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A novel cervical vertebral bone quality score can independently predict cage subsidence after anterior cervical corpectomy and fusion

Authors :
Junhu Li
Linnan Wang
Zhipeng Deng
Shuxin Zheng
Lei Wang
Yueming Song
Source :
BMC Musculoskeletal Disorders, Vol 25, Iss 1, Pp 1-8 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Objectives 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. Methods 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. Results 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. Conclusions 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.

Details

Language :
English
ISSN :
14712474
Volume :
25
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Musculoskeletal Disorders
Publication Type :
Academic Journal
Accession number :
edsdoj.1cb2cf3b080a41ddb5d7667895b9f3e1
Document Type :
article
Full Text :
https://doi.org/10.1186/s12891-024-07791-6