Analysis in risk factors of non-infectious fever within 7 days after total knee arthroplasty and establishment of a nomogram model

Objective To explore the risk factors of non-infectious fever (NIF) within 7 days after total knee arthroplasty (TKA), and to construct and verify the nomogram predictive model, so as to provide a concise and quantitative tool for clinical early diagnosis of NIF.

Methods A total of 201 patients with knee osteoarthritis underwent unilateral TKA were enrolled as study objects by retrospective cohort study. According to whether NIF occurred within 7 days after operation, the patients were divided into NIF group (n=57) and non-NIF group (n=144). The clinical data between the two groups were compared, and the risk factors of NIF were screened by LASSO regression and multivariate Logistic regression. The nomogram model was established and verified internally.

Results Compared with the non-NIF group, the intraoperative blood loss, postoperative drainage volume, the number of patients with blood transfusion, operation time, antibiotic use time and hospital stay in the NIF group were significantly more or longer(P < 0.05). LASSO regression screened four variables with non-zero characteristics, namely intraoperative blood loss, postoperative drainage volume, blood transfusion and operation time. Multivariate Logistic regression analysis showed that intraoperative blood loss (OR=3.652, 95%CI, 2.856 to 3.958, P < 0.001), postoperative drainage volume(OR=2.857, 95%CI, 2.242 to 3.234, P < 0.001), blood transfusion (OR=4.001, 95%CI, 3.562 to 4.659, P < 0.001) and operation time (OR=1.859, 95%CI, 1.326 to 2.525, P < 0.001) were the independent risk factors to NIF within 7 days after TKA. R software was used to establish the nomogram model, total score was 120. The receiver operating curve (ROC) showed that the area under the curve (AUC) of nomogram for predicting NIF was 0.865(95%CI, 0.799 to 0.901), suggesting that the discrimination of the model was good. Calibration correction curve showed a good consistency of the model. Decision curve analysis (DCA) showed that the clinical value of the model was the greatest when the risk threshold of NIF exceeded 8%.

Conclusion There is a high incidence of NIF within 7 days after TKA. Intraoperative blood loss, postoperative drainage volume, blood transfusion and operation time are the independent risk factors for the occurrence of NIF. The nomogram model constructed has good visualization effect, which has high efficiency in predicting the occurrence of NIF.