Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures

Abstract

The aim was to investigate the independent risk factors for postoperative incisional infection in ankle fractures and to establish a nomogram prediction model accordingly. Data were collected from ankle fracture patients in the Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2022. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for postoperative incisional infection in ankle fractures and to establish the corresponding nomogram. Receiver operating characteristic curves were plotted and area under the curve was calculated, and calibration curves and decision curve analysis were plotted to evaluate the model performance. A total of 722 patients with ankle fractures were included in the study, and 76 patients developed postoperative incisional infections, with an incidence of 10.53%. After univariate and multivariate logistic regression analysis, a total of 5 variables were identified as independent risk factors for postoperative incisional infection in ankle fractures, namely, age ≥ 60 years (OR, 1.885; 95% CI, 1.156–3.045), having diabetes (OR1.625; 95% CI, 1.095–2.876), open fracture (OR, 5.564; 95% CI, 3.099–9.990), albumin < 35 g/L (OR, 2.618; 95% CI, 1.217–4.215), and operative time ≥ 2 hours (OR, 1.606; 95% CI, 1.077–3.247). The nomogram for postoperative incisional infection after ankle fracture constructed in this study has good predictive accuracy and helps orthopedic surgeons to intervene earlier in patients at high risk of postoperative incisional infection after ankle fracture.