Dental anomalies in an Albanian orthodontic sample: a retrospective study.

BACKGROUND: To evaluate the prevalence and the distribution of dental anomalies in an Albanian orthodontic sample. METHODS: For this retrospective study, a sample of panoramic radiographs (PR) of n. 779 (456 F and 323 M, mean age of 15.1 ± 5.5 years) Albanian subjects with no genetic syndromes or craniofacial malformations (e.g., cleft lip/palate), history of extraction, trauma or previous orthodontic treatment drawn from the archives of the University Dental Clinic Our Lady of Good Counsel, was examined. The inclusion criteria were: subjects from 8 to 30 years of age, good quality of PRs in order to allow the assessment of crown and root development. For different dental anomalies, both the prevalence and the association were evaluated by using Chi-square test (p < 0.05). RESULTS: 24.4% of the sample had at least one dental anomaly and 4.6% had more than one. The following dental anomalies were most prevalent: hypodontia (9.8%), dental impaction (7.6%), and ectopic eruption (5.3%). No statistically significant correlation was found between males and females (p > 0.05). CONCLUSIONS: The most common anomalies in this group are found to be those of number and position, and only radiological investigations can reveal either of these anomalies. Early diagnosis of dental anomalies can contribute to prevent their complications and to establish the most suitable therapy to achieve a functional occlusion.

Accuracy and Completeness of ChatGPT-Generated Information on Interceptive Orthodontics: A Multicenter Collaborative Study.

Background: this study aims to investigate the accuracy and completeness of ChatGPT in answering questions and solving clinical scenarios of interceptive orthodontics. Materials and Methods: ten specialized orthodontists from ten Italian postgraduate orthodontics schools developed 21 clinical open-ended questions encompassing all of the subspecialities of interceptive orthodontics and 7 comprehensive clinical cases. Questions and scenarios were inputted into ChatGPT4, and the resulting answers were evaluated by the researchers using predefined accuracy (range 1-6) and completeness (range 1-3) Likert scales. Results: For the open-ended questions, the overall median score was 4.9/6 for the accuracy and 2.4/3 for completeness. In addition, the reviewers rated the accuracy of open-ended answers as entirely correct (score 6 on Likert scale) in 40.5% of cases and completeness as entirely correct (score 3 n Likert scale) in 50.5% of cases. As for the clinical cases, the overall median score was 4.9/6 for accuracy and 2.5/3 for completeness. Overall, the reviewers rated the accuracy of clinical case answers as entirely correct in 46% of cases and the completeness of clinical case answers as entirely correct in 54.3% of cases. Conclusions: The results showed a high level of accuracy and completeness in AI responses and a great ability to solve difficult clinical cases, but the answers were not 100% accurate and complete. ChatGPT is not yet sophisticated enough to replace the intellectual work of human beings.