Risk factors for adjacent vertebral fracture after PVP in patients with OVCF

Objective: To identify the risk factors and evaluate the predictive performance for adjacent vertebral fracture (AVF) after Percutaneous vertebroplasty (PVP). Methods: < 0.05), which were subsequently entered into a binary logistic regression model to determine independent risk factors. Predictive performance was assessed using receiver operating characteristic (ROC) curve analysis. Results: < 0.001) were independent risk factors. predictive performance analysis showed that age had an AUC of 0.623 (sensitivity 56.6%, specificity 62.6%), and BMD had an AUC of 0.629 (sensitivity 86.0%, specificity 39.9%). A combined prediction model achieved an AUC of 0.706 (95% CI: 0.565-0.976). Conclusion: Advanced age and low bone mineral density are independent risk factors for AVF after PVP, with OR = 1.045 per year of age and OR = 2.85 per SD decrease in BMD T-score. Although the predictive value of individual indicators is limited (AUC < 0.7), a comprehensive model (AUC = 0.706) achieves moderate accuracy suitable for preliminary risk stratification, supporting the prioritization of systemic osteoporosis management over surgical technical details in prevention strategies.

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Publication Details

Journal
Frontiers in Surgery
Published
2026-04-07
DOI
https://doi.org/10.3389/fsurg.2026.1779681
Primary Topic
Spinal Fractures and Fixation Techniques
Type
article
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article

Risk factors for adjacent vertebral fracture after PVP in patients with OVCF

Chang Li, Q. Chen, Zhanjun Ma, Yifei Huang et al.
Frontiers in Surgery
Spinal Fractures and Fixation Techniques
article

Risk factors for adjacent vertebral fracture after PVP in patients with OVCF

Chang Li, Q. Chen, Zhanjun Ma, Yifei Huang, Yuanyuan Dou, Lin Li
article en

Abstract

Objective: To identify the risk factors and evaluate the predictive performance for adjacent vertebral fracture (AVF) after Percutaneous vertebroplasty (PVP). Methods: < 0.05), which were subsequently entered into a binary logistic regression model to determine independent risk factors. Predictive performance was assessed using receiver operating characteristic (ROC) curve analysis. Results: < 0.001) were independent risk factors. predictive performance analysis showed that age had an AUC of 0.623 (sensitivity 56.6%, specificity 62.6%), and BMD had an AUC of 0.629 (sensitivity 86.0%, specificity 39.9%). A combined prediction model achieved an AUC of 0.706 (95% CI: 0.565-0.976). Conclusion: Advanced age and low bone mineral density are independent risk factors for AVF after PVP, with OR = 1.045 per year of age and OR = 2.85 per SD decrease in BMD T-score. Although the predictive value of individual indicators is limited (AUC < 0.7), a comprehensive model (AUC = 0.706) achieves moderate accuracy suitable for preliminary risk stratification, supporting the prioritization of systemic osteoporosis management over surgical technical details in prevention strategies.

Frontiers in SurgeryVol. 13
Xinjiang Medical University (CN), Xinjiang Uygur Autonomous Region Uygur Medicine Hospital (CN), Xinjiang Uygur Autonomous Region Education Department (CN)
Openalex Percentile: Top 32%
Spinal Fractures and Fixation Techniques
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