causes of external surface resorption. Predictive risk factors of impacted supernumerary tooth-associated root resorption (ISTARR) mentioned in this article include supernumerary teeth and patient factors. To investigate the risk factors of impacted supernumerary tooth-associated root resorption and predict the incidence of root resorption.
METHODS: This restrospective study enrolled 324 patients with impacted supernumerary tooth. All Cone-Beam Computed Tomography (CBCT) data and patient information were divided into two groups (without tooth root resorption and with root resorption). CBCT images and patient information (age and gender) of 133 patients had adjacent tooth root resorption and 191 did not. seven variables were analysed using binary logistic regression.
RESULTS: Individual analysis of potential risk factors showed that age, crown mesiodistal direction, root formation, and odontotheca of the impacted supernumerary tooth were associated significantly with ISTARR. Binary logistic regression showed that impacted supernumerary tooth with odontotheca (Odd Ratio = 2.926), the crown is in the middle (Odd Ratio = 1.446), located at the middle third of the adjacent tooth root (Odd Ratio = 1.614), complete root development (Odd Ratio = 1.334), and patient's age (Odd Ratio = 1.261) were significantly associated with ISTARR risk.
CONCLUSIONS: The risk factors of root resorption can be detected and predicted early according to the features of supernumerary tooth and patient's age. Still, more prospective studies with larger sample size are needed to validate the result.