Construction and validation of a nomogram prediction model for chronic low back pain after PKP for lumbar compression fractures

Abstract

The aim was to study the independent risk factors for chronic low back pain after lumbar compression fractures undergoing percutaneous kyphoplasty (PKP), and to establish a nomogram prediction model accordingly. Data were collected from patients with lumbar compression fractures from January 2017 to December 2021 at the Affiliated Hospital of Xinjiang Medical University. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for chronic low back pain after receiving PKP for lumbar compression fractures, and the corresponding nomogram was established. Receiver operating characteristic (ROC) curves were plotted and area under the curve (AUC) was calculated, and calibration curves and decision curve analysis (DCA) were plotted to evaluate the model performance. A total of 792 patients with lumbar compression fractures were included in the study, and 188 patients had chronic postoperative low back pain, with an incidence of 23.74%. After univariate and multivariate logistic regression analysis, a total of 5 variables were identified as independent risk factors for chronic low back pain after undergoing PKP for lumbar compression fractures, namely having diabetes (OR, 1.607; 95% CI, 1.157–3.205), preoperative T value < −2.5 SD (OR, 2.697; 95% CI, 1.417–5.021), multiple lumbar fractures (OR, 1.815; 95% CI, 1.415–3.201), lumbar compression ≥ 50% (OR, 2.854; 95% CI, 1.411–6.524), and bone cement leakage (OR, 2.911; 95% CI, 1.715–6.817). The nomogram for chronic low back pain after PKP for lumbar compression fractures constructed in this study has good predictive accuracy and helps orthopedic surgeons to intervene earlier in patients at high risk of chronic low back pain after undergoing PKP for lumbar compression fractures.