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Caries prevention is essential for oral hygiene. A fully automated procedure that reduces human labor and human error is needed. This paper presents a fully automated method that segments tooth regions of interest from a panoramic radiograph to diagnose caries. A patient’s panoramic oral radiograph, which can be taken at any dental facility, is first segmented into several segments of individual teeth. Then, informative features are extracted from the teeth using a pre-trained deep learning network such as VGG, Resnet, or Xception. Each extracted feature is learned by a classification model such as random forest, k-nearest neighbor, or support vector machine. The prediction of each classifier model is considered as an individual opinion that contributes to the final diagnosis, which is decided by a majority voting method. The proposed method achieved an accuracy of 93.58%, a sensitivity of 93.91%, and a specificity of 93.33%, making it promising for widespread implementation. The proposed method, which outperforms existing methods in terms of reliability, and can facilitate dental diagnosis and reduce the need for tedious procedures.

Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children. This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations. We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses. The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Frequent consumption of sports and energy drinks among athletes is of concern due to its detrimental impact on oral health. The present study aimed to assess sports and energy drink consumption, oral health status and impacts on daily activities and sports performance among elite athletes from Pakistan. Data regarding socio-demographic characteristics, sports and energy drink consumption, oral health and hygiene practices, self-reported oral health and psychosocial and performance impact was assessed using a self-administered, structured questionnaire followed by clinical oral examination by a single, experienced dentist. A total of 104 athletes, a majority of whom were male (80.8%), participated in the study. Around two third of the participants reported consumption of sports and energy drinks, energy gels or bars at least once a week, the commonest being Sting. Despite good oral hygiene practices, the athletes generally had poor oral health with high prevalence of dental caries (63.5%), gingivitis (46.1%), irreversible periodontitis (26.9%) and erosive tooth wear (21.2%). More than a quarter (28.8%) of the athletes rated their oral health as fair—very poor. Four in five athletes (80%) also experienced at least one oral problem with negative impacts on daily activities (64.4%) and participation training and sports performance (36.5%). Regression analyses revealed a significant association between periodontal disease and impact on both daily activities and sports performance. To our knowledge, this is the first study reporting that high-prevalence sports and energy drink consumption and oral problems among elite athletes from Pakistan has a negative impact on daily activities and sports performance. These findings may have important implications for oral health education programs, and the need to create awareness among the athletes regarding the use of sports and energy drinks, as well as regular oral health screening of athletes to minimize the impact on performance.

Background Dental caries is a significant public health problem and one of the most common chronic conditions affecting children. The potential for the non-dental workforce to improve children’s oral health is well documented. For well over a decade, there have been calls for pediatricians to address children’s oral health, but the incorporation of oral health screening, referral, and oral healthcare in pediatric practice remains underdeveloped. Developing action to strengthen the role of pediatricians’ in children’s oral health requires an understanding of their current knowledge and practice. In this scoping review, we aimed to comprehensively map what is known about the knowledge and practice of pediatricians regarding children’s oral health. Methods Arksey & O’Malley’s five-stage review process was used to comprehensively map studies undertaken on pediatrician’s knowledge and practice regarding children’s oral health. Key search terms were developed and a total of 42 eligible articles are included in the review. Results The studies were conducted in 19 countries. The majority (41/42) were quantitative, with over 90% using self-reported surveys. Only four studies used previously validated survey tools, with most adapting questions from previous studies. Observational designs were used in two studies and one used qualitative methods. Sample size ranged from 15 to 862. Oral health knowledge amongst pediatricians was reported to be mostly poor, with many gaps in key areas including age for first dental visit, dental caries and oral health risk assessments. Studies on the translation of oral health knowledge to practice were limited, with wide variation in rates of assessment. Few studies assessed actual practice. Conclusions This scoping review highlights growing international interest in the role of pediatricians in children’s oral health. Findings demonstrate that pediatricians have limited knowledge and understanding in critical areas, including; initial clinical signs of dental caries, recommended age for first dental visit, etiology of dental caries and recommended use of fluorides. Barriers for pediatricians include inadequate education and training, time constraints in practice and lack of referral pathways. Development of a validated tool to assess knowledge and practice is needed. This review provides a starting point to guide future research and areas for systematic reviews.

