BMC Musculoskeletal Disorders (Apr 2024)

Reliability of thoracolumbar burst fracture classification in the Swedish Fracture Register

  • Simon Blixt,
  • Fabian Burmeister,
  • Sebastian Mukka,
  • Lukas Bobinski,
  • Peter Försth,
  • Olof Westin,
  • Paul Gerdhem

DOI
https://doi.org/10.1186/s12891-024-07395-0
Journal volume & issue
Vol. 25, no. 1
pp. 1 – 9

Abstract

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Abstract Background The Swedish Fracture Register (SFR) is a national quality register for all types of fractures in Sweden. Spine fractures have been included since 2015 and are classified using a modified AOSpine classification. The aim of this study was to determine the accuracy of the classification of thoracolumbar burst fractures in the SFR. Methods Assessments of medical images were conducted in 277 consecutive patients with a thoracolumbar burst fracture (T10-L3) identified in the SFR. Two independent reviewers classified the fractures according to the AOSpine classification, with a third reviewer resolving disagreement. The combined results of the reviewers were considered the gold standard. The intra- and inter-rater reliability of the reviewers was determined with Cohen’s kappa and percent agreement. The SFR classification was compared with the gold standard using positive predictive values (PPV), Cohen’s kappa and percent agreement. Results The reliability between reviewers was high (Cohen’s kappa 0.70–0.97). The PPV for correctly classifying burst fractures in the SFR was high irrespective of physician experience (76–89%), treatment (82% non-operative, 95% operative) and hospital type (83% county, 95% university). The inter-rater reliability of B-type injuries and the overall SFR classification compared with the gold standard was low (Cohen’s kappa 0.16 and 0.17 respectively). Conclusions The SFR demonstrates a high PPV for accurately classifying burst fractures, regardless of physician experience, treatment and hospital type. However, the reliability of B-type injuries and overall classification in the SFR was found to be low. Future studies on burst fractures using SFR data where classification is important should include a review of medical images to verify the diagnosis.

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