Zhang Xiaofeng, Yu Chunsheng, Liu Hu, Li Zhihao
Objective To explore the influencing factors of incision infection after open reduction and internal fixation (ORIF) of tibial fractures, develop an individualized nomogram prediction model and verify it. Methods The clinical data of 180 patients with tibial plateau fractures who received ORIF treatment in our hospital from February 2021 to September 2022 were retrospectively analyzed, and the occurrence of postoperative incision infection in these patients was analyzed. The potential warning indicators of incision infection after ORIF of tibial fractures were preliminarily screened by lasso regression; the influencing factors of postoperative incision infection were analyzed by multivariate binary logistic regression; an individualized nomogram prediction model was constructed; the goodness of fit, calibration degree and clinical applicability of the individualized nomogram prediction model were evaluated by Hosmer-Lemeshow test, calibration curve and decision curve; and the receiver operating characteristic (ROC) curve of the model was drawn. In addition, 180 patients with tibial plateau fractures who received ORIF treatment in our hospital from October 2022 to May 2024 were selected for external verification. Results Among 180 patients with tibial plateau fractures who received ORIF treatment, 38 cases had incision infection, with an incidence rate of 21.11%, including 14 cases (7.78%) of deep infection and 24 cases (13.33%) of superficial infection. Compared with the non-infected group, the infected group had a higher body mass index (BMI), a longer operation time, and a higher proportion of smoking, diabetes mellitus, open injury, and American Society of Anesthesiologists (ASA) grade III-IV (P < 0.05). BMI, smoking, diabetes mellitus, open injury, ASA grade, and operation time were potential warning indicators of incision infection after ORIF of tibial plateau fractures. BMI, smoking, diabetes mellitus, open injury, ASA grade, and operation time were influencing factors of incision infection after ORIF of tibial plateau fractures. The Hosmer-Lemeshow test (χ² = 3.998, P = 0.857) suggested that the individualized nomogram prediction model had a high goodness of fit. The calibration and decision curves indicated a high calibration degree and good clinical net benefit. The ROC curve showed that the area under the curve (AUC) was 0.918, the 95% confidence interval (CI) was 0.868-0.954, the sensitivity was 81.58%, and the specificity was 88.73%, suggesting that the individualized nomogram model had a high predictive efficiency. External verification showed that the prediction model established based on the data of the modeling group had good discrimination and consistency. Conclusion The individualized nomogram prediction model constructed in this study based on BMI, smoking, diabetes mellitus, open injury, ASA grade, and operation time can effectively predict the occurrence of incision infection after ORIF of tibial plateau fractures, which is helpful to reduce the occurrence of postoperative incision infection and promote the rapid recovery and good prognosis of patients.