Cheng Hanwen, Wen Huilong, Ma Yong, Liu Zhuojie, Wu Haoyu, Luowu Lajing, Xioa Yong, Liang Lianbin, Kong Fanjie, Xiao Longyi, Li Chunhai
Department of Orthopaedic Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Department of Orthopaedic Trauma, Peking University People's Hospital, Peking University, Beijing, China.
Neurospine. 2025 Apr 16. doi: 10.14245/ns.2449338.669.
Osteoporotic vertebral compression fractures (OVCF) are a major public health concern. While percutaneous vertebral augmentation (PVA) is an effective treatment for OVCF, adjacent vertebral fractures (AVF) often occur post-PVA, adversely affecting treatment outcomes. This study aims to develop a nomogram for predicting AVF risk using multicenter data to aid clinical decision-making for OVCF patients.
We retrospectively analyzed patients who underwent PVA at three hospitals between 2017 and 2022. The cohort was divided into a training set (80%) and a validation set (20%). Independent risk factors for AVF were identified using LASSO and logistic regression. Seven significant factors were: bone mineral density, diabetes, total fractured vertebrae, intravertebral vacuum cleft sign, recovery of local kyphosis angle, regular aerobic exercise, and lumbar brace use.
Among the 483 patients, 52 (10.76%) developed adjacent vertebral refractures within two years. The nomogram demonstrated high predictive accuracy, with AUCs of 89.21% in the training set and 98.33% in the validation set.
This pioneering nomogram, incorporating baseline, surgical, and postoperative factors, provides valuable guidance for spine surgeons in preoperative planning and postoperative management, enabling personalized prognosis and rehabilitation for OVCF patients.
骨质疏松性椎体压缩骨折（OVCF）是一个重大的公共卫生问题。虽然经皮椎体强化术（PVA）是治疗OVCF的有效方法，但PVA术后常发生邻近椎体骨折（AVF），对治疗结果产生不利影响。本研究旨在利用多中心数据开发一种预测AVF风险的列线图，以辅助OVCF患者的临床决策。
我们回顾性分析了2017年至2022年期间在三家医院接受PVA的患者。该队列被分为训练集（80%）和验证集（20%）。使用LASSO和逻辑回归确定AVF的独立危险因素。七个显著因素为：骨密度、糖尿病、椎体骨折总数、椎体内真空裂隙征、局部后凸角恢复情况、规律有氧运动和使用腰部支具。
在483例患者中，52例（10.76%）在两年内发生了邻近椎体骨折。该列线图显示出较高的预测准确性，训练集的曲线下面积（AUC）为89.21%，验证集为98.33%。
这一开创性的列线图纳入了基线、手术和术后因素，为脊柱外科医生在术前规划和术后管理方面提供了有价值的指导，能够为OVCF患者实现个性化的预后和康复。
