Quantitative analysis of the correlation between extraforaminal structures of lumbar spondylolisthesis and L5 nerve injury
Abstract
OBJECTIVE: This study aims to analyze the relevant factors leading to extraforaminal L5 nerve root injury (efL5NRI) in patients with lumbar spondylolisthesis based on commonly used radiological data and to develop a diagnostic model. METHODS: In this study, patients with lumbar spondylolisthesis accompanied by efL5NRI (positive group) were compared to those in a control group (patients with lumbar disc herniation or central canal stenosis at the L5 level). Participants were randomly assigned to a training set and a validation set in a 7:3 ratio. Relevant risk factors were then analyzed using Least Absolute Shrinkage and Selection Operator regression. Factors identified in this analysis were subjected to multivariate logistic regression to establish a predictive model. The model's performance was evaluated by analyzing its sensitivity, specificity, and the area under the receiver operating characteristic curve in the validation cohort. Calibration plots and decision curve analysis (DCA) were used to assess the model's calibration and clinical utility. RESULTS: Through logistic regression analysis, we identified four relevant factors, including L5 transverse process width, the lumbosacral distance, the pedicle spacing and foraminal area. The logistic model demonstrated that the area under the curve for the training cohort and the validation cohort were 0.949 and 0.899, indicating that the model had good predictive performance. Calibration plots and DCA demonstrated that the model was effective for the diagnosis of efL5NRI. CONCLUSION: We identified four relevant factors associated with efL5NRI, and subsequently developed a useful predictive model.
Fields of Study & Subjects
Spine and Intervertebral Disc Pathology
Pain Mechanisms and Treatments
Spondyloarthritis Studies and Treatments
Publication details
- Journal / source
- Journal of Orthopaedic Surgery and Research
- Volume
- 21
- Issue
- 1
- Pages
- 83–83
- Publication date
- 3 January 2026
- Language
- EN