Establishment and Verification of a Predictive Nomogram for New Vertebral Compression Fracture Occurring after Bone Cement Injection in Middle‐Aged and Elderly Patients with Vertebral Compression Fracture

Abstract

ObjectiveNew vertebral compression fracture (NVCF) occurring after bone cement injection in middle-aged and elderly patients with vertebral compression fracture is very common. Preoperative baseline characteristics and surgical treatment parameters have been widely studied as a risk factor, but the importance of the patients' laboratory indicators has not been thoroughly explored. We aimed to explore the relationship between laboratory indicators and NVCF, and attempt to construct a clinical prediction model of NVCF together with other risk factors. MethodsRetrospective analysis was performed for 200 patients who underwent bone cement injection (percutaneous kyphoplasty or vertebroplasty) for vertebral compression fractures between January 2019 and January 2020. We consulted the relevant literature and collated the factors affecting the occurrence of NVCF. Feature selection of patients with NVCF was optimized using the least absolute shrinkage and selection operator regression model, which was used to conduct multivariable logistic regression analysis, to create a predictive model incorporating the selected features. The discrimination, calibration, and clinical feasibility of the predictive model were assessed using the concordance index (C-index), calibration plots, and decision curve analysis. Internal validation was performed using Bootstrap resampling verification. ResultsTime from injury to surgery exceeding 7 days, low osteocalcin levels, elevated homocysteine levels, osteoporosis, mode of operation (percutaneous vertebroplasty), lack of postoperative anti-osteoporosis treatment, and poor diffusion of bone cement were independent risk factors for NVCF in middle-aged and elderly patients with vertebral compression fracture after bone cement injection. The C-index of the nomogram constructed using these seven factors was 0.895, indicating good discriminatory ability. The calibration plot showed that the model was well calibrated. Bootstrap resampling verification yielded a significant C-index of 0.866. Decision curve analysis demonstrated that the greatest clinical net benefit for predicting NVCF after bone cement injection could be achieved with a threshold of 1%-91%. ConclusionThis nomogram can effectively predict NVCF incidence after bone cement injection in middle-aged and elderly patients with vertebral compression fracture, thus aiding clinical decision-making and postoperative management, promoting effective postoperative rehabilitation, and improving the quality of life.