Pediatric dentistry最新文献

Purpose: The purpose of this study was to examine trends in primary and early permanent dentition treatment patterns and the relationships between them. Methods: A secondary data analysis was performed using Medicaid claims from 2011 to 2022 for North Carolina children ages zero to 12 years. Trends and expenditures of two primary dental treatment patterns were analyzed: early childhood caries (ECC), defined as treatment to primary maxillary incisors and/or primary first molars in zero- to five-year-olds; and late childhood caries (LCC), which comprised treatment to the proximal surfaces of primary molars in six to 12-year-olds. Trends in four early permanent dentition restorative treatment pat- terns were analyzed: (1) mesial surfaces of the permanent first molars; (2) pits and fissures of the permanent first molars; (3) maxillary anterior teeth; and (4) maxillary anterior and permanent first molars. The likelihood of children who had the listed restorative treatment to their early permanent dentition also having ECC and/or LCC treatment was investigated. Data analysis relied on descriptive statistics. Results: The proportion of children with LCC treatment and the yearly treatment expenditure were consistently two times more than that associated with ECC treatment throughout the 12-year period. Children who had early permanent dentition restorative treatment were, on average, two times as likely to have had LCC treament than ECC treatment. Conclusion: Future prevention and education strategies should target late childhood caries.

Purpose: To compare the compressive strength of traditional open-faced stainless-steel crown (OFSSC) to novel Preformed OFSSC (POFSSC) filled with different restorative materials. Methods: Seventy-five uniform 3D-printed models were divided into five groups (n=15): Group one (G1) traditional OFSSC; Group two (G2) POFSSC with restorative composite; Group three (G3) POFSSC with bulk-fill composite; Group four (G4) POFSSC with flowable resin restorative; and Group 5 (G5) POFSSC with resin-reinforced glass-ionomer. Samples were subjected to 1,000 cycles of thermocycling, at five degrees to 55 degrees Celsius, followed by a tactile exam. Instron was used for compressive strength test, with the maximum force at fracture initiation recorded in Newtons (N). Failure of the facial-surface was categorized as <50% facial-surface chipped, ≥50% to <100% facial-surface chipped, or the entire facial-surface came-off. One-way analysis of variance and the Kruskal-Wallis test was used (P<0.05). Results: All samples were intact during the tactile exam following thermocycling. The compressive strengths are ranked as: G2???784.66±86.29 N; G3???730.46±159.52 N; G4???726.33±150.47 N; G1???650.59±116.05 N; G5???556.60±137.65 N. The compressive strength of G2 was significantly higher than G1 (P=0.007). G5 showed significantly lower compressive strength than G2 (P=0.0), G3 (P=0.001), and G4 (P=0.001). The entire facial-surface cameoff as follows: G2???6.67%; G4???13.33%; G5???26.67%; G3???53.33%; G1???66.67%. Conclusion: Compressive strength of G2 was significantly higher than control; and G2 had the lowest percentage of the entire facial-surface coming-off.

Purpose: To develop a no-code artificial intelligence (AI) model capable of identifying primary proximal surface caries using bitewings among pediatric patients. Methods: One hundred bitewing radiographs acquired at pediatric dental clinics were anonymized and reviewed. The inclusion criteria encompassed bitewing radiographs of adequate diagnostic quality of primary and mixed-dentition stages. The exclusion criteria included artifacts related to sensors' quality, positioning errors, and motion. Sixty-six bitewing radiographs were selected. Images were uploaded to LandingLens™, a no-code AI platform. A calibrated consensus panel determined the presence or absence of proximal caries lesions on all surfaces (using ground truth labeling). The radiographs were divided into training (70 percent), development (20 percent), and testing (10 percent) subsets. Data augmentation techniques were applied to artificially increase the sample size. Sensitivity, specificity, accuracy, precision, F1-score, and receiver operating characteristic area under the curve (ROC-AUC) were calculated. Results: Among the 755 proximal surfaces identified from 66 bitewings, 178 were annotated as caries lesions by experts. The model achieved the following metrics: 88.8 percent sensitivity, 98.8 percent specificity, 95.8 percent precision, 96.4 percent accuracy, and an F1-score of 92 percent by surface. The ROC-AUC was 0.965. Conclusions: The developed model demonstrated strong performance despite the limited dataset size. This may be attributed to the exclusion of unsuitable radiographs and the use of expert-labeled ground truth annotations. The utilization of no-code artificial intelligence may improve outcomes for computer vision tasks.

