Background: One of the primary concerns in the paediatric emergencies is traumatic dental injuries.Objective: This study aimed to create trauma in primary teeth and reveal its effects finite element analysis.Design: Three‐dimensional models were created using cone‐beam computed tomography images, representing a maxillary primary central incisor. An impact force moving at a speed of 10 m/s was simulated on the labial tooth surface in two directions: buccal and incisal.Results: The stress and deformation experienced in the adjacent tooth due to the primary tooth were higher than those generated in the permanent tooth. Forces applied in the incisal direction resulted in higher levels of stress and deformation in the permanent tooth germ. The difference between the stress and deformation values in primary teeth in the forces applied in the buccal and incisal directions is 21% and 75%, respectively; in the permanent tooth germ, this difference was 233% and 100%, respectively.Conclusions: Based on the findings of this study, it is crucial to thoroughly evaluate not only the affected primary tooth but also the adjacent teeth and the permanent tooth germ in traumatic dental injuries. This comprehensive examination allows for the anticipation and management of potential long‐term problems.

Dental caries is a prevalent oral disease affecting young children, leading to significant negative impacts on oral health-related quality of life (OHRQoL). This study aims to evaluate the relationship between extension of dental caries lesions and OHRQoL in children aged 3–6 years using the Early Childhood Oral Health Impact Scale (ECOHIS). This cross-sectional study involved 300 children aged 3–6 years and their parents or caregivers. Clinical examinations were conducted using the decayed, missing, and filled teeth (dmft) Index, the pufa Index, and the International Caries Detection and Assessment System (ICDAS) II. The ECOHIS was administered through interviews with parents or caregivers to assess the impact of dental caries on OHRQoL. Statistical analyses, including Kruskal-Wallis and binomial logistic regression, were performed to evaluate the relationship between pufa scores and ECOHIS results. The findings revealed a significant negative impact of dental caries on OHRQoL (p < 0.05). The mean ECOHIS score was 0.62 ± 0.552, with higher scores observed in children with a pufa Index score > 0 compared to those with a pufa Index score of 0 (p < 0.05). Significant impacts were observed in specific ECOHIS items, such as oral/dental pain (mean score 1.61 ± 1.13), difficulty eating (mean score 1.26 ± 1.26), and trouble sleeping (mean score 0.528 ± 0.942). Parental distress was also notably high, with significant scores in feeling upset (mean score 1.07 ± 1.31) and feeling guilty (mean score 0.929 ± 1.26). Binomial logistic regression analysis showed that a higher pufa score was a significant predictor of increased ECOHIS scores (adjusted OR = 1.929, p = 0.039). The dmft score also significantly predicted higher ECOHIS scores (adjusted OR = 6.597, p = 0.048). Spearman correlation analysis revealed a significant positive correlation between pufa and ECOHIS scores (r = 0.33, p < 0.05). The study demonstrates that extension of dental caries lesions, particularly when measured by the pufa Index, significantly impacts specific aspects of OHRQoL, including pain, eating difficulties, and sleep disturbances in children, as well as emotional distress in parents. Early detection and management of dental caries are crucial in improving the quality of life for affected individuals. Dental practitioners should prioritize preventive measures and parental education to mitigate the adverse effects of dental caries.

This study aims to evaluate the performance of a deep learning system for the evaluation of tooth development stages on images obtained from panoramic radiographs from child patients. The study collected a total of 1500 images obtained from panoramic radiographs from child patients between the ages of 5 and 14 years. YOLOv5, a convolutional neural network (CNN)-based object detection model, was used to automatically detect the calcification states of teeth. Images obtained from panoramic radiographs from child patients were trained and tested in the YOLOv5 algorithm. True-positive (TP), false-positive (FP), and false-negative (FN) ratios were calculated. A confusion matrix was used to evaluate the performance of the model. Among the 146 test group images with 1022 labels, there were 828 TPs, 308 FPs, and 1 FN. The sensitivity, precision, and F1-score values of the detection model of the tooth stage development model were 0.99, 0.72, and 0.84, respectively. In conclusion, utilizing a deep learning-based approach for the detection of dental development on pediatric panoramic radiographs may facilitate a precise evaluation of the chronological correlation between tooth development stages and age. This can help clinicians make treatment decisions and aid dentists in finding more accurate treatment options.

İstanbul Üniversitesi | Tarihten Geleceğe Bilim Köprüsü - 1453

Objective: The World Health Organization declared a COVID-19 pandemic in March 2020. Dentists and their patients are at a particularly higher risk of infection, emphasizing the need for implementation of measures preventing the spread of the virus during emergency dental treatments. YouTube, a digital platform where anyone can upload videos and get feedback from other users about their content, represents a significant resource for accessing information. The aim of the current study was to analyze the content quality and reliability of YouTube videos on the topics of coronavirus and dentistry.Methods: The keywords “coronavirus” and “dentistry” were used to identify relevant videos on YouTube. Approximately 120 videos uploaded between March and November 2020, were reviewed by two independent researchers. Of these, 91 videos fulfilled the inclusion criteria and were scored for content quality and reliability.Results: The majority of videos analyzed were uploaded by public institutions, associations, or hospitals (35.2%) and had a target audience made up of the general population (79.1%). The coronavirus index and total index scores of the videos uploaded by public institutions were significantly higher than those uploaded by dentists (p = 0.017; p < 0.05; p = 0.006; p < 0.01). The mean modified DISCERN (mDISCERN) score, used to assess the reliability of the videos, was 2.88 ± 1.08.Conclusion: The results of this study suggest that specialist physicians should play a more active role in sharing accurate educational videos. Although YouTube, a popular video streaming site, is a valuable resource for accessing useful and accurate information, it also contains large amounts of incomplete and incorrect information which is a significant disadvantage as it can confuse the general public and healthcare professionals and prevent identification of videos produced or verified by authorized healthcare professionals.