经皮椎体后凸成形术后邻近椎体压缩性骨折的预测模型：一项回顾性研究。
Prediction model of adjacent vertebral compression fractures after percutaneous kyphoplasty: a retrospective study.
机构信息
Department of Spine Surgery, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou, Zhejiang, China.
Department of Spine Surgery, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou, Zhejiang, China
出版信息
BMJ Open. 2023 May 31;13(5):e064825. doi: 10.1136/bmjopen-2022-064825.
OBJECTIVES
The purpose of this study was to develop a prediction model to assess the risk of adjacent vertebral compression fractures (AVCFs) after percutaneous kyphoplasty (PKP) surgery.
DESIGN
A retrospective chart review.
SETTING AND PARTICIPANTS
Patients were collected from the Quzhou People's Hospital, from March 2017 to May 2019. Patients were included if they suffered from osteoporotic vertebral compression fractures (OVCFs), underwent PKP surgery and were followed up for 2 years.
INTERVENTIONS
None.
METHODS
This was a retrospective cohort study of all PKP surgery procedures of the thoracic, lumbar and thoracolumbar (TL) spine that have been performed for OVCF from 1 March 2017 up to 1 May 2019. The least absolute shrinkage and selection operator (LASSO) regression model was used to optimise feature selection for the AVCF risk model. Multivariable logistic regression analysis was applied to build a predicting model incorporating the feature selected in the LASSO regression model. The C-index, calibration plot and decision curve analysis were applied to assess this model.
RESULTS
Gender, age, the number of surgical vertebrae, cement volume, bone mineral density, diabetes, hypertension, bone cement leakage, duration of anti-osteoporosis treatment after surgery and TL junction were identified as predictors. The model displayed good discrimination with a C-index of 0.886 (95% CI 0.828-0.944) and good calibration. High C-index value of 0.833 could still be reached in the interval validation. Decision curve analysis showed that the AVCF nomogram was clinically useful when intervention was decided at the AVCF possibility threshold of 1%.
CONCLUSIONS
This study developed a clinical prediction model to identify the risk factors for AVCF after PKP surgery, and this tool is of great value in sharing surgical decision-making among patients consulted before surgery.
TRIAL REGISTRATION NUMBER
researchregistry7716.
目的
本研究旨在开发一种预测模型，以评估经皮椎体后凸成形术（PKP）后邻近椎体压缩性骨折（AVCF）的风险。
设计
回顾性图表回顾。
地点和参与者
患者从 2017 年 3 月至 2019 年 5 月从衢州市人民医院收集。如果患者患有骨质疏松性椎体压缩性骨折（OVCF），接受 PKP 手术并随访 2 年，则将其纳入研究。
干预措施
无。
方法
这是一项回顾性队列研究，纳入了 2017 年 3 月 1 日至 2019 年 5 月 1 日期间接受胸、腰和胸腰（TL）段 PKP 手术治疗 OVCF 的所有患者。使用最小绝对收缩和选择算子（LASSO）回归模型对 AVCF 风险模型进行特征选择优化。应用多变量逻辑回归分析建立包含 LASSO 回归模型中选择特征的预测模型。应用 C 指数、校准图和决策曲线分析评估该模型。
结果
性别、年龄、手术椎体数、骨水泥体积、骨密度、糖尿病、高血压、骨水泥渗漏、术后抗骨质疏松治疗时间和 TL 交界处被确定为预测因子。该模型显示出良好的区分度，C 指数为 0.886（95%CI 0.828-0.944），校准良好。在间隔验证中，仍可达到 0.833 的高 C 指数值。决策曲线分析表明，在 AVCF 可能性阈值为 1%时决定干预，AVCF 列线图具有临床应用价值。
结论
本研究开发了一种预测模型，以确定 PKP 术后 AVCF 的危险因素，该工具在手术前咨询的患者中进行手术决策共享方面具有重要价值。
试验注册号
researchregistry7716。
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