The Michigan Caries Prevention Program (MCPP) aimed to reduce the burden of childhood dental disease in the state of Michigan by offering training programs to implement preventive oral health services during well-child medical visits. The purpose of this study was to elicit feedback from the participants of the MCPP and determine which oral health services were implemented post-training, identify implementation barriers and assess provider comfort levels in performing oral screenings and fluoride applications. A descriptive electronic survey was utilized for data collection. A 15-item survey consisting of multiple choice and Likert scale questions was sent to medical providers who had participated in the MCPP from 2015-2017 (n=1115). Descriptive statistics were used to analyze the data. A total of 170 surveys were completed for a 15% response rate. The majority of the participants were physicians (82%, n=134). Nearly all participants reported performing oral screenings and fluoride varnish application post-training (93%, n=153). Participants felt more comfortable applying fluoride varnish than performing oral screenings (80%, n=121 vs 70%, n=112), respectively. Barriers included lack of time, understaffed, staff resistance, feeling that procedures were outside of their scope of practice and disinterest from parents or safety concerns. A majority (70%, n=112) reported that the MCPP training did not help to establish new relationships with community dental providers. Medical providers indicate that the MCPP training was beneficial and that they were willing and able to incorporate oral health screenings and fluoride varnish applications in their practice, but that they face challenges in developing relationships with dental care providers. Opportunities for dental hygienists to work in non-traditional medical-dental integration practice settings may help to increase oral health services offered to patients and improve communication between health care providers.

Objectives: Deep learning methods have achieved impressive diagnostic performance in the field of radiology. The current study aimed to use deep learning methods to detect caries lesions, classify different radiographic extensions on panoramic films, and compare the classification results with those of expert dentists. Methods: A total of 1160 dental panoramic films were evaluated by three expert dentists. All caries lesions in the films were marked with circles, whose combination was defined as the reference dataset. A training and validation dataset (1071) and a test dataset (89) were then established from the reference dataset. A convolutional neural network, called nnU-Net, was applied to detect caries lesions, and DenseNet121 was applied to classify the lesions according to their depths (dentin lesions in the outer, middle, or inner third D1/2/3 of dentin). The performance of the test dataset in the trained nnU-Net and DenseNet121 models was compared with the results of six expert dentists in terms of the intersection over union (IoU), Dice coefficient, accuracy, precision, recall, negative predictive value (NPV), and F1-score metrics. Results: nnU-Net yielded caries lesion segmentation IoU and Dice coefficient values of 0.785 and 0.663, respectively, and the accuracy and recall rate of nnU-Net were 0.986 and 0.821, respectively. The results of the expert dentists and the neural network were shown to be no different in terms of accuracy, precision, recall, NPV, and F1-score. For caries depth classification, DenseNet121 showed an overall accuracy of 0.957 for D1 lesions, 0.832 for D2 lesions, and 0.863 for D3 lesions. The recall results of the D1/D2/D3 lesions were 0.765, 0.652, and 0.918, respectively. All metric values, including accuracy, precision, recall, NPV, and F1-score values, were proven to be no different from those of the experienced dentists. Conclusion: In detecting and classifying caries lesions on dental panoramic radiographs, the performance of deep learning methods was similar to that of expert dentists. The impact of applying these well-trained neural networks for disease diagnosis and treatment decision making should be explored.

