| Objective To analyze the factors contributing to the development of traumatic arthritis (TA) after surgery for tibial plateau fractures and construct a risk warning model. Methods A total of 286 patients who underwent surgical treatment for tibial plateau fracture in our hospital from March 2016 to May 2021 were selected and divided into TA group (n=73) and non-TA group (n=213) according to whether TA occurred after surgery. The clinical data of the two groups of patients were collected.The factors affecting the occurrence of TA in patients after surgery were analyzed using Lasso-Logistic regression. Based on these factors, a Nomogram risk warning model for the occurrence of TA in patients after surgery was constructed and validated. Results There were significant differences in age, osteoporosis, Schatzker classification, meniscus injury, injury mode, time from injury to surgery, physical labor, postoperative Rasmussen score, interleukin (IL-6), matrix metalloproteinase-13 (MMP-13), tumor necrosis factor- α (TNF- α), bone morphogenetic protein (BMP) -2, and BMP-9 levels between the two groups of patients (P<0.05). Thirteen significant factors from the single factor were included in the Lasso regression, and the best nine predictive variables were selected as osteoporosis, Schatzker classification, injury method, postoperative Rasmussen score, serum MMP-13, BMP-2, BMP-9, IL-6, and TNF-α levels. Osteoporosis, Schatzker classification, injury mode, postoperative Rasmussen score, serum levels of MMP- 13, IL-6, and TNF-α were risk factors for the development of TA in patients after surgery, while serum levels of BMP-2 and BMP-9 were protective factors for the development of TA in patients after surgery (P<0.05). A Nomogram risk warning model for patients with postoperative TA was constructed based on the relevant factors obtained from logistic regression, and internal validation was performed. The decision curve and receiver operating characteristic (ROC) curve showed that the model had good clinical net benefit and predictive performance. The calibration curve showed that the model was in good agreement with the actual observation results. The CIC curve Results showed that the number of people with high risk of TA within the threshold probability range had a high consistency with the actual situation. Conclusion The factors that contribute to the occurrence of TA after tibial plateau fractures include osteoporosis, Schatzker classification, injury method, postoperative Rasmussen score, serum levels of MMP-13, BMP-2, BMP-9, IL-6, and TNF-α. The risk warning model constructed based on these factors has good predictive performance and clinical applicability. |