Purpose: To evaluate the accuracy and consistency of chatbots in answering questions related to special needs dentistry. Methods: Nine publicly accessible chatbots, including Google Bard, ChatGPT 4, ChatGPT 3.5, Llama, Sage, Claude 2 100k, Claude-instant, Claude-instant-100k, and Google PaLM, were evaluated on their ability to answer a set of 25 true/false questions related to special needs dentistry and 15 questions for syndrome diagnosis based on their oral manifestations. Each chatbot was asked independently three times at a three-week interval from November to December 2023, and the responses were evaluated by dental professionals. The Wilcoxon exact test was used to compare accuracy rates among the chatbots while Cronbach's alpha was utilized to measure the consistency of the chatbots' responses. Results: Chatbots had an average accuracy of 55??4 percent in answering all questions, 37±6 percent in diagnosis, and 67±8 percent in answering true/false questions. No significant difference (P>0.05) in the accuracy proportion was detected between any pairwise chatbot comparison. All chatbots demonstrated acceptable reliability (Cronbach's alpha greater than 0.7), with Claude instant having the highest reliability of 0.93. Conclusion: Chatbots exhibit acceptable consistency in responding to questions related to special needs dentistry and better accuracy in responding to true/false questions than diagnostic questions. The clinical relevance is not fully established at this stage, but it may become a useful tool in the future.

Purpose: To examine the association between parental divorce or separation (PDS) and oral health outcomes in children and adolescents in the United States (U.S.), and learn whether the association was mediated by a lack of needed dental care in the past 12 months. Methods: Data obtained from a sample of individuals who participated in the 2020 to 2021 National Survey of Children's Health (NSCH), representing 65,790,496 U.S. children and adolescents, were analyzed. A child's exposure to PDS was the independent variable. The outcome of interest was pediatric oral health, measured through parental responses to survey questionnaires indicating whether their child had dental caries, toothaches, and/or bleeding gums within the past 12 months. Analyses included descriptive statistics, bivariate analyses, logistic regression, and casual mediation analysis. Results: After controlling for demographic factors and insurance coverage, children who experienced PDS, had 30 percent higher odds of suffering from oral health problems versus those who did not (odds ratio equals 1.29; 95 percent confidence interval equals 1.16 to 1.45). The association appeared to be partially mediated by failure to receive needed dental care. Conclusions: Parental divorce or separation is associated with the oral health of children and adolescents in the United States. Findings from this population-based study highlight the potential impact of PDS on children's oral health.

Purpose: To compare the efficacy of laser phototherapy, Buzzy®, and lignocaine gel in minimizing pain during intraoral injections. Methods: In this randomized controlled trial, the efficacy of standard lignocaine gel (Group A) was compared with Buzzy® (Group B) and laser phototherapy (Group C) as pre-anesthetic agents in 15 children aged eight to 12 years undergoing intraoral local anesthesia (LA). Pain perception during needle insertion was assessed objectively using the Face, Legs, Activity, Cry, Consolability (FLACC) scale and subjectively using the Visual Analogue Scale (VAS). Statistical analysis included chi-square and analysis of variance tests (P<0.05). Results: Objective assessment of pain perception using FLACC scores demonstrated that Buzzy® resulted in the highest comfort levels; 60 percent of the subjects treated with Buzzy®, 40 percent treated with laser phototherapy, and 6.7 percent treated with lignocaine topical anesthetic were judged to be relaxed and comfortable or exhibiting mild discomfort, respectively. Subjective pain assessment (self-reported using the VAS) was significantly lower in Buzzy® (0.67±0.82 standard deviation) followed by laser phototherapy (1.00±1.13) and Lignocaine gel group (2.13±1.51). Conclusions: The Buzzy® and laser phototherapy effectively reduced intraoral injection pain compared to the standard control, lignocaine gel. However, Buzzy® showed better efficacy.