Abstract: Objective To analyze the predictive value of dynamic changes in key factors of the toll-like receptor (TLR)/nuclear factor-κB (NF-κB) signaling axis during the perioperative period for bone infection inpatients with open fractures. Methods A total of 55 patients with open fractures who developed bone infections during the perioperative period were selected as infection group, and 110 patients with open fractures who did not develop infections during the same period were selected as non-infection group. Clinical data, pre-and post-operative serum levels of routine inflammatory markers C-reactive protein (CRP), interleukin-6 (IL-6) and procalcitonin (PCT) and key factors of the TLR/NF-κB signaling axis (TLR4, NF-κB) were compared between the two groups. Logistic multivariate regression analysis was used to identify risk factors for bone infection during the perioperative period in patients with open fractures. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of the absolute change (the absolute value of the changes was expressed as △) in the levels of key factors of the TLR/NF-κB signaling axis before and after surgery for bone infection, and these results were compared with the predictive value of routine inflammatory markers. A nomogram prediction model was developed based on the identified risk factors, and its value in predicting perioperative bone infection was analyzed. Results The time from fracture to surgery and the duration of surgery were significantly longer, and the proportion of Gustilo type Ⅲ fractures and wounds with a depth ≥2 cm was significantly higher in the infection group compared to the non-infection group (P<0.05). At 24 h after surgery, serum CRP, IL-6, PCT, TLR4 and NF-κB levels in two groups were significantly higher than before surgery, and serum CRP, IL-6, PCT, TLR4 as well as NF-κB levels and their changes in bone infection group were significantly higher than those in the non-infection group (P<0.05). Logistic regression analysis indicated that time from fracture to surgery, surgical duration, Gustilo type Ⅲ and wound depth ≥2 cm, and △CRP, △IL-6, △PCT, △TLR4 as well as △NF-κB were risk factors for perioperative bone infection in patients with open fractures (P<0.05). ROC results showed that the area under the curve (AUC) of △CRP, △IL-6, △PCT, △TLR4 and △NF-κB for predicting bone infection were 0.786, 0.833, 0.772, 0.826 and 0.736, respectively. ROC curve showed that the AUC of the nomogram prediction model for perioperative bone infection was 0.893(95%CI, 0.834 to 0.952), indicating high predictive efficacy. The decision curve showed that the nomogram prediction model had a significant positive net benefit, and it had good clinical utility in predicting the risk of bone infection. Conclusion The dynamic changes of key factors of TLR/NF-κB signal axis in perioperative period of patients with open fracture have certain predictive value for postoperative bone infection. The nomogram prediction model based on the above influencing factors has good predictive value and positive clinical net benefit.