| 刘进辉,刘欣哲,孙智,等.骨质疏松性椎体压缩骨折患者行经皮椎体后凸成形术后出现进展性后凸畸形的风险因素分析.骨科,2026,17(4): 318-324. |
| 骨质疏松性椎体压缩骨折患者行经皮椎体后凸成形术后出现进展性后凸畸形的风险因素分析 |
| Risk factors for progressive kyphosis after percutaneous kyphoplasty in patients with osteoporotic vertebral compression fractures |
| 投稿时间：2025-09-18 |
| DOI：10.3969/j.issn.1674-8573.2026.04.003 |
| CN KeyWords: 骨质疏松性椎体压缩骨折 经皮椎体后凸成形术 进展性后凸畸形 风险因素 列线图 |
| EN KeyWords: Osteoporotic vertebral compression fractures Percutaneous kyphoplasty Progressive kyphosis Risk factors Nomogram |
| Fund Project:河北省医学科学研究课题（20251420） |
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| CN Abstract: |
| 目的 探讨骨质疏松性椎体压缩骨折（OVCF）患者接受经皮椎体后凸成形术（PKP）后发生进展性后凸畸形（PK）的风险因素，并构建个体化预测模型。方法 回顾性分析2020年1月至2024年1月收治的197例行PKP手术的单节段OVCF患者的临床资料。根据末次随访时后凸角（KA）增加是否≥10°将患者分为PK组（69例）和非PK组（128例）。收集并比较两组的临床、手术及影像学资料。采用单因素及多因素Logistic回归分析筛选PK发生的独立危险因素，并基于此构建列线图预测模型。通过受试者工作特征（receiver operating characteristic，ROC）曲线、校准曲线和决策曲线分析评估模型的区分度、校准度和临床实用性。结果 197例患者中，术后PK的发生率为35.03%（69/197）。多因素Logistic回归分析显示，MRI STIR序列黑线征（OR=58.075，95% CI：4.019~89.631，P=0.003）、较高的椎体高度丢失（VHL）恢复率（OR=1.443，95% CI：1.167~1.785，P<0.001）、较大的术前KA（OR=1.418，95% CI：1.104~1.822，P=0.006）和较大的术后KA（OR=1.452，95% CI：1.159~1.819，P=0.001）是PK发生的独立危险因素。基于上述因素构建的列线图预测模型表现出优异的预测性能，其ROC曲线下面积（AUC）为0.99（95% CI：0.98~1.00），校准度和临床决策能力良好。结论 OVCF患者PKP术后PK的发生与黑线征、过度的椎体高度恢复以及较大的术前和术后残留KA密切相关。本研究构建的列线图模型能有效预测PK发生风险，有助于临床早期识别高风险患者并实施个体化干预策略。 |
| EN Abstract: |
| Objective To investigate the risk factors for progressive kyphosis (PK) after percutaneous kyphoplasty (PKP) in patients with osteoporotic vertebral compression fractures (OVCFs) and to develop an individualized prediction model. Methods A retrospective analysis was conducted on 197 patients with single-segment OVCFs who underwent PKP between January 2020 and January 2024. The patients were divided into the PK group (69 cases) and the non-PK group (128 cases) according to whether the kyphotic angle (KA) at the final follow-up had increased by ≥10° compared with the postoperative value. Clinical, surgical, and radiological data from the two groups were collected and compared. Univariate and multivariate Logistic regression analyses were performed to identify independent risk factors for PK, and a Nomogram prediction model was constructed. The discrimination, calibration, and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis. Results Among the 197 patients, the incidence of postoperative PK was 35.03% (69/197). Multivariate Logistic regression analysis demonstrated that the following were independent risk factors for PK: MRI STIR sequence black line sign (OR=58.075, 95% CI: 4.019-89.631, P=0.003), higher vertebral height loss (VHL) recovery rate (OR=1.443, 95% CI: 1.167-1.785, P<0.001), larger preoperative KA (OR=1.418, 95% CI: 1.104-1.822, P=0.006), and larger postoperative KA (OR=1.452, 95% CI: 1.159-1.819, P=0.001). The Nomogram prediction model based on these factors exhibited excellent predictive performance, with an area under the ROC curve (AUC) of 0.99 (95% CI: 0.98-1.00), as well as good calibration and clinical utility. Conclusion The occurrence of PK after PKP in OVCF patients is closely associated with the black line sign, excessive vertebral height restoration, and larger preoperative and postoperative residual KA. The established Nomogram model can effectively predict the risk of PK, facilitating early identification of high-risk patients and implementation of individualized intervention strategies. |
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