Intraoral Scanning for Monitoring Dental Wear and Its Risk Factors: A Prospective Study.

Dental wear arises from mechanical (attrition or abrasion) and chemical (erosion) factors. Despite its prevalence and clinical significance, accurately measuring and understanding its causes remain challenging in everyday practice. This one-year study with 39 participants involved comprehensive examinations and full-arch intraoral scans at the start and after 12 months. Volume loss exceeding 100 µ on each tooth's surfaces (buccal, lingual/palatine and incisal/occlusal) was measured by comparing three-dimensional scans from both time points. This study also assessed factors such as abrasion and erosion through clinical exams and questionnaires. There were no significant differences in dental wear in participants with sleep bruxism. However, noticeable wear occurred in the front teeth of those with waking bruxism and joint-related symptoms. Increased wear was associated with frequent consumption of acidic drinks, regular swimming, dry mouth, nocturnal drooling and heartburn, while no significant wear was found in patients with reflux. The used methodology proved effective in accurately assessing the progression of dental wear, which is important as many patients may initially be asymptomatic. The variability observed in dental wear patterns underscores the need to develop specific software applications that allow immediate and efficient comparison of wear areas based on extensive analysis of patient databases.

ChatGPT performance in prosthodontics: Assessment of accuracy and repeatability in answer generation.

STATEMENT OF PROBLEM: The artificial intelligence (AI) software program ChatGPT is based on large language models (LLMs) and is widely accessible. However, in prosthodontics, little is known about its performance in generating answers. PURPOSE: The purpose of this study was to determine the performance of ChatGPT in generating answers about removable dental prostheses (RDPs) and tooth-supported fixed dental prostheses (FDPs). MATERIAL AND METHODS: Thirty short questions were designed about RDPs and tooth-supported FDP, and 30 answers were generated for each of the questions using ChatGPT-4 in October 2023. The 900 generated answers were independently graded by experts using a 3-point Likert scale. The relative frequency and absolute percentage of answers were described. Accuracy was assessed using the Wald binomial method, while repeatability was evaluated using percentage agreement, Brennan and Prediger coefficient, Conger generalized Cohen kappa, Fleiss kappa, Gwet AC, and Krippendorff alpha methods. Confidence intervals were set at 95%. Statistical analysis was performed using the STATA software program. RESULTS: The performance of ChatGPT in generating answers related to RDP and tooth-supported FDP was limited. The answers showed a reliability of 25.6%, with a confidence range between 22.9% and 28.6%. The repeatability ranged from substantial to moderate. CONCLUSIONS: The results show that currently ChatGPT has limited ability to generate answers related to RDPs and tooth-supported FDPs. Therefore, ChatGPT cannot replace a dentist, and, if professionals were to use it, they should be aware of its limitations.

Beyond the Scalpel: Assessing ChatGPT's potential as an auxiliary intelligent virtual assistant in oral surgery.

AI has revolutionized the way we interact with technology. Noteworthy advances in AI algorithms and large language models (LLM) have led to the development of natural generative language (NGL) systems such as ChatGPT. Although these LLM can simulate human conversations and generate content in real time, they face challenges related to the topicality and accuracy of the information they generate. This study aimed to assess whether ChatGPT-4 could provide accurate and reliable answers to general dentists in the field of oral surgery, and thus explore its potential as an intelligent virtual assistant in clinical decision making in oral surgery. Thirty questions related to oral surgery were posed to ChatGPT4, each question repeated 30 times. Subsequently, a total of 900 responses were obtained. Two surgeons graded the answers according to the guidelines of the Spanish Society of Oral Surgery, using a three-point Likert scale (correct, partially correct/incomplete, and incorrect). Disagreements were arbitrated by an experienced oral surgeon, who provided the final grade Accuracy was found to be 71.7%, and consistency of the experts' grading across iterations, ranged from moderate to almost perfect. ChatGPT-4, with its potential capabilities, will inevitably be integrated into dental disciplines, including oral surgery. In the future, it could be considered as an auxiliary intelligent virtual assistant, though it would never replace oral surgery experts. Proper training and verified information by experts will remain vital to the implementation of the technology. More comprehensive research is needed to ensure the safe and successful application of AI in oral surgery.

Comparative study of torsional and bending stress in NiTi, graphene, and GUM metal endodontic files by finite element analysis.

