Data analysis
REGRESSION
A sample size of 30 patients was targeted for detecting a difference of 35% in CRC (number needed to treat = 3) at 6 months between the test and control group, using a multilevel logistic regression analysis adjusted for clustering (with an expected mean cluster size of 2.5 teeth/patient), with an 80% power and a critical level of significance of 0.05.Descriptive characteristics of the study participants and teeth were expressed for continuous variables as mean (standard deviation—SD), while for categorical variables as number (percentage—%). Results were expressed as differences in means (MD) or odds ratios (OR), with 95% confidence intervals (CI). Differences between groups for tooth-level variables were tested through multilevel logistic (binary) or linear (continuous) regression analyses adjusted for clustering. Patient-level variables were compared between groups applying the χ2 test for binary variables and unpaired Student’s t-test for continuous ones. All comparisons between groups were carried out using 2-sided hypothesis and an alpha < 0.05 level of significance.Data analysis was performed by a blinded statistician using STATA version 17.1 software (StataCorp LLC, Texas, USA) and applying the intention-to-treat principle.