Establishment of a risk prediction model for residual back pain after percutaneous kyphoplasty in osteoporotic vertebral compression fractures.

Purpose: Severe residual back pain (RBP) after percutaneous kyphoplasty (PKP) significantly impacts postoperative prognosis and quality of life in patients. The aim of this study was to identify the risk factors for RBP in osteoporotic vertebral compression fracture (OVCF) patients after PKP, to establish a risk prediction model, and to validate its effectiveness. Methods: A case-control study was carried out among OVCF patients, who were assigned to either the training set (these patients were recruited from January 2018 and June 2020) or the validation set (these patients were recruited from July 2020 and December 2020). Risk factors were identified by univariate analysis and multifactor logistic regression analysis. The performance of the prediction model was determined by using the area under the receiver operating characteristic (ROC) curve (AUC) to assess discrimination. A nomogram for risk prediction was constructed, the Hosmer-Lemeshow test and calibration curves were used to assess calibration, and decision curve analysis was used to assess the clinical use of the model. Results: A total of 647 patients were included, 569 cases were used to train the model and 78 cases were used for external validation. Based on the data of model training set, age, bone mineral density, trauma history, posterior fascial edema, platelet distribution width, serum chloride, and middle vertebral height were independent risk factors for RBP after PKP ( Conclusion: The constructed model showed good predictive ability in the occurrence of residual back pain after PKP, which can provide a scientific basis and guidance for clinical prevention and treatment.