INTRODUCTION: This study investigates the behavior of graphene and GUM in terms of cyclic fatigue resistance and torsion through a finite element analysis on a file with an eccentric rectangular cross section and variable taper, and on a file with a centered triangular cross section, constant taper, and constant pitch. METHODS: Root canals and endodontic files were created using Catia V5R21 software. For torsional analysis, the tip of the file was fixed at 1 and 3 mm, and a moment of 2.5 N-mm was generated at the handle. For the bending analysis in curved canals (45° and 60°), the handle was kept fixed and a force of 1 N was applied at the tip while the file was kept fixed at 9 mm. RESULTS: GUM metal instruments showed better torsional resistance. On the other hand, NiTi and graphene performed better under the applied loads during flexion at 45° and 60°. CONCLUSION: GUM metal is emerging as a promising material in the field of endodontic instrument design due to its physical properties.

Unveiling the ChatGPT phenomenon: Evaluating the consistency and accuracy of endodontic question answers.

AIM: Chatbot Generative Pre-trained Transformer (ChatGPT) is a generative artificial intelligence (AI) software based on large language models (LLMs), designed to simulate human conversations and generate novel content based on the training data it has been exposed to. The aim of this study was to evaluate the consistency and accuracy of ChatGPT-generated answers to clinical questions in endodontics, compared to answers provided by human experts. METHODOLOGY: Ninety-one dichotomous (yes/no) questions were designed and categorized into three levels of difficulty. Twenty questions were randomly selected from each difficulty level. Sixty answers were generated by ChatGPT for each question. Two endodontic experts independently answered the 60 questions. Statistical analysis was performed using the SPSS program to calculate the consistency and accuracy of the answers generated by ChatGPT compared to the experts. Confidence intervals (95%) and standard deviations were used to estimate variability. RESULTS: The answers generated by ChatGPT showed high consistency (85.44%). No significant differences in consistency were found based on question difficulty. In terms of answer accuracy, ChatGPT achieved an average accuracy of 57.33%. However, significant differences in accuracy were observed based on question difficulty, with lower accuracy for easier questions. CONCLUSIONS: Currently, ChatGPT is not capable of replacing dentists in clinical decision-making. As ChatGPT's performance improves through deep learning, it is expected to become more useful and effective in the field of endodontics. However, careful attention and ongoing evaluation are needed to ensure its accuracy, reliability and safety in endodontics.

Influence of the use of social media on patients changing dental practice: a web-based questionnaire study.

BACKGROUND: Recent years have seen an increase in the use of social media, by the healthcare sector, including dentistry. Indeed, social media may now be important communication tools for dental practices and patients. This work analyzes the influence of patient (male and female) use of dental practice social media on their decision to change practice. The results also provide insight into the factors patients considered important when choosing a dental practice. METHODS: This study was approved by the Ethics Committee of the Universidad Europea de Madrid (No. CIPI/22.022). Using a web-based questionnaire, a cross-sectional study was undertaken involving a Spanish population that made use of dental services. The questionnaire consisted of four parts covering provision of informed consent, the collection of sociodemographic data, patient use of dental practice social media, and the factors considered important when changing dental practice. RESULTS: All participants gave their informed consent regarding inclusion. No compensation was provided for participation. 588 people responded to the questionnaire, of whom 503 were eligible for inclusion. Most respondents were female (312/503; 62%). Most (151/503; 30%) last changed dental practice during the previous 2-5 years. 208/503 (41.4%) indicated that they had visited dental practice social media. 118/503 (23.5%) indicated that they had made use of such the last time they changed dental practice; 102 of these 118 (85.6%) reported their experience to have influenced their decision to change. Respondents who had changed practice in the last 5 years had interacted with dental practice social media more than those who changed over 11 years ago (p < .05), and those who changed practice in the present/past year were more influenced by these media (p < .05). The factor considered most important was 'Facilities and technology'. No gender-based differences were seen for any measured variable (p < .05). CONCLUSIONS: Different factors affect the selection of a new dental practice, but respondents who changed practice in the last few years were more likely to have made use of dental practice social media, which, for some, influenced their final decision to change. Dental practices might do well to consider using social media as communication and marketing tools.

Using a Virtual Patient via an Artificial Intelligence Chatbot to Develop Dental Students' Diagnostic Skills.

