The Subaxial Cervical Spine Injury Classification System: an external agreement validation study
SourceSpine Journal, 13, 9, (2013), pp. 1055-1063
Article / Letter to editor
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SubjectNCEBP 10: Human Movement & Fatigue; NCEBP 2: Evaluation of complex medical interventions ONCOL 5: Aetiology, screening and detection
BACKGROUND CONTEXT: In 2007, the Subaxial Cervical Spine Injury Classification (SLIC) system was introduced demonstrating moderate reliability in an internal validation study. PURPOSE: To assess the agreement on the SLIC system using clinical data from a spinal trauma population and whether the SLIC treatment algorithm outcome improved agreement on treatment decisions among surgeons. STUDY DESIGN: An external classification validation study. PATIENT SAMPLE: Twelve spinal surgeons (five consultants and seven fellows) assessed 51 randomly selected cases. OUTCOME MEASURES: Raw agreement, Fleiss kappa, and intraclass correlation coefficient statistics were used for reliability analysis. Majority rules and latent class modeling were used for accuracy analysis. METHODS: Fifty-one randomly selected cases with significant injuries of the cervical spine from a prospective consecutive series of trauma patients were assessed using the SLIC system. Neurologic details, plain radiographs, and computed tomography scans were available for all cases as well as magnetic resonance imaging in 21 cases (41%). No funds were received in support of this study. The authors have no conflict of interest in the subject of this article. Results : The inter-rater agreement on the most severely affected level of injury was strong (kappa=0.76). The agreement on the morphologic injury characteristics was poor (kappa=0.29) and agreement on the integrity of the discoligamentous complex was average (kappa=0.46). The inter-rater agreement on the treatment verdict after the total SLIC injury severity score was slightly lower than the surgeons' agreement on personal treatment preference (kappa=0.55 vs. kappa=0.63). Latent class analysis was not converging and did not present accurate estimations of the true classification categories. Based on these findings, no second survey for testing intrarater agreement was performed. CONCLUSIONS: We found poor agreement on the morphologic injury characteristics of the SLIC system, and its treatment algorithm showed no improved agreement on treatment decisions among surgeons. The authors discuss that the reproducibility of the SLIC system is likely to improve when unambiguous true morphologic injury characteristics are being implemented.
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