Dental Traumatology最新文献

Objective: To verify the association between physical activity (PA) and prevalence and severity of traumatic dental injuries (TDIs) in 4-year-old children.

Methods: A cohort study was conducted involving all children born in 2015 in Pelotas, Brazil. During the 4-year follow-up period, mothers answered a questionnaire regarding their child's health and demographic characteristics. All children underwent a clinical examination to assess their oral health, including TDIs, classified as per the United Kingdom Children's Dental Health Survey criteria and Glendor's classification for injury severity. PA levels were measured using an accelerometer and maternal perceptions.

Results: The prevalence of TDI was 14.5% and 85.5% for complicated and uncomplicated TDIs, respectively. The cohort comprised 50.5% boys and 49.5% girls, with a higher TDI prevalence observed in boys (22.4%) than in girls (17.9%) (p = 0.001). Furthermore, boys exhibited more severe TDIs (p < 0.001). No association was observed between PA and the prevalence of TDIs in the overall cohort. However, a trend toward an increase in the severity of complicated trauma (TDI) with higher levels of PA was observed. In particular, children in the higher tertile had a higher proportion of severe TDIs compared to those in the lower PA tertile (relative risk [RR]: 2.42; 95% confidence interval [CI]: 1.34-4.36). Moreover, children whose mothers considered them more active than their counterparts were more likely to have complicated TDIs (RR: 1.52; 95% CI: 1.06-2.20).

Conclusion: We found an association between the severity of TDIs and increased PA. To avoid TDIs, a safer environment for PA should be provided.

Background/aims: Emergency department visits for dental issues are mainly related to traumatic injuries. Knowledge of emergency department staff regarding diagnosis and treatment of dentofacial injuries is quite significant for prognosis of teeth and peripheral tissues. The aim of this study is to assess attitude, knowledge, education and self-confidence of undergraduate nursing students, who will work at emergency departments in the future, regarding diagnosis and treatment of dental traumatic injuries.

Materials and methods: This survey was prepared by modifying questions of the previous survey that had been internationally published. It was a face-to-face survey consisting of 15 questions regarding management of the dental traumas. Questions addressing participants' genders and year of study were added to the survey form. The survey was distributed to 1st, 2nd, 3rd and 4th-year undergraduate nursing students. Analysis results were presented in the form of frequencies. Pearson's chi-squared test and the Fisher-Freeman-Halton test were used for analysis of the categorical data. Multiple comparisons were made using the Bonferroni-correction Z test. The level of significance was set at p < 0.05.

Results: The survey was responded by a total of 297 participants, including 47 men and 250 women. Participants consisted of 35.4% first-year, 28.6% second-year, 15.5% third-year, and 20.5% fourth-year nursing students. The third-year undergraduate students believed that they had adequate knowledge, and they were also the group that most strongly supported for administration of tetanus vaccine (p < 0.05). No significant difference was observed among nursing students regarding other topics. Students' knowledge and awareness levels respecting particularly avulsion injuries were found to be inadequate regardless of their year of study.

Conclusions: Knowledge of most undergraduate nursing students regarding diagnosis and treatment of dentofacial traumatic injuries were insufficient. An additional education is required for students during and after their formal education to manage dental traumas following graduation.

Background: Dentoalveolar ankylosis posttrauma or external cervical resorption (ECR) post orthodontics might affect permanent teeth in growing individuals. Decoronation and root submergence attempt to minimize the impact of these sequelae. This is one of the few reports in which the survival of provisional restorations and preservation of the marginal bone post long-term follow-up of this treatment modality were evaluated for several cases.

Materials and methods: Nine upper permanent incisors with ankylosis or ECR, treated using decoronation and root submergence were examined. The qualitative changes in the vertical dimension of the alveolar ridge were measured on periapical radiographs by means of a three-point scoring system, and the time to moderate and considerable bone increase was assessed using Kaplan-Meier curves. The quantitative changes in vertical bone dimension were measured on the periapical radiographs and the inter-rater reliability was assessed. The survival of the temporary restoration post decoronation and the presence of root remnants were evaluated. The mean age of the patients was 11 years at the time of trauma and 15.3 years when decoronated. The follow-up period post decoronation was 1.5-8.5 years (mean 3.5 years). Post decoronation, quantitatively, 5 cases presented a slight bone increase (0.01-2 mm) and 4 unchanged or slightly decreased bone levels (0.2-1.3 mm). Qualitatively, 60% (95% CI; 15%-90%) of the female patients showed moderate bone increase and 40% (95% CI; 10%-70%) considerable, respectively, 1.7-8.3 and 2.5-8.3 years post decoronation. Age was inversely proportional with bone increase, independent of gender. At 1.5 years follow-up, root remnants were present in all cases. The tooth shaped as a pontic failed the most as a temporary restoration.