Knowing how to diagnose effectively and efficiently is a fundamental skill that a good dental professional should acquire. If students perform a greater number of clinical cases, they will improve their performance with patients. In this sense, virtual patients with artificial intelligence offer a controlled, stimulating, and safe environment for students. To assess student satisfaction after interaction with an artificially intelligent chatbot that recreates a virtual patient, a descriptive cross-sectional study was carried out in which a virtual patient was created with artificial intelligence in the form of a chatbot and presented to fourth and fifth year dental students. After several weeks interacting with the AI, they were given a survey to find out their assessment. A total of 193 students participated. A large majority of the students were satisfied with the interaction (mean 4.36), the fifth year students rated the interaction better and showed higher satisfaction values. The students who reached a correct diagnosis rated this technology more positively. Our research suggests that the incorporation of this technology in dental curricula would be positively valued by students and would also ensure their training and adaptation to new technological developments.

Application of the Intraoral Scanner in the Diagnosis of Dental Wear: An In Vivo Study of Tooth Wear Analysis.

In recent years, there has been an increase in the incidence of dental wear; thus, an early diagnosis is important. Conventional methods of diagnosis are based primarily on the visual abilities of the dentist, and therefore the use of new technologies for the detection of dental wear may be very useful. The aim of the study was to analyze the sensitivity and specificity of the intraoral scanner for measuring dental wear, as well as to evaluate patients' satisfaction with the use of the scanner. The study was conducted with 46 volunteers who underwent three intraoral analyses: a first baseline scanning, a second scanning after 6 months and a final scanning after one year performed by four operators divided into two groups. One of the operators performed the visual analysis of dental wear, and the other performed the analysis using the intraoral scanner 3M™ True Definition intraoral scanner (ESPE, Seefeld, Germany). The data obtained from the intraoral scanner showed levels of specificity and sensitivity that enable the intraoral scanner to be used as a diagnostic tool in the assessment of tooth wear. The participants also showed a high degree of satisfaction with the scanner as a communication tool.

Evaluation of the marginal fit of monolithic crowns fabricated by direct and indirect digitization.

Purpose To evaluate the influence of intraoral and extraoral digitization systems on marginal discrepancy of monolithic lithium disilicate and monolithic zirconia computer-aided design-computer-aided manufacturing (CAD-CAM) crowns.Methods Forty standardized machined stainless steel specimens with the characteristics of a first molar were manufactured and randomly assigned to two groups (n=20 each), depending on their material: monolithic lithium disilicate ceramic (LM), and monolithic zirconia (ZM). Then, each group was subdivided into two depending on the scanning system used: intraoral scanner (IOS), and extraoral scanner (EOS). The digitization process was standardized with two methacrylate devices, one for each scanner. After scanning and manufacturing of the crowns, the marginal discrepancy was measured under a scanning electron microscope (SEM). Data analysis was made using two-way analysis of variance (ANOVA) and the effect size with Cohen's d.Results All the measurements were within the limits considered acceptable. Regardless the restorative material significant differences between scanners were observed, being the effect from low to moderate. However, no differences were observed between the scanners in either the lithium disilicate or zirconia group.Conclusions The intraoral scan showed lower marginal discrepancy than the extraoral scan in CAD-CAM monolithic crowns, but these differences were not observed in each of the ceramic systems.

The Marginal Fit of CAD/CAM Monolithic Ceramic and Metal-Ceramic Crowns.

PURPOSE: Studies on the marginal fit of monolithic restorations are limited. This study aimed to evaluate the marginal fit among monolithic zirconia, monolithic lithium disilicate, and conventional metal-ceramic crowns and to compare the buccal and lingual surfaces. MATERIALS AND METHODS: Thirty standardized stainless steel master dies were fabricated (height: 5 mm; convergence: 6°; chamfer: 1 mm). The dies were randomly divided into three groups (n = 10 each) according to the material used to construct the crowns: group 1 (LM): Lava Plus; group 2 (DM): IPS e.max CAD; and group 3 (MC): Metal-ceramic. The crowns were luted in a standard manner onto the stainless steel master dies using conventional glass ionomer cement. The vertical marginal gap of the restorations was evaluated under a scanning electron microscope (SEM) at 500x magnification. One-way ANOVA, Tukey´s HSD test, and Student's paired t test were used to assess the marginal discrepancy among the groups. The cutoff value for statistical significance was set at α = 0.05. RESULTS: Significant differences among the three groups (p = 0.0001) were recorded. DM group showed the lowest discrepancies (27.95 ± 9.37 µm). Significant differences were observed for the buccal (p = 0.007) and lingual (p = 0.0001) surfaces between the DM group and the other groups. CONCLUSIONS: The accuracy of fit achieved for the three groups was within the range of clinical acceptance. IPS e.max CAD showed the lowest discrepancies.