Development and validation of machine learning based prediction model for postoperative pain risk after extraction of impacted mandibular third molars.

ABSTRACT:

Background

Predicting postoperative pain risk in patients with impacted mandibular third molar extractions is helpful in guiding clinical decision-making, enhancing perioperative pain management, and improving the patients' medical experience. This study aims to develop a prediction model based on machine learning algorithms to identify patients at high risk of postoperative pain after tooth extraction.

Methods

We conducted a prospective cohort study. Outpatients with impacted mandibular third molars were recruited and the outcome was defined as the NRS (Numerical Rating Scale) score of peak postoperative pain within 24 h after the operation ≥7, which is considered a high risk of postoperative pain. We compared the models built using nine different machine learning algorithm

SUBMITTER: Yu D 

PROVIDER: S-EPMC10703859 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature