Endodontic Treatment and Postoperative Pain

With the development of endodontic treatment, the incidence of pain and swelling during RCT is only approximately 10%. However, patients frequently report postoperative pain.

Prospective clinical studies have revealed that approximately 21%, 15%, and 7% of patients have mild, moderate, and severe pain, respectively, after RCT. The rapid and accurate prediction of postoperative pain is necessary in root canal therapy, which can be conducive to the formulation of follow-up diagnosis and treatment plans, and the adoption of preventive measures. To date, practitioners often assess pain after RCT on the basis of personal clinical experience with no universally accepted objective methods.

According to recent research where researchers used an Artificial Neural Network (ANN) model to estimate the postoperative pain of RCT, an accuracy as high as 95.60% was highlighted, which can prove to be of significant clinical value in assessing dental pain post RCT by dentists. The novel research has been put forth in Scientific Reports, a Nature publication.

Artificial Neural Network (ANN) is the most recent and rapid development in the field of nature-inspired algorithms. ANN is a system based on the human brain structure and function imitation. It may play an important role in providing technical possibilities for predicting pain, as well as understanding the individual physiological mechanisms of pain and treatment.

With the aim to evaluate the accuracy of the back propagation (BP) artificial neural network model for predicting postoperative pain following root canal treatment (RCT), the team tested data from 300 patients who underwent RCT. The inclusion criteria were as follows:

• The affected teeth were receiving their first RCT.
• No contraindications for RCT were found.
• No psychoactive or analgesic drugs had been orally taken or infused for the past 1 month.

Observing the high accuracy rates, the team noted that "Therefore, ANN based on BP algorithm exhibits high prediction accuracy and may benefit dentists and patients in future root canal therapy. After further optimizing the measurement method, the precision of the ANN model will continue to improve."

"The application of ANN to anticipate postoperative pain following RCT has never been reported before. In the present study, we utilized the ANN model of error BP algorithm to predict the occurrence and degree of spontaneous postoperative pain after RCT. We wish that in RCT treatment, this model could effectively improve patients' trust in dentists and help dentists make suitable decisions," the team added.

For the full article, follow the link: Gao, X., Xin, X., Li, Z. et al. Predicting postoperative pain following root canal treatment by using artificial neural network evaluation. Sci Rep 11, 17243 (2021).

Source: Scientific Reports