JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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The timing and influence of MRI on the management of patients with cervical facet dislocations remains highly variable: a survey of members of the Spine Trauma Study Group.

BACKGROUND: Traumatic cervical facet dislocations are potentially devastating injuries. Magnetic resonance imaging (MRI) is an excellent means of assessing ligamentous disruption, disk herniation, and compression of the neural elements. However, despite an improved understanding of these facet dislocations with imaging, treatment remains controversial.

PURPOSE: To survey the timing and influence of MRI on the management of patients with traumatic cervical facet dislocations.

STUDY DESIGN: Questionnaire study.

METHODS: Clinical vignettes, plain radiographs, and computed tomography scans of 10 cases of cervical facet dislocation were presented to 25 fellowship trained spine surgeons. Participants were analyzed as to their next step in diagnosis or treatment: closed reduction, obtaining an MRI, or proceeding directly with open treatment. A revised vignette was then presented; however, on this occasion, an MRI was included with the imaging and had been obtained before a reduction attempt. Participants were then surveyed on their choice of closed or open reduction. Each of the vignettes consisted of 3 different clinical scenarios based on neurologic examination: intact, incomplete, or complete spinal cord injury.

RESULTS: The interrater reliability of treatment decisions was very poor, and the reliability after MRI was available and was significantly worse when the patient was considered to have a complete spinal cord injury. After reviewing the MRI, orthopedic surgeons were significantly more likely to choose a closed versus open reduction. Neurosurgeons were significantly more likely than orthopedic surgeons to order an MRI before open or closed treatment.

CONCLUSIONS: The timing and utilization of MRI for patients with traumatic cervical facet dislocations remains variable. Further outcome analysis in the form of evidence-based algorithms is necessary to optimize patient management and outcomes.

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