This study evaluated dental caries detection ability between the Qraycam and Qraypen on the same dental caries lesions. A total of 178teeth from 61patients were imaged using Qraypen C®(QC) and Qraycam Pro®(QP) devices and evaluated using analysis software (QA2). Occlusal, secondary, and proximal dental caries were evaluated and scored according to International Caries Detection and Assessment System(ICDAS II) and X-ray criteria. Bland–Altman plots were used to compare quantitative light-induced fluorescence(QLF) parameters obtained from the different QLF devices. Sensitivity, specificity, and area under the receiver operating characteristic curve(AUROC) were calculated. The ΔF aver. of the QLF-parameters showed that the mean difference between the two different QLF devices was close to zero and that the ± 5 error value was included in the mean ± 1.96SD range for the detection of dental caries. The accuracies for diagnosing occlusal dental caries were 0.83–0.96 and 0.81–0.82 and the accuracies for diagnosing proximal dental caries were 0.52–0.62 and 0.52–0.71 for the QC and QP devices, respectively. In conclusion, the ΔF aver. obtained from the QP showed diagnostic value mainly for screening of demineralized teeth. For teeth selected through screening, the depth of the lesion must be precisely evaluated using additional QP and radiographic imaging.

Background Most studies assessing the sensitivity and specificity of caries detection methods have been performed in vitro using the histological method as the gold standard showing inconsistent values. The aim of this study was to compare the sensitivity and specificity in detecting occlusal caries using the International Caries Detection and Assessment System (ICDAS II) with the radiographic method (RM), while using the Spectra™ Caries Detection System (SCDS) as the reference test. Methods One hundred sixty children, ages 7–12 years, participated in the study. Five zones in the occlusal surfaces of 859 primary and 632 first permanent molars were examined visually using ICDAS-II, the RM using bitewing radiographs and SCDS. The descriptive statistics of sensitivity and specificity were calculated and compared. Results For all molars combined and for primary molars only, the sensitivity of ICDAS II was higher for detecting total caries ( p  < 0.001), caries in enamel ( p  < 0.001), and caries in dentin ( p  = 0.016), but it was not different for detecting caries in the dentin of permanent first molars ( p  = 0.214), and primary second molars ( p  = 0.761). The specificity of RM was higher for detecting total caries, caries in enamel for all molars combined and for permanent first molars ( p  < 0.001). For caries in dentin, the specificity of ICDAS II was higher for all molars combined and for primary molars only ( p  < 0.001). For total caries in primary molars only, and caries in dentin of permanent first molars only, the specificity was not different ( p  = 0.156 and p  = 0.181 respectively). Conclusions The sensitivity and specificity of ICDAS II and RM changes depending on whether the carious lesion compromises the enamel or dentin, and if the caries detection is performed in the primary molars or permanent first molars.

We sought to determine the effectiveness of an interprofessional health team in improving access to oral health care among American Indian children enrolled in Head Start. Our team provided preventive treatments and case management during 11 visits from 2018 to 2022. Case management reduced the time between referral and dental treatment from a median of 166 days to 58.3 days over four years. An interprofessional team is an effective way to improve access to oral health care among rural American Indian Head Start children. (Am J Public Health. 2023;113(4):368–371. https://doi.org/10.2105/AJPH.2022.307205 )

Schools are the only institution regularly reaching the majority of school-age children and adolescents across the globe. Although at least 102 countries have school health services, there is no rigorous, evidence-based guidance on which school health services are effective and should be implemented in schools. To investigate the effectiveness of school health services for improving the health of school-age children and adolescents, a systematic review of systematic reviews (overview) was conducted. Five databases were searched through June 2018. Systematic reviews of intervention studies that evaluated school-based or school-linked health services delivered by a health provider were included. Review quality was assessed using a modified Ballard and Montgomery four-item checklist. 1654 references were screened and 20 systematic reviews containing 270 primary studies were assessed narratively. Interventions with evidence for effectiveness addressed autism, depression, anxiety, obesity, dental caries, visual acuity, asthma, and sleep. No review evaluated the effectiveness of a multi-component school health services intervention addressing multiple health areas. From the limited amount of information available in existing systematic reviews, the strongest evidence supports implementation of anxiety prevention programs, indicated asthma education, and vision screening with provision of free spectacles. Additional systematic reviews are needed that analyze the effectiveness of comprehensive school health services, and specific services for under-researched health areas relevant for this population.