Explore the vast range of titles available.

Background: The growing integration of digital technologies in orthodontics is shifting the orthodontic diagnosis and recordkeeping paradigm, replacing conventional plaster models with intraoral scanning and 3D photography. This study investigated the impact of orthodontic plaster models on orthodontic diagnosis and treatment planning decisions by orthodontists. Methods: Thirty-three orthodontists assessed six patients’ records with different malocclusion cases. Each case was assessed twice by each orthodontist evaluating a case: the first evaluation with digital records without diagnostic casts and the second evaluation with the added diagnostic orthodontic plaster model. Diagnostic and treatment plan decisions for each malocclusion case were compared with and without the aid of the diagnostic orthodontic plaster models to assess the plaster model’s impact on the treatment plan’s soundness. Results: Statistically insignificant differences were found for the diagnoses and treatment plans with or without the aid of orthodontic plaster models. Intraclass correlation coefficients revealed agreement among orthodontists for both evaluated situations (0.685; p < 0.0001). Plaster models were found to significantly influence orthodontists’ decisions about the need for surgical intervention (p = 0.026), but they did not significantly impact the overall malocclusion diagnostic classification nor the decision regarding the extent of treatment, whether comprehensive or limited (p = 0.146) and extraction versus non-extraction approaches (p = 0.266). Conclusions: These findings support the idea that digital record alternatives may be viable for orthodontic recordkeeping purposes. Within the limitations of this study, it can be concluded that the presence or absence of orthodontic plaster models does not significantly impact the orthodontic diagnosis or treatment planning process.

OBJECTIVE: Whitening toothpastes are widely used. Hence, it is important to understand their effect on the surface properties of restorative materials. To evaluate the effect of three over-the-counter whitening toothpastes and toothbrushing simulation on microhardness of three restorative materials. Study design: Forty cylindrical (10×2mm) specimens were prepared from each restorative material and randomly assigned into four groups/10 each according to the whitening toothpastes used and distilled water (control). All specimens were measured for microhardness (Baseline–T1). The specimens were brushed with a soft brush using an in vitro tooth-brushing simulator with the assigned whitening toothpaste using the same setting for brushing cycles/load for all groups. Specimens were then measured for microhardness (T2) similar to baseline. Results: The highest (mean±SD) microhardness after application of the whitening toothpastes and brushing was recorded for Intense White and Filtek Z250 XT (127.6±1.8), followed by Optic White and Fuji ll LC (73.9±0.9) and Optic White and Photac Fill (72.7±1.3). There was statistically significant difference for microhardness between pre- and post-application of the whitening toothpastes and brushing for all tested restorative materials (P=0.0001). The microhardness of Filtek Z250XT with 3D White post-application of the whitening toothpastes and brushing was lowest compared to other toothpastes and control (P=0.0001). Conclusion: Microhardness increased after application of the whitening toothpastes and toothbrushing simulation for all combination of tested restorative materials and whitening toothpastes. The microhardness of FIiltek Z250XT with 3D White post-application of the whitening toothpastes and brushing was lowest compared to other toothpastes and control.