Predicting the sagittal skeletal pattern using dental cast and facial profile photographs in children aged 9 to 14 years - Rashna Hoshang Sukhia; Nuruddin, Rozina; Azam, Syed Iqbal; Fida, Mubassar (Journal of the Pakistan Medical Association, 2022)
Introduction: To quantify prediction of sagittal skeletal pattern using anteroposterior dental relationships on dental casts and facial profile photograph. Method: The cross-sectional study was conducted at the Aga Khan University Hospital, Karachi, from December 2016 to July 2017, and comprised orthodontic patients of either gender aged 9-14 years who attended the outpatient dental clinic. The sagittal skeletal relationship assessed on cephalometric radiographs was compared with anteroposterior dental and facial measurements on their dental cast and facial profile photographs. A prediction model was developed using multiple linear regression. The applicability of the prediction model was checked on an independent sample. Data was analysed using STATA 12. Results: Of the 76 patients, about two-third (n=47) were females. The overall median age was 12.3 years (inter-quartile range: 1.8), with majority (60.5%) aged 12-14 years. The proportion of Class I, II and III malocclusion was (n=25) 32.9%, (n=50) 65.8% and (n=1) 1.3% respectively. Highest percentage of variability 47.4% in ANB angle was determined by the soft tissue ANB angle. 54.9% of the variability in the ANB angle could be explained by overjet, soft tissue ANB’ angle, lower lip to E-line distance, Class II incisor relationship, history of malocclusion and thumb sucking, interaction terms between Class II incisor relationship and history of malocclusion, and history of thumb sucking and soft tissue ANB’ angle. Conclusion: Sagittal skeletal relationship in an individual can be predicted with moderate accuracy using the prediction equation incorporating dental and facial variables along with history of malocclusion and thumb-sucking without potentially harmful exposure to cephalometric radiographs. Key Words: Cephalometry, Clinical prediction, Dental cast, Facial photographs, Skeletal pattern.