Conclusion: Despite limitations, the following can be concluded: decoronation and root submergence of permanent incisors in growing individuals seem promising in terms of long-term vertical alveolar ridge preservation. The restorative temporary replacement of decoronized teeth is challenging.

Background: This study assessed the accuracy and consistency of responses provided by six Artificial Intelligence (AI) applications, ChatGPT version 3.5 (OpenAI), ChatGPT version 4 (OpenAI), ChatGPT version 4.0 (OpenAI), Perplexity (Perplexity.AI), Gemini (Google), and Copilot (Bing), to questions related to emergency management of avulsed teeth.

Materials and methods: Two pediatric dentists developed 18 true or false questions regarding dental avulsion and asked public chatbots for 3 days. The responses were recorded and compared with the correct answers. The SPSS program was used to calculate the obtained accuracies and their consistency.

Results: ChatGPT 4.0 achieved the highest accuracy rate of 95.6% over the entire time frame, while Perplexity (Perplexity.AI) had the lowest accuracy rate of 67.2%. ChatGPT version 4.0 (OpenAI) was the only AI that achieved perfect agreement with real answers, except at noon on day 1. ChatGPT version 3.5 (OpenAI) was the AI that showed the weakest agreement (6 times).

Conclusions: With the exception of ChatGPT's paid version, 4.0, AI chatbots do not seem ready for use as the main resource in managing avulsed teeth during emergencies. It might prove beneficial to incorporate the International Association of Dental Traumatology (IADT) guidelines in chatbot databases, enhancing their accuracy and consistency.

Background/aims: Preformed zirconia crowns have emerged as the preferred choice for restoring damaged primary incisors. However, they differ from natural teeth in their biophysical properties and can potentially alter the overall response of crowned teeth to a traumatic load. This in silico study aimed to compare the response of three different traumatic loading conditions for the (i) natural (M1) and (ii) zirconia-restored tooth models (M2) models.

Methodology: A 3D dynamic finite element (FE) analysis was performed, and minimum dynamic loads required for fracture and coronal portion disjunction of both tooth models were applied in frontal, oblique, and incisal directions. Stress concentrations, von Mises stresses, fracture patterns, and displacements were compared at different periods of the loading pulse.

Results: The computed minimum threshold loads resulting in fracture of the natural tooth model were 82 N, 166 N, and 171 N for the frontal, oblique, and incisal impacts, respectively. Fracture of the coronal portion started at 1.8 and 1.68 ms in natural tooth and zirconia-restored tooth models, respectively. Complete disjunction of coronal and radicular portions occurred earlier in the zirconia-restored tooth model (2.46 ms) than in the natural tooth model (4.5 ms) for frontal impact. The maximum von Mises stresses causing fracture ranged from 254 to 314 MPa for both models, following assigned element erosion criteria. The zirconia-restored tooth model did not experience fracture during an oblique impact.

Conclusion: The stress concentration patterns were seen to be altered in the zirconia-restored tooth model. On incisal impact, the permanent tooth germ in the natural tooth model displayed stress concentrations that were not seen in the zirconia-restored tooth model.

Background/aim: The use of AI-driven chatbots for accessing medical information is increasingly popular among educators and students. This study aims to assess two different ChatGPT models-ChatGPT 3.5 and ChatGPT 4.0-regarding their responses to queries about traumatic dental injuries, specifically for dental students and professionals.

Material and methods: A total of 40 questions were prepared, divided equally between those concerning definitions and diagnosis and those on treatment and follow-up. The responses from both ChatGPT versions were evaluated on several criteria: quality, reliability, similarity, and readability. These evaluations were conducted using the Global Quality Scale (GQS), the Reliability Scoring System (adapted DISCERN), the Flesch Reading Ease Score (FRES), the Flesch-Kincaid Reading Grade Level (FKRGL), and the Similarity Index. Normality was checked with the Shapiro-Wilk test, and variance homogeneity was assessed using the Levene test.

Results: The analysis revealed that ChatGPT 3.5 provided more original responses compared to ChatGPT 4.0. According to FRES scores, both versions were challenging to read, with ChatGPT 3.5 having a higher FRES score (39.732 ± 9.713) than ChatGPT 4.0 (34.813 ± 9.356), indicating relatively better readability. There were no significant differences between the ChatGPT versions regarding GQS, DISCERN, and FKRGL scores. However, in the definition and diagnosis section, ChatGPT 4.0 had a statistically higher quality score than ChatGPT 3.5. In contrast, ChatGPT 3.5 provided more original answers in the treatment and follow-up section. For ChatGPT 4.0, the readability and similarity rates for the definition and diagnosis section were higher than those for the treatment and follow-up section. No significant differences were observed between ChatGPT 3.5's DISCERN, FRES, FKRGL, and similarity index measurements by topic.

Conclusions: Both ChatGPT versions offer high-quality and original information, though they present challenges in readability and reliability. They are valuable resources for dental students and professionals but should be used in conjunction with additional sources of information for a comprehensive understanding.

