A simple score for evaluation of the complexity of third-molar extractions

Hyaluronic Acid Treatment of Post-Extraction Tooth Socket Healing in Subjects with Diabetes Mellitus Type 2: A Randomized Split-Mouth Controlled Study

The present study aimed to investigate the effect of HA in improving post-extraction socket healing in subjects with diabetes mellitus (DM) type 2. DM patients requiring bilateral extraction of the homologous teeth were visited at the C.I.R. Dental School, University of Turin. After the extractions, one site was randomly assigned to the test (T) group (postoperative application of HA), while the other site was assigned to the control group (C, no treatment). Patients were then followed after 3, 7, 14, and 21 days. Primary outcomes were the healing index and socket closure. The Mann-Whitney test or the Student's t-test was used for nonparametric or parametric distributed variables. The chi-square test was used if the estimated data in any given cell were >5, otherwise the Fisher test was adopted. A p < 0.05 was considered statistically significant. In total, 36 patients (n = 36) were enrolled in this study for a total of 72 extractions (n = 72). Sockets treated with HA showed significantly (p < 0.05) better healing index values at day 7 (p = 0.01) and at day 14 (p = 0.02) and significantly (p < 0.05) better socket closure values at day 3 (p = 0.04), day 7 (p = 0.001) and day 14 (p = 0.001) compared to the C group. Based on the clinical results, HA seems to be promising in improving the timing and the quality of post-extractive wound healing in DM patients. Further clinical research, as well as histological investigations, are required to confirm the results.

A Validated Model to Predict Postoperative Symptom Severity After Mandibular Third Molar Removal

PURPOSE

The individualized prediction of postoperative symptom severity is essential for selecting interventions after mandibular third molar (M3M) removal. The purpose of the present study was to develop and validate a nomogram for personal prediction of postoperative symptom severity.

MATERIALS AND METHODS

A prospective cohort study was performed in the Stomatology Hospital of Tianjin Medical University. The sample was divided into training and testing data sets by time. The demographic, anatomic, radiographic, and operative variables were recorded. The self-reported postoperative symptom severity was recorded and defined as the primary outcome variable. Stepwise forward algorithms were applied to informative predictors based on Akaike's information criterion. Multivariable logistic regression analysis was used to develop the nomogram. An independent testing data set was used to validate the nomogram. Receiver operating characteristic curves and the Hosmer-Lemeshow test were used to assess model performance. P < .05 was considered to indicate statistical significance.

RESULTS

The sample included 321 subjects who had undergone M3M removal. An independent validation data set included 103 consecutive patients. The median operation time was 15.0 minutes (interquartile range, 8.3 to 21.6 minutes) in the training data set (n = 218). Patients with serious postoperative symptoms accounted for 48.6 and 47.6% of the training and testing data sets, respectively. Gender, age, smoking status, operation time, Pell-Gregory ramus classification, and preoperative symptoms were identified as predictors and assembled into the nomogram. The area under curve demonstrated adequate discrimination in the validation data set (0.69; 95% confidence interval, 0.59 to 0.80). The nomogram was well calibrated, with a Hosmer-Lemeshow χ² statistic of 6.33 (P = .78) in the testing data set. The confusion matrix was also summarized, and the accuracy was 63.3 and 65.1% in the training and testing data set, respectively.

CONCLUSIONS

The present study has proposed an effective nomogram with potential application in facilitating the individualized prediction of postoperative symptom severity after M3M removal.