Abstract

This prospective observational study sought to investigate the incidence of intraoperative pain (IOP) among emergency endodontic patients and to construct an IOP prediction model that includes preoperative pain level (PPL). All patients who underwent emergency endodontic treatment at Gazi University, Ankara, Turkey, during the spring term of 2016 were considered for inclusion in the study. Demographic and clinical variables and PPL were recorded. Local anesthesia was provided to all patients before beginning routine endodontic treatment. IOP was defined as the condition of requiring supplementary anesthesia before the working length was established and exhibiting persistent moderate or severe pain despite supplementary anesthesia. Data from 85% and 15% of 435 patients (178 men, 257 women; mean age: 35 years) were used to develop predictive models by multiple logistic regression analysis and to test external validity of the models, respectively. Two multiple logistic regression models achieved good model fits. Model 1 included age, pulpal diagnosis, and arc (p < 0.05). In addition to these variables, Model 2 included periapical diagnosis and PPL (p < 0.15). Models 1 and 2 showed accuracies of 0.76 and 0.75, sensitivities of 0.74 and 0.77, and specificities of 0.76 and 0.74, respectively for the modeling data (internal validity), and accuracies of 0.82 and 0.80, sensitivities of 0.83 and 0.67, and specificities of 0.81 and 0.81, respectively for the control data (external validity). The IOP incidence was 10.3%. IOP in patients undergoing emergency endodontic treatment can be successfully predicted by using models that account for demographic and clinical variables, including PPL.

Highlights

  • The following demographic and clinical variables were recorded: age, sex, health status, whether pain was present within the previous 24 hours, whether the patient had taken analgesic for toothache within the previous 24 hours, and pulpal and periapical diagnoses

  • Construction of models 1 and 2 We performed multiple regression analyses of variables that were significantly associated with pain (VAS code 1) in the univariate analysis

  • A patient was predicted to have intraoperative pain (IOP) if their probability of pain was higher than a threshold value of 0.125, which was chosen after testing different threshold values around the IOP incidence of 10%

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Summary

Introduction

The aims of this study were to assess the incidence of IOP among emergency endodontic patients receiving treatment at a dental faculty clinic and to construct a model from demographic and clinical factors, including PPL, for predicting the probability of IOP. The following demographic and clinical variables were recorded: age (years), sex (male/female), health status (good/not good), whether pain was present within the previous 24 hours (yes/no), whether the patient had taken analgesic for toothache within the previous 24 hours (yes/no/yes, but for other reasons), and pulpal and periapical diagnoses.

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