Translating Knowledge Into Practice in Dental Trauma: From Education to Emergency Response and Prevention
Notice bibliographique
Résumé
Ana Beatriz Cantao Liran Levin Traumatic dental injuries (TDIs) are highly prevalent among children and adolescents and are associated with functional, esthetic, and psychosocial consequences that can significantly affect quality of life [1, 2]. Effective management of TDIs depends on timely and evidence-based interventions, yet these injuries are often difficult to treat due to their complex nature and the need for rapid clinical treatment [3-5]. General dentists frequently act as the first point of contact for patients with TDIs [6, 7]. However, research consistently shows the gaps in knowledge and preparedness that may compromise treatment outcomes [5-7]. These gaps are closely linked to the quality of predoctoral dental education, where insufficient training in Dental Traumatology (DT) may limit the confidence and competence of future dental professionals [5, 6]. In this issue, Berlin-Broner et al. [8] assessed the curricula for TDIs education at the predoctoral level in North American dental schools, identified the gaps in existing predoctoral dental trauma education, and gathered suggestions for improvement from DT educators. This multi-center study highlights the importance of evaluating how TDIs are taught in North American dental schools and worldwide, with particular emphasis on curriculum design, clinical exposure, and strategies to strengthen student preparedness for managing TDIs. Early childhood is a critical stage for developing both motor and cognitive abilities [9]. When psychomotor development is delayed, children may experience challenges in locomotion, reflexes, and movement precision, making them more vulnerable to accidents such as falls [1, 10]. TDIs represent a significant public health issue in this context, not only because of their high frequency and treatment burden, but also due to their long-term consequences for oral health [11-13]. Falls are a leading cause of TDIs in children [14, 15], and children with delayed psychomotor development may be at a higher risk of falling during play and school activities. Thus, it is important to explore the connection between psychomotor developmental delays and TDIs [1]. In this issue, Primo-Miranda et al. [16] investigated the association between psychomotor development and TDIs in pre-school children in Brazil. This study highlighted the relationship between developmental and health factors and the occurrence of TDIs in preschool children, while also emphasizing the potential role of dental professionals in early detection and interdisciplinary collaboration for prevention. E-scooters have become an increasingly popular mode of urban transportation, promoted as a convenient and environmentally friendly option. However, their rapid integration into urban traffic has been accompanied by growing concerns about safety, particularly with respect to accidents, including facial and TDIs [17-19]. Compared to bicycles, which are well established in traffic systems and widely studied in the DT literature, e-scooters present different risks due to their design, lower stability, frequent use on sidewalks, and the limited use of helmets [18, 20]. Although research on bicycle-related trauma is extensive, investigations focusing on e-scooter accidents remain relatively recent, and direct comparisons between the two are scarce. In this issue, Dudde et al. [21] analyzed and compared facial trauma patterns between e-scooter and bicycle accidents in a metropolitan setting. This comparative analysis emphasized the need for improved safety measures, evidence-based prevention strategies, and integration of these injury patterns into trauma training and emergency protocols. It also highlighted the value of continued research to inform guidelines and enhance preparedness for managing urban mobility-related accidents. Interpersonal violence, occurring in family or community settings, represents a major public health concern, contributing to substantial physical and psychological harm [22]. The head and neck region is particularly vulnerable, with facial fractures, soft tissue injuries, and TDIs commonly observed among victims [22, 23]. Despite the frequency of such injuries, research on the patterns and types of TDIs resulting from interpersonal violence remains limited, and few studies have examined associations between violence type and dental trauma [22-25]. Additionally, no study has applied person-oriented statistical approaches, such as latent class analysis, to identify subgroups with similar TDI patterns in this context. Given the critical role of oral health professionals in identifying and managing these cases, understanding the prevalence and patterns of TDIs associated with interpersonal violence is essential [26]. Therefore, in this issue, Jalil et al. [27] described the occurrence of TDIs linked to interpersonal violence in a referral center in Brazil, identified and characterized latent classes of TDIs, and explored the relationship between types of interpersonal violence and both individual and grouped trauma patterns. This study underscores the importance of dental professionals understanding the patterns of TDIs related to interpersonal violence, adopting a patient-centered approach, while also emphasizing the critical role of dentists in recognizing and reporting cases of violence. Sport-related injuries are a common cause of TDIs among young athletes [28]. In Kuwait, a considerable proportion of adolescent players report dental trauma during training and competition, pointing to a need for improved prevention and emergency management in sports contexts [29]. The prognosis of injured teeth depends heavily on immediate and appropriate care [30], yet many of those most likely to be first on the scene, such as coaches or athletes, lack adequate training to manage TDIs [31-33]. Evidence shows that in the absence of medical staff, coaches in amateur and youth soccer often assume responsibility for injury response, but their knowledge of TDI management and preventive practices, such as the use of custom-made mouthguards, remains limited [34]. Despite the high prevalence of TDIs among the soccer players in Kuwait, the country does not have standardized first aid programs tailored to sport-related dental injuries, nor are mouthguards mandatory. In this issue, Behbehani et al. [35] assessed the knowledge and attitudes of youth soccer team coaches regarding the management and prevention of dental injuries. This cross-sectional study underscored the importance of assessing youth soccer coaches' preparedness in handling TDIs and promoting preventive practices such as mouthguard use, and the need for targeted educational initiatives to strengthen emergency response and injury prevention in sports settings. TDIs are frequent during childhood and adolescence and often compromise both teeth and surrounding tissues [15, 36]. While early and appropriate emergency care is essential to ensure favorable outcomes [4, 30, 33], parents, who are commonly the first responders, frequently lack the knowledge needed to manage these injuries effectively [33, 37, 38]. Traditional awareness efforts, such as brochures and lectures, have shown limited impact, prompting interest in digital health tools that provide immediate, evidence-based guidance [39, 40]. The ToothSOS mobile application, developed by the International Association of Dental Traumatology [41-43], offers step-by-step instructions for managing TDIs and is considered more reliable and user-friendly than earlier educational resources. In this issue, Barutcigil and Oz [44] evaluated the effectiveness of ToothSOS in improving parents' awareness and preparedness regarding emergency management of TDIs. This study shows the role of mobile applications like ToothSOS as promising tools for strengthening preparedness in managing TDIs. Effective care of traumatic dental injuries often depends on immediate first aid measures, particularly in cases of avulsion where quick action is critical for prognosis [45-47]. In cases of TDIs in school- and pre-school-aged children, teachers are frequently the first to witness such accidents in school settings [5, 48-50]; however, there is a lack of awareness among school teachers regarding immediate care. This lack of sufficient knowledge and confidence to act properly can compromise treatment outcomes. To address this challenge, dos Santos et al. [51] evaluated the attitudes of elementary school teachers in Southeast Brazil regarding various TDI scenarios using structured questionnaires. The work emphasized the need for structured educational programs to improve teachers' knowledge and preparedness for managing cases of tooth avulsion in school settings. Pediatric maxillofacial fractures present unique challenges due to anatomical, developmental, and clinical considerations [52, 53]. Accurate diagnosis and management are complicated by the presence of developing teeth, limited cooperation, and the need to protect facial growth, while dental injuries often accompany such fractures and are frequently underreported [54, 55]. Machine learning offers a promising approach to analyzing complex datasets in health science, enabling the identification of patterns and risk factors that traditional statistical methods may overlook [56, 57]. In this issue, Antony et al. [58] applied machine learning algorithms, including Bayesian Networks, CHAID, and artificial neural networks, to improve the understanding of pediatric maxillofacial trauma and associated dental injuries, aiming to enhance predictive capabilities, guide clinical decision-making, and inform preventive strategies. The authors presented the value of machine learning for understanding complex trauma patterns and the importance of targeted preventive policies and educational programs to support effective management of pediatric maxillofacial injuries. Although TDIs often require immediate management to optimize outcomes, limited public knowledge of first-aid protocols continues to hinder effective response [59-61]. The rise of digital health technologies, mobile applications, and AI-based chatbots has emerged as accessible tools for providing timely, evidence-based guidance in emergency situations [39, 62-64]. The ToothSOS application offers structured instructions for the management of TDIs according to international guidelines [43, 65]. Recently, large multimodal models such as ChatGPT-4o and Gemini Advanced have introduced advanced capabilities