Department of Orthopedic Surgery and Orthopedic Research Institute, West China Hospital and West China, School of Medicine, Sichuan University, Chengdu, 610041, P.R. China.
BMC Musculoskelet Disord. 2024 Aug 26;25(1):667. doi: 10.1186/s12891-024-07791-6.
To optimize cervical vertebral bone quality (C-VBQ) score and explore its effectiveness in predicting cage subsidence in Anterior Cervical Corpectomy and Fusion (ACCF) and identify a new method for evaluating subsidence without different equipment and image scale interference.
Collecting demographic, imaging, and surgical related information. Measuring Cage Subsidence with a new method. Multifactorial logistic regression was used to identify risk factors associated with subsidence. Pearson's correlation was used to determine the relationship between C-VBQ and computed tomography (CT) Hounsfield units (HU). The receiver operating characteristic (ROC) curve was used to assess C-VBQ predictive ability. Correlations between demographics and C-VBQ scores were analyzed using linear regression models.
92 patients were included in this study, 36 (39.1%) showed subsidence with a C-VBQ value of 2.05 ± 0.45, in the no-subsidence group C-VBQ Value was 3.25 ± 0.76. The multifactorial logistic regression showed that C-VBQ is an independent predictor of cage subsidence with a predictive accuracy of 93.4%. Pearson's correlation analysis showed a negative correlation between C-VBQ and HU values. Linear regression analysis showed a positive correlation between C-VBQ and cage subsidence. Univariate analyses showed that only age was associated with C-VBQ.
The C-VBQ values obtained using the new measurements independently predicted postoperative cage subsidence after ACCF and showed a negative correlation with HU values. By adding the measurement of non-operated vertebral heights as a control standard, the results of cage subsidence measured by the ratio method are likely to be more robust, perhaps can exclude unavoidable errors caused by different equipment and proportional.
优化颈椎骨质量(C-VBQ)评分,并探讨其在预测前路颈椎椎体次全切除融合术(ACCF)中 cage 下沉的有效性,以及寻找一种无需使用不同设备和图像比例干扰即可评估下沉的新方法。
收集人口统计学、影像学和手术相关信息。使用新方法测量 cage 下沉。采用多因素逻辑回归分析与下沉相关的危险因素。采用 Pearson 相关分析评估 C-VBQ 与 CT 亨氏单位(HU)之间的关系。采用受试者工作特征(ROC)曲线评估 C-VBQ 的预测能力。采用线性回归模型分析人口统计学与 C-VBQ 评分之间的相关性。
本研究共纳入 92 例患者,其中 36 例(39.1%)出现下沉,C-VBQ 值为 2.05±0.45,无下沉组 C-VBQ 值为 3.25±0.76。多因素逻辑回归显示,C-VBQ 是 cage 下沉的独立预测因子,预测准确率为 93.4%。Pearson 相关分析显示 C-VBQ 与 HU 值呈负相关。线性回归分析显示 C-VBQ 与 cage 下沉呈正相关。单因素分析显示,只有年龄与 C-VBQ 相关。
使用新测量方法获得的 C-VBQ 值可独立预测 ACCF 术后 cage 下沉,与 HU 值呈负相关。通过添加未手术椎体高度的测量作为对照标准,比值法测量 cage 下沉的结果可能更稳健,或许可以排除因不同设备和比例引起的不可避免的误差。