Does displacement of cervical and thoracolumbar dislocation-translation injuries predict spinal cord injury or recovery?

Publication/Presentation Date

12-1-2022

Abstract

OBJECTIVE: For patients with cervical and thoracolumbar AO Spine type C injuries, the authors sought to 1) identify whether preoperative vertebral column translation is predictive of a complete spinal cord injury (SCI) and 2) identify whether preoperative or postoperative vertebral column translation is predictive of neurological improvement after surgical decompression.

METHODS: All patients who underwent operative treatment for cervical and thoracolumbar AO Spine type C injuries at the authors' institution between 2006 and 2021 were identified. CT and MRI were utilized to measure vertebral column translation in millimeters prior to and after surgery. A receiver operating characteristic (ROC) curve was generated to predict the probability of sustaining a complete SCI on the basis of the amount of preoperative vertebral column translation. ROC curves were then used to predict the probability of neurological recovery on the basis of preoperative and postoperative vertebral column translation.

RESULTS: ROC analysis of 67 patients identified 6.10 mm (area under the curve [AUC] 0.77, 95% CI 0.650-0.892) of preoperative vertebral column translation as predictive of complete SCI. Additionally, ROC curve analysis found that 10.4 mm (AUC 0.654, 95% CI 0.421-0.887) of preoperative vertebral column translation was strongly predictive of no postoperative neurological improvement. Residual postoperative vertebral column translation after fracture reduction and instrumentation had no predictive value on neurological recovery (AUC 0.408, 95% CI 0.195-0.622).

CONCLUSIONS: For patients with cervical and thoracolumbar AO Spine type C injuries, the amount of preoperative vertebral column translation is highly predictive of complete SCI and the likelihood of postoperative neurological recovery.

Volume

37

Issue

6

First Page

821

Last Page

827

ISSN

1547-5646

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

35962960

Department(s)

Administration and Leadership

Document Type

Article

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