A nomogram for postoperative pain relief in patients with osteoporotic vertebral compression fracture treated with polymethylmethacrylate bone cement.

Osteoporotic vertebral compression fractures (OVCFs) can be painful. Percutaneous kyphoplasty (PKP) aims at strengthening the vertebra and reducing pain, but efficacy can vary among patients. The purpose of this study was to establish a risk prediction model for pain relief following PKP in patients with OVCF. This retrospective study included 208 (training set) and 54 (validation set) OVCF patients who underwent bone cement treatment between January 2018 and October 2023. Based on postoperative VAS scores, patients were divided into two groups (0-2 and 3-6). Univariable and multivariable logistic regression identified significant factors affecting VAS scores, leading to the creation of a nomogram model. Internal validation was performed using the bootstrap method. The model's performance and clinical value were evaluated using the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and calibration curves. Four predictors were identified: number of segments, PMMA dose, comorbidities, and central nervous system (CNS) medications. The AUC, DCA, and calibration curves demonstrated good model discrimination and accuracy. The clinical impact plot highlighted the model's practical value. We developed and validated an intuitive nomogram model for predicting a postoperative VAS score ≤ 2, reflecting therapeutic efficacy in OVCF patients treated with PMMA. The model could be used for a more careful selection of patients suitable for PKP and who would benefit the most from PKP. The other patients should at least be advised of the risk of suboptimal pain control or directed toward other treatments.