Preoperative CT attenuation value classification assesses cage subsidence risk in 112 OLIF surgery cases

术前CT衰减值分类评估112例OLIF手术病例中椎间融合器下沉风险

阅读:1

Abstract

Retrospective Study. This study investigates the effectiveness of preoperative vertebral computed tomography (CT) attenuation value classification in predicting cage subsidence in Oblique lumbar interbody fusion (OLIF) surgeries. This study aims to evaluate the feasibility of using CT attenuation value classification to predict cage subsidence. A retrospective analysis of L4-5 OLIF surgeries from May 2019 to June 2022, with over one year of follow-ups, was performed. Patients were classified into subsidence and non-subsidence groups based on postoperative outcomes. Demographic and perioperative variables, preoperative CT attenuation values, and changes in Oswestry Disability Index (ODI) and Visual Analog Scale (VAS) scores were compared. Of 112 patients (29 in the subsidence group, 83 in the non-subsidence group), significant differences in gender (P = 0.032) and DXA T-value (P = 0.010) were noted, with the subsidence group predominantly female. The consistency of CT attenuation values across L1-L5 vertebral bodies demonstrated strong reliability, with intraclass correlation coefficient (ICC) ranging from 0.76 to 0.91. CT attenuation values, categorized into osteoporosis, osteopenia, and regular bone mass groups, correlated significantly with bone density and subsidence, especially at the L1 vertebra (r = 0.548, P < 0.001). Multivariate logistic regression confirmed the predictive value of vertebral CT stratification, with L1-L5 Odds Ratios (OR) ranging from 0.07 to 0.26. Females are more prone to OLIF-related cage subsidence. The measurement of CT attenuation values demonstrated strong reliability and consistency. Preoperative vertebral CT attenuation value classification correlates with bone density and subsidence risk, particularly at the L1 vertebra, and strongly predicts cage subsidence.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。