by processing both text and image inputs, allowing information to be delivered in a conversational and context-sensitive format, which can improve users' knowledge about specific questions about healthcare [64]. In this issue, Çege et al. [66] examined the ability of these AI-based chatbots to provide emergency recommendations for dental trauma from intraoral photographs, evaluating their responses against the standardized guidance available in the ToothSOS application. This study highlighted the evolving role of AI in supporting rapid, accessible, and guideline-oriented trauma management. Sports mouthguards are removable protective devices widely recommended to prevent dental trauma during athletic activities [67, 68]. They can be categorized into stock, mouth-formed, and custom-made types, with the latter considered the most effective due to its superior fit, comfort, and protective capacity [33, 67, 69]. For a sports mouthguard to function properly, it must distribute impact forces evenly and absorb energy efficiently. Ethylene-vinyl acetate (EVA), a thermoplastic polymer known for its elasticity and shock-absorbing properties, has become the most commonly used material in sport mouthguard fabrication through thermoforming techniques [69-71]. Athletes who regularly wear mouthguards often consume isotonic beverages during training and competitions to maintain hydration and energy balance. However, the chemical composition of these drinks, including carbohydrates, electrolytes, acids, and dyes, has been linked to potential alterations in both dental structures and restorative materials [72, 73]. In this issue, da Costa et al. [74] evaluated in vitro the influence of different isotonic sports drinks on the thickness and color stability of EVA used in custom-made mouthguards. This experimental study emphasized the importance of evaluating beverage-related changes in mouthguard materials to ensure their protective performance over time. Simulation-based training has been proposed as a valuable educational strategy for improving dental students' preparedness in managing TDIs [3, 75, 76]. Conventional teaching relies heavily on theoretical instruction, while the unpredictable and emergency-driven nature of TDIs limits opportunities for students to gain practical experience, often leaving graduates underconfident in diagnosis and treatment [3, 75]. Artificial models, particularly 3D-printed systems, offer a promising alternative to biological specimens, allowing reproducible simulation of various trauma scenarios and overcoming the limitations of availability and ethical concerns [77, 78]. In this issue, Koç et al. [79] analyzed the effectiveness of 3D-printed models designed to replicate common dental trauma types in enhancing students' knowledge, confidence, and stress management. This work underscores the potential of simulation-based approaches to strengthen dental education in trauma care. Global Evidence Mapping was first introduced in 2007 as a method to examine the breadth of research within a field and to organize available evidence across its domains and subdomains [80]. In dental traumatology, an evidence mapping published in 2020 assessed the quality of systematic reviews, providing an overview of the highest level of available evidence at that time [81]. While dental traumatology research often relies on case series and cohort studies due to the uniqueness of trauma scenarios, ethical challenges, and methodological limitations, this reliance contributes to the predominance of low-to-moderate quality evidence [82-84]. Given the rapid increase in published systematic reviews, an updated evidence mapping was warranted to evaluate recent trends, assess methodological quality, and determine how the evidence base in dental traumatology has evolved. In this issue, Tewari et al. [85] assessed the distribution of systematic reviews related to dental traumatology published during 54 months in various domains and subdomains and evaluated their quality. This study underscores the progress made in evidence-based dental traumatology in recent years. Autotransplantation of teeth, which involves repositioning a tooth within the same individual, has emerged as a reliable biological alternative for tooth replacement [86-88]. Unlike the prosthetic or implant-based solutions, which may be unsuitable in growing patients, autotransplantation preserves periodontal ligament vitality and supports continued adaptation in the region, where skeletal changes persist throughout life. This biological advantage makes it a favorable long-term option, minimizing the risk of interrupted tooth eruption and improving both esthetic and functional outcomes [88, 89]. The success of the procedure depends largely on maintaining periodontal ligament cell viability during extraoral handling [90]. In this issue, Barendregt et al. [91] reported a case describing a novel technique in which a mandibular incisor was temporarily stored beneath the periosteum of the maxillary buccal bone before its definitive transplantation into the recipient site. This innovative approach underscores the importance of biologically informed handling protocols in improving predictability and long-term outcomes of autotransplantation.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».