Background: This study aimed to classify the pathomorphology of impacted proximal humeral fractures according to the control volume theory, with the intention to introduce a severity index to support surgeons in decision making.
Methods: In total, 50 proximal humeral fractures were randomly selected from 200 medical records of adult patients treated from 2009 to 2016. Four nonindependent observers used 2 different imaging modalities (computed tomography scans plus volume rendering; 3D model) to test the classification reliability. A fracture classification system was created according to the control volume theory to provide simple and understandable patterns that would help surgeons make quick assessments. The impacted fractures table was generated based on an evaluation of the calcar condition, determined by the impairment of a defined volumetric area under the cephalic cup and the humeral head malposition. In addition to the main fracture pattern, the comminution degree (low, medium, high), providing important information on fracture severity, could also be evaluated.
Results: From 3D imaging, the inter- and intraobserver reliability revealed a k value (95% confidence interval) of 0.55 (0.50-0.60) and 0.91 (0.79-1.00), respectively, for the pattern code, and 0.52 (0.43-0.76) and 0.91 (0.56-0.96), respectively, for the comminution degree.
Conclusions: The new classification provides a useful synoptic framework for identifying complex fracture patterns. It can provide the surgeon with useful information for fracture analysis and may represent a good starting point for an automated system.
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