Construction of a Risk Prediction Model for Fever After Painless Bronchoscopy

BACKGROUND The aim of this study was to construct a risk prediction model for fever after painless bronchoscopy. MATERIAL AND METHODS A total of 188 patients were included, and a self-designed data collection form was used. By collecting relevant clinical data of patients before, during, and after the painless bronchoscopy, the influencing factors were analyzed through univariate analysis, and multiple logistic regression analysis was performed to construct the prediction equation, which was tested by ROC curve analysis. RESULTS Of the 188 patients undergoing painless bronchoscopy, 49 had postoperative fever, and the incidence rate was 26.0%. The prediction probability model was: P=eˣ/1+eˣ, where e is the natural logarithm, X=-4.337+0.020×(CRP)+1.014 (whether the examination time was greater than 30 minutes)+1.912×(whether remifentanil was used during anesthesia)+1.514×(whether nausea or vomiting occurred during surgery or during recovery). The prediction sensitivity and specificity were 78.26% 76.72%, respectively. CONCLUSIONS Use of this risk prediction model of fever after painless bronchoscopy can improve the recognition of people at high risk of postoperative fever, and it has good ability to guide clinical nursing observation and early screening of fever after painless bronchoscopy.