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Shoulder & Elbow

Recognition of the pattern of complex fractures of the elbow using 3D-printed models



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Abstract

Aims

This study aimed to answer the following questions: do 3D-printed models lead to a more accurate recognition of the pattern of complex fractures of the elbow?; do 3D-printed models lead to a more reliable recognition of the pattern of these injuries?; and do junior surgeons benefit more from 3D-printed models than senior surgeons?

Methods

A total of 15 orthopaedic trauma surgeons (seven juniors, eight seniors) evaluated 20 complex elbow fractures for their overall pattern (i.e. varus posterior medial rotational injury, terrible triad injury, radial head fracture with posterolateral dislocation, anterior (trans-)olecranon fracture-dislocation, posterior (trans-)olecranon fracture-dislocation) and their specific characteristics. First, fractures were assessed based on radiographs and 2D and 3D CT scans; and in a subsequent round, one month later, with additional 3D-printed models. Diagnostic accuracy (acc) and inter-surgeon reliability (κ) were determined for each assessment.

Results

Accuracy significantly improved with 3D-printed models for the whole group on pattern recognition (acc2D/3D = 0.62 vs acc3Dprint= 0.69; Δacc = 0.07 (95% confidence interval (CI) 0.00 to 0.14); p = 0.025). A significant improvement was also seen in reliability for pattern recognition with the additional 3D-printed models (κ2D/3D = 0.41 (moderate) vs κ3Dprint = 0.59 (moderate); Δκ = 0.18 (95% CI 0.14 to 0.22); p ≤ 0.001). Accuracy was comparable between junior and senior surgeons with the 3D-printed model (accjunior = 0.70 vs accsenior = 0.68; Δacc = -0.02 (95% CI -0.17 to 0.13); p = 0.904). Reliability was also comparable between junior and senior surgeons without the 3D-printed model (κjunior = 0.39 (fair) vs κsenior = 0.43 (moderate); Δκ = 0.03 (95% CI -0.03 to 0.10); p = 0.318). However, junior surgeons showed greater improvement regarding reliability than seniors with 3D-printed models (κjunior = 0.65 (substantial) vs κsenior = 0.54 (moderate); Δκ = 0.11 (95% CI 0.04 to 0.18); p = 0.002).

Conclusion

The use of 3D-printed models significantly improved the accuracy and reliability of recognizing the pattern of complex fractures of the elbow. However, the current long printing time and non-reusable materials could limit the usefulness of 3D-printed models in clinical practice. They could be suitable as a reusable tool for teaching residents.

Cite this article: Bone Joint J 2023;105-B(1):56–63.


Correspondence should be sent to Huub H. de Klerk. E-mail:

Traumaplatform 3D Consortium: W. Bekkers, C. van Bergen, D. Eygendaal, N. Fagerberg, T. Gajic, M. Janssen, N. Kruger, L. Langenberg, O. Leonardsson, J. Nestorson, S. Nota, B. The, H. Weel, L. Worner.


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