METHODOLOGY: A cohort (n = 206) of fourth-year undergraduate dental students were recruited from four different Dental Schools and divided randomly into two groups (Group A and B). The participants assessed six test endodontic cases using anonymized versions of the American Association of Endodontists (AAE) case difficulty assessment form (AAE Endodontic Case Difficulty Assessment Form and Guidelines, 2006) and EndoApp, a web-based CDA tool. Group A (n = 107) used the AAE form for assessment of the first three cases, followed by EndoApp for the latter. Group B (n = 99) used EndoApp for the initial three cases and switched to the AAE form for the remainder. Data were collected online and analysed to assess participants' knowledge reinforcement and agreement with the recommendation generated. Statistical analysis was performed using the two-way mixed model anova, Cohen's Kappa (κ) and independent t-tests, with the levels of significance set at P
METHODS: A random sample of digital panoramic radiographs from the database of a dental hospital was evaluated. Two calibrated examiners (κ ≥ 0.89) assessed the technical quality of the root fillings and the radiographic periapical health status by using the periapical index. Descriptive statistical analysis was carried out, followed by multilevel modeling by using tooth-level and patient-level predictors. Model fit information was obtained, and the findings of the best-fit model were reported.
RESULTS: A total of 6409 teeth were included in the analysis. The predicted probability of a tooth having AP was 0.42%. There was a statistically significant variability between patients (P