Background: Traumatic dental injuries (TDI) are a global health concern, affecting millions of people annually. The prevalence of traumatic dental injuries (TDIs) can vary significantly with change in geographic region, occupation, and lifestyle. Animal handlers, such as cattle farmers, are at risk of experiencing TDIs due to their interactions with animals. However, there have been no previous studies investigating the prevalence of TDI among cattle farmers.

Aim: To determine the prevalence and associated risk of TDI among cattle farmers in Vadodara City, Gujarat, India.

Methodology: A cross-sectional study was conducted among cattle farmers residing in Vadodara City. Purposive snowball sampling was used to recruit the cattle farmers. A questionnaire was used to collect data on demographic variables, animal handling practices, experience, history of trauma. Clinical examination was carried out to screen for TDI and possible risk factors.

Results: A total of 357 cattle farmers participated in the study. The prevalence of TDI among cattle farmers was 7.8%. All the respondents reported some form of soft tissue injury (100%). Luxation (60.71%) was the most frequent dental injury, followed by tooth fracture (57.14%). Maxillary incisors were the most commonly affected teeth (75.61%). Kicking (39%) and head-butting (43%) were the most frequent causes of injury. Increased overjet, inadequate lip coverage, and Class II molar relationship were associated with a higher risk of TDI.

Conclusion: Prevalence of TDI among cattle farmers was found to be 7.8%. Since the cattle farmers are inherently at risk for TDI as occupational hazard, preventing dental trauma-related injuries in cattle farmers is crucial.

Background/aim: An injury sustained during sports activity can lead to the development of reinjury anxiety and hamper performance. Although tools exist to assess re-injury anxiety, a domain of interest in the field of sports medicine, research in the psychological impact of an orofacial injury is rudimentary. The present study envisaged to develop an instrument to assess the presence of reinjury anxiety following orofacial and dental injury in boxers aged between 10 and 16 years.

Methods: In Phase 1, items were generated following literature search and focus-group discussions (FGD). In Phase 2, a group discussion was conducted with three experienced boxing coaches to assess face validity, followed by two rounds of scrutiny by expert groups to assess the content validity through the content-validity-index (CVI), respectively. In Phase 3, the modified tool was pre-tested on an independent sample of young boxers. Finally, in Phase 4, to determine dimensionality, the modified tool was administered to 183 young boxers and their responses were subject to an exploratory factor analysis through Principal component analysis, followed by Promax rotation to determine the factor loading. Internal consistency reliability was measured through calculation of Cronbach's-alpha.

Results: From the 29-items devised initially, the tool was sequentially modified. Analysis of the responses by the second expert group, an average Scale-level-CVI of 0.9 and Universal agreement of 0.526 was obtained, which resulted in the inclusion of 20 items for the final phase of the study. From the factor analysis, the items were found to fit to a five-factor structure, which explained 56.4% of the variance in the constructs. Internal consistency of the tool was measured to be 0.74.

Conclusion: A 10-item oral re-injury anxiety scale for young boxers (ORAS-YB) tool was developed. It was found to have high face and content validity, and acceptable reliability. Further research with a larger sample is required to confirm the factor structure and determine test-retest reliability of the developed tool.

Background/aim: To explore transfer learning (TL) techniques for enhancing vertical root fracture (VRF) diagnosis accuracy and to assess the impact of artificial intelligence (AI) on image enhancement for VRF detection on both extracted teeth images and intraoral images taken from patients.

Materials and methods: A dataset of 378 intraoral periapical radiographs comprising 195 teeth with fractures and 183 teeth without fractures serving as controls was included. DenseNet, ConvNext, Inception121, and MobileNetV2 were employed with model fusion. Prior to evaluation, Particle Swarm Optimization (PSO) and Deep Learning (DL) image enhancement were applied. Performance assessment included accuracy rate, precision, recall, F1-score, AUC, and kappa values. Intra- and inter-observer agreement, according to the Gold Standard (GS), were assessed using ICC and t-tests. Statistical significance was set at p < 0.05.

Results: The DenseNet + Inception fusion model achieved the highest accuracy rate of 0.80, with commendable recall, F1-score, and AUC values, supported by precision (0.81) and kappa (0.60) values. Molar tooth examination yielded an accuracy rate, precision, recall, and F1-score of 0.80, with an AUC of 0.84 and kappa of 0.60. For premolar teeth, the fusion network showed an accuracy rate of 0.78, an AUC of 0.78, and notable metrics, including F1-score (0.80), recall (0.85), precision (0.71), and kappa (0.55). ICC results demonstrated acceptable agreement (≥ 0.57 for molars, ≥ 0.52 for premolars).

Conclusion: TL methods have demonstrated significant potential in enhancing diagnostic accuracy for VRFs in radiographic imaging. TL is emerging as a valuable tool in the development of robust, automated diagnostic systems for VRF identification, ultimately supporting clinicians in delivering more accurate diagnoses.