Adjacent Vertebral Refracture Prediction Model Based on Imaging Data After Vertebroplasty for Osteoporotic Vertebral
Shufeng Shen1, Xinmao You1, Yingqing Ren1
1Department of Spinal Surgery, Yuyao People's Hospital, Zhejiang, China.
Objectives:
To establish a predictive model to evaluate the risk of adjacent vertebral refracture (VRF) after percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fracture (OVCF) based on perioperative imaging data.
Methods:
This study was a retrospective cohort study which established a predictive model of VRF after PKP for OVCF. Patients who underwent PKP for OVCF in our hospital between January 2018 and December 2020 were enrolled and divided into a refracture group and normal group. Perioperative imaging data including preoperative bone mineral density (BMD), fatty infiltration (FI%) of paravertebral muscle, sagittal parameters of the spine and pelvis, and recovery rate of vertebral height were collected. The prediction model is obtained by multifactor logistic regression analysis.
Results:
A total of 242 patients were included, including 23 cases in the VRF group and 219 cases in the normal group. There were statistical differences in BMD, FI%, recovery rate of vertebral height, and sagittal imbalance between the 2 groups. Receiver operating characteristic curve analysis of continuous variables showed that BMD ≤-2.80, FI% ≥40%, and recovery rate of vertebral height ≥ 10% were the cutoff values. Logistic regression analysis showed that BMD ≤-2.80, FI% ≥40%, and sagittal imbalance were independent risk factors for VRF. The area under the curve according to the predicted probability was 0.85 (P < 0.05). After simplifying the model, the total point of the model was 7 points, with a cutoff value of 5 points.
Conclusions:
The prediction model obtained in this study can predict refracture after PKP for OVCF early and effectively. It has an excellent predictive effect which is suitable for